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USRE47057E1 - Methods and compositions for evaluating graft survival in a solid organ transplant recipient - Google Patents

Methods and compositions for evaluating graft survival in a solid organ transplant recipient Download PDF

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USRE47057E1
USRE47057E1 US13/529,768 US201213529768A USRE47057E US RE47057 E1 USRE47057 E1 US RE47057E1 US 201213529768 A US201213529768 A US 201213529768A US RE47057 E USRE47057 E US RE47057E
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blood
genes
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biopsy
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Minnie M. Sarwal
Elaine S. Mansfield
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Leland Stanford Junior University
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/118—Prognosis of disease development
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers

Definitions

  • Transplantation of a graft organ or tissue from a donor to a host patient is a feature of certain medical procedures and treatment protocols.
  • immunosuppressive therapy is generally required to the maintain viability of the donor organ in the host.
  • organ transplant rejection can occur.
  • Organ transplant rejection comprises three separate categories: hyperacute, acute and chronic.
  • Hyperacute rejection is characterized by rapid thrombotic occlusion of the graft vasculature within minutes to hours after organ transplantation.
  • Hyperacute rejection is mediated in large part by preexisting antibodies that bind to the epithelium and activate the complement cascade. Complement activation results in endothelial cell damage and subsequent exposure of the basement membrane, resulting in the activation of platelets, leading to thrombosis and vascular occlusion.
  • hyperacute rejection has become less common due to blood antigen and MHC molecule matching between the donor organ and the recipient.
  • Acute rejection is sub-classified into acute vascular rejection and acute cellular rejection.
  • Acute vascular rejection is characterized by necrosis of individual cells in the graft blood vessels. The process is similar to that of hyperacute rejection, but onset is often slower, within one week of rejection, and a T cell component may be involved.
  • Acute vascular rejection is initiated by a response to alloantigens present on the vascular endothelial cells of the donor organ, resulting in the release of a cytokine cascade, inflammation, and eventual necrosis.
  • Acute cellular rejection is often characterized by necrosis of the essential or parenchymal cells of the transplanted organ caused by the infiltration of host T lymphocytes and macrophages.
  • the lymphocytes involved are usually cytotoxic T lymphocytes (CTL) and macrophages, both resulting in lysis of targeted cells.
  • CTLs are usually specific for graft alloantigens displayed in the context of MHC class I molecules.
  • Chronic rejection is the major cause of allograft loss and is characterized by fibrosis and loss of normal organ structures. Fibrosis may be the result of wound healing following the cellular necrosis of acute rejection, or may occur independently and without prior acute rejection. In addition, chronic rejection may lead to vascular occlusions thought to stem from a delayed type hypersensitivity response to alloantigens present on the transplanted organ. These alloantigens stimulate lymphocytes to secrete cytokines which attract macrophages and other effector cells eventually leading to an arteriosclerosis-like blockage.
  • chronic graft injury or rejection is largely due to calcineurin-inhibitor drug nephrotoxicity (DT) and chronic allograft nephropathy (CAN), two conditions which may result in loss of graft function and early graft loss, premature to the life expectancy of the recipient.
  • DT calcineurin-inhibitor drug nephrotoxicity
  • CAN chronic allograft nephropathy
  • a biopsy is the only current gold standard for CAN and DT diagnosis. As both conditions are progressive post-transplantation, multiple graft protocol biopsies are required. However, the invasiveness of biopsy procedures is a limitation to this form of monitoring. In addition, variability of biopsy sampling and pathology analysis (2) adds a confounder to the differential diagnosis of these 2 conditions—the result of either too much drug (DT) vs. too little/inappropriate drugs (CAN)—with a common outcome of chronic fibrotic injury from differing mechanisms (non-immune vs. immune).
  • DT too much drug
  • CAN too little/inappropriate drugs
  • AR acute rejection
  • Methods are provided for evaluating a subject for graft survival, e.g., in terms of predicting graft survival, identifying the presence of a deleterious graft condition, such as CAN and DT, identifying the severity and class of acute rejection, etc, in a subject are provided.
  • the expression of at least one gene in a sample from the subject e.g., a blood or biopsy sample, is assayed, e.g., at the nucleic acid and/or protein level, to evaluate the subject.
  • compositions, systems and kits that find use in practicing the subject methods.
  • Acute rejection or AR is the rejection by the immune system of a tissue transplant recipient when the transplanted tissue is immunologically foreign. Acute rejection is characterized by infiltration of the transplanted tissue by immune cells of the recipient, which carry out their effector function and destroy the transplanted tissue. The onset of acute rejection is rapid and generally occurs in humans within a few weeks after transplant surgery. Generally, acute rejection can be inhibited or suppressed with immunosuppressive drugs such as rapamycin, cyclosporin A, anti-CD40L monoclonal antibody and the like.
  • Chronic transplant rejection or CR generally occurs in humans within several months to years after engraftment, even in the presence of successful immunosuppression of acute rejection. Fibrosis is a common factor in chronic rejection of all types of organ transplants. Chronic rejection can typically be described by a range of specific disorders that are characteristic of the particular organ.
  • disorders include fibroproliferative destruction of the airway (bronchiolitis obliterans); in heart transplants or transplants of cardiac tissue, such as valve replacements, such disorders include fibrotic atherosclerosis; in kidney transplants, such disorders include, obstructive nephropathy, nephrosclerorsis, tubulointerstitial nephropathy; and in liver transplants, such disorders include disappearing bile duct syndrome.
  • Chronic rejection can also be characterized by ischemic insult, denervation of the transplanted tissue, hyperlipidemia and hypertension associated with immunosuppressive drugs.
  • transplant rejection encompasses both acute and chronic transplant rejection.
  • stringent assay conditions refers to conditions that are compatible to produce binding pairs of nucleic acids, e.g., surface bound and solution phase nucleic acids, of sufficient complementarity to provide for the desired level of specificity in the assay while being less compatible to the formation of binding pairs between binding members of insufficient complementarity to provide for the desired specificity.
  • Stringent assay conditions are the summation or combination (totality) of both hybridization and wash conditions.
  • Stringent hybridization conditions and “stringent hybridization wash conditions” in the context of nucleic acid hybridization (e.g., as in array, Southern or Northern hybridizations) are sequence dependent, and are different under different experimental parameters.
  • Stringent hybridization conditions that can be used to identify nucleic acids within the scope of the invention can include, e.g., hybridization in a buffer comprising 50% formamide, 5 ⁇ SSC, and 1% SDS at 42° C., or hybridization in a buffer comprising 5 ⁇ SSC and 1% SDS at 65° C., both with a wash of 0.2 ⁇ SSC and 0.1% SDS at 65° C.
  • Exemplary stringent hybridization conditions can also include hybridization in a buffer of 40% formamide, 1 M NaCl, and 1% SDS at 37° C., and a wash in 1 ⁇ SSC at 45° C.
  • hybridization to filter-bound DNA in 0.5 M NaHPO 4 , 7% sodium dodecyl sulfate (SDS), 1 mM EDTA at 65° C., and washing in 0.1 ⁇ SSC/0.1% SDS at 68° C. can be employed.
  • Yet additional stringent hybridization conditions include hybridization at 60° C. or higher and 3 ⁇ SSC (450 mM sodium chloride/45 mM sodium citrate) or incubation at 42° C.
  • wash conditions used to identify nucleic acids may include, e.g.: a salt concentration of about 0.02 molar at pH 7 and a temperature of at least about 50° C. or about 55° C. to about 60° C.; or, a salt concentration of about 0.15 M NaCl at 72° C. for about 15 minutes; or, a salt concentration of about 0.2 ⁇ SSC at a temperature of at least about 50° C. or about 55° C. to about 60° C.
  • hybridization complex is washed twice with a solution with a salt concentration of about 2 ⁇ SSC containing 0.1% SDS at room temperature for 15 minutes and then washed twice by 0.1 ⁇ SSC containing 0.1% SDS at 68° C. for 15 minutes; or, equivalent conditions.
  • Stringent conditions for washing can also be, e.g., 0.2 ⁇ SSC/0.1% SDS at 42° C.
  • a specific example of stringent assay conditions is rotating hybridization at 65° C. in a salt based hybridization buffer with a total monovalent cation concentration of 1.5 M (e.g., as described in U.S. patent application Ser. No. 09/655,482 filed on Sep. 5, 2000, the disclosure of which is herein incorporated by reference) followed by washes of 0.5 ⁇ SSC and 0.1 ⁇ SSC at room temperature.
  • Stringent assay conditions are hybridization conditions that are at least as stringent as the above representative conditions, where a given set of conditions are considered to be at least as stringent if substantially no additional binding complexes that lack sufficient complementarity to provide for the desired specificity are produced in the given set of conditions as compared to the above specific conditions, where by “substantially no more” is meant less than about 5-fold more, typically less than about 3-fold more.
  • Other stringent hybridization conditions are known in the art and may also be employed, as appropriate.
  • the term “gene” or “recombinant gene” refers to a nucleic acid comprising an open reading frame encoding a polypeptide, including exon and (optionally) intron sequences.
  • the term “intron” refers to a DNA sequence present in a given gene that is not translated into protein and is generally found between exons in a DNA molecule.
  • a gene may optionally include its natural promoter (i.e., the promoter with which the exons and introns of the gene are operably linked in a non-recombinant cell, i.e., a naturally occurring cell), and associated regulatory sequences, and may or may not have sequences upstream of the AUG start site, and may or may not include untranslated leader sequences, signal sequences, downstream untranslated sequences, transcriptional start and stop sequences, polyadenylation signals, translational start and stop sequences, ribosome binding sites, and the like.
  • its natural promoter i.e., the promoter with which the exons and introns of the gene are operably linked in a non-recombinant cell, i.e., a naturally occurring cell
  • associated regulatory sequences may or may not have sequences upstream of the AUG start site, and may or may not include untranslated leader sequences, signal sequences, downstream untranslated sequences, transcriptional start and stop sequences, polyadenylation
  • a “protein coding sequence” or a sequence that “encodes” a particular polypeptide or peptide is a nucleic acid sequence that is transcribed (in the case of DNA) and is translated (in the case of mRNA) into a polypeptide in vitro or in vivo when placed under the control of appropriate regulatory sequences.
  • the boundaries of the coding sequence are determined by a start codon at the 5′ (amino) terminus and a translation stop codon at the 3′ (carboxy) terminus.
  • a coding sequence can include, but is not limited to, cDNA from viral, procaryotic or eukaryotic mRNA, genomic DNA sequences from viral, procaryotic or eukaryotic DNA, and even synthetic DNA sequences.
  • a transcription termination sequence may be located 3′ to the coding sequence.
  • reference and “control” are used interchangebly to refer to a known value or set of known values against which an observed value may be compared.
  • known means that the value represents an understood parameter, e.g., a level of expression of a marker gene in a graft survival or loss phenotype.
  • nucleic acid includes DNA, RNA (double-stranded or single stranded), analogs (e.g., PNA or LNA molecules) and derivatives thereof.
  • ribonucleic acid and RNA as used herein mean a polymer composed of ribonucleotides.
  • deoxyribonucleic acid and “DNA” as used herein mean a polymer composed of deoxyribonucleotides.
  • mRNA means messenger RNA.
  • oligonucleotide generally refers to a nucleotide multimer of about 10 to 100 nucleotides in length, while a “polynucleotide” includes a nucleotide multimer having any number of nucleotides.
  • polypeptide refers to a polymer of amino acids (amino acid sequence) and does not refer to a specific length of the molecule. Thus peptides and oligopeptides are included within the definition of polypeptide. This term does also refer to or include post-translational modifications of the polypeptide, for example, glycosylations, acetylations, phosphorylation and the like. Included within the definition are, for example, polypeptides containing one or more analogs of an amino acid, polypeptides with substituted linkages, as well as other modifications known in the art, both naturally occurring and non-naturally occurring.
  • assessing and “evaluating” are used interchangeably to refer to any form of measurement, and includes determining if an element is present or not.
  • determining includes determining if an element is present or not.
  • assessing includes determining if an element is present or not.
  • determining includes determining if an element is present or not.
  • assessing includes determining if an element is present or not.
  • determining includes determining if an element is present or not.
  • determining means determining determining,” “measuring,” “assessing,” and “assaying” are used interchangeably and include both quantitative and qualitative determinations. Assessing may be relative or absolute. “Assessing the presence of” includes determining the amount of something present, as well as determining whether it is present or absent.
  • FIG. 1 Predictive Analysis of Microarrays (PAM) using a set of 3,170 differentially expressed genes identifies the 33 classifiers with similar power ( FIG. 1A ). The PAM classification scores grouped the samples with 100% concordance to assigned classes and reported scores are aligned with the clustered samples ( FIG. 1B ).
  • PAM Microarrays
  • FIG. 2 Kaplan-Meier survival analysis for graft loss (red) and no-loss (blue).
  • FIG. 3 Kaplan-Meier survival curves for 8 genes from whole blood samples that are predictive of graft loss. Genes include AHSA2 ( FIG. 3A ), IGHG1 ( FIG. 3B ), IFNAR2 ( FIG. 3C ), IGKC ( FIG. 3D ), HIST1H2BC ( FIG. 3E ), IL1R2 ( FIG. 3F ), MAPK1 ( FIG. 3G ), and MAPK9 ( FIG. 3H ).
  • AHSA2 FIG. 3A
  • IGHG1 FIG. 3B
  • IFNAR2 FIG. 3C
  • IGKC FIG. 3D
  • HIST1H2BC FIG. 3E
  • IL1R2 FIG. 3F
  • MAPK1 FIG. 3G
  • MAPK9 FIG. 3H
  • FIG. 4 Demonstrates that gene expression is generally uniform/consistent across the full clinical groups analyzed as the gene expression levels segregate well within patient groups.
  • Methods are provided for evaluating a subject for graft function, e.g., in terms of predicting graft survival, identifying the presence of a deleterious graft condition, such as CAN and DT, identifying the severity and class of acute rejection, etc, in a subject are provided.
  • the expression of at least one gene in a sample from the subject e.g., a blood or biopsy sample, is assayed, e.g., at the nucleic acid and/or protein level, to evaluate the subject.
  • compositions, systems and kits that find use in practicing the subject methods. The methods and compositions find use in a variety of applications.
  • the subject invention is directed to methods of evaluating graft function in a subject, as well as reagents and kits for use in practicing the subject methods.
  • the subject methods are described first, followed by a review of the reagents and kits for use in practicing the subject methods.
  • the subject invention provides methods for evaluating a subject for graft survival.
  • the methods provide for evaluating a subject for graft survival in terms of a number of different factors.
  • the factor evaluated is a basic prediction of graft survival.
  • the factor evaluated is the presence of a deleterious graft condition, such as CAN and DT.
  • the factor identified is the severity and/or class of acute rejection, where these embodiments are distinguished from methods that just identify the presence of acute rejection, since one is further determining the severity and/or class of acute rejection, and therefore an aspect of graft survival
  • certain embodiments of the invention provide methods of evaluating, e.g., in terms of predicting, graft survival in a subject comprising a graft.
  • the subject invention provides methods of evaluating whether a graft in a transplant patient or subject will survive or be lost.
  • the methods may be viewed as methods of determining whether a transplant subject has a graft survival phenotype, i.e., a phenotype in which the graft will survive.
  • a graft survival phenotype is a phenotype characterized by the presence of long-term graft survival.
  • graft survival is meant graft survival for at least about 5 years beyond current sampling, despite the occurrence of one or more prior episodes of AR.
  • graft survival is determined for patients in which at least one episode of acute rejection (AR) has occurred.
  • these embodiments are methods of determining or predicting graft survival following AR.
  • Graft survival is determined or predicted in certain embodiments in the context of transplant therapy, e.g., immunosuppressive therapy, where immunosuppressive therapies are known in the art.
  • methods of distinguishing being organ rejection disease conditions, such as CAN and DT are provided.
  • methods of determining the class and/or severity of acute rejection are provided.
  • the graft organ, tissue or cell(s) may be allogeneic or xenogeneic, such that the grafts may be allografts or xenografts.
  • Organs and tissues of interest include, but are not limited to: skin, heart, kidney, liver, bone marrow, and other organs.
  • a subject or patient sample e.g., cells or collections thereof, e.g., tissues
  • graft survival in the host e.g., whether the graft will survive in the host from which the assayed sample was obtained.
  • the first step of the subject methods is to obtain a suitable sample from the subject or patient of interest, i.e., a patient having at least one graft, e.g., allograft.
  • sample sources of interest include, but are not limited to, many different physiological sources, e.g., CSF, urine, saliva, tears, tissue derived samples, e.g., homogenates (such as biopsy samples of the transplanted tissue or organ (including, but not limited to kidney, heart, lung biopsies), and blood or derivatives thereof.
  • physiological sources e.g., CSF, urine, saliva, tears
  • tissue derived samples e.g., homogenates (such as biopsy samples of the transplanted tissue or organ (including, but not limited to kidney, heart, lung biopsies), and blood or derivatives thereof.
  • a suitable initial source for the patient sample is blood.
  • the sample employed in the subject assays of these embodiments is generally a blood-derived sample.
  • the blood derived sample may be derived from whole blood or a fraction thereof, e.g., serum, plasma, etc., where in certain embodiments the sample is derived from blood cells harvested from whole blood.
  • PBL peripheral blood lymphocytes
  • Any convenient protocol for obtaining such samples may be employed, where suitable protocols are well known in the art and a representative protocol is reported in the Experimental Section, below.
  • the sample is assayed to obtain an expression evaluation, e.g., expression profile, for one or more genes, where the term expression profile is used broadly to include a genomic expression profile, e.g., an expression profile of nucleic acid transcripts, e.g., mRNAs, of the one or more genes of interest, or a proteomic expression profile, e.g., an expression profile of one or more different proteins, where the proteins/polypeptides are expression products of the one or more genes of interest.
  • an expression evaluation e.g., expression profile
  • expression profile is used broadly to include a genomic expression profile, e.g., an expression profile of nucleic acid transcripts, e.g., mRNAs, of the one or more genes of interest, or a proteomic expression profile, e.g., an expression profile of one or more different proteins, where the proteins/polypeptides are expression products of the one or more genes of interest.
  • the expression of only one gene is evaluated.
  • the expression of two or more, e.g., about 5 or more, about 10 or more, about 15 or more, about 25 or more, about 50 or more, about 100 or more, about 200 or more, etc., genes is evaluated. Accordingly, in the subject methods, the expression of at least one gene in a sample is evaluated. In certain embodiments, the evaluation that is made may be viewed as an evaluation of the transcriptosome, as that term is employed in the art. See e.g., Gomes et al., Blood (2001 Jul. 1) 98(1): 93-9.
  • a sample is assayed to generate an expression profile that includes expression data for at least one gene/protein, usually a plurality of genes/proteins, where by plurality is meant at least two different genes/proteins, and often at least about 5, typically at least about 10 and more usually at least about 20 different genes/proteins or more, such as 50 or more, 100 or more, etc.
  • the expression evaluation may be qualitative or quantitative.
  • the methods provide a reading or evaluation, e.g., assessment, of whether or not the target analyte, e.g., nucleic acid or expression product, is present in the sample being assayed.
  • the methods provide a quantitative detection of whether the target analyte is present in the sample being assayed, i.e., an evaluation or assessment of the actual amount or relative abundance of the target analyte, e.g., nucleic acid in the sample being assayed.
  • the quantitative detection may be absolute or, if the method is a method of detecting two or more different analytes, e.g., target nucleic acids, in a sample, relative.
  • the term “quantifying” when used in the context of quantifying a target analyte, e.g., nucleic acid(s), in a sample can refer to absolute or to relative quantification.
  • Absolute quantification may be accomplished by inclusion of known concentration(s) of one or more control analytes and referencing the detected level of the target analyte with the known control analytes (e.g., through generation of a standard curve).
  • relative quantification can be accomplished by comparison of detected levels or amounts between two or more different target analytes to provide a relative quantification of each of the two or more different analytes, e.g., relative to each other.
  • Genes/proteins of interest are graft survival/loss indicative genes, i.e., genes/proteins that are differentially expressed or present at different levels in graft survival and graft loss individuals (more specifically, individuals in which graft loss will occur vs. individuals in which a graft will survive).
  • Representative genes/proteins of interest in certain embodiments include, but are not limited to, the genes/proteins provided in Tables 1 and 2.
  • At least one of the genes/proteins in the prepared expression profile is a graft survival/rejection indicative gene from Tables 1 and/or 2, where the expression profile may include expression data for 5, 10, 20, 50, 75 or more of, including all of, the genes/proteins listed in Tables 1 and/or 2.
  • the number of different genes/proteins whose expression and/or quantity data, i.e., presence or absence of expression, as well as expression/quantity level, that are included in the expression profile that is generated may vary, but may be at least 2, and in certain embodiments ranges from 2 to about 100 or more, sometimes from 3 to about 75 or more, including from about 4 to about 70 or more.
  • additional genes beyond those listed in Tables 1 and/or 2 may be assayed, such as genes whose expression pattern can be used to evaluate additional transplant characteristics, including but not limited to: acute rejection (e.g., the genes identified as AR in Table 3, below); chronic allograft injury (chronic rejection) in blood (e.g., the genes identified as CR in Table 3, below); immunosuppressive drug toxicity or adverse side effects including drug-induced hypertension (e.g., the genes identified as DT in Table 3, below); age or body mass index associated genes that correlate with renal pathology or account for differences in recipient age-related graft acceptance (e.g., the genes identified as BMI in Table 3, below); immune tolerance markers in whole blood (e.g., the genes identified as TOL in Table 3, below); genes found in literature surveys with immune modulatory roles that may play a role in transplant outcomes (e.g., the genes identified as Lit.
  • acute rejection e.g., the genes identified as AR in Table 3, below
  • CASP3 Caspase 3 apoptosis-related cysteine protease NM_004346 All Lit.
  • CASP4 Caspase 4 apoptosis-related cysteine protease NM_001225 All Lit.
  • CASP7 Caspase 7 apoptosis-related cysteine protease NM_001227 All Lit.
  • CASP9 Caspase 9 apoptosis-related cysteine protease NM_001229 All Lit.
  • CD20 Membrane-spanning 4A1 NM_152866 All Lit.
  • CD48 CD48 antigen B-cell membrane protein
  • CD80 CD80 antigen B7-1 antigen
  • CDA08 T-cell immunomodulatory protein NM_030790 All Lit. CDC2 Cell division cycle 2, G1 to S and G2 to M NM_001786 All Lit.
  • CDW52 CDW52 antigen (CAMPATH-1 antigen) NM_001803 All Lit.
  • CIS4 STAT induced STAT inhibitor-4 NM_004232 All Lit.
  • ICAM3 Intercellular adhesion molecule 3 NM_002162 All Lit.
  • IRF1 Interferon regulatory factor 1 NM_002198 All Lit. ITGAE Integrin, alpha E (CD103) NM_002208 All Lit. JAK1 Janus kinase 1 NM_002227 All Lit. JAK2 Janus kinase 2 NM_004972 All Lit. MADH2 SMAD, mothers against DPP NM_005901 All Lit. MAPK3 Mitogen-activated protein kinase 3 NM_002746 All Lit. MDM2 p53 binding protein NM_002392 All Lit. MHC2TA MHC class II transactivator NM_000246 All Lit. NK4 Natural killer cell transcript 4 NM_004221 All Lit.
  • TLR5 Toll-like receptor 5 NM_003268 All Lit. TNFRSF1A TNF receptor superfamily, member 1A NM_001065 All Lit. TNFRSF1B TNF receptor superfamily, member 1B NM_001066 All Lit. TNFSF7 TNF (ligand) superfamily, member 7 NM_001252 All Lit. TP53BP1 Tumor protein p53 binding protein, 1 NM_005657 All Lit. TP53BP2 Tumor protein p53 binding protein, 2 NM_005426 All Lit. TRAF1 TNF receptor-associated factor 1 NM_005658 All Lit. TRAF2 TNF receptor-associated factor 2 NM_021138 All Lit.
  • TRAF3 TNF receptor-associated factor 3 NM_003300 All Lit.
  • TRAF4 TNF receptor-associated factor 4 NM_004295 All Lit.
  • TRAP1 TNF receptor-associated protein 1 NM_004257 All Lit.
  • UBE1L Ubiquitin-activating enzyme E1-like NM_003335 All Lit.
  • VPREB3 Pre-B lymphocyte gene 3 NM_013378 All Lit. WNT1 MMTV integration site (WNT1) NM_005430 All Lit. ACE1 Ig receptor (PIGR) IgA nephritis NM_002644 All Lit. BAX BCL2-associated X protein NM_138763 All Lit.
  • a collection of genes from Table 3 is assayed, where in these embodiments the number of genes from Table 3 may be at least about 5%, at least about 10%, at least about 25%, at least about 50%, at least about 75%, at least about 90% or more, including all of the genes from Table 3.
  • the expression profile obtained is a genomic or nucleic acid expression profile, where the amount or level of one or more nucleic acids in the sample is determined, e.g., the nucleic acid transcript of the gene of interest.
  • the sample that is assayed to generate the expression profile employed in the diagnostic methods is one that is a nucleic acid sample.
  • the nucleic acid sample includes a plurality or population of distinct nucleic acids that includes the expression information of the phenotype determinative genes of interest of the cell or tissue being diagnosed.
  • the nucleic acid may include RNA or DNA nucleic acids, e.g., mRNA, cRNA, cDNA etc., so long as the sample retains the expression information of the host cell or tissue from which it is obtained.
  • the sample may be prepared in a number of different ways, as is known in the art, e.g., by mRNA isolation from a cell, where the isolated mRNA is used as is, amplified, employed to prepare cDNA, cRNA, etc., as is known in the differential expression art.
  • the sample is prepared from a cell or tissue harvested from a subject to be diagnosed, e.g., via biopsy of tissue, using standard protocols, where cell types or tissues from which such nucleic acids may be generated include any tissue in which the expression pattern of the to be determined phenotype exists, including, but not limited to, peripheral blood lymphocyte cells, etc, as reviewed above.
  • the expression profile may be generated from the initial nucleic acid sample using any convenient protocol. While a variety of different manners of generating expression profiles are known, such as those employed in the field of differential gene expression analysis, one representative and convenient type of protocol for generating expression profiles is array-based gene expression profile generation protocols. In certain embodiments, such applications are hybridization assays in which a nucleic acid array that displays “probe” nucleic acids for each of the genes to be assayed/profiled in the profile to be generated is employed. In these assays, a sample of target nucleic acids is first prepared from the initial nucleic acid sample being assayed, where preparation may include labeling of the target nucleic acids with a label, e.g., a member of signal producing system.
  • a label e.g., a member of signal producing system.
  • target nucleic acid sample preparation Following target nucleic acid sample preparation, the sample is contacted with the array under hybridization conditions, whereby complexes are formed between target nucleic acids that are complementary to probe sequences attached to the array surface. The presence of hybridized complexes is then detected, either qualitatively or quantitatively.
  • Specific hybridization technology which may be practiced to generate the expression profiles employed in the subject methods includes the technology described in U.S. Pat. Nos.
  • the resultant pattern of hybridized nucleic acid provides information regarding expression for each of the genes that have been probed, where the expression information is in terms of whether or not the gene is expressed and, typically, at what level, where the expression data, i.e., expression profile (e.g., in the form of a transcriptosome), may be both qualitative and quantitative.
  • non-array based methods for quantitating the levels of one or more nucleic acids in a sample may be employed, including quantitative PCR, and the like.
  • any convenient protein quantitation protocol may be employed, where the levels of one or more proteins in the assayed sample are determined.
  • Representative methods include, but are not limited to: proteomic arrays, flow cytometry, standard immunoassays (e.g., ELISA assays), protein activity assays, including multiplex protein activity assays, etc.
  • the expression profile is compared with a reference or control profile to determine the particular graft tolerant/intolerant phenotype of the cell or tissue, and therefore host, from which the sample was obtained/derived.
  • the terms “reference” and “control” as used herein mean a standardized pattern of gene expression or levels of expression of certain genes to be used to interpret the expression signature of a given patient and assign a graft tolerant/intolerant phenotype thereto.
  • the reference or control profile may be a profile that is obtained from a cell/tissue known to have the desired phenotype, e.g., tolerant phenotype, and therefore may be a positive reference or control profile.
  • the reference/control profile may be from a cell/tissue known to not have the desired phenotype, e.g., an intolerant phenotype, and therefore be a negative reference/control profile.
  • the obtained expression profile is compared to a single reference/control profile to obtain information regarding the phenotype of the cell/tissue being assayed. In yet other embodiments, the obtained expression profile is compared to two or more different reference/control profiles to obtain more in depth information regarding the phenotype of the assayed cell/tissue. For example, the obtained expression profile may be compared to a positive and negative reference profile to obtain confirmed information regarding whether the cell/tissue has the phenotype of interest.
  • the comparison of the obtained expression profile and the one or more reference/control profiles may be performed using any convenient methodology, where a variety of methodologies are known to those of skill in the array art, e.g., by comparing digital images of the expression profiles, by comparing databases of expression data, etc.
  • Patents describing ways of comparing expression profiles include, but are not limited to, U.S. Pat. Nos. 6,308,170 and 6,228,575, the disclosures of which are herein incorporated by reference. Methods of comparing expression profiles are also described above.
  • the comparison step results in information regarding how similar or dissimilar the obtained expression profile is to the control/reference profile(s), which similarity/dissimilarity information is employed to determine the phenotype of the cell/tissue being assayed and thereby evaluate graft survival in the subject. For example, similarity with a positive control indicates that the assayed cell/tissue has a graft survival phenotype. Likewise, similarity with a negative control indicates that the assayed cell/tissue has a graft loss phenotype.
  • the above comparison step yields a variety of different types of information regarding the cell/tissue that is assayed.
  • the above comparison step can yield a positive/negative determination of a graft survival phenotype of an assayed cell/tissue.
  • the above-obtained information about the cell/tissue being assayed is employed to diagnose a host, subject or patient with respect to graft survival, as described above.
  • the determination/prediction of graft survival and loss can be coupled with a determination of additional characteristics of the graft and function thereof.
  • the first 9 genes in the cluster illustrated in FIG. 4 are highly-differentially expressed between CAN and DT. As such, evaluating one or more of these genes permits these two overlapping conditions to be readily distinguished, such that one can readily determine the presence of CAN or DT.
  • a subject/host/patient is first diagnosed for graft function according to the subject invention, and then treated using a protocol determined, at least in part, on the results of the diagnosis. For example, a host may be evaluated for the presence of absence of the graft survival phenotype using a protocol such as the diagnostic protocol described in the preceding section. The subject may then be treated using a protocol whose suitability is determined using the results of the diagnosis step. In embodiments, where the host is evaluated for the presence or absence of CAN or DT, treatment protocols may correspondingly be adjusted based on the obtained results.
  • immunosuppressive therapy can be modulated, e.g., increased or drugs changed, as is known in the art for the treatment of CAN.
  • the immunosuppressive therapy can be reduced in order to treat the DT.
  • a subject is typically screened for the presence of a graft survival or loss phenotype following receipt of a graft or transplant.
  • the subject may be screened once or serially following transplant receipt, e.g., weekly, monthly, bimonthly, half-yearly, yearly, etc.
  • the subject is screened following occurrence of acute rejection (AR).
  • the methods are employed to evaluate, e.g., predict, ultimate graft loss or survival in the subject following AR.
  • the subject methods may be employed with a variety of different types of transplant subjects.
  • the subjects are within the class mammalian, including the orders carnivore (e.g., dogs and cats), rodentia (e.g., mice, guinea pigs, and rats), lagomorpha (e.g. rabbits) and primates (e.g., humans, chimpanzees, and monkeys).
  • the animals or hosts i.e., subjects (also referred to herein as patients) will be humans.
  • Grafts of interest include, but are not limited to: transplanted heart, kidney, lung, liver, pancreas, pancreatic islets, brain tissue, stomach, large intestine, small intestine, cornea, skin, trachea, bone, bone marrow, muscle, bladder or parts thereof.
  • databases of expression profiles of graft survival and/or graft loss phenotype determinative genes will typically comprise expression profiles of various cells/tissues having graft tolerant phenotypes, negative expression profiles, etc., where such profiles are further described below.
  • the expression profiles and databases thereof may be provided in a variety of media to facilitate their use.
  • Media refers to a manufacture that contains the expression profile information of the present invention.
  • the databases of the present invention can be recorded on computer readable media, e.g. any medium that can be read and accessed directly by a computer. Such media include, but are not limited to: magnetic storage media, such as floppy discs, hard disc storage medium, and magnetic tape; optical storage media such as CD-ROM; electrical storage media such as RAM and ROM; and hybrids of these categories such as magnetic/optical storage media.
  • magnetic storage media such as floppy discs, hard disc storage medium, and magnetic tape
  • optical storage media such as CD-ROM
  • electrical storage media such as RAM and ROM
  • hybrids of these categories such as magnetic/optical storage media.
  • Recorded refers to a process for storing information on computer readable medium, using any such methods as known in the art. Any convenient data storage structure may be chosen, based on the means used to access the stored information. A variety of data processor programs and formats can be used for storage, e.g. word processing text file, database format, etc.
  • a computer-based system refers to the hardware means, software means, and data storage means used to analyze the information of the present invention.
  • the minimum hardware of the computer-based systems of the present invention comprises a central processing unit (CPU), input means, output means, and data storage means.
  • CPU central processing unit
  • input means input means
  • output means output means
  • data storage means may comprise any manufacture comprising a recording of the present information as described above, or a memory access means that can access such a manufacture.
  • a variety of structural formats for the input and output means can be used to input and output the information in the computer-based systems of the present invention.
  • One format for an output means ranks expression profiles possessing varying degrees of similarity to a reference expression profile. Such presentation provides a skilled artisan with a ranking of similarities and identifies the degree of similarity contained in the test expression profile.
  • reagents, systems and kits thereof for practicing one or more of the above-described methods.
  • the subject reagents, systems and kits thereof may vary greatly.
  • Reagents of interest include reagents specifically designed for use in production of the above-described expression profiles of phenotype determinative genes, i.e., a gene expression evaluation element made up of one or more reagents.
  • system refers to a collection of reagents, however compiled, e.g., by purchasing the collection of reagents from the same or different sources.
  • kit refers to a collection of reagents provided, e.g., sold, together.
  • One type of such reagent is an array of probe nucleic acids in which the phenotype determinative genes of interest are represented.
  • array formats are known in the art, with a wide variety of different probe structures, substrate compositions and attachment technologies.
  • Representative array structures of interest include those described in U.S. Pat. Nos.
  • the arrays include probes for at least 1 of the genes listed in Tables 1 and/or 2. In certain embodiments, the number of genes that are from Tables 1 and/or 2 that is represented on the array is at least 5, at least 10, at least 25, at least 50, at least 75 or more, including all of the genes listed in Tables 1 and/or 2.
  • the subject arrays may include only those genes that are listed in Tables 1 and/or 2, or they may include additional genes that are not listed in Tables 1 and/or 2, such as probes for genes whose expression pattern can be used to evaluate additional transplant characteristics, including but not limited to: acute rejection; chronic allograft injury (chronic rejection) in blood; immunosuppressive drug toxicity or adverse side effects including drug-induced hypertension; age or body mass index associated genes that correlate with renal pathology or account for differences in recipient age-related graft acceptance; immune tolerance markers in whole blood; genes found in literature surveys with immune modulatory roles that may play a role in transplant outcomes (see e.g., Table 3 for a list of representative additional genes); as well as other array assay function related genes, e.g., for assessing sample quality (3′- to 5′-bias in probe location), sampling error in biopsy-based studies, cell surface markers, and normalizing genes for calibrating hybridization results; and the like.
  • probes for genes whose expression pattern can be used to evaluate additional transplant characteristics including but not limited
  • the number % of additional genes that are represented and are not directly or indirectly related to transplantation does not exceed about 50%, usually does not exceed about 25%.
  • additional genes are included, a great majority of genes in the collection are transplant characterization genes, where by great majority is meant at least about 75%, usually at least about 80% and sometimes at least about 85, 90, 95% or higher, including embodiments where 100% of the genes in the collection are phenotype determinative genes.
  • Transplant characterization genes are genes whose expression can be employed to characterize transplant function in some manner, e.g., presence of rejection, etc.
  • Another type of reagent that is specifically tailored for generating expression profiles of phenotype determinative genes is a collection of gene specific primers that is designed to selectively amplify such genes.
  • Gene specific primers and methods for using the same are described in U.S. Pat. No. 5,994,076, the disclosure of which is herein incorporated by reference.
  • Of particular interest are collections of gene specific primers that have primers for at least 1 of the genes listed in one Tables 1 and/or 2, often a plurality of these genes, e.g., at least 2, 5, 10, 15 or more.
  • the number of genes that are from Tables 1 and/or 2 that have primers in the collection is at least 5, at least 10, at least 25, at least 50, at least 75 or more, including all of the genes listed in Tables 1 and/or 2.
  • the subject gene specific primer collections may include only those genes that are listed in Tables 1 and/or 2, or they may include primers for additional genes that are not listed in Tables 1 and/or 2, such as probes for genes whose expression pattern can be used to evaluate additional transplant characteristics, including but not limited to: acute rejection; chronic allograft injury (chronic rejection) in blood; immunosuppressive drug toxicity or adverse side effects including drug-induced hypertension; age or body mass index associated genes that correlate with renal pathology or account for differences in recipient age-related graft acceptance; immune tolerance markers in whole blood; genes found in literature surveys with immune modulatory roles that may play a role in transplant outcomes (see e.g., Table 3 for a list of representative additional genes); as well as other array assay function related genes, e.g., for assessing
  • the subject arrays include probes for such additional genes
  • the number % of additional genes that are represented and are not directly or indirectly related to transplantation does not exceed about 50%, usually does not exceed about 25%.
  • additional genes are included, a great majority of genes in the collection are transplant characterization genes, where by great majority is meant at least about 75%, usually at least about 80% and sometimes at least about 85, 90, 95% or higher, including embodiments where 100% of the genes in the collection are phenotype determinative genes.
  • the systems and kits of the subject invention may include the above-described arrays and/or gene specific primer collections.
  • the systems and kits may further include one or more additional reagents employed in the various methods, such as primers for generating target nucleic acids, dNTPs and/or rNTPs, which may be either premixed or separate, one or more uniquely labeled dNTPs and/or rNTPs, such as biotinylated or Cy3 or Cy5 tagged dNTPs, gold or silver particles with different scattering spectra, or other post synthesis labeling reagent, such as chemically active derivatives of fluorescent dyes, enzymes, such as reverse transcriptases, DNA polymerases, RNA polymerases, and the like, various buffer mediums, e.g.
  • hybridization and washing buffers prefabricated probe arrays, labeled probe purification reagents and components, like spin columns, etc.
  • signal generation and detection reagents e.g. streptavidin-alkaline phosphatase conjugate, chemifluorescent or chemiluminescent substrate, and the like.
  • the subject systems and kits may also include a phenotype determination element, which element is, in many embodiments, a reference or control expression profile that can be employed, e.g., by a suitable computing means, to make a phenotype determination based on an “input” expression profile, e.g., that has been determined with the above described gene expression evaluation element.
  • phenotype determination elements include databases of expression profiles, e.g., reference or control profiles, as described above.
  • the subject kits will further include instructions for practicing the subject methods. These instructions may be present in the subject kits in a variety of forms, one or more of which may be present in the kit.
  • One form in which these instructions may be present is as printed information on a suitable medium or substrate, e.g., a piece or pieces of paper on which the information is printed, in the packaging of the kit, in a package insert, etc.
  • Yet another means would be a computer readable medium, e.g., diskette, CD, etc., on which the information has been recorded.
  • Yet another means that may be present is a website address which may be used via the internet to access the information at a removed site. Any convenient means may be present in the kits.
  • the objective of this study was to determine whether gene expression markers could be identified in RNA extracted from peripheral blood leukocytes (PBL) or renal biopsies predictive of future graft loss following AR.
  • RNA was isolated (Tri Reagent; MRC Inc., Cincinnati, Ohio) from buffy coats isolated from whole blood samples.
  • a common reference RNA pool (Perou et al., Nature (2000) 406:747-52) was used as an internal standard. Sample or reference RNA were subjected to two successive rounds of amplification before hybridization to microarrays using an improved protocol based on the method described by Wang et al (please provide entire cite).
  • Array data for 62 renal biopsy samples and 56 whole blood samples were stored in the Stanford Microarray database (Sherlock et al., Nuc. Acids Res.
  • AR expression overlaps with the innate immune response to infection, as evidenced by cluster analysis and by differential expression of several TGF- ⁇ -modulated genes including RANTES, MIC-1, several cytokines, chemokines, and cell-adhesion molecules.
  • AR-1 is the most severe class with the highest rate of graft loss and highest expression of B-cell specific genes.
  • AR-2 resembles a drug-toxicity signature and also co-clusters with patients with active viral infections.
  • the most striking feature of AR-3 is the expression of genes involved in cellular proliferation and cell cycling suggesting active tissue repair and regeneration. The presence of proliferating-cell nuclear antigen (PCNA), a marker of cell proliferation, was confirmed in all AR-3 samples tested (Sarwal et al. New Engl. J. Med. 2003 349(2):125-38).
  • PCNA proliferating-cell nuclear antigen
  • FIG. 2 Kaplan-Meier survival analysis for graft loss (red) and no-loss (blue.
  • the gene signature is dominated by increased expression of cell adhesion genes, selected cytokines, B-cell genes, representatives in the STAT signaling pathway and several immune response genes including multiple representatives of both class I and class II HLA genes.
  • HLA-F HLA-F
  • HLA-G HLA class II
  • HLA-DRB HLA class II
  • HLA-DRB4 signal transducers
  • STAT1 STAT6 immunoglobulin genes
  • ICM5 interferon gamma induced genes
  • the Kaplan-Meier survival curves for 8 of these genes are illustrated in FIG. 3 .
  • the genes in FIG. 3 include A) AHSA2, B) IGHG1, C) IFNAR2, D) IGKC, E) HIST1H2BC, F) IL1R2, G) MAPK1, and H) MAPK9.
  • Acute rejection including markers associated with graft loss and/or rate of recovery of renal function following AR (Table 3);
  • Control genes for assessing sample quality (3′- to 5′-bias in probe location), sampling error in biopsy-based studies, cell surface markers, and normalizing genes for calibrating hybridization results;
  • FIG. 4 illustrates that the gene expression is generally uniform/consistent across the full clinical groups analyzed as the gene expression levels segregate well within patient groups. Further, within each group (DT, CAN, AR or Normal) expression levels of these marker genes are independent of immunosuppression use.
  • the 479 gene list of Table 3 comprises design and specification for a customized thematic Transplant Chip (TxChip V1) and full-length mRNA sequences for these genes are listed in Table 3.
  • the gene listing is cross-indexed to the studies listed above. We observe a modest overlap in the list of informative genes. For example, expression levels of IGHM positively correlate with acute rejection risk and negatively correlate with immune tolerance.
  • An advantage of having the full compilation of genes on a common platform is that new discoveries like this can be made in future studies.
  • subject invention provides a convenient and effective way of determining whether a graft in a subject will survive, e.g., following acute rejection.
  • the subject invention provides a number of distinct benefits, including the ability to identify clinically relevant AR groups with differing therapeutic responses and prognosis, and allow for individualized treatment and monitoring. As such, the subject invention represents a significant contribution to the art.

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Abstract

Methods are provided for evaluating a subject for graft survival, e.g., in terms of predicting graft survival, identifying the presence of a deleterious graft condition, such as CAN and DT, identifying the severity and class of acute rejection, etc, in a subject are provided. In practicing the subject methods, the expression of at least one gene in a sample from the subject, e.g., a blood or biopsy sample, is assayed, e.g., at the nucleic acid and/or protein level, to evaluate the subject. Also provided are compositions, systems and kits that find use in practicing the subject methods. The methods and compositions find use in a variety of applications.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS
Notice: More than one reissue application has been filed for the reissue of U.S. Pat. No. 7,741,038. The reissue applications are application Ser. No. 13/529,768 (the present application), and Ser. No. 13/943,626, filed Jul. 16, 2013 (a continuation reissue application).
Pursuant to 35 U.S.C. §119 (e), this application This application is a Reissue of U.S. Pat. No. 7,741,038, which patent issued on Jun. 22, 2010, and which patent claims priority to the filing date of U.S. Provisional Patent Application Ser. No. 60/662,083 filed on Mar. 14, 2005; the disclosure of which application is herein incorporated by reference.
BACKGROUND
Transplantation of a graft organ or tissue from a donor to a host patient is a feature of certain medical procedures and treatment protocols. Despite efforts to avoid graft rejection through host-donor tissue type matching, in transplantation procedures where a donor organ is introduced into a host, immunosuppressive therapy is generally required to the maintain viability of the donor organ in the host.
After an organ has been transplanted into the patient, the patient's immune system is suppressed to prevent rejection of the new organ. Despite the wide use of immunosuppressive therapy, organ transplant rejection can occur.
Organ transplant rejection comprises three separate categories: hyperacute, acute and chronic. Hyperacute rejection is characterized by rapid thrombotic occlusion of the graft vasculature within minutes to hours after organ transplantation. Hyperacute rejection is mediated in large part by preexisting antibodies that bind to the epithelium and activate the complement cascade. Complement activation results in endothelial cell damage and subsequent exposure of the basement membrane, resulting in the activation of platelets, leading to thrombosis and vascular occlusion. As the field of transplantation has matured, hyperacute rejection has become less common due to blood antigen and MHC molecule matching between the donor organ and the recipient.
Acute rejection is sub-classified into acute vascular rejection and acute cellular rejection. Acute vascular rejection is characterized by necrosis of individual cells in the graft blood vessels. The process is similar to that of hyperacute rejection, but onset is often slower, within one week of rejection, and a T cell component may be involved. Acute vascular rejection is initiated by a response to alloantigens present on the vascular endothelial cells of the donor organ, resulting in the release of a cytokine cascade, inflammation, and eventual necrosis. Acute cellular rejection is often characterized by necrosis of the essential or parenchymal cells of the transplanted organ caused by the infiltration of host T lymphocytes and macrophages. The lymphocytes involved are usually cytotoxic T lymphocytes (CTL) and macrophages, both resulting in lysis of targeted cells. The CTLs are usually specific for graft alloantigens displayed in the context of MHC class I molecules.
Chronic rejection is the major cause of allograft loss and is characterized by fibrosis and loss of normal organ structures. Fibrosis may be the result of wound healing following the cellular necrosis of acute rejection, or may occur independently and without prior acute rejection. In addition, chronic rejection may lead to vascular occlusions thought to stem from a delayed type hypersensitivity response to alloantigens present on the transplanted organ. These alloantigens stimulate lymphocytes to secrete cytokines which attract macrophages and other effector cells eventually leading to an arteriosclerosis-like blockage.
In many cases, chronic graft injury or rejection (CR) is largely due to calcineurin-inhibitor drug nephrotoxicity (DT) and chronic allograft nephropathy (CAN), two conditions which may result in loss of graft function and early graft loss, premature to the life expectancy of the recipient. The incidence of chronic graft loss has remained unchanged over the last decade.
A biopsy is the only current gold standard for CAN and DT diagnosis. As both conditions are progressive post-transplantation, multiple graft protocol biopsies are required. However, the invasiveness of biopsy procedures is a limitation to this form of monitoring. In addition, variability of biopsy sampling and pathology analysis (2) adds a confounder to the differential diagnosis of these 2 conditions—the result of either too much drug (DT) vs. too little/inappropriate drugs (CAN)—with a common outcome of chronic fibrotic injury from differing mechanisms (non-immune vs. immune).
There is currently no method available to detect or to monitor future graft loss at the time of transplantation or acute rejection (AR) episodes. AR is a risk factor both for eventual graft loss, delayed recovery of graft function and even chronic rejection. Non-invasive monitoring methods for AR stratification, CR, DT and developing or established tolerance is currently not available, but would be very valuable, as the transplant biopsy, though the current gold standard, fails to stratify or prognosticate AR, differentiate CR clearly from DT or diagnose tolerance.
Accordingly, of interest would be the ability to evaluate likelihood of graft survival in a transplant recipient, e.g., following an AR episode, such that treatment protocols for transplant patients may be customized.
SUMMARY OF THE INVENTION
Methods are provided for evaluating a subject for graft survival, e.g., in terms of predicting graft survival, identifying the presence of a deleterious graft condition, such as CAN and DT, identifying the severity and class of acute rejection, etc, in a subject are provided. In practicing the subject methods, the expression of at least one gene in a sample from the subject, e.g., a blood or biopsy sample, is assayed, e.g., at the nucleic acid and/or protein level, to evaluate the subject. Also provided are compositions, systems and kits that find use in practicing the subject methods.
DEFINITIONS
For convenience, certain terms employed in the specification, examples, and appended claims are collected here.
“Acute rejection or AR” is the rejection by the immune system of a tissue transplant recipient when the transplanted tissue is immunologically foreign. Acute rejection is characterized by infiltration of the transplanted tissue by immune cells of the recipient, which carry out their effector function and destroy the transplanted tissue. The onset of acute rejection is rapid and generally occurs in humans within a few weeks after transplant surgery. Generally, acute rejection can be inhibited or suppressed with immunosuppressive drugs such as rapamycin, cyclosporin A, anti-CD40L monoclonal antibody and the like.
“Chronic transplant rejection or CR” generally occurs in humans within several months to years after engraftment, even in the presence of successful immunosuppression of acute rejection. Fibrosis is a common factor in chronic rejection of all types of organ transplants. Chronic rejection can typically be described by a range of specific disorders that are characteristic of the particular organ. For example, in lung transplants, such disorders include fibroproliferative destruction of the airway (bronchiolitis obliterans); in heart transplants or transplants of cardiac tissue, such as valve replacements, such disorders include fibrotic atherosclerosis; in kidney transplants, such disorders include, obstructive nephropathy, nephrosclerorsis, tubulointerstitial nephropathy; and in liver transplants, such disorders include disappearing bile duct syndrome. Chronic rejection can also be characterized by ischemic insult, denervation of the transplanted tissue, hyperlipidemia and hypertension associated with immunosuppressive drugs.
The term “transplant rejection” encompasses both acute and chronic transplant rejection.
The term “stringent assay conditions” as used herein refers to conditions that are compatible to produce binding pairs of nucleic acids, e.g., surface bound and solution phase nucleic acids, of sufficient complementarity to provide for the desired level of specificity in the assay while being less compatible to the formation of binding pairs between binding members of insufficient complementarity to provide for the desired specificity. Stringent assay conditions are the summation or combination (totality) of both hybridization and wash conditions.
“Stringent hybridization conditions” and “stringent hybridization wash conditions” in the context of nucleic acid hybridization (e.g., as in array, Southern or Northern hybridizations) are sequence dependent, and are different under different experimental parameters. Stringent hybridization conditions that can be used to identify nucleic acids within the scope of the invention can include, e.g., hybridization in a buffer comprising 50% formamide, 5×SSC, and 1% SDS at 42° C., or hybridization in a buffer comprising 5×SSC and 1% SDS at 65° C., both with a wash of 0.2×SSC and 0.1% SDS at 65° C. Exemplary stringent hybridization conditions can also include hybridization in a buffer of 40% formamide, 1 M NaCl, and 1% SDS at 37° C., and a wash in 1×SSC at 45° C. Alternatively, hybridization to filter-bound DNA in 0.5 M NaHPO4, 7% sodium dodecyl sulfate (SDS), 1 mM EDTA at 65° C., and washing in 0.1×SSC/0.1% SDS at 68° C. can be employed. Yet additional stringent hybridization conditions include hybridization at 60° C. or higher and 3×SSC (450 mM sodium chloride/45 mM sodium citrate) or incubation at 42° C. in a solution containing 30% formamide, 1M NaCl, 0.5% sodium sarcosine, 50 mM MES, pH 6.5. Those of ordinary skill will readily recognize that alternative but comparable hybridization and wash conditions can be utilized to provide conditions of similar stringency.
In certain embodiments, the stringency of the wash conditions that set forth the conditions which determine whether a nucleic acid is specifically hybridized to a surface bound nucleic acid. Wash conditions used to identify nucleic acids may include, e.g.: a salt concentration of about 0.02 molar at pH 7 and a temperature of at least about 50° C. or about 55° C. to about 60° C.; or, a salt concentration of about 0.15 M NaCl at 72° C. for about 15 minutes; or, a salt concentration of about 0.2×SSC at a temperature of at least about 50° C. or about 55° C. to about 60° C. for about 15 to about 20 minutes; or, the hybridization complex is washed twice with a solution with a salt concentration of about 2×SSC containing 0.1% SDS at room temperature for 15 minutes and then washed twice by 0.1×SSC containing 0.1% SDS at 68° C. for 15 minutes; or, equivalent conditions. Stringent conditions for washing can also be, e.g., 0.2×SSC/0.1% SDS at 42° C.
A specific example of stringent assay conditions is rotating hybridization at 65° C. in a salt based hybridization buffer with a total monovalent cation concentration of 1.5 M (e.g., as described in U.S. patent application Ser. No. 09/655,482 filed on Sep. 5, 2000, the disclosure of which is herein incorporated by reference) followed by washes of 0.5×SSC and 0.1×SSC at room temperature.
Stringent assay conditions are hybridization conditions that are at least as stringent as the above representative conditions, where a given set of conditions are considered to be at least as stringent if substantially no additional binding complexes that lack sufficient complementarity to provide for the desired specificity are produced in the given set of conditions as compared to the above specific conditions, where by “substantially no more” is meant less than about 5-fold more, typically less than about 3-fold more. Other stringent hybridization conditions are known in the art and may also be employed, as appropriate.
As used herein, the term “gene” or “recombinant gene” refers to a nucleic acid comprising an open reading frame encoding a polypeptide, including exon and (optionally) intron sequences. The term “intron” refers to a DNA sequence present in a given gene that is not translated into protein and is generally found between exons in a DNA molecule. In addition, a gene may optionally include its natural promoter (i.e., the promoter with which the exons and introns of the gene are operably linked in a non-recombinant cell, i.e., a naturally occurring cell), and associated regulatory sequences, and may or may not have sequences upstream of the AUG start site, and may or may not include untranslated leader sequences, signal sequences, downstream untranslated sequences, transcriptional start and stop sequences, polyadenylation signals, translational start and stop sequences, ribosome binding sites, and the like.
A “protein coding sequence” or a sequence that “encodes” a particular polypeptide or peptide, is a nucleic acid sequence that is transcribed (in the case of DNA) and is translated (in the case of mRNA) into a polypeptide in vitro or in vivo when placed under the control of appropriate regulatory sequences. The boundaries of the coding sequence are determined by a start codon at the 5′ (amino) terminus and a translation stop codon at the 3′ (carboxy) terminus. A coding sequence can include, but is not limited to, cDNA from viral, procaryotic or eukaryotic mRNA, genomic DNA sequences from viral, procaryotic or eukaryotic DNA, and even synthetic DNA sequences. A transcription termination sequence may be located 3′ to the coding sequence.
The terms “reference” and “control” are used interchangebly to refer to a known value or set of known values against which an observed value may be compared. As used herein, known means that the value represents an understood parameter, e.g., a level of expression of a marker gene in a graft survival or loss phenotype.
The term “nucleic acid” includes DNA, RNA (double-stranded or single stranded), analogs (e.g., PNA or LNA molecules) and derivatives thereof. The terms “ribonucleic acid” and “RNA” as used herein mean a polymer composed of ribonucleotides. The terms “deoxyribonucleic acid” and “DNA” as used herein mean a polymer composed of deoxyribonucleotides. The term “mRNA” means messenger RNA. An “oligonucleotide” generally refers to a nucleotide multimer of about 10 to 100 nucleotides in length, while a “polynucleotide” includes a nucleotide multimer having any number of nucleotides.
The terms “protein” and “polypeptide” used in this application are interchangeable. “Polypeptide” refers to a polymer of amino acids (amino acid sequence) and does not refer to a specific length of the molecule. Thus peptides and oligopeptides are included within the definition of polypeptide. This term does also refer to or include post-translational modifications of the polypeptide, for example, glycosylations, acetylations, phosphorylation and the like. Included within the definition are, for example, polypeptides containing one or more analogs of an amino acid, polypeptides with substituted linkages, as well as other modifications known in the art, both naturally occurring and non-naturally occurring.
The term “assessing” and “evaluating” are used interchangeably to refer to any form of measurement, and includes determining if an element is present or not. The terms “determining,” “measuring,” “assessing,” and “assaying” are used interchangeably and include both quantitative and qualitative determinations. Assessing may be relative or absolute. “Assessing the presence of” includes determining the amount of something present, as well as determining whether it is present or absent.
BRIEF DESCRIPTION OF THE FIGURES
FIG. 1. Predictive Analysis of Microarrays (PAM) using a set of 3,170 differentially expressed genes identifies the 33 classifiers with similar power (FIG. 1A). The PAM classification scores grouped the samples with 100% concordance to assigned classes and reported scores are aligned with the clustered samples (FIG. 1B).
FIG. 2. Kaplan-Meier survival analysis for graft loss (red) and no-loss (blue). The genes include ICAM5 (FIG. 2A; p=0.007), IL6R (FIG. 2B; p=0.003), STAT1 (FIG. 2C; p=0.036), and STAT6 (FIG. 2D (p=0.020).
FIG. 3. Kaplan-Meier survival curves for 8 genes from whole blood samples that are predictive of graft loss. Genes include AHSA2 (FIG. 3A), IGHG1 (FIG. 3B), IFNAR2 (FIG. 3C), IGKC (FIG. 3D), HIST1H2BC (FIG. 3E), IL1R2 (FIG. 3F), MAPK1 (FIG. 3G), and MAPK9 (FIG. 3H).
FIG. 4. Demonstrates that gene expression is generally uniform/consistent across the full clinical groups analyzed as the gene expression levels segregate well within patient groups.
 DESCRIPTION OF THE SPECIFIC EMBODIMENTS
Methods are provided for evaluating a subject for graft function, e.g., in terms of predicting graft survival, identifying the presence of a deleterious graft condition, such as CAN and DT, identifying the severity and class of acute rejection, etc, in a subject are provided. In practicing the subject methods, the expression of at least one gene in a sample from the subject, e.g., a blood or biopsy sample, is assayed, e.g., at the nucleic acid and/or protein level, to evaluate the subject. Also provided are compositions, systems and kits that find use in practicing the subject methods. The methods and compositions find use in a variety of applications.
Before the present invention is described in greater detail, it is to be understood that this invention is not limited to particular embodiments described, as such may vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present invention will be limited only by the appended claims.
Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limit of that range and any other stated or intervening value in that stated range, is encompassed within the invention. The upper and lower limits of these smaller ranges may independently be included in the smaller ranges and are also encompassed within the invention, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present invention, representative illustrative methods and materials are now described.
All publications and patents cited in this specification are herein incorporated by reference as if each individual publication or patent were specifically and individually indicated to be incorporated by reference and are incorporated herein by reference to disclose and describe the methods and/or materials in connection with which the publications are cited. The citation of any publication is for its disclosure prior to the filing date and should not be construed as an admission that the present invention is not entitled to antedate such publication by virtue of prior invention. Further, the dates of publication provided may be different from the actual publication dates which may need to be independently confirmed.
It is noted that, as used herein and in the appended claims, the singular forms “a”, “an”, and “the” include plural referents unless the context clearly dictates otherwise. It is further noted that the claims may be drafted to exclude any optional element. As such, this statement is intended to serve as antecedent basis for use of such exclusive terminology as “solely,” “only” and the like in connection with the recitation of claim elements, or use of a “negative” limitation.
As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present invention. Any recited method can be carried out in the order of events recited or in any other order which is logically possible.
As summarized above, the subject invention is directed to methods of evaluating graft function in a subject, as well as reagents and kits for use in practicing the subject methods. In further describing the invention, the subject methods are described first, followed by a review of the reagents and kits for use in practicing the subject methods.
Methods of Evaluating Graft Function
As reviewed above, the subject invention provides methods for evaluating a subject for graft survival. The methods provide for evaluating a subject for graft survival in terms of a number of different factors. In certain embodiments, the factor evaluated is a basic prediction of graft survival. In certain embodiments, the factor evaluated is the presence of a deleterious graft condition, such as CAN and DT. In certain embodiments, the factor identified is the severity and/or class of acute rejection, where these embodiments are distinguished from methods that just identify the presence of acute rejection, since one is further determining the severity and/or class of acute rejection, and therefore an aspect of graft survival
As such, certain embodiments of the invention provide methods of evaluating, e.g., in terms of predicting, graft survival in a subject comprising a graft. As such, the subject invention provides methods of evaluating whether a graft in a transplant patient or subject will survive or be lost. In certain embodiments, the methods may be viewed as methods of determining whether a transplant subject has a graft survival phenotype, i.e., a phenotype in which the graft will survive. A graft survival phenotype is a phenotype characterized by the presence of long-term graft survival. By “long-term” graft survival is meant graft survival for at least about 5 years beyond current sampling, despite the occurrence of one or more prior episodes of AR. In certain embodiments, graft survival is determined for patients in which at least one episode of acute rejection (AR) has occurred. As such, these embodiments are methods of determining or predicting graft survival following AR. Graft survival is determined or predicted in certain embodiments in the context of transplant therapy, e.g., immunosuppressive therapy, where immunosuppressive therapies are known in the art. In yet other embodiments, methods of distinguishing being organ rejection disease conditions, such as CAN and DT, are provided. In yet other embodiments, methods of determining the class and/or severity of acute rejection (and not just the presence thereof are provided.
As in known in the transplantation field, the graft organ, tissue or cell(s) may be allogeneic or xenogeneic, such that the grafts may be allografts or xenografts. Organs and tissues of interest include, but are not limited to: skin, heart, kidney, liver, bone marrow, and other organs.
In practicing the subject methods, a subject or patient sample, e.g., cells or collections thereof, e.g., tissues, is assayed to evaluate graft survival in the host, e.g., whether the graft will survive in the host from which the assayed sample was obtained. Accordingly, the first step of the subject methods is to obtain a suitable sample from the subject or patient of interest, i.e., a patient having at least one graft, e.g., allograft.
The sample is derived from any initial suitable source, where sample sources of interest include, but are not limited to, many different physiological sources, e.g., CSF, urine, saliva, tears, tissue derived samples, e.g., homogenates (such as biopsy samples of the transplanted tissue or organ (including, but not limited to kidney, heart, lung biopsies), and blood or derivatives thereof.
In certain embodiments, a suitable initial source for the patient sample is blood. As such, the sample employed in the subject assays of these embodiments is generally a blood-derived sample. The blood derived sample may be derived from whole blood or a fraction thereof, e.g., serum, plasma, etc., where in certain embodiments the sample is derived from blood cells harvested from whole blood. Of particular interest as a sample source are peripheral blood lymphocytes (PBL). Any convenient protocol for obtaining such samples may be employed, where suitable protocols are well known in the art and a representative protocol is reported in the Experimental Section, below.
In practicing the subject methods, the sample is assayed to obtain an expression evaluation, e.g., expression profile, for one or more genes, where the term expression profile is used broadly to include a genomic expression profile, e.g., an expression profile of nucleic acid transcripts, e.g., mRNAs, of the one or more genes of interest, or a proteomic expression profile, e.g., an expression profile of one or more different proteins, where the proteins/polypeptides are expression products of the one or more genes of interest. As such, in certain embodiments the expression of only one gene is evaluated. In yet other embodiments, the expression of two or more, e.g., about 5 or more, about 10 or more, about 15 or more, about 25 or more, about 50 or more, about 100 or more, about 200 or more, etc., genes is evaluated. Accordingly, in the subject methods, the expression of at least one gene in a sample is evaluated. In certain embodiments, the evaluation that is made may be viewed as an evaluation of the transcriptosome, as that term is employed in the art. See e.g., Gomes et al., Blood (2001 Jul. 1) 98(1): 93-9.
In generating the expression profile, in certain embodiments a sample is assayed to generate an expression profile that includes expression data for at least one gene/protein, usually a plurality of genes/proteins, where by plurality is meant at least two different genes/proteins, and often at least about 5, typically at least about 10 and more usually at least about 20 different genes/proteins or more, such as 50 or more, 100 or more, etc.
In the broadest sense, the expression evaluation may be qualitative or quantitative. As such, where detection is qualitative, the methods provide a reading or evaluation, e.g., assessment, of whether or not the target analyte, e.g., nucleic acid or expression product, is present in the sample being assayed. In yet other embodiments, the methods provide a quantitative detection of whether the target analyte is present in the sample being assayed, i.e., an evaluation or assessment of the actual amount or relative abundance of the target analyte, e.g., nucleic acid in the sample being assayed. In such embodiments, the quantitative detection may be absolute or, if the method is a method of detecting two or more different analytes, e.g., target nucleic acids, in a sample, relative. As such, the term “quantifying” when used in the context of quantifying a target analyte, e.g., nucleic acid(s), in a sample can refer to absolute or to relative quantification. Absolute quantification may be accomplished by inclusion of known concentration(s) of one or more control analytes and referencing the detected level of the target analyte with the known control analytes (e.g., through generation of a standard curve). Alternatively, relative quantification can be accomplished by comparison of detected levels or amounts between two or more different target analytes to provide a relative quantification of each of the two or more different analytes, e.g., relative to each other.
Genes/proteins of interest are graft survival/loss indicative genes, i.e., genes/proteins that are differentially expressed or present at different levels in graft survival and graft loss individuals (more specifically, individuals in which graft loss will occur vs. individuals in which a graft will survive). Representative genes/proteins of interest in certain embodiments include, but are not limited to, the genes/proteins provided in Tables 1 and 2. (Note that for Tables 1 and 2, the exact sequence of the clone identified in the table can be determined through the NCBI Entrez nucleotide database located at the website produced by placing “http://www.” before: “ncbi.nlm.nih.gov/entrez/query.fcgi?CMD=search&db=nucleotide” in the navigation window of a web browser (e.g., Netscape); the sequence for a specific clone is then obtained by entering the clone ID in quotes as the search term).
TABLE 1
Genes of known function in whole blood predictive of graft loss following acute
rejection
Rank Clone Symbol Gene UnigeneID
1 IMAGE: 214006 HIST1H2BC Histone 1, H2bc Hs.356901
2 IMAGE: 826131 IGHG3 Ig heavy constant gamma 3 Hs.413826
3 IMAGE: 626318 UBN1 Ubinuclein 1 Hs.21479
4 IMAGE: 511387 GLG1 Golgi apparatus protein 1 Hs.78979
5 IMAGE: 810057 CSDA Cold shock domain protein A Hs.221889
6 IMAGE: 283919 HIST1H2AC Histone 1, H2ac Hs.28777
7 IMAGE: 453710 PLEK2 Pleckstrin 2 Hs.170473
8 IMAGE: 840821 SSR4 Signal sequence receptor, delta Hs.409223
9 IMAGE: 70201 MSCP Mitochondrial solute carrier Hs.283716
10 IMAGE: 66686 RPL10 Ribosomal protein L10 Hs.77091
11 IMAGE: 1306420 AHSA2 Activator of heat shock ATPase Hs.122440
12 IMAGE: 2578221 UBB Ubiquitin B Hs.356190
13 IMAGE: 811062 CGI-69 CGI-69 protein Hs.237924
14 IMAGE: 1272566 TNFRSF10D TNF receptor superfamily 10d Hs.129844
15 IMAGE: 1240649 RPL10 Ribosomal protein L10 Hs.77091
16 IMAGE: 85224 RBM25 RNA binding motif protein 25 Hs.197184
17 IMAGE: 2114004 HIST1H3D Histone 1, H3d Hs.239458
18 IMAGE: 789091 HIST1H2AC Histone 1, H2ac Hs.28777
19 IMAGE: 591025 JMJD3 Jumonji domain containing 3 Hs.103915
20 IMAGE: 1354406 SSR4 Signal sequence receptor, delta Hs.409223
21 IMAGE: 812276 SNCA Synuclein Hs.76930
22 IMAGE: 344720 GYPC Glycophorin C Hs.81994
23 IMAGE: 683899 JMJD3 Jumonji domain containing 3 Hs.103915
24 IMAGE: 825006 CYorf15A Chromosome Y ORF Hs.171857
25 IMAGE: 1492412 UBA52 Ubiquitin A-52 fusion product 1 Hs.5308
26 IMAGE: 854079 ACTN1 Actinin, alpha 1 Hs.119000
27 IMAGE: 366884 IFNAR2 Interferon (a- B- and o) receptor 2 Hs.86958
28 IMAGE: 812967 TM4SF9 Transmembrane 4 superfamily Hs.8037
29 IMAGE: 207794 NFE2 Erythroid nuclear factor Hs.75643
30 IMAGE: 359835 SAT Spermidine N1-acetyltransferase Hs.28491
31 IMAGE: 565849 KLHL12 Kelch-like 12 (Drosophila) Hs.3826
32 IMAGE: 256260 RFC3 Replication factor C activator Hs.115474
33 IMAGE: 191826 MSCP Mitochondrial solute carrier protein Hs.283716
34 IMAGE: 202242 MIF Macrophage migration inhibitor Hs.407995
35 IMAGE: 323506 MAPK1 Mitogen-activated protein kinase 1 Hs.324473
36 IMAGE: 1286850 MME Membrane metallo-endopeptidase Hs.259047
37 IMAGE: 129725 RBPSUH Recombining binding protein Hs.347340
38 IMAGE: 882522 ASS Argininosuccinate synthetase Hs.160786
39 IMAGE: 2129439 UBE2B Ubiquitin-conjugating enzyme E2B Hs.385986
40 IMAGE: 1687138 HIST1H2AM Histone 1, H2am Hs.134999
41 IMAGE: 209655 TGFBR3 TGFb receptor III Hs.342874
42 IMAGE: 75254 CSRP2 Cysteine and glycine-rich protein 2 Hs.10526
43 IMAGE: 1715851 HBG2 Hemoglobin, gamma G Hs.302145
44 IMAGE: 155467 SLC9A3R2 Solute carrier family 9 Hs.440896
45 IMAGE: 561743 PPP1R1A Protein phosphatase 1 Hs.435238
46 IMAGE: 565075 STC1 Stanniocalcin 1 Hs.25590
47 IMAGE: 1541958 POU2AF1 POU domain associating factor Hs.2407
48 IMAGE: 324122 ESM1 Endothelial cell-specific molecule 1 Hs.129944
49 IMAGE: 80338 SELENBP1 Selenium binding protein 1 Hs.334841
50 IMAGE: 1472754 COX6B1 Cytochrome c oxidase (ubiquitous) Hs.431668
51 IMAGE: 233583 IL1R2 Interleukin 1 receptor, type II Hs.25333
52 IMAGE: 490060 RNF159 Ring finger protein (C3HC4 type) Hs.246914
53 IMAGE: 1185475 ABCC5 ATP-binding cassette C Hs.22010
54 IMAGE: 120551 LPIN2 Lipin 2 Hs.437425
55 IMAGE: 162772 EGR1 Early growth response 1 Hs.326035
56 IMAGE: 322029 MAPK9 Mitogen-activated protein kinase 9 Hs.348446
57 IMAGE: 1305158 KIAA1219 KIAA1219 protein Hs.348929
58 IMAGE: 2505604 SCYE1 Endothelial monocyte-activating) Hs.105656
59 IMAGE: 1240813 IGKC Immunoglobulin kappa constant Hs.377975
60 IMAGE: 257637 RRBP1 Ribosome binding protein 1 homolog Hs.98614
61 IMAGE: 381522 PP1057 Hypothetical protein PP1057 Hs.108557
62 IMAGE: 455123 MTSS1 Metastasis suppressor 1 Hs.77694
TABLE 2
Genes of known function in renal biopsies whole blood predictive of graft loss following
acute rejection.
Unigene
Rank Clone Symbol Gene ID
1 IMAGE: 2134209 ZNF41 Zinc finger protein 41 Hs.143700
2 IMAGE: 1241524 TCL1A T-cell leukemia/lymphoma 1A Hs.2484
3 IMAGE: 704915 TAP1 Transporter 1 (MDR/TAP) Hs.352018
4 IMAGE: 267600 STAT6 Interleukin-4 induced STAT6 Hs.437475
5 IMAGE: 26599 STAT1 Interleukin-4 induced STAT1 Hs.21486
6 IMAGE: 210405 PSME2 Proteasome activator Hs.434081
7 IMAGE: 1240661 PSMB9 Proteasome beta type, 9 Hs.381081
8 IMAGE: 705046 PML Promyelocytic leukemia Hs.89633
9 IMAGE: 824340 NCF1 Neutrophil cytosolic factor 1 Hs.1583
10 IMAGE: 753313 LAPTM5 Lysosomal-associated protein-5 Hs.436200
11 IMAGE: 1351990 ISG20 Interferon stimulated gene 20 kDa Hs.105434
12 IMAGE: 1672498 IGLV@ Ig lambda variable group Hs.449601
13 IMAGE: 1240590 IGLC2 Ig lambda constant 2 Hs.405944
14 IMAGE: 1240813 IGKC Ig kappa constant Hs.377975
15 IMAGE: 1604703 HLA-F MHC complex, class I, F Hs.411958
16 IMAGE: 2448698 HLA-DRB6 MHC, class II, DR beta 6 (pseudogene) Hs.534338
17 IMAGE: 461769 HLA-DRB5 MHC complex, class II, DR beta 5 Hs.308026
18 IMAGE: 1241341 HLA-DRB3 MHC complex, class II, DR beta 3 Hs.520049
19 IMAGE: 1241211 HLA-DPB1 MHC complex, class II, DP beta 1 Hs.368409
20 IMAGE: 203527 HLA-A MHC complex, class I, A Hs.181244
21 IMAGE: 853906 HCG4P6 HLA complex group 4 pseudogene 6 Hs.512759
22 IMAGE: 841008 GBP1 Guanylate binding 1, interferon-inducible Hs.62661
23 IMAGE: 277522 DAF Decay accelerating factor complement (CD55) Hs.408864
24 IMAGE: 269295 CD83 CD83 antigen (Activated B lymphocytes) Hs.444310
25 IMAGE: 276727 CD69 CD69 antigen (early T-cell activation antigen) Hs.82401
26 IMAGE: 200720 CD38 CD38 antigen (p45) Hs.174944
27 IMAGE: 2000918 CAS1 O-acetyltransferase Hs.324725
28 IMAGE: 67042 APOM Apolipoprotein M Hs.247323
29 IMAGE: 488143 IGHM Immunoglobulin heavy locus Hs.103995
30 IMAGE: 207718 TASS Ig light chain variable region Hs.449578
In certain embodiments, at least one of the genes/proteins in the prepared expression profile is a graft survival/rejection indicative gene from Tables 1 and/or 2, where the expression profile may include expression data for 5, 10, 20, 50, 75 or more of, including all of, the genes/proteins listed in Tables 1 and/or 2. The number of different genes/proteins whose expression and/or quantity data, i.e., presence or absence of expression, as well as expression/quantity level, that are included in the expression profile that is generated may vary, but may be at least 2, and in certain embodiments ranges from 2 to about 100 or more, sometimes from 3 to about 75 or more, including from about 4 to about 70 or more.
In certain embodiments, additional genes beyond those listed in Tables 1 and/or 2, may be assayed, such as genes whose expression pattern can be used to evaluate additional transplant characteristics, including but not limited to: acute rejection (e.g., the genes identified as AR in Table 3, below); chronic allograft injury (chronic rejection) in blood (e.g., the genes identified as CR in Table 3, below); immunosuppressive drug toxicity or adverse side effects including drug-induced hypertension (e.g., the genes identified as DT in Table 3, below); age or body mass index associated genes that correlate with renal pathology or account for differences in recipient age-related graft acceptance (e.g., the genes identified as BMI in Table 3, below); immune tolerance markers in whole blood (e.g., the genes identified as TOL in Table 3, below); genes found in literature surveys with immune modulatory roles that may play a role in transplant outcomes (e.g., the genes identified as Lit. in Table 3, below); as well as other array assay function related genes, e.g., for assessing sample quality (3′- to 5′-bias in probe location), sampling error in biopsy-based studies, cell surface markers, and normalizing genes for calibrating hybridization results (see e.g., the genes identified as Contr. in Table 3, below); and the like.
A representative collection of genes that includes not only graft survival/rejection genes of Tables 1 and 2 above, but also additional graft characterizing genes (e.g., specific for DT, CAN, and immune tolerance) is in Table 3.
TABLE 3
Genes of known function of prognostic value compiled for a custom transplantation
chip (TxChip VI).
Symbol Name mRNA Tissue Study
ACOX1 Acyl-Coenzyme A oxidase 1, palmitoyl NM_004035 Blood AR
ADD3 Adducin 3 (gamma) NM_016824 Blood AR
ADM Adrenomedullin NM_001124 Blood AR
AHR Aryl hydrocarbon receptor NM_001621 Blood AR
ATP1A1 ATPase, Na+/K+ transporting, alpha 1 NM_000701 Blood AR
BUB1B BUB1 budding uninhibited by benzimidazoles NM_001211 Blood AR
CASP8 Caspase 8, apoptosis-related cysteine protease NM_001228 Blood AR
CASP8AP2 CASP8 associated protein 2 NM_012115 Blood AR
CCNC Cyclin C NM_005190 Blood AR
CD21 CD21 B-cell receptor for complement C3d0 Y00649 Blood AR
CD69 CD69 antigen (early T-cell activation antigen) NM_001781 Blood AR
CD8A CD8 antigen, alpha polypeptide (p32) NM_001768 Blood AR
CDIPT Phosphatidylinositol synthase NM_145752 Blood AR
COX6C Cytochrome c oxidase subunit VIc NM_004374 Blood AR
CSNK1A1 Casein kinase 1, alpha 1 NM_001892 Blood AR
DUSP1 Dual specificity phosphatase 1 NM_004417 Blood AR
DUSP3 Dual specificity phosphatase 3 NM_004090 Blood AR
EIF1A Eukaryotic translation initiation factor 1A NM_001412 Blood AR
EIF2S3 Eukaryotic translation initiation factor 2 NM_001415 Blood AR
GNLY Granulysin NM_006433 Blood AR
GOLGIN-67 Golgin-67 XM_496064 Blood AR
AHSA2 Activator of heat shock ATPase NM_152392 Blood AR
HIST1H2BC Histone 1, H2bc NM_003526 Blood AR
IFNAR2 Interferon (alpha, beta and omega) receptor 2 NM_000874 Blood AR
IGHG1 Ig heavy constant gamma 1 (G1m marker) AB067073 Blood AR
IL1R2 Interleukin 1 receptor, type II NM_004633 Blood AR
MAPK1 Mitogen-activated protein kinase 1 NM_002745 Blood AR
MIF Macrophage migration inhibitory factor NM_002415 Blood AR
SCYE1 Endothelial monocyte-activating NM_004757 Blood AR
TGFBR3 TGFb receptor III (betaglycan) NM_003243 Blood AR
TM4SF9 Transmembrane 4 superfamily member 9 NM_005723 Blood AR
IGHM Immunoglobulin heavy constant mu X58529 Blood AR
ISG20 Interferon stimulated gene 20 kDa NM_002201 Blood AR
KIAA1014 FNBP4 formin binding protein 4 AB023231 Blood AR
LIV-1 SLC39A6 metal ion transporter NM_015359 Blood AR
MAPKAPK5 Mitogen-activated protein kinase NM_003668 Blood AR
MDM4 p53 binding protein NM_002393 Blood AR
MYT1 Myelin transcription factor 1 NM_004535 Blood AR
NAB1 EGR1 binding protein 1 NM_005966 Blood AR
NFKB1 NFkB enhancer in B-cells 1 (p105) NM_003998 Blood AR
PC4 RNA polymerase II transcription cofactor 4 NM_006713 Blood AR
PKM2 Pyruvate kinase, muscle NM_002654 Blood AR
PTP4A1 Protein tyrosine phosphatase NM_003463 Blood AR
RBL2 Retinoblastoma-like 2 (p130) NM_005611 Blood AR
RBM3 RNA binding motif 3 (RNP1, RRM) NM_006743 Blood AR
REL V-rel viral oncogene homolog NM_002908 Blood AR
RPL22 Ribosomal protein L22 NM_000983 Blood AR
RPS24 Ribosomal protein S24 NM_033022 Blood AR
RPS27 Ribosomal protein S27 NM_001030 Blood AR
RPS4Y RPS4Y ribosomal protein S4 NM_001008 Blood AR
SATB1 Special AT-rich sequence binding protein NM_002971 Blood AR
SDS3 Likely ortholog of mouse Sds3 NM_022491 Blood AR
SSBP1 Single-stranded DNA binding protein 1 NM_003143 Blood AR
SSI-3 SOCS3 suppressor of cytokine signaling 3 NM_003955 Blood AR
STK4 Serine/threonine kinase 4 NM_006282 Blood AR
TBRG1 Transforming growth factor beta regulator 1 NM_032811 Blood AR
TCF7 Transcription factor 7 (T-cell specific) NM_201633 Blood AR
TOP2B Topoisomerase (DNA) II beta 180 kDa NM_001068 Blood AR
TRIM T-cell receptor interacting molecule NM_016388 Blood AR
TRRAP Transcription domain-associated protein NM_003496 Blood AR
UBA52 Ubiquitin A-52-ribosomal protein fusion NM_003333 Blood AR
UBB Ubiquitin B NM_018955 Blood AR
UBE2B Ubiquitin-conjugating enzyme E2B NM_003337 Blood AR
UBN1 Ubinuclein 1 NM_016936 Blood AR
USP25 Ubiquitin specific protease 25 NM_013396 Blood AR
AIM1 Absent in melanoma 1 XM_166300 Biopsy AR
CD38 CD38 antigen (p45) NM_001775 Biopsy AR
CDS1 CDP-diacylglycerol synthase NM_001263 Biopsy AR
CSF1R Feline sarcoma viral (v-fms) homolog NM_005211 Biopsy AR
DR1 Down-regulator of transcription 1 NM_001938 Biopsy AR
FGL2 Fibrinogen-like 2 NM_006682 Biopsy AR
FLJ13612 Calcium binding protein AI635773 Biopsy AR
HLA-A MHC class I, A NM_002116 Biopsy AR
HLA-B MHC class I, B NM_005514 Biopsy AR
HLA-C MHC class I, C NM_002117 Biopsy AR
HLA-DPA1 MHC class II, DP alpha 1 NM_033554 Biopsy AR
HLA-DRA MHC class II, DR alpha NM_019111 Biopsy AR
IGKC Ig kappa constant AB064140 Blood AR
TNFSF10 TNF superfamily, member 10 NM_003810 Blood AR
IGLJ3 IGLa Immunoglobulin lambda AI146764 Biopsy AR
MYH10 Myosin, heavy polypeptide 10 NM_005964 Biopsy AR
NKTR Natural killer-tumor recognition sequence NM_005385 Biopsy AR
PAX8 Paired box gene 8 NM_013951 Biopsy AR
POLR2B Polymerase (RNA) II polypeptide B NM_000938 Biopsy AR
RGN Regucalcin (senescence marker protein-30) NM_004683 Biopsy AR
SCNN1A Sodium channel, nonvoltage-gated 1 alpha NM_001038 Biopsy AR
SIM2 Single-minded homolog 2 NM_009586 Biopsy AR
TACSTD2 Calcium signal transducer 2 NM_002353 Biopsy AR
VCAM1 Vascular cell adhesion molecule 1 NM_001078 Biopsy AR
YARS Tyrosyl-tRNA synthetase NM_003680 Biopsy AR
ZFP36L1 Zinc finger protein 36 NM_004926 Biopsy AR
HLA-DPB1 MHC, class II, DP beta 1 NM_002121 Biopsy AR
HLA-DRB3 MHC, class II, DR beta 4 NM_022555 Biopsy AR
ACK1 Cdc42-associated kinase 1 NM_005781 Biopsy AR
HLA-F MHC, class I, F NM_018950 Biopsy AR
ICAM5 Intercellular adhesion molecule 5 NM_003259 Biopsy AR
REG1A Regenerating islet-derived 1 alpha NM_002909 Biopsy AR
GSTA2 Glutathione S-transferase A2 NM_000846 Biopsy AR
HLA-DRB5 MHC class II, DR beta 4 NM_002125 Biopsy AR
HLA-DQA1 MHC class II, DQ alpha 1 NM_002122 Biopsy AR
HLA-DQB1 MHC class II, DQ beta 1 NM_002123 Biopsy AR
RFXANK Regulatory factor X-associated ankyrin NM_003721 Biopsy AR
STAT6 Interleukin-4 induced STAT6 NM_003153 Biopsy AR
TAP1 Transporter 1 (MDR/TAP) NM_000593 Biopsy AR
DAF Decay accelerating factor (CD55) NM_000574 Biopsy AR
CD83 CD83 antigen (activated B lymphocytes) NM_004233 Biopsy AR
STAT1 Interleukin-4 induced STAT1 NM_007315 Biopsy AR
LTBR Lymphotoxin beta receptor NM_002342 Biopsy AR
KCNJ1 Potassium inwardly-rectifying channel NM_000220 Biopsy AR
SLPI Secretory leukocyte protease inhibitor NM_003064 Biopsy AR
CD34 CD34 antigen NM_001773 Biopsy AR
HOXB5 Homeo box B5 NM_002147 Biopsy AR
IL6R Interleukin 6 receptor NM_181359 Biopsy AR
DAPK1 Death-associated protein kinase 1 NM_004938 Biopsy AR
HOXD9 Homeo box D9 NM_014213 Biopsy AR
TCF21 Transcription factor 21 NM_003206 Biopsy AR
MAL T-cell differentiation protein NM_022438 Biopsy AR
MAF V-maf fibrosarcoma homolog NM_005360 Blood AR
NCOR2 Nuclear receptor co-repressor 2 NM_006312 Blood CR
ZFP106 Zinc finger protein 106 homolog NM_022473 Blood CR
RPL23 Ribosomal protein L23 NM_000978 Blood CR
CPVL Carboxypeptidase, vitellogenic-like NM_019029 Blood CR
ENO2 Enolase 2 (gamma, neuronal) NM_001975 Blood CR
CAPN2 Calpain 2, (m/II) large subunit NM_001748 Blood CR
FGFR4 Fibroblast growth factor receptor 4 NM_002011 Blood CR
CD68 CD68 antigen NM_001251 Blood CR
HK3 Hexokinase 3 (white cell) NM_002115 Blood CR
DUSP6 Dual specificity phosphatase 6 NM_001946 Blood CR
IL6ST Interleukin 6 signal transducer NM_002184 Blood CR
LATS2 LATS, large tumor suppressor 2 NM_014572 Blood CR
MIC2 CD99 antigen NM_002414 Blood CR
MMP23B Matrix metalloproteinase 23B NM_006983 Blood CR
ZNF511 Zinc finger protein 511 NM_145806 Blood CR
ANXA5 Annexin A5 NM_001154 Blood CR
ID2 Inhibitor of DNA binding 2 NM_002166 Blood CR
PRKRIR RNA dependent p58 repressor NM_004705 Blood CR
SGK Serum/glucocorticoid regulated kinase NM_005627 Blood CR
S100A10 S100 calcium binding protein A10 NM_002966 Blood CR
CYP51 Cytochrome P450, family 51A NM_000786 Blood CR
ITGA4 Integrin, alpha 4 (antigen CD49D) NM_000885 Blood CR
ADAM10 A disintegrin and metalloproteinase10 NM_001110 Blood CR
HNRPK Nuclear ribonucleoprotein K NM_031262 Blood CR
ITGAV Integrin, alpha V (CD51) NM_002210 Blood CR
JUN V-jun sarcoma virus 17 homolog NM_002228 Blood CR
PRKAR2B Protein kinase regulator NM_002736 Blood CR
TIE Tyrosine kinase with Ig and EGF domains NM_005424 Blood CR
IQGAP2 GTPase activating protein 2 NM_006633 Blood CR
MAP4K1 Mitogen-activated protein kinase 1 NM_007181 Blood CR
ILF3 Interleukin enhancer binding factor 3 NM_012218 Blood CR
SGKL Serum/glucocorticoid regulated kinase-like NM_013257 Blood CR
GLS Glutaminase NM_014905 Blood CR
DPYD Dihydropyrimidine dehydrogenase NM_000110 Blood CR
ACADM Acyl-Coenzyme A dehydrogenase NM_000016 Biopsy DT
AUTS2 Autism susceptibility candidate 2 NM_015570 Biopsy DT
CA2 Carbonic anhydrase II NM_000067 Biopsy DT
CTNNA1 Catenin (cadherin-associated protein) NM_001903 Biopsy DT
CXCL12 Stromal cell-derived factor 1 NM_000609 Biopsy DT
DDR1 Discoidin domain receptor family, member 1 NM_013994 Biopsy DT
DECR1 2,4-dienoyl CoA reductase 1, mitochondrial NM_001359 Biopsy DT
DEDD Death effector domain containing NM_032998 Biopsy DT
DPP4 Dipeptidylpeptidase 4 (CD26) NM_001935 Biopsy DT
ITM2B Integral membrane protein 2B NM_021999 Biopsy DT
KIAA0436 L-type neutral amino acid transporter AB007896 Biopsy DT
LDHB Lactate dehydrogenase B NM_002300 Biopsy DT
LEPR Leptin receptor NM_002303 Biopsy DT
LRBA LPS-responsive vesicle trafficking NM_006726 Biopsy DT
MUT Methylmalonyl Coenzyme A mutase NM_000255 Biopsy DT
NAT1 N-acetyltransferase 1 NM_000662 Biopsy DT
NAT2 N-acetyltransferase 2 NM_000015 Biopsy DT
NUP50 Nucleoporin 50 kDa NM_153645 Biopsy DT
PAFAH1B1 Platelet-activating factor NM_000430 Biopsy DT
PDZK3 PDZ domain containing 3 NM_178140 Biopsy DT
PLCL2 Phospholipase C-like 2 NM_015184 Biopsy DT
PPP2CB Protein phosphatase 2 NM_004156 Biopsy DT
PRKCM Protein kinase C, mu NM_002742 Biopsy DT
PTPN3 Protein tyrosine phosphatase NM_002829 Biopsy DT
REST RE1-silencing transcription factor NM_005612 Biopsy DT
SGCB Sarcoglycan, beta NM_000232 Biopsy DT
SHB Src homology 2 domain containing NM_003028 Biopsy DT
SORL1 Sortilin-related receptor, L NM_003105 Biopsy DT
SULT1E1 Sulfotransferase family 1E NM_005420 Biopsy DT
CBL Cas-Br-Transforming sequence NM_005188 Biopsy DT
CXCL1 Chemokine (C—X—C motif) ligand 1 NM_001511 Biopsy DT
FGF2 Fibroblast growth factor 2 (basic) NM_002006 Biopsy DT
GPRK5 G protein-coupled receptor kinase 5 NM_005308 Biopsy DT
ITSN2 Intersectin 2 NM_006277 Biopsy DT
BCL2L13 BCL2-like 13 (apoptosis facilitator) AA279535 Biopsy BMI
BDKRB2 Bradykinin receptor B2 NM_000623 Biopsy BMI
DDX3 DEAD/H (Asp-Glu-Ala-Asp/His) box 3 NM_001356 Biopsy BMI
FOXM1 Forkhead box M1 NM_021953 Biopsy BMI
HMOX2 Heme oxygenase (decycling) 2 NM_002134 Biopsy BMI
IFNGR1 Interferon gamma receptor 1 NM_000416 Biopsy BMI
IGFBP1 Insulin-like growth factor binding protein 1 NM_000596 Biopsy BMI
IGFBP5 Insulin-like growth factor binding protein 5 NM_000599 Biopsy BMI
LRP2 Low density lipoprotein-related protein 2 NM_004525 Biopsy BMI
MCM7 Minichromosome maintenance deficient 7 NM_182776 Biopsy BMI
NPPB Natriuretic peptide precursor B NM_002521 Biopsy BMI
NPR1 Natriuretic peptide receptor A NM_000906 Biopsy BMI
PAXIP1L PAX transcription activation interacting NM_007349 Biopsy BMI
PDCD5 Programmed cell death 5 NM_004708 Biopsy BMI
RBX1 Ring-box 1 NM_014248 Biopsy BMI
RPL27 Ribosomal protein L27 NM_000988 Biopsy BMI
SBA2 WD repeat and SOCS box containing protein AA043793 Biopsy BMI
SERPINB6 Proteinase inhibitor, clade B (ovalbumin) NM_004568 Biopsy BMI
SLC22A5 Solute carrier family 22 NM_003060 Biopsy BMI
SLC38A2 Solute carrier family 38, member 2 NM_018976 Biopsy BMI
SMT3H2 Suppressor of MIF NM_006937 Biopsy BMI
TJP4 Tight junction protein 4 (peripheral) NM_080604 Biopsy BMI
TP53INP1 p53 inducible nuclear protein 1 NM_033285 Biopsy BMI
BHLHB2 Basic helix-loop-helix domain containing NM_003670 Biopsy BMI
CSPG2 Chondroitin sulfate proteoglycan 2 NM_004385 Biopsy BMI
GPD1 Glycerol-3-phosphate dehydrogenase 1 NM_005276 Biopsy BMI
GTPBP4 GTP binding 4; Chronic renal failure gene NM_012341 Biopsy BMI
HIF1A Hypoxia-inducible factor 1, alpha NM_001530 Biopsy BMI
MMP7 Matrix metalloproteinase 7 NM_002423 Biopsy BMI
SLC2A3 Facilitated glucose transporter NM_006931 Biopsy BMI
THBS1 Thrombospondin 1 NM_003246 Biopsy BMI
TNC Tenascin C (hexabrachion) NM_002160 Biopsy BMI
HLA-G HLA-G histocompatibility antigen, class I, G NM_002127 Blood TOL
IGHG3 Ig heavy constant gamma 3 AK097306 Blood TOL
BUR1 Budding uninhibited (cell cycle regulator) NM_004336 Blood TOL
CCNB2 Cyclin B2 NM_004701 Blood TOL
TACSTD1 Tumor-associated calcium signaling NM_002354 Blood TOL
DHRS2 Dehydrogenase/reductase (SDR family) AK092834 Blood TOL
BMP7 Bone morphogenetic protein 7 NM_001719 Blood TOL
AKR1C1 Aldo-keto reductase family 1C1 NM_001353 Blood TOL
B4GALT2 UDP-Gal 1,4-galactosyltransferase NM_003780 Blood TOL
TCEB3 Transcription elongation factor B (SIII) NM_003198 Blood TOL
MLPH Melanophilin NM_024101 Blood TOL
SERPINH2 Heat shock protein 47 (proteinase inhibitor) NM_001235 Blood TOL
RRM2 Ribonucleotide reductase M2 polypeptide NM_001034 Blood TOL
SERPINA3 Alpha-1 antiproteinase, antitrypsin NM_001085 Blood TOL
SERPINA5 Alpha-1 antiproteinase, antitrypsin NM_000624 Blood TOL
CTNNAL1 Catenin (cadherin-associated protein) NM_003798 Blood TOL
SPARC Secreted protein, cysteine-rich (osteonectin) NM_003118 Blood TOL
C1S C1S complement component 1 NM_001734 Blood TOL
SRPUL SRPUL sushi-repeat protein NM_006307 Blood TOL
MMP2 Matrix metalloproteinase 2 NM_004530 Blood TOL
SLC7A7 Cationic amino acid transporter NM_003982 Blood TOL
EPOR Erythropoietin receptor NM_000121 Blood TOL
PRAME Preferentially expressed antigen in melanoma NM_006115 Blood TOL
AFP Alpha-fetoprotein NM_001134 Blood TOL
MAPK9 Mitogen-activated protein kinase 9 NM_002752 Blood TOL
NR2F2 Nuclear receptor subfamily 2F2 NM_021005 Blood TOL
PFN2 Profilin 2 NM_053024 Blood TOL
SLC38A6 Solute carrier family 38, member 6 BC050349 Blood TOL
MYOM2 Myomesin (M-protein) 2, 165 kDa NM_003970 Blood TOL
RBP1 Retinol binding protein 1, cellular NM_002899 Blood TOL
TK1 Thymidine kinase 1, soluble NM_003258 Blood TOL
IFITM3 Interferon induced transmembrane protein 3 NM_021034 Blood TOL
APOH Apolipoprotein H (beta-2-glycoprotein I) NM_000042 Blood TOL
EVI2A Ecotropic viral integration site 2A NM_014210 Blood TOL
CD9 CD9 antigen (p24) NM_001769 Blood TOL
NKG7 Natural killer cell group 7 sequence NM_005601 Blood TOL
CDKN3 Cyclin-dependent kinase inhibitor 3 NM_005192 Blood TOL
TCL1A T-cell leukemia/lymphoma 1A NM_021966 Blood TOL
PYCR1 Pyrroline-5-carboxylate reductase 1 NM_153824 Blood TOL
TM4SF5 Transmembrane 4 superfamily member 5 NM_003963 Blood TOL
GAGEB1 G antigen, family B, 1 (prostate associated) NM_003785 Blood TOL
PCP4 Purkinje cell protein 4 NM_006198 Blood TOL
LGMN Legumain NM_005606 Blood TOL
PIR Pirin (iron-binding nuclear protein) NM_178238 Blood TOL
PAICS Phosphoribosylaminoimidazole carboxylase NM_006452 Blood TOL
IGFBP3 Insulin-like growth factor binding protein 3 NM_000598 Blood TOL
PSMB9 Proteasome subunit NM_002800 Blood TOL
N33 Putative prostate cancer tumor suppressor NM_006765 Blood TOL
DP1 Polyposis locus protein 1 (DP1) NM_005669 Blood TOL
TFDP1 Transcription factor Dp-1 NM_007111 Blood TOL
OSF-2 OSF-2 osteoblast specific factor 2 NM_000358 Blood TOL
COL3A1 Collagen, type III, alpha 1 NM_000090 Blood TOL
TIMP3 TIMP3 tissue inhibitor of metalloproteinase 3 NM_000362 Blood TOL
SPP1 Osteopontin, early T-lymphocyte activation 1 NM_000582 Blood TOL
NQO1 NQO1 NAD(P)H dehydrogenase NM_000903 Blood TOL
TOP2A Topoisomerase (DNA) II alpha 170 kDa NM_001067 Blood TOL
CCND2 Cyclin D2 NM_001759 Blood TOL
CNN3 CNN3 calponin 3, acidic AI969128 NM_001839 Blood TOL
COL6A1 Collagen, type VI, alpha 1 NM_001848 Blood TOL
CTGF Connective tissue growth factor NM_001901 Blood TOL
EGR1 Early growth response 1 (EGR1) NM_001964 Blood TOL
SDC2 Syndecan 2 NM_002998 Blood TOL
TCF3 Transcription factor 3 NM_003200 Blood TOL
TFAP2C Transcription factor AP-2 gamma NM_003222 Blood TOL
NRP1 Neuropilin 1 NM_003873 Blood TOL
GITR TNF receptor superfamily18 (TNFRSF18) NM_004195 Blood TOL
COL6A3 Collagen, type VI, alpha 3 NM_004369 Blood TOL
EPHA2 EPHA2 EphA2 NM_004431 Blood TOL
PDE1A ARHE ras homolog gene family NM_005168 Blood TOL
FAT Tumor suppressor homolog 1 NM_005245 Blood TOL
KIFC3 Kinesin family member C3 NM_005550 Blood TOL
NR2F1 Nuclear receptor subfamily 2F1 NM_005654 Blood TOL
CAP2 CAP, adenylate cyclase-associated 2 NM_006366 Blood TOL
BACE2 Beta-site APP-cleaving enzyme 2 NM_012105 Blood TOL
FADS1 Fatty acid desaturase 1 NM_013402 Blood TOL
MELK Maternal embryonic leucine zipper kinase NM_014791 Blood TOL
DKK3 Dickkopf homolog 3 (Xenopus laevis) NM_015881 Blood TOL
CCNB1 Cyclin B1 NM_031966 Blood TOL
CALD1 Caldesmon 1 NM_033138 Blood TOL
CASP1 Caspase 1, (interleukin 1b convertase) NM_033292 Blood TOL
KNSL5 Kinesin-like 5 (mitotic kinesin-like protein 1) NM_138555 Blood TOL
STK6 Serine/threonine kinase 6 NM_198433 Blood TOL
CD59 CD59 antigen p18-20 NM_203330 Blood TOL
FN1 Fibronectin 1 NM_212482 Blood TOL
SERPINE2 Serine proteinase inhibitor NM_006216 Blood TOL
CDH2 Cadherin 2, type 1, N-cadherin NM_001792 Blood TOL
CCNE1 Cyclin E1 NM_001238 Blood TOL
SEMA3F Ig short basic domain, secreted NM_004186 Blood TOL
MAD2L1 MAD2 mitotic arrest deficient-like 1 NM_002358 Blood TOL
CYR61 Cysteine-rich, angiogenic inducer, 61 NM_001554 Blood TOL
TNFRSF7 CD27 TNF receptor superfamily 7 NM_001242 Blood TOL
FOXP3 Forkhead box P3 (FOXP3), mRNA NM_014009 Blood TOL
ABCA4 ATP-binding cassette, sub-family A (ABC1) NM_000350 Biopsy Control
HNK-1 HNK-1 sulfotransferase AF033827 Biopsy Control
UCP2 Uncoupling protein 2 NM_003355 Biopsy Control
DAB2 Mitogen-responsive phosphoprotein NM_001343 Biopsy Control
AQP3 Aquaporin 3 NM_004925 Biopsy Control
CRABP1 Cellular retinoic acid binding protein 1 NM_004378 Biopsy Control
KCNAB2 Potassium voltage-gated channel NM_003636 Biopsy Control
TNNT2 Troponin T2, cardiac NM_000364 Biopsy Control
APP Amyloid beta (A4) precursor protein NM_000484 Biopsy Control
FABP3 Fatty acid binding protein 3 NM_004102 Biopsy Control
PODXL Podocalyxin-like NM_005397 Biopsy Control
ALPI Alkaline phosphatase, intestinal NM_001631 Biopsy Control
MAPT Microtubule-associated protein tau NM_005910 Biopsy Control
KHK Ketohexokinase (fructokinase) NM_000221 Biopsy Control
18S 18s ribosomal RNA M10098 All Control
ACTB Actin, beta NM_001101 All Control
GAPD Glyceraldehyde-3-phosphate dehydrogenase NM_002046 All Control
GSUSB Glucuronidase, beta NM_000181 All Control
HPRT1 Hypoxanthine phosphoribosyltransferase 1 NM_000194 All Control
SCYA3 Chemokine (C—C motif) ligand 3 NM_002983 All Control
LMO2 LIM domain only 2 (LMO2) NM_005574 All Control
BCL6 B-cell CLL/lymphoma 6 NM_001706 All Control
IkB2 NFkB enhancer in B-cells inhibitor NM_020529 All Control
APC Adenomatosis polyposis coli NM_000038 All Control
BAG2 BCL2-associated athanogene 2 (BAG2) NM_004282 All Control
CREBBP CREB binding protein NM_004380 All Control
KLRB1 Killer cell lectin-like receptor B1 NM_002258 All Control
TRADD TNFRSF1A-associated via death domain NM_003789 All Control
CXCL14 Chemokine (C—X—C motif) ligand 14 NM_004887 All Control
IL1A Interleukin 1, alpha NM_000575 All Control
MMP1 Matrix metalloproteinase 1 NM_002421 All Control
MMP9 Matrix metalloproteinase 9 NM_004994 All Control
VEGFC Vascular endothelial growth factor C NM_005429 All Control
CD8A CD8 antigen, alpha polypeptide (p32) NM_171827 Blood Control
CD3G CD3G antigen, gamma (TiT3 complex) NM_000073 Blood Control
CD44 CD44 antigen NM_000610 Blood Control
CD4 CD4 antigen (p55) NM_000616 Blood Control
CD3D CD3D antigen, delta (TiT3 complex) NM_000732 Blood Control
CD3E CD3E antigen, epsilon (TiT3 complex) NM_000733 Blood Control
CD3Z CD3Z antigen, zeta (TiT3 complex) NM_000734 Blood Control
CD19 CD19 antigen NM_001770 Blood Control
B220 Protein tyrosine phosphatase receptor NM_002838 Blood Control
CD138 CD138 syndecan 1 (SDC1) NM_002997 Blood Control
CD43 Sialophorin (CD43) NM_003123 Blood Control
CD8B1 CD8 antigen, beta polypeptide 1 (p37) NM_004931 Blood Control
API5 Apoptosis inhibitor 5 NM_006595 All Lit.
Axin1 Axin 1 NM_003502 All Lit.
Axin2 Axin 2 (conductin, axil) NM_004655 All Lit.
BAD BCL2-antagonist of cell death NM_032989 All Lit.
BIK BCL2-interacting killer (apoptosis-inducing) NM_001197 All Lit.
BMP4 Bone morphogenetic protein 4 NM_001202 All Lit.
BTG1 B-cell translocation gene 1 NM_001731 All Lit.
CASP10 Caspase 10, apoptosis-related cysteine protease NM_001230 All Lit.
CASP3 Caspase 3, apoptosis-related cysteine protease NM_004346 All Lit.
CASP4 Caspase 4, apoptosis-related cysteine protease NM_001225 All Lit.
CASP7 Caspase 7, apoptosis-related cysteine protease NM_001227 All Lit.
CASP9 Caspase 9, apoptosis-related cysteine protease NM_001229 All Lit.
CCL18 Chemokine (C—C motif) ligand 18 NM_002988 All Lit.
CD161 Killer cell lectin-like receptor B1 BC027885 All Lit.
CD20 Membrane-spanning 4A1 NM_152866 All Lit.
CD22 CD22 antigen NM_001771 All Lit.
CD48 CD48 antigen (B-cell membrane protein) NM_001778 All Lit.
CD80 CD80 antigen (B7-1 antigen) NM_005191 All Lit.
CDA08 T-cell immunomodulatory protein NM_030790 All Lit.
CDC2 Cell division cycle 2, G1 to S and G2 to M NM_001786 All Lit.
CDw108 Semaphorin Ig and GPI membrane anchor 7A, NM_003612 All Lit.
CDW52 CDW52 antigen (CAMPATH-1 antigen) NM_001803 All Lit.
CIS4 STAT induced STAT inhibitor-4 NM_004232 All Lit.
CTLA4 Cytotoxic T-lymphocyte-associated protein 4 NM_005214 All Lit.
DAD1 Defender against cell death 1 NM_001344 All Lit.
DAP3 Death associated protein 3 NM_033657 All Lit.
DAPK2 Death-associated protein kinase 2 NM_014326 All Lit.
DAPK3 Death-associated protein kinase 3 NM_001348 All Lit.
DAXX Death-associated protein 6 NM_001350 All Lit.
EBF Early B-cell factor NM_024007 All Lit.
FCGR1A Fc fragment of IgG (receptor for CD64) NM_000566 All Lit.
GADD45B Growth arrest and DNA-damage-inducible NM_015675 All Lit.
GSR Glutathione reductase NM_000637 All Lit.
GZMA Granzyme A NM_006144 All Lit.
GZMB Granzyme B NM_004131 All Lit.
Gzmc Granzyme C M18459 All Lit.
GZMK Granzyme K NM_002104 All Lit.
HLA-E MHC class I, E NM_005516 All Lit.
ICAM1 Intercellular adhesion molecule 1 (CD54) NM_000201 All Lit.
ICAM3 Intercellular adhesion molecule 3 NM_002162 All Lit.
IFI16 Interferon, gamma-inducible protein 16 NM_005531 All Lit.
IFI35 Interferon-induced protein 35 NM_005533 All Lit.
IFNG Interferon, gamma NM_000619 All Lit.
IGBP1 Ig (CD79A) binding protein 1 NM_001551 All Lit.
IGJ Ig J polypeptide, linker protein NM_144646 All Lit.
IK IK cytokine, down-regulator of HLA II NM_006083 All Lit.
IL2RA Interleukin 2 receptor, alpha NM_000417 All Lit.
IL4R Interleukin 4 receptor NM_000418 All Lit.
IL6 Interleukin 6 (interferon, beta 2) NM_000600 All Lit.
IL7R Interleukin 7 receptor NM_002185 All Lit.
IL8RB Interleukin 8 receptor, beta NM_001557 All Lit.
IRF1 Interferon regulatory factor 1 NM_002198 All Lit.
ITGAE Integrin, alpha E (CD103) NM_002208 All Lit.
JAK1 Janus kinase 1 NM_002227 All Lit.
JAK2 Janus kinase 2 NM_004972 All Lit.
MADH2 SMAD, mothers against DPP NM_005901 All Lit.
MAPK3 Mitogen-activated protein kinase 3 NM_002746 All Lit.
MDM2 p53 binding protein NM_002392 All Lit.
MHC2TA MHC class II transactivator NM_000246 All Lit.
NK4 Natural killer cell transcript 4 NM_004221 All Lit.
NMI N-myc (and STAT) interactor NM_004688 All Lit.
PCNA Proliferating cell nuclear antigen NM_002592 All Lit.
PDCD2 Programmed cell death 2 NM_002598 All Lit.
PDCD7 Programmed cell death 7 NM_005707 All Lit.
PDCD8 Programmed cell death 8 NM_004208 All Lit.
PDGFRB Platelet-derived growth factor receptor NM_002609 All Lit.
RhoA Ras homolog gene family, member A NM_001664 All Lit.
SIMRP7 Multidrug resistance-associated protein 7 NM_033450 All Lit.
SOD2 Superoxide dismutase 2, mitochondrial NM_000636 All Lit.
SSI-1 suppressor of cytokine signaling 1 NM_003745 All Lit.
STAT2 Signal transducer2, 113 kDa NM_005419 All Lit.
STAT3 Signal transducer 3 (acute-phase response factor) NM_139276 All Lit.
STAT4 Signal transducer 4 NM_003151 All Lit.
STAT5A Signal transducer 5A NM_003152 All Lit.
STAT5B Signal transducer a5B NM_012448 All Lit.
STK21 Rho-interacting NM_007174 All Lit.
TA-LRRP TNF receptor-associated factor 6 NM_145803 All Lit.
TCRA T-cell receptor active alpha-chain M12423 All Lit.
TCRB T cell receptor beta locus X60096 All Lit.
TCRD T-cell receptor delta chain (VJC-region) M21624 All Lit.
TCRG T cell receptor gamma locus X06774 All Lit.
TFRC Transferrin receptor (p90, CD71) NM_003234 All Lit.
TGFA Transforming growth factor, alpha NM_003236 All Lit.
TGFB2 Transforming growth factor, beta 2 NM_003238 All Lit.
THBS2 Thrombospondin 2 NM_003247 All Lit.
TIA1 Cytotoxic granule-associated RNA binding NM_022173 All Lit.
TIEG2 TGFB inducible early growth response 2 NM_003597 All Lit.
TLR5 Toll-like receptor 5 NM_003268 All Lit.
TNFRSF1A TNF receptor superfamily, member 1A NM_001065 All Lit.
TNFRSF1B TNF receptor superfamily, member 1B NM_001066 All Lit.
TNFSF7 TNF (ligand) superfamily, member 7 NM_001252 All Lit.
TP53BP1 Tumor protein p53 binding protein, 1 NM_005657 All Lit.
TP53BP2 Tumor protein p53 binding protein, 2 NM_005426 All Lit.
TRAF1 TNF receptor-associated factor 1 NM_005658 All Lit.
TRAF2 TNF receptor-associated factor 2 NM_021138 All Lit.
TRAF3 TNF receptor-associated factor 3 NM_003300 All Lit.
TRAF4 TNF receptor-associated factor 4 NM_004295 All Lit.
TRAP1 TNF receptor-associated protein 1 NM_004257 All Lit.
TTK TTK protein kinase NM_003318 All Lit.
UBE1L Ubiquitin-activating enzyme E1-like NM_003335 All Lit.
VPREB3 Pre-B lymphocyte gene 3 NM_013378 All Lit.
WNT1 MMTV integration site (WNT1) NM_005430 All Lit.
ACE1 Ig receptor (PIGR) IgA nephritis NM_002644 All Lit.
BAX BCL2-associated X protein NM_138763 All Lit.
BCL2 B-cell CLL/lymphoma 2 NM_000633 All Lit.
C3 Complement component 3 NM_000064 All Lit.
CD28 CD28 antigen (Tp44) NM_006139 All Lit.
CD86 CD86 antigen (B7-2 antigen) NM_006889 All Lit.
ICOS Inducible T-cell co-stimulator NM_012092 All Lit.
IL10 Interleukin 10 NM_000572 All Lit.
IL15 Interleukin 15 NM_000585 All Lit.
IL2 Interleukin 2 NM_000586 All Lit.
IL4 Interleukin 4 NM_000589 All Lit.
IL7 Interleukin 7 NM_000880 All Lit.
IL8 Interleukin 8 NM_000584 All Lit.
PRF1 Perforin 1 (pore forming protein) NM_005041 All Lit.
RANTES Chemokine (C—C motif) ligand 5 (CCL5) NM_002985 All Lit.
TBET Th1-specific T-box transcription factor NM_013351 All Lit.
TGFB1 TGF beta 1 NM_000660 All Lit.
TNF TNF superfamily, member 2 NM_000594 All Lit.
TNFB Lymphotoxin alpha (TNF1 or LTA) NM_000595 All Lit.
TNFRSF5 CD40 TNF receptor superfamily 5 NM_001250 All Lit.
TNFRSF6 CD95 = Fas TNF receptor superfamily 6 NM_000043 All Lit.
VEGF Vascular endothelial growth factor NM_003376 All Lit.
In certain embodiments, a collection of genes from Table 3 is assayed, where in these embodiments the number of genes from Table 3 may be at least about 5%, at least about 10%, at least about 25%, at least about 50%, at least about 75%, at least about 90% or more, including all of the genes from Table 3.
In certain embodiments, the expression profile obtained is a genomic or nucleic acid expression profile, where the amount or level of one or more nucleic acids in the sample is determined, e.g., the nucleic acid transcript of the gene of interest. In these embodiments, the sample that is assayed to generate the expression profile employed in the diagnostic methods is one that is a nucleic acid sample. The nucleic acid sample includes a plurality or population of distinct nucleic acids that includes the expression information of the phenotype determinative genes of interest of the cell or tissue being diagnosed. The nucleic acid may include RNA or DNA nucleic acids, e.g., mRNA, cRNA, cDNA etc., so long as the sample retains the expression information of the host cell or tissue from which it is obtained. The sample may be prepared in a number of different ways, as is known in the art, e.g., by mRNA isolation from a cell, where the isolated mRNA is used as is, amplified, employed to prepare cDNA, cRNA, etc., as is known in the differential expression art. In certain embodiments, the sample is prepared from a cell or tissue harvested from a subject to be diagnosed, e.g., via biopsy of tissue, using standard protocols, where cell types or tissues from which such nucleic acids may be generated include any tissue in which the expression pattern of the to be determined phenotype exists, including, but not limited to, peripheral blood lymphocyte cells, etc, as reviewed above.
The expression profile may be generated from the initial nucleic acid sample using any convenient protocol. While a variety of different manners of generating expression profiles are known, such as those employed in the field of differential gene expression analysis, one representative and convenient type of protocol for generating expression profiles is array-based gene expression profile generation protocols. In certain embodiments, such applications are hybridization assays in which a nucleic acid array that displays “probe” nucleic acids for each of the genes to be assayed/profiled in the profile to be generated is employed. In these assays, a sample of target nucleic acids is first prepared from the initial nucleic acid sample being assayed, where preparation may include labeling of the target nucleic acids with a label, e.g., a member of signal producing system. Following target nucleic acid sample preparation, the sample is contacted with the array under hybridization conditions, whereby complexes are formed between target nucleic acids that are complementary to probe sequences attached to the array surface. The presence of hybridized complexes is then detected, either qualitatively or quantitatively. Specific hybridization technology which may be practiced to generate the expression profiles employed in the subject methods includes the technology described in U.S. Pat. Nos. 5,143,854; 5,288,644; 5,324,633; 5,432,049; 5,470,710; 5,492,806; 5,503,980; 5,510,270; 5,525,464; 5,547,839; 5,580,732; 5,661,028; 5,800,992; the disclosures of which are herein incorporated by reference; as well as WO 95/21265; WO 96/31622; WO 97/10365; WO 97/27317; EP 373 203; and EP 785 280. In these methods, an array of “probe” nucleic acids that includes a probe for each of the phenotype determinative genes whose expression is being assayed is contacted with target nucleic acids as described above. Contact is carried out under hybridization conditions, e.g., stringent hybridization conditions, and unbound nucleic acid is then removed.
The resultant pattern of hybridized nucleic acid provides information regarding expression for each of the genes that have been probed, where the expression information is in terms of whether or not the gene is expressed and, typically, at what level, where the expression data, i.e., expression profile (e.g., in the form of a transcriptosome), may be both qualitative and quantitative.
Alternatively, non-array based methods for quantitating the levels of one or more nucleic acids in a sample may be employed, including quantitative PCR, and the like.
Where the expression profile is a protein expression profile, any convenient protein quantitation protocol may be employed, where the levels of one or more proteins in the assayed sample are determined. Representative methods include, but are not limited to: proteomic arrays, flow cytometry, standard immunoassays (e.g., ELISA assays), protein activity assays, including multiplex protein activity assays, etc.
Following obtainment of the expression profile from the sample being assayed, the expression profile is compared with a reference or control profile to determine the particular graft tolerant/intolerant phenotype of the cell or tissue, and therefore host, from which the sample was obtained/derived. The terms “reference” and “control” as used herein mean a standardized pattern of gene expression or levels of expression of certain genes to be used to interpret the expression signature of a given patient and assign a graft tolerant/intolerant phenotype thereto. The reference or control profile may be a profile that is obtained from a cell/tissue known to have the desired phenotype, e.g., tolerant phenotype, and therefore may be a positive reference or control profile. In addition, the reference/control profile may be from a cell/tissue known to not have the desired phenotype, e.g., an intolerant phenotype, and therefore be a negative reference/control profile.
In certain embodiments, the obtained expression profile is compared to a single reference/control profile to obtain information regarding the phenotype of the cell/tissue being assayed. In yet other embodiments, the obtained expression profile is compared to two or more different reference/control profiles to obtain more in depth information regarding the phenotype of the assayed cell/tissue. For example, the obtained expression profile may be compared to a positive and negative reference profile to obtain confirmed information regarding whether the cell/tissue has the phenotype of interest.
The comparison of the obtained expression profile and the one or more reference/control profiles may be performed using any convenient methodology, where a variety of methodologies are known to those of skill in the array art, e.g., by comparing digital images of the expression profiles, by comparing databases of expression data, etc. Patents describing ways of comparing expression profiles include, but are not limited to, U.S. Pat. Nos. 6,308,170 and 6,228,575, the disclosures of which are herein incorporated by reference. Methods of comparing expression profiles are also described above.
The comparison step results in information regarding how similar or dissimilar the obtained expression profile is to the control/reference profile(s), which similarity/dissimilarity information is employed to determine the phenotype of the cell/tissue being assayed and thereby evaluate graft survival in the subject. For example, similarity with a positive control indicates that the assayed cell/tissue has a graft survival phenotype. Likewise, similarity with a negative control indicates that the assayed cell/tissue has a graft loss phenotype.
Depending on the type and nature of the reference/control profile(s) to which the obtained expression profile is compared, the above comparison step yields a variety of different types of information regarding the cell/tissue that is assayed. As such, the above comparison step can yield a positive/negative determination of a graft survival phenotype of an assayed cell/tissue. In many embodiments, the above-obtained information about the cell/tissue being assayed is employed to diagnose a host, subject or patient with respect to graft survival, as described above. In certain embodiments, the determination/prediction of graft survival and loss can be coupled with a determination of additional characteristics of the graft and function thereof. For example, in certain embodiments one can predict not only whether graft loss will occur, but the mechanism of graft loss, e.g., via CAN or DT. The first 9 genes in the cluster illustrated in FIG. 4 are highly-differentially expressed between CAN and DT. As such, evaluating one or more of these genes permits these two overlapping conditions to be readily distinguished, such that one can readily determine the presence of CAN or DT.
The subject methods further find use in pharmacogenomic applications. In these applications, a subject/host/patient is first diagnosed for graft function according to the subject invention, and then treated using a protocol determined, at least in part, on the results of the diagnosis. For example, a host may be evaluated for the presence of absence of the graft survival phenotype using a protocol such as the diagnostic protocol described in the preceding section. The subject may then be treated using a protocol whose suitability is determined using the results of the diagnosis step. In embodiments, where the host is evaluated for the presence or absence of CAN or DT, treatment protocols may correspondingly be adjusted based on the obtained results. For example, where the subject methods are employed to determine the presence of CAN, immunosuppressive therapy can be modulated, e.g., increased or drugs changed, as is known in the art for the treatment of CAN. Likewise, where the subject methods are employed and detect the presence of DT, the immunosuppressive therapy can be reduced in order to treat the DT. In practicing the subject methods, a subject is typically screened for the presence of a graft survival or loss phenotype following receipt of a graft or transplant. The subject may be screened once or serially following transplant receipt, e.g., weekly, monthly, bimonthly, half-yearly, yearly, etc. In certain embodiments, the subject is screened following occurrence of acute rejection (AR). In such embodiments, the methods are employed to evaluate, e.g., predict, ultimate graft loss or survival in the subject following AR.
The subject methods may be employed with a variety of different types of transplant subjects. In many embodiments, the subjects are within the class mammalian, including the orders carnivore (e.g., dogs and cats), rodentia (e.g., mice, guinea pigs, and rats), lagomorpha (e.g. rabbits) and primates (e.g., humans, chimpanzees, and monkeys). In certain embodiments, the animals or hosts, i.e., subjects (also referred to herein as patients) will be humans.
The methods may be used to evaluate survival of a variety of different types of grafts. Grafts of interest include, but are not limited to: transplanted heart, kidney, lung, liver, pancreas, pancreatic islets, brain tissue, stomach, large intestine, small intestine, cornea, skin, trachea, bone, bone marrow, muscle, bladder or parts thereof.
Databases of Expression Profiles of Phenotype Determinative Genes
Also provided are databases of expression profiles of graft survival and/or graft loss phenotype determinative genes. Such databases will typically comprise expression profiles of various cells/tissues having graft tolerant phenotypes, negative expression profiles, etc., where such profiles are further described below.
The expression profiles and databases thereof may be provided in a variety of media to facilitate their use. “Media” refers to a manufacture that contains the expression profile information of the present invention. The databases of the present invention can be recorded on computer readable media, e.g. any medium that can be read and accessed directly by a computer. Such media include, but are not limited to: magnetic storage media, such as floppy discs, hard disc storage medium, and magnetic tape; optical storage media such as CD-ROM; electrical storage media such as RAM and ROM; and hybrids of these categories such as magnetic/optical storage media. One of skill in the art can readily appreciate how any of the presently known computer readable mediums can be used to create a manufacture comprising a recording of the present database information. “Recorded” refers to a process for storing information on computer readable medium, using any such methods as known in the art. Any convenient data storage structure may be chosen, based on the means used to access the stored information. A variety of data processor programs and formats can be used for storage, e.g. word processing text file, database format, etc.
As used herein, “a computer-based system” refers to the hardware means, software means, and data storage means used to analyze the information of the present invention. The minimum hardware of the computer-based systems of the present invention comprises a central processing unit (CPU), input means, output means, and data storage means. A skilled artisan can readily appreciate that any one of the currently available computer-based system are suitable for use in the present invention. The data storage means may comprise any manufacture comprising a recording of the present information as described above, or a memory access means that can access such a manufacture.
A variety of structural formats for the input and output means can be used to input and output the information in the computer-based systems of the present invention. One format for an output means ranks expression profiles possessing varying degrees of similarity to a reference expression profile. Such presentation provides a skilled artisan with a ranking of similarities and identifies the degree of similarity contained in the test expression profile.
Reagents, Systems and Kits
Also provided are reagents, systems and kits thereof for practicing one or more of the above-described methods. The subject reagents, systems and kits thereof may vary greatly. Reagents of interest include reagents specifically designed for use in production of the above-described expression profiles of phenotype determinative genes, i.e., a gene expression evaluation element made up of one or more reagents. The term system refers to a collection of reagents, however compiled, e.g., by purchasing the collection of reagents from the same or different sources. The term kit refers to a collection of reagents provided, e.g., sold, together.
One type of such reagent is an array of probe nucleic acids in which the phenotype determinative genes of interest are represented. A variety of different array formats are known in the art, with a wide variety of different probe structures, substrate compositions and attachment technologies. Representative array structures of interest include those described in U.S. Pat. Nos. 5,143,854; 5,288,644; 5,324,633; 5,432,049; 5,470,710; 5,492,806; 5,503,980; 5,510,270; 5,525,464; 5,547,839; 5,580,732; 5,661,028; 5,800,992; the disclosures of which are herein incorporated by reference; as well as WO 95/21265; WO 96/31622; WO 97/10365; WO 97/27317; EP 373 203; and EP 785 280.
In certain embodiments, the arrays include probes for at least 1 of the genes listed in Tables 1 and/or 2. In certain embodiments, the number of genes that are from Tables 1 and/or 2 that is represented on the array is at least 5, at least 10, at least 25, at least 50, at least 75 or more, including all of the genes listed in Tables 1 and/or 2. The subject arrays may include only those genes that are listed in Tables 1 and/or 2, or they may include additional genes that are not listed in Tables 1 and/or 2, such as probes for genes whose expression pattern can be used to evaluate additional transplant characteristics, including but not limited to: acute rejection; chronic allograft injury (chronic rejection) in blood; immunosuppressive drug toxicity or adverse side effects including drug-induced hypertension; age or body mass index associated genes that correlate with renal pathology or account for differences in recipient age-related graft acceptance; immune tolerance markers in whole blood; genes found in literature surveys with immune modulatory roles that may play a role in transplant outcomes (see e.g., Table 3 for a list of representative additional genes); as well as other array assay function related genes, e.g., for assessing sample quality (3′- to 5′-bias in probe location), sampling error in biopsy-based studies, cell surface markers, and normalizing genes for calibrating hybridization results; and the like. Where the subject arrays include probes for such additional genes, in certain embodiments the number % of additional genes that are represented and are not directly or indirectly related to transplantation does not exceed about 50%, usually does not exceed about 25%. In certain embodiments where additional genes are included, a great majority of genes in the collection are transplant characterization genes, where by great majority is meant at least about 75%, usually at least about 80% and sometimes at least about 85, 90, 95% or higher, including embodiments where 100% of the genes in the collection are phenotype determinative genes. Transplant characterization genes are genes whose expression can be employed to characterize transplant function in some manner, e.g., presence of rejection, etc.
Another type of reagent that is specifically tailored for generating expression profiles of phenotype determinative genes is a collection of gene specific primers that is designed to selectively amplify such genes. Gene specific primers and methods for using the same are described in U.S. Pat. No. 5,994,076, the disclosure of which is herein incorporated by reference. Of particular interest are collections of gene specific primers that have primers for at least 1 of the genes listed in one Tables 1 and/or 2, often a plurality of these genes, e.g., at least 2, 5, 10, 15 or more. In certain embodiments, the number of genes that are from Tables 1 and/or 2 that have primers in the collection is at least 5, at least 10, at least 25, at least 50, at least 75 or more, including all of the genes listed in Tables 1 and/or 2. The subject gene specific primer collections may include only those genes that are listed in Tables 1 and/or 2, or they may include primers for additional genes that are not listed in Tables 1 and/or 2, such as probes for genes whose expression pattern can be used to evaluate additional transplant characteristics, including but not limited to: acute rejection; chronic allograft injury (chronic rejection) in blood; immunosuppressive drug toxicity or adverse side effects including drug-induced hypertension; age or body mass index associated genes that correlate with renal pathology or account for differences in recipient age-related graft acceptance; immune tolerance markers in whole blood; genes found in literature surveys with immune modulatory roles that may play a role in transplant outcomes (see e.g., Table 3 for a list of representative additional genes); as well as other array assay function related genes, e.g., for assessing sample quality (3′- to 5′-bias in probe location), sampling error in biopsy-based studies, cell surface markers, and normalizing genes for calibrating hybridization results; and the like. Where the subject arrays include probes for such additional genes, in certain embodiments the number % of additional genes that are represented and are not directly or indirectly related to transplantation does not exceed about 50%, usually does not exceed about 25%. In certain embodiments where additional genes are included, a great majority of genes in the collection are transplant characterization genes, where by great majority is meant at least about 75%, usually at least about 80% and sometimes at least about 85, 90, 95% or higher, including embodiments where 100% of the genes in the collection are phenotype determinative genes.
The systems and kits of the subject invention may include the above-described arrays and/or gene specific primer collections. The systems and kits may further include one or more additional reagents employed in the various methods, such as primers for generating target nucleic acids, dNTPs and/or rNTPs, which may be either premixed or separate, one or more uniquely labeled dNTPs and/or rNTPs, such as biotinylated or Cy3 or Cy5 tagged dNTPs, gold or silver particles with different scattering spectra, or other post synthesis labeling reagent, such as chemically active derivatives of fluorescent dyes, enzymes, such as reverse transcriptases, DNA polymerases, RNA polymerases, and the like, various buffer mediums, e.g. hybridization and washing buffers, prefabricated probe arrays, labeled probe purification reagents and components, like spin columns, etc., signal generation and detection reagents, e.g. streptavidin-alkaline phosphatase conjugate, chemifluorescent or chemiluminescent substrate, and the like.
The subject systems and kits may also include a phenotype determination element, which element is, in many embodiments, a reference or control expression profile that can be employed, e.g., by a suitable computing means, to make a phenotype determination based on an “input” expression profile, e.g., that has been determined with the above described gene expression evaluation element. Representative phenotype determination elements include databases of expression profiles, e.g., reference or control profiles, as described above.
In addition to the above components, the subject kits will further include instructions for practicing the subject methods. These instructions may be present in the subject kits in a variety of forms, one or more of which may be present in the kit. One form in which these instructions may be present is as printed information on a suitable medium or substrate, e.g., a piece or pieces of paper on which the information is printed, in the packaging of the kit, in a package insert, etc. Yet another means would be a computer readable medium, e.g., diskette, CD, etc., on which the information has been recorded. Yet another means that may be present is a website address which may be used via the internet to access the information at a removed site. Any convenient means may be present in the kits.
The following examples are offered by way of illustration and not by way of limitation.
EXPERIMENTAL I. Introduction
The objective of this study was to determine whether gene expression markers could be identified in RNA extracted from peripheral blood leukocytes (PBL) or renal biopsies predictive of future graft loss following AR.
II. Array Experiments
Each microarray contained approximately 32,000 DNA spots representing approximately 12,440 human genes. Total RNA was isolated (Tri Reagent; MRC Inc., Cincinnati, Ohio) from buffy coats isolated from whole blood samples. A common reference RNA pool (Perou et al., Nature (2000) 406:747-52) was used as an internal standard. Sample or reference RNA were subjected to two successive rounds of amplification before hybridization to microarrays using an improved protocol based on the method described by Wang et al (please provide entire cite). Array data for 62 renal biopsy samples and 56 whole blood samples were stored in the Stanford Microarray database (Sherlock et al., Nuc. Acids Res. (2001) 29:152-55) and gene lists filtered at retrieval to provide expression markers with high fidelity. The two groups of samples were analyzed in two separate studies. All PBL were used for initial unsupervised hierarchical clustering (Eisen et al., Proc. Nat'l Acad. Sci. USA (1998) 95:14863-8), for subsequent supervised analyses between groups (Significance Analysis of Microarrays; SAM (Tusher et al., Proc. Nat'l Acad. Sci. USA (2001) 98:5116-21).
III. Customizing a Minimal Gene-Set for AR Class Prediction and Risk Assessment
We used Predictive Analysis of Microarrays (PAM) (Tusher et al., supra) to identify only 97 genes within the renal biopsy dataset, all having >5-fold difference in expression level, which classify our learning set of 26 AR samples with 100% concordance to assigned phenotype. Another analysis using a larger set of 3,170 differentially expressed genes identifies the 33 classifiers with similar power (FIGS. 1A and 1B). Reproducibility of the diagnostic signature, in particular within the majority of the AR-1 samples, is evident by the short branches in the cluster dendogram. AR expression overlaps with the innate immune response to infection, as evidenced by cluster analysis and by differential expression of several TGF-β-modulated genes including RANTES, MIC-1, several cytokines, chemokines, and cell-adhesion molecules. AR-1 is the most severe class with the highest rate of graft loss and highest expression of B-cell specific genes. AR-2 resembles a drug-toxicity signature and also co-clusters with patients with active viral infections. The most striking feature of AR-3 is the expression of genes involved in cellular proliferation and cell cycling suggesting active tissue repair and regeneration. The presence of proliferating-cell nuclear antigen (PCNA), a marker of cell proliferation, was confirmed in all AR-3 samples tested (Sarwal et al. New Engl. J. Med. 2003 349(2):125-38).
The PAM classification scores grouped the samples with 100% concordance to assigned classes and reported scores are aligned with the clustered samples (FIG. 1B). In addition, all 33 genes selected by PAM have Significance Analysis of Microarrays significance scores of 0.09% or lower suggesting that they would be highly significant biomarkers for a customized array list.
A. PAM Class Prediction—
PAM class prediction has also proven to be a powerful approach to identify putative biomarkers for graft recovery and graft loss. We have used both Cox-regression and PAM to correlate expression differences with graft outcome with good success. Both methods yield significant results in Kaplan-Meier survival analysis although at the initial 2-year follow-up genes identified by PAM also yield greater significance. (FIG. 2—Kaplan-Meier survival analysis for graft loss (red) and no-loss (blue. The genes include ICAM5-FIG. 2A; (p=0.007), IL6R; FIG. 2B; (p=0.003), STAT1; FIG. 2C; (p=0.036), and STAT6; FIG. 2D; (p=0.020)).
The gene signature is dominated by increased expression of cell adhesion genes, selected cytokines, B-cell genes, representatives in the STAT signaling pathway and several immune response genes including multiple representatives of both class I and class II HLA genes.
Representative genes include those from HLA class I (HLA-F, HLA-G), HLA class II (HLA-DRB1, HLA-DRB5, HLA-DRB4), signal transducers (STAT1, STAT6), immunoglobulin genes (IGKC, IGHG3), and 2 interferon gamma induced genes (ICAM5, IL6R).
A similar approach was used to identify graft-loss markers in whole blood samples. The list of the most highly-predictive significant genes in blood is summarized in Table 4, including the Kaplan-Meier survival significance score.
TABLE 4
Fold
Unigene Loss/
Symbol Gene ID No-loss p-value
HIST1H2BC Histone
1, H2bc Hs.356901 −3.46 0.00018
IGHG3 Ig heavy constant gamma 3 (G3m marker) Hs.413826 4.14 0.00134
AHSA2 Activator of heat shock ATPase Hs.122440 2.91 0.00041
TNFRSF10D TNF receptor superfamily 10b Hs.129844 −2.55 0.00010
MAPK9 Mitogen-activated protein kinase 9 Hs.348446 8.14 0.00444
IFNAR2 Interferon (alpha, beta and omega) receptor 2 Hs.86958 −2.37 0.01760
TM4SF9 Transmembrane 4 superfamily member 9 Hs.8037 −15.29 0.00580
MIF Macrophage migration inhibitory factor Hs.407995 −2.31 0.00674
SCYE1 Small inducible cytokine (Monocyte-activating) Hs.105656 2.51 0.00154
MAPK1 Mitogen-activated protein kinase 1 Hs.324473 −2.32 0.00019
TGFBR3 TGFb receptor III (betaglycan) Hs.342874 −2.94 0.00318
IGKC Immunoglobulin kappa constant Hs.377975 2.35 0.00290
IL1R2 Interleukin 1 receptor, type II Hs.25333 −4.06 0.01762
IGL Immunoglobulin lambda light chain 3.04 0.02093
The Kaplan-Meier survival curves for 8 of these genes are illustrated in FIG. 3. The genes in FIG. 3 include A) AHSA2, B) IGHG1, C) IFNAR2, D) IGKC, E) HIST1H2BC, F) IL1R2, G) MAPK1, and H) MAPK9.
The functional composition of genes associated with acute rejection, predicted by analysis of Gene Ontology annotations, is summarized in Table 5.
TABLE 5
Genes on EASE Fisher
Gene Category Genes Array Score Exact
defense response 105 747 7.15E−12 3.35E−12
response to stimulus/ 152 1482 0.00000108 7.24E−07
acute phase response
apoptosis
50 361 0.00000772 3.63E−06
cell cycle 71 597 0.0000174 9.84E−06
cell proliferation 96 899 0.0000403 0.0000256
protein metabolism 176 1941 0.000228 0.000172
antigen presentation 9 29 0.000707 0.000123
cell growth and/or 244 2887 0.000766 0.000623
maintenance
phosphorylation 53 512 0.00539 0.00353
protein modification 84 902 0.00775 0.00545
hemopoiesis 10 53 0.0116 0.00374
DNA replication 17 122 0.0125 0.00571
B-cell activation 6 22 0.0171 0.00356
The full list of known genes (in ranked order) in whole blood that are predictive of graft loss following acute rejection is summarized in Table 1. Of the 81 cDNA clones identified to have the highest predictive power, 62 are of known function or assigned unique Unigene Cluster IDs. Similarly, the list of known genes identified in renal biopsies predictive of graft loss following acute rejection is summarized in Table 2 (including 30 unique genes of known function from the 50 cDNA associated clones).
IV. Generation of a Transplant Custom Expression Chip TxChip
We have compiled the gene lists described in this document for AR and graft loss along with other expression-based markers identified to be associated with clinical outcomes and severity of:
1. Acute rejection—including markers associated with graft loss and/or rate of recovery of renal function following AR (Table 3);
2. Chronic allograft injury (chronic rejection) in blood (Table 3);
3. Immunosuppressive drug toxicity or adverse side effects including drug-induced hypertension (Table 3);
4. Age or body mass index associated genes that correlate with renal pathology or account for differences in recipient age-related graft acceptance (Table 3);
5. Immune tolerance markers in whole blood (Table 3);
6. Control genes for assessing sample quality (3′- to 5′-bias in probe location), sampling error in biopsy-based studies, cell surface markers, and normalizing genes for calibrating hybridization results;
7. Genes found in literature surveys with immune modulatory roles that may play a role in transplant outcomes (Table 3) to produce the list for a representative array having probes to genes listed in Table 3.
A. Test of Expression Uniformity Across a Pilot Study of Renal Biopsies.
In the identification of the gene markers described in this invention disclosure, we compared the expression across a set of 67 renal biopsies described in detail by our laboratory. A subset of the biopsy-generated gene expression markers was used clustered to compare expression profiles in patients with confirmed cases of DT, CAN, AR and no significant abnormality (Normal). These patients were on two very different immunosuppressant regimes, either steroid-based or steroid-free (clinical regiment previously described in (Sarwal et al., Transplantation (2001) 72:13-21) and Sarwal et al., Transplantation (2003) 76:1331-9).
FIG. 4 illustrates that the gene expression is generally uniform/consistent across the full clinical groups analyzed as the gene expression levels segregate well within patient groups. Further, within each group (DT, CAN, AR or Normal) expression levels of these marker genes are independent of immunosuppression use.
The 479 gene list of Table 3 comprises design and specification for a customized thematic Transplant Chip (TxChip V1) and full-length mRNA sequences for these genes are listed in Table 3. The gene listing is cross-indexed to the studies listed above. We observe a modest overlap in the list of informative genes. For example, expression levels of IGHM positively correlate with acute rejection risk and negatively correlate with immune tolerance. An advantage of having the full compilation of genes on a common platform is that new discoveries like this can be made in future studies.
It is evident that subject invention provides a convenient and effective way of determining whether a graft in a subject will survive, e.g., following acute rejection. As such, the subject invention provides a number of distinct benefits, including the ability to identify clinically relevant AR groups with differing therapeutic responses and prognosis, and allow for individualized treatment and monitoring. As such, the subject invention represents a significant contribution to the art.
Although the foregoing invention has been described in some detail by way of illustration and example for purposes of clarity of understanding, it is readily apparent to those of ordinary skill in the art in light of the teachings of this invention that certain changes and modifications may be made thereto without departing from the spirit or scope of the appended claims.
Accordingly, the preceding merely illustrates the principles of the invention. It will be appreciated that those skilled in the art will be able to devise various arrangements which, although not explicitly described or shown herein, embody the principles of the invention and are included within its spirit and scope. Furthermore, all examples and conditional language recited herein are principally intended to aid the reader in understanding the principles of the invention and the concepts contributed by the inventors to furthering the art, and are to be construed as being without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, and embodiments of the invention as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents and equivalents developed in the future, i.e., any elements developed that perform the same function, regardless of structure. The scope of the present invention, therefore, is not intended to be limited to the exemplary embodiments shown and described herein. Rather, the scope and spirit of present invention is embodied by the appended claims.

Claims (21)

What is claimed is:
1. A method of evaluating graft survival in a subject gene expression levels of at least two genes in a sample from a transplant recipient, said method comprising:
providing a sample from a transplant recipient; and
assessingmeasuring an amount of expression of at least two genes in athe sample from said subject to evaluate graft survival in said subject, wherein said at least two genes comprises HIST1H2BHIST1H2BC and IGHG3.
2. The method according to claim 1, wherein said expression of at least two genes is assessed by assaying said sample for a nucleic acid transcript of said gene.
3. The method according to claim 1, wherein said expression of at least two genes is assessed by assaying said sample for an expression product of said gene.
4. The method according to any of claim 1, wherein said sample is a blood sample.
5. The method according to claim 4, wherein said blood sample is a peripheral blood sample.
6. The method according to claim 1, wherein said sample is a tissue biopsy sample.
7. A method according to claim 1, wherein the method comprises: obtaining an expression profile for a sample from said subject.
8. The method according to claim 7, wherein said expression profile is compared to a reference expression profile.
9. The method according to claim 8 7, wherein said expression profile is a nucleic acid expression profile.
10. The method according to claim 8 7, wherein said expression profile comprises expression measurements for at least 5 different genes.
11. The method according to claim 8 7, wherein said expression profile is determined using a microarray.
12. The method according to claim 11, wherein said microarray is a genomic array.
13. A method of managing post-transplantation therapy in a subject, said method treating a transplant recipient comprising:
(a) evaluating determining that a transplant recipient has a graft survival in said subject by a method according to claim 1; and phenotype by evaluating results previously obtained from a quantitative determination of nucleic acid expression levels of at least two genes in a sample from the transplant recipient, and
treating said transplant recipient by maintaining a current therapeutic regimen; or
(b) determining a post-transplantation therapy protocol based on said evaluation step (a); that a transplant recipient has a graft loss phenotype by evaluating results previously obtained from a quantitative determination of nucleic acid expression levels of at least two genes in a sample from the transplant recipient, and
treating said transplant recipient by increasing or decreasing a therapeutic regimen;
wherein, said evaluating comprises comparing said results to a reference nucleic acid expression profile comprising said at least two genes; and
to manage post-transplantation therapy in said subjectwherein said at least two genes comprises HIST1H2BC and IGHG3.
14. The method according to claim 13, wherein said subject is a human.
15. The method according to claim 1, wherein said at least two genes further comprises one or more genes selected from: AHSA2, TNFRSF10D, MAPK9, IFNAR2, TM4SF9, MIF, SCYE1, MAPK1, TGFBR3, IGKC, IL1R2 and IGL.
16. The method of claim 7, wherein said expression profile comprises expression measurements for at least ten different genes.
17. A method of assaying gene expression in a blood sample from a graft recipient, the method comprising:
a) receiving a sample of blood from a patient that has received a graft; and
b) assaying the expression of at least two genes in the blood sample, wherein said at least two genes comprises HIST1H2BC and IGHG3.
18. The method according to claim 13, wherein the therapeutic regimen is an immunosuppressive therapy.
19. The method according to claim 13, comprising: determining that the transplant recipient has a graft loss phenotype that is calcineurin-inhibitor drug nephrotoxicity (DT); and decreasing an immunosuppressive therapy.
20. The method according to claim 13, comprising: (i) determining that the transplant recipient has a graft loss phenotype that is chronic allograft nephropathy (CAN); and (ii) increasing an immunosuppressive therapy, or changing an immunosuppressive therapy by administering a different immunosuppressive drug.
21. The method according to claim 1, further comprising measuring an amount of expression of control genes in the sample.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10538813B2 (en) 2009-01-15 2020-01-21 The Board Of Trustees Of The Leland Stanford Junior University Biomarker panel for diagnosis and prediction of graft rejection
US11768208B2 (en) 2010-03-25 2023-09-26 The Board Of Trustees Of The Leland Stanford Junior University Protein and gene biomarkers for rejection of organ transplants

Families Citing this family (47)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
AU2002950779A0 (en) * 2002-08-15 2002-09-12 The Corporation Of The Trustees Of The Order Of The Sisters Of Mercy In Queensland A method of immunomodulation
EP1718768B1 (en) * 2004-01-21 2012-05-09 The Board Of Trustees Of The Leland Stanford Junior University Methods and compositions for determining a graft tolerant phenotype in a subject
USRE46843E1 (en) 2005-03-14 2018-05-15 The Board Of Trustees Of The Leland Stanford Junior University Methods and compositions for evaluating graft survival in a solid organ transplant recipient
US7741038B2 (en) 2005-03-14 2010-06-22 The Board Of Trustees Of The Leland Stanford Junior University Methods and compositions for evaluating graft survival in a solid organ transplant recipient
CA2661487A1 (en) * 2006-08-28 2008-03-06 Source Precision Medicine Gene expression profiling for identification, monitoring and treatment of transplant rejection
US8003333B2 (en) * 2007-09-28 2011-08-23 Mayo Foundation For Medical Education And Research Serum biomarkers for early detection of acute cellular rejection
EP2088205A1 (en) 2008-02-11 2009-08-12 Institut National De La Sante Et De La Recherche Medicale (Inserm) PSMB10: A diagnosis marker and therapeutic target of chronic rejection.
ES2341419B1 (en) * 2008-08-14 2011-05-03 Hospital Clinic I Provincial De Barcelona WNT1 AS RENAL DAMAGE BIOMARCATOR.
WO2010021696A1 (en) 2008-08-18 2010-02-25 The Board Of Trustees Of The Leland Stanford Junior University Methods and compositions for determining a graft tolerant phenotype in a subject
AU2009285550B2 (en) * 2008-08-28 2015-06-18 Astute Medical, Inc. Methods and compositions for diagnosis and prognosis of renal injury and renal failure
EP2813848A3 (en) * 2008-08-29 2015-03-11 Astute Medical, Inc. Methods and compositions for diagnosis and prognosis of renal injury and renal failure
EP2364444A4 (en) 2008-10-21 2012-08-08 Astute Medical Inc Methods and compositions for diagnosis and prognosis of renal injury and renal failure
US20110207161A1 (en) * 2008-10-21 2011-08-25 Astute Medical, Inc. Methods and compositions for diagnosis and prognosis of renal injury and renal failure
US8993250B2 (en) 2008-11-10 2015-03-31 Astute Medical, Inc. Methods and compositions for diagnosis and prognosis of renal injury and renal failure
AU2009316387B2 (en) * 2008-11-22 2015-01-29 Astute Medical, Inc. Methods and compositions for diagnosis and prognosis of renal injury and renal failure
US9229010B2 (en) 2009-02-06 2016-01-05 Astute Medical, Inc. Methods and compositions for diagnosis and prognosis of renal injury and renal failure
WO2011017654A1 (en) 2009-08-07 2011-02-10 Astute Medical, Inc. Methods and compositions for diagnosis and prognosis of renal injury and renal failure
WO2011006119A2 (en) 2009-07-09 2011-01-13 The Scripps Research Institute Gene expression profiles associated with chronic allograft nephropathy
CA2779902A1 (en) 2009-11-07 2011-05-12 Astute Medical, Inc. Methods and compositions for diagnosis and prognosis of renal injury and renal failure
WO2011066380A1 (en) * 2009-11-25 2011-06-03 The Board Of Trustees Of The Leland Stanford Junior University Biomarkers for the diagnosis of kidney graft rejection
CA2782803C (en) 2009-12-02 2020-09-01 The Board Of Trustees Of The Leland Stanford Junior University Biomarkers for determining an allograft tolerant phenotype
CN102725636B (en) 2009-12-20 2015-04-01 阿斯图特医药公司 Methods and compositions for diagnosis and prognosis of renal injury and renal failure
US11454635B2 (en) 2010-02-05 2022-09-27 Astute Medical, Inc. Methods and compositions for diagnosis and prognosis of renal injury and renal failure
WO2011106746A1 (en) 2010-02-26 2011-09-01 Astute Medical, Inc. Methods and compositions for diagnosis and prognosis of renal injury and renal failure
GB201007454D0 (en) * 2010-05-04 2010-06-16 King S College London Method of determining tolerance
CA2804297A1 (en) 2010-06-23 2011-12-29 Astute Medical, Inc. Methods and compositions for diagnosis and prognosis of renal injury and renal failure
NZ703055A (en) * 2010-06-23 2016-07-29 Astute Medical Inc Methods and compositions for diagnosis and prognosis of renal injury and renal failure
US20130210043A1 (en) * 2010-06-23 2013-08-15 Astute Medical, Inc. Methods and compositions for diagnosis and prognosis of renal injury and renal failure
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WO2012106632A1 (en) * 2011-02-03 2012-08-09 The Board Of Trustees Of The Leland Stanford Junior University Biomarkers for determining an allograft tolerant phenotype
WO2012139051A2 (en) 2011-04-06 2012-10-11 The Board Of Trustees Of The Leland Stanford Junior University Autoantibody biomarkers for iga nephropathy
KR20150044834A (en) * 2011-10-24 2015-04-27 소마로직, 인크. Selection of preferred sample handling and processing protocol for identification of disease biomarkers and sample quality assessment
EP2788759B1 (en) 2011-12-08 2019-02-20 Astute Medical, Inc. Methods and uses for diagnosis of renal injury and renal failure
EP4105657B1 (en) 2013-01-17 2024-09-25 Astute Medical, Inc. Methods and compositions for diagnosis and prognosis of renal injury and renal failure
EP3041955A4 (en) * 2013-09-06 2017-05-03 Immucor GTI Diagnostics, Inc. Compositions and methods for diagnosis and prediction of solid organ graft rejection
CN103675300B (en) * 2014-01-03 2015-10-14 苏州工业园区为真生物医药科技有限公司 RBX1 is as the application of blood serum designated object and kit thereof
US11104951B2 (en) 2014-05-22 2021-08-31 The Scripps Research Institute Molecular signatures for distinguishing liver transplant rejections or injuries
US10443100B2 (en) 2014-05-22 2019-10-15 The Scripps Research Institute Gene expression profiles associated with sub-clinical kidney transplant rejection
WO2017214203A1 (en) 2016-06-06 2017-12-14 Astute Medical, Inc. Management of acute kidney injury using insulin-like growth factor-binding protein 7 and tissue inhibitor of metalloproteinase 2
US10975438B2 (en) * 2016-09-08 2021-04-13 INSERM (Institut National de la Santé et de la Recherche Médicale) Methods and compositions for predicting chronic lung allograft dysfunction
WO2018145117A1 (en) 2017-02-06 2018-08-09 Astute Medical, Inc. Methods and compositions for diagnosis and prognosis of renal injury and renal failure
WO2019107673A1 (en) * 2017-11-29 2019-06-06 서울대학교병원 Bio-marker for monitoring antibody-mediated rejection in abo blood type-incompatible transplantation
CN111593113A (en) * 2020-05-21 2020-08-28 中国科学院大学宁波华美医院 VEGF gene binding site detection method based on novel acute rejection reaction mechanism
WO2022031877A1 (en) * 2020-08-05 2022-02-10 Children's Hospital Medical Center Compositions and methods for the treatment of bronchiolitis obliterans
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CN116486922B (en) * 2023-04-18 2024-01-23 中日友好医院(中日友好临床医学研究所) Method for predicting lung transplant rejection based on gene polymorphism and plasma cytokines and application thereof

Citations (50)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030007968A1 (en) 2001-01-26 2003-01-09 Larsen Christian P. Methods of inducing organ transplant tolerance and correcting hemoglobinopathies
US20030017619A1 (en) 1998-03-31 2003-01-23 Asahi Kasei Kabushiki Kaisha Test method for IgA nephropathy
US20030022252A1 (en) 2001-07-13 2003-01-30 Thomson Angus W. Method for identifying tolerance in graft recipients
US20030104371A1 (en) 1997-09-24 2003-06-05 Strom Terry B. Methods of evaluating transplant rejection
US6607879B1 (en) 1998-02-09 2003-08-19 Incyte Corporation Compositions for the detection of blood cell and immunological response gene expression
US20040163654A1 (en) 2002-11-21 2004-08-26 Genzyme Corporation Inhibition of chronic tissue transplant rejection
WO2004074815A2 (en) 2003-02-14 2004-09-02 Beth Israel Deaconess Medical Center, Inc. Predicting graft rejection
WO2005005601A2 (en) 2003-06-09 2005-01-20 The Regents Of The University Of Michigan Compositions and methods for treating and diagnosing cancer
US20050025769A1 (en) 1999-01-22 2005-02-03 Fujisawa Pharmaceutical Company, Ltd. Method of suppressing ongoing acute allograft rejection
WO2005070086A2 (en) 2004-01-21 2005-08-04 The Board Of Trustees Of The Leland Stanford Junior University Methods and compositions for determining a graft tolerant phenotype in a subject
US20060073496A1 (en) 2004-07-20 2006-04-06 O'toole Margot Methods of identifying patients at risk of developing encephalitis following immunotherapy for Alzheimer's disease
US7026121B1 (en) 2001-06-08 2006-04-11 Expression Diagnostics, Inc. Methods and compositions for diagnosing and monitoring transplant rejection
US20060088836A1 (en) 2002-04-24 2006-04-27 Jay Wohlgemuth Methods and compositions for diagnosing and monitoring transplant rejection
US20060088876A1 (en) 2004-08-03 2006-04-27 Bauer A R Method for the early detection of breast cancer, lung cancer, pancreatic cancer and colon polyps, growths and cancers as well as other gastrointestinal disease conditions and the preoperative and postoperative monitoring of transplanted organs from the donor and in the recipient and their associated conditions related and unrelated to the organ transplantation
WO2006099421A2 (en) 2005-03-14 2006-09-21 The Board Of Trustees Of The Leland Stanford Junior University Methods and compositions for evaluating graft survival in a solid organ transplant recipient
US20060269949A1 (en) 2005-05-23 2006-11-30 Halloran Philip F Tissue rejection
EP1731620A1 (en) 2005-06-07 2006-12-13 Institut National De La Sante Et De La Recherche Medicale (Inserm) Method for the diagnosis of immune graft tolerance
US20060281122A1 (en) 2005-06-08 2006-12-14 Millennium Pharmaceuticals, Inc. Methods for the identification, assessment, and treatment of patients with cancer therapy
US20070111210A1 (en) 2003-12-03 2007-05-17 Marc Bigaud Biomarkers for graft rejection
US20070134261A1 (en) 2001-12-03 2007-06-14 Hancock Robert E Effectors of innate immunity
US20070134728A1 (en) 2005-10-25 2007-06-14 Renovar Incorporated Systems and methods for characterizing conditions and diseases associated with organ transplantation and organ health
US20070212701A1 (en) 2001-05-11 2007-09-13 O'toole Margot M Methods for diagnosing and treating ischemia and reperfusion injury and compositions thereof
WO2007104537A2 (en) 2006-03-15 2007-09-20 Novartis Ag Methods and compositions for assessing acute rejection
US20070232658A1 (en) 2004-04-08 2007-10-04 Jurgen Wagner Protein Kinase C Inhibitors for the Treatment of Autoimmune Diseases and of Transplant Rejiction
WO2007121922A2 (en) 2006-04-21 2007-11-01 Novartis Ag Biomarkers for chronic transplant dysfunction
US20070264272A1 (en) 2006-04-27 2007-11-15 Universite De Montreal Assessment and reduction of risk of graft-versus-host disease
WO2008009132A1 (en) 2006-07-21 2008-01-24 The Governors Of The University Of Alberta Tissue rejection
WO2008084331A2 (en) 2006-06-21 2008-07-17 Hopitaux Universitaires De Geneve Biomarkers for renal disorders
US20080233573A1 (en) 2006-08-28 2008-09-25 Kathleen Storm Gene expression profiling for identification, monitoring and treatment of transplant rejection
US20080274906A1 (en) 2004-01-30 2008-11-06 Thomas Cappola Novel Predictors of Transplant Rejection Determined by Peripheral Blood Gene-Expression Profiling
US20080280282A1 (en) 2004-08-03 2008-11-13 Bauer Jr A Robert Method for early detection of various cancers and gastrointestinal disease and monitoring of transplanted organs
US20080305493A1 (en) 2004-03-08 2008-12-11 Avalon Pharmaceuticals Determining Cancer-Linked Genes and Therapeutic Targets Using Molecular Cytogenetic Methods
US20090155784A1 (en) 2007-01-22 2009-06-18 Wyeth Assessment of asthma and allergen-dependent gene expression
US20090197286A1 (en) 2006-02-06 2009-08-06 Rappaport Family Institute For Research In The Med Methods and Kit for Diagnosing T1DM
US20090220518A1 (en) 2005-06-07 2009-09-03 Regents Of The University Of Colorado Methods and compositions for treatment of graft rejection and promotion of graft survival
US20090232825A1 (en) 1997-11-07 2009-09-17 Trillium Therapeutics Inc. Methods and Compositions For Modulating Immunity
WO2009143624A1 (en) 2008-05-30 2009-12-03 The University Of British Columbia Methods of diagnosing rejection of a kidney allograft using genomic or proteomic expression profiling
US20090324618A1 (en) 2006-03-24 2009-12-31 Armstrong Scott A Novel signature self renewal gene expression programs
WO2010038974A2 (en) 2008-10-01 2010-04-08 경북대학교 산학협력단 Composition and kit for diagnosing immunoglobulin a nephropathy and tgbm nephropathy
US20100120629A1 (en) 2003-06-20 2010-05-13 Ellis Tamir M Biomarkers for Differentiating Between Type 1 and Type 2 Diabetes
WO2010083121A1 (en) 2009-01-15 2010-07-22 The Board Of Trustees Of The Leland Stanford Junior University Biomarker panel for diagnosis and prediction of graft rejection
US20100234292A1 (en) 2007-04-16 2010-09-16 Ipsogen Methods of assessing a propensity of clinical outcome for a female mammal suffering from breast cancer
US20100305188A1 (en) 2007-10-03 2010-12-02 Kyowa Hakko Kirin Co., Ltd. Nucleic acid capable of regulating the proliferation of cell
US20100304987A1 (en) 2007-01-04 2010-12-02 Alberto Sanchez Fueyo Methods and kits for diagnosis and/or prognosis of the tolerant state in liver transplantation
US7879556B2 (en) 2003-04-24 2011-02-01 Xdx, Inc. Methods and compositions for diagnosing and monitoring transplant rejection
EP2295966A1 (en) 2008-06-02 2011-03-16 Eisai R&D Management Co., Ltd. IgA NEPHROPATHY DETECTION METHOD AND DETECTION KIT
US20110064709A1 (en) 2009-09-16 2011-03-17 Northwestern University Use of ecdi-fixed cell tolerance as a method for preventing allograft rejection
US20110171645A1 (en) 2008-04-09 2011-07-14 The University Of British Columbia Methods of diagnosing acute cardiac allograft rejection
US20110201519A1 (en) 2008-08-18 2011-08-18 Sarwal Minnie M Methods and Compositions for Determining a Graft Tolerant Phenotype in a Subject
US20130157888A1 (en) 2010-05-13 2013-06-20 University Of Medicine And Dentistry Of New Jersey Diagnostic autoantibody profiles for the detection and diagnosis of neurodegenerative diseases

Family Cites Families (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5202231A (en) 1987-04-01 1993-04-13 Drmanac Radoje T Method of sequencing of genomes by hybridization of oligonucleotide probes
US5525464A (en) 1987-04-01 1996-06-11 Hyseq, Inc. Method of sequencing by hybridization of oligonucleotide probes
GB8810400D0 (en) 1988-05-03 1988-06-08 Southern E Analysing polynucleotide sequences
US5143854A (en) 1989-06-07 1992-09-01 Affymax Technologies N.V. Large scale photolithographic solid phase synthesis of polypeptides and receptor binding screening thereof
US5547839A (en) 1989-06-07 1996-08-20 Affymax Technologies N.V. Sequencing of surface immobilized polymers utilizing microflourescence detection
US6040138A (en) 1995-09-15 2000-03-21 Affymetrix, Inc. Expression monitoring by hybridization to high density oligonucleotide arrays
US5800992A (en) 1989-06-07 1998-09-01 Fodor; Stephen P.A. Method of detecting nucleic acids
EP0430881A3 (en) 1989-11-29 1991-10-23 Ciba-Geigy Ag Photochromic compounds, process for their preparation and their use
US5288644A (en) 1990-04-04 1994-02-22 The Rockefeller University Instrument and method for the sequencing of genome
US5324633A (en) 1991-11-22 1994-06-28 Affymax Technologies N.V. Method and apparatus for measuring binding affinity
ATE173767T1 (en) 1992-04-03 1998-12-15 Perkin Elmer Corp SAMPLES COMPOSITION AND METHODS
US5503980A (en) 1992-11-06 1996-04-02 Trustees Of Boston University Positional sequencing by hybridization
US5858659A (en) 1995-11-29 1999-01-12 Affymetrix, Inc. Polymorphism detection
US5470710A (en) 1993-10-22 1995-11-28 University Of Utah Automated hybridization/imaging device for fluorescent multiplex DNA sequencing
GB9401833D0 (en) 1994-02-01 1994-03-30 Isis Innovation Method for discovering ligands
WO1997027317A1 (en) 1996-01-23 1997-07-31 Affymetrix, Inc. Nucleic acid analysis techniques
GB9507238D0 (en) 1995-04-07 1995-05-31 Isis Innovation Detecting dna sequence variations
US5661028A (en) 1995-09-29 1997-08-26 Lockheed Martin Energy Systems, Inc. Large scale DNA microsequencing device
JP2000504575A (en) 1996-02-08 2000-04-18 アフィメトリックス，インコーポレイテッド Chip-based speciation and phenotypic characterization of microorganisms
US5994076A (en) 1997-05-21 1999-11-30 Clontech Laboratories, Inc. Methods of assaying differential expression
US6229911B1 (en) 1997-07-25 2001-05-08 Affymetrix, Inc. Method and apparatus for providing a bioinformatics database

Patent Citations (57)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030104371A1 (en) 1997-09-24 2003-06-05 Strom Terry B. Methods of evaluating transplant rejection
US20090232825A1 (en) 1997-11-07 2009-09-17 Trillium Therapeutics Inc. Methods and Compositions For Modulating Immunity
US6607879B1 (en) 1998-02-09 2003-08-19 Incyte Corporation Compositions for the detection of blood cell and immunological response gene expression
US20030017619A1 (en) 1998-03-31 2003-01-23 Asahi Kasei Kabushiki Kaisha Test method for IgA nephropathy
US20050025769A1 (en) 1999-01-22 2005-02-03 Fujisawa Pharmaceutical Company, Ltd. Method of suppressing ongoing acute allograft rejection
US20030007968A1 (en) 2001-01-26 2003-01-09 Larsen Christian P. Methods of inducing organ transplant tolerance and correcting hemoglobinopathies
US20070212701A1 (en) 2001-05-11 2007-09-13 O'toole Margot M Methods for diagnosing and treating ischemia and reperfusion injury and compositions thereof
US7026121B1 (en) 2001-06-08 2006-04-11 Expression Diagnostics, Inc. Methods and compositions for diagnosing and monitoring transplant rejection
US20070031890A1 (en) 2001-06-08 2007-02-08 Jay Wohlgemuth Methods and compositions for diagnosing and monitoring transplant rejection
US20030022252A1 (en) 2001-07-13 2003-01-30 Thomson Angus W. Method for identifying tolerance in graft recipients
US20070134261A1 (en) 2001-12-03 2007-06-14 Hancock Robert E Effectors of innate immunity
US20060088836A1 (en) 2002-04-24 2006-04-27 Jay Wohlgemuth Methods and compositions for diagnosing and monitoring transplant rejection
US20040163654A1 (en) 2002-11-21 2004-08-26 Genzyme Corporation Inhibition of chronic tissue transplant rejection
WO2004074815A2 (en) 2003-02-14 2004-09-02 Beth Israel Deaconess Medical Center, Inc. Predicting graft rejection
US20070122806A1 (en) 2003-02-14 2007-05-31 Strom Terry B Predicting graft rejection
US7879556B2 (en) 2003-04-24 2011-02-01 Xdx, Inc. Methods and compositions for diagnosing and monitoring transplant rejection
WO2005005601A2 (en) 2003-06-09 2005-01-20 The Regents Of The University Of Michigan Compositions and methods for treating and diagnosing cancer
US20100120629A1 (en) 2003-06-20 2010-05-13 Ellis Tamir M Biomarkers for Differentiating Between Type 1 and Type 2 Diabetes
US20070111210A1 (en) 2003-12-03 2007-05-17 Marc Bigaud Biomarkers for graft rejection
US20090269334A1 (en) 2003-12-03 2009-10-29 Marc Bigaud Biomarkers for graft rejection
WO2005070086A2 (en) 2004-01-21 2005-08-04 The Board Of Trustees Of The Leland Stanford Junior University Methods and compositions for determining a graft tolerant phenotype in a subject
US20080274906A1 (en) 2004-01-30 2008-11-06 Thomas Cappola Novel Predictors of Transplant Rejection Determined by Peripheral Blood Gene-Expression Profiling
US20080305493A1 (en) 2004-03-08 2008-12-11 Avalon Pharmaceuticals Determining Cancer-Linked Genes and Therapeutic Targets Using Molecular Cytogenetic Methods
US20070232658A1 (en) 2004-04-08 2007-10-04 Jurgen Wagner Protein Kinase C Inhibitors for the Treatment of Autoimmune Diseases and of Transplant Rejiction
US20060073496A1 (en) 2004-07-20 2006-04-06 O'toole Margot Methods of identifying patients at risk of developing encephalitis following immunotherapy for Alzheimer's disease
US20060088876A1 (en) 2004-08-03 2006-04-27 Bauer A R Method for the early detection of breast cancer, lung cancer, pancreatic cancer and colon polyps, growths and cancers as well as other gastrointestinal disease conditions and the preoperative and postoperative monitoring of transplanted organs from the donor and in the recipient and their associated conditions related and unrelated to the organ transplantation
US20080280282A1 (en) 2004-08-03 2008-11-13 Bauer Jr A Robert Method for early detection of various cancers and gastrointestinal disease and monitoring of transplanted organs
US20060246485A1 (en) 2005-03-14 2006-11-02 Sarwal Minnie S Methods and compositions for evaluating graft survival in a solid organ transplant recipient
WO2006099421A2 (en) 2005-03-14 2006-09-21 The Board Of Trustees Of The Leland Stanford Junior University Methods and compositions for evaluating graft survival in a solid organ transplant recipient
US20060269949A1 (en) 2005-05-23 2006-11-30 Halloran Philip F Tissue rejection
US20090220518A1 (en) 2005-06-07 2009-09-03 Regents Of The University Of Colorado Methods and compositions for treatment of graft rejection and promotion of graft survival
EP1731620A1 (en) 2005-06-07 2006-12-13 Institut National De La Sante Et De La Recherche Medicale (Inserm) Method for the diagnosis of immune graft tolerance
US20060281122A1 (en) 2005-06-08 2006-12-14 Millennium Pharmaceuticals, Inc. Methods for the identification, assessment, and treatment of patients with cancer therapy
US20070134728A1 (en) 2005-10-25 2007-06-14 Renovar Incorporated Systems and methods for characterizing conditions and diseases associated with organ transplantation and organ health
US20090197286A1 (en) 2006-02-06 2009-08-06 Rappaport Family Institute For Research In The Med Methods and Kit for Diagnosing T1DM
WO2007104537A2 (en) 2006-03-15 2007-09-20 Novartis Ag Methods and compositions for assessing acute rejection
US20090022730A1 (en) 2006-03-15 2009-01-22 Friedrich Raulf Methods and compositions for assessing acute rejection
US20090324618A1 (en) 2006-03-24 2009-12-31 Armstrong Scott A Novel signature self renewal gene expression programs
US20090304705A1 (en) 2006-04-21 2009-12-10 Peter Grass Biomarkers for chronic transplant dysfunction
WO2007121922A2 (en) 2006-04-21 2007-11-01 Novartis Ag Biomarkers for chronic transplant dysfunction
US20070264272A1 (en) 2006-04-27 2007-11-15 Universite De Montreal Assessment and reduction of risk of graft-versus-host disease
WO2008084331A2 (en) 2006-06-21 2008-07-17 Hopitaux Universitaires De Geneve Biomarkers for renal disorders
WO2008009132A1 (en) 2006-07-21 2008-01-24 The Governors Of The University Of Alberta Tissue rejection
US20080233573A1 (en) 2006-08-28 2008-09-25 Kathleen Storm Gene expression profiling for identification, monitoring and treatment of transplant rejection
US20100304987A1 (en) 2007-01-04 2010-12-02 Alberto Sanchez Fueyo Methods and kits for diagnosis and/or prognosis of the tolerant state in liver transplantation
US20090155784A1 (en) 2007-01-22 2009-06-18 Wyeth Assessment of asthma and allergen-dependent gene expression
US20100234292A1 (en) 2007-04-16 2010-09-16 Ipsogen Methods of assessing a propensity of clinical outcome for a female mammal suffering from breast cancer
US20100305188A1 (en) 2007-10-03 2010-12-02 Kyowa Hakko Kirin Co., Ltd. Nucleic acid capable of regulating the proliferation of cell
US20110171645A1 (en) 2008-04-09 2011-07-14 The University Of British Columbia Methods of diagnosing acute cardiac allograft rejection
WO2009143624A1 (en) 2008-05-30 2009-12-03 The University Of British Columbia Methods of diagnosing rejection of a kidney allograft using genomic or proteomic expression profiling
US20110189680A1 (en) 2008-05-30 2011-08-04 The University Of British Columbia Methods of Diagnosing Rejection of a Kidney Allograft Using Genomic or Proteomic Expression Profiling
EP2295966A1 (en) 2008-06-02 2011-03-16 Eisai R&D Management Co., Ltd. IgA NEPHROPATHY DETECTION METHOD AND DETECTION KIT
US20110201519A1 (en) 2008-08-18 2011-08-18 Sarwal Minnie M Methods and Compositions for Determining a Graft Tolerant Phenotype in a Subject
WO2010038974A2 (en) 2008-10-01 2010-04-08 경북대학교 산학협력단 Composition and kit for diagnosing immunoglobulin a nephropathy and tgbm nephropathy
WO2010083121A1 (en) 2009-01-15 2010-07-22 The Board Of Trustees Of The Leland Stanford Junior University Biomarker panel for diagnosis and prediction of graft rejection
US20110064709A1 (en) 2009-09-16 2011-03-17 Northwestern University Use of ecdi-fixed cell tolerance as a method for preventing allograft rejection
US20130157888A1 (en) 2010-05-13 2013-06-20 University Of Medicine And Dentistry Of New Jersey Diagnostic autoantibody profiles for the detection and diagnosis of neurodegenerative diseases

Non-Patent Citations (99)

* Cited by examiner, † Cited by third party
Title
"Agilent-014850 whole human genome microarray 4x44K G4112F (Probe Name version)", XP002594592
"Affymetrix Human Genome U133 Plus 2.0 Array", Gene Expression Omnibus (Nov. 2003), XP002627319, 3 pgs.
"GeneChip 3′ IVT PLUS Reagent Kit", Affymetrix (2013), User Manual, 45 pgs.
Agilent-014850 whole human genome microarray 4×44K G4112F (Probe Name Version), GEO (2008), XP002594592.
AKALIN E,ET AL: "Gene expression analysis in human renal allograft biopsy samples using high-density oligoarray technology.", TRANSPLANTATION, WILLIAMS AND WILKINS, GB, vol. 72, no. 5, 15 September 2001 (2001-09-15), GB, pages 948 - 953, XP002371138, ISSN: 0041-1337, DOI: 10.1097/00007890-200109150-00034
Akalin, Enver; et al., "Gene expression analysis in human renal allograft biopsy samples using high-density oligoarray technology", Transplantation, Sep. 15, 2001, 72(5):948-53, XP002371138 ISSN: 0041-1337.
Akalin; et al., "Bocking Cell Microtubule Assembly Inhibits the Alloimmune Response In Vitro and Prolongs Renal Allograft Survival by Inhibition of Th1 and Sparing of Th2 Cell Function In Vivo", Journal of the American Society of Nephrology (1995), 5(7):1418-1425.
Alarcon; et al. "Time to renal disease and end-stage renal disease in Profile: a multiethnic lupus cohort", PLos Med (Oct. 2006), 3(10):e396.
Alizadeh A. et al. Nature, vol. 403, Feb. 3, 2000, p. 503-511.
Al-Lamki; et al., "Expression of Tumor Necrosis Factor Receptors in Normal Kidney and Rejecting Renal Transplants", Laboratory Investigation (Nov. 2001), 81(11):1503-1515.
Anglicheau et al. "Noninvasive Prediction of Organ Graft Rejection and Outcome Using Gene Expression Patterns", Transplantation, vol. 86, No. 2, Jul. 27, 2008, pp. 192-199.
Braud; et al., "Immunosuppresive Drug-Free Operational Immune Tolerance in Human Kidney Transplant Recipients: Part 1. Blood Gene Expression Statistical Analysis", Journal of Cellular Biochemistry (Apr. 2008),103(6):1681-1692.
Brouard; et al., "Identification of a peripheral blood transcriptional biomarker panel associated with operational renal allograft tolerance", PNAS (Sep. 2007), 104(39):15448-15453.
Butte; et al., "Protein microarrays discover angiotensinogen and PRKRIP1 as novel targets for autoantibodies in chronic renal disease", Mol Cell Proteomics (Mar. 2011), 10(3):M110.000497.
Carvalho-Gaspar; et al., "Chemokine gene expression during allograft rejection: Comparison of two quantitative PCR techniques", Journal of Immunological Methods (Jun. 2005), 301(1-2):41-52.
Chan, "Integrating Transcriptomics and Proteomics", Drug Discovery and Development (Apr. 2006), printed from www.ddmag.com, 6 pages.
Chen; et al., "Differentially Expressed RNA from Public Microarray Data Identifies Serum Protein Biomarkers for Cross-Organ Transplant Rejection and Other Conditions", PLOS Computational Biology (Sep. 2010), 6(9):e1000940.
Chen; et al., "Discordant protein and mRNA expression in lung adenocarcinomas", Molecular and Cellular Proteomics (Apr. 2002), 1(4):304-13.
Cheung; et al., "Natural Variation in Human Gene Expression Assessed in Lymphoblastoid Cells", Nature Genetics (Mar. 2003), 33:422-425.
Chu; et al., "Cloning of a new "finger" protein gene (ZNF173) within the class I region of the human MHC", Genomics (Sep. 1995), 29(1):229-39.
CHUA M-S, MANSFIELD E, SARWAL M: "APPLICATIONS OF MICROARRAYS TO RENAL TRANSPLANTATION:PROGRESS AND POSSIBILITIES", FRONTIERS IN BIOSCIENCE, FRONTIERS IN BIOSCIENCE, ALBERTSON, NY, US, vol. 8, 1 September 2003 (2003-09-01), US, pages S913 - S923, XP008071504, ISSN: 1093-9946
Chua, Mei-Sze; et al., "Applications of Microarrays to Renal Transplantation: Progress and Possibilities" Frontiers in Bioscience, Sep. 2003, 8:S913-23, XP008071504 ISSN: 1093-9946.
Communal; et al. "Reciprocal modulation of mitogen-activated protein kinases and mitogen-activated protein kinase phosphatase 1 and 2 in failing human myocardium", J Cardiac Failure (Apr. 2002), 8(2):86-92.
Cox; et al., "Altered modulation of WNT-beta-catenin and PI3K/Akt pathways in IgA nephropathy", Kidney Int (Aug. 2010), 78(4):396-407.
Database Embl [Online], "Thymidine Kinase, Cytosolic (human), mRNA Sequence", (1998), 2pages, XP002434108, Database accession No. AA778098.
DATABASE EMBL 1 January 1900 (1900-01-01), HILLIER L, ET AL: "ZF45G01.S1 SOARES FETAL HEART NBHH19W HOMO SAPIENS CDNA CLONE IMAGE:379920 3' SIMILAR TO GB:K02581 THYMIDINE KINASE, CYTOSOLIC (HUMAN);, MRNA SEQUENCE", XP002434108, Database accession no. AA778098
DATABASE Gene Expression Omnibus "Affymetrix Human Genome U133 Plus 2.0 Array", XP002627319
Dinarello; et al., "Anti-inflammatory Agents: Present and Future", Cell (Mar. 2010), 140(6):935-950.
Dugré; et al., "Cytokine and cytotoxic molecule gene expression determined in peripheral blood mononuclear cells in the diagnosis of acute renal rejection.", Transplantation (Oct. 2000), 70(7):1074-1080.
Enard; et al., "Intra- and interspecific variation in primate gene expression pattems", Science (Apr. 2002), 296 (5566):340-3.
Famulski; et al., "Changes in the Transcriptome in Allograft Rejection: IFN-.gamma.-Induced Transcripts in Mouse Kidney Allografts", American Journal of Transplantation (Jun. 2006), 6(6):1342-1354.
Farivar; et al., "The role of CC and CXC chemokines in cardiac allograft rejection in rats", Experimental and Molecular Pathology (Jun. 2005), 78(3):171-176.
First Examination Report for India patent application serial No. 9066/CHENP/2012, dated Feb. 26, 2018, translation letter reporting office action dated Mar. 19, 2018, 13 pages.
Flechner; et al., "Kidney transplant rejection and tissue injury by gene profiling of biopsies and peripheral blood lymphocytes", American Journal of Transplantation (Sep. 2004), 4(9):1475-89.
Fujiwaki; et al., "Thymidine Kinase in Epitheliar Ovarian Cancer: Relationship with the Other Pyrimidine Pathway Enzymes", Int. J. Cancer (May 2002), 99(3):328-335.
Gerrits; et al., "Donor-reactive cytokine production after HLA-identical living related kidney transplantation: a protein-array analysis", (Nov. 2006), 38(9):2825-7.
Gimino; et al., "Gene Expression Profiling of Broncholveolar Lavage Cells in Acute Lung Rejection", American Journal of Respiratory and Critical Care Medicine (Nov. 2003), 168:1237-1242.
Godfrey T.E. et al., Journal of Molecular Diagnostics, vol. 2, No. 2, May 2000.
Gronowitz; et al., "Serum Thymidine Kinase in Transplant Patients: Its Relation to Cytomegalovirus Activity, Renal Transplant Rejection and its Use for Monitoring of Antiviral Therapy", Annals of Clinical Research (1986), 18(2):71-75.
Gwinner; et al. "Renal transplant rejection markers." World J Urol (Oct. 2007), 25(5):445-455.
Hardiman, "Microarray platforms—comparisons and contrasts", Pharmacogenomics (Jan. 2004), 5(5): 487-502.
Hartono et al. "Noninvasive Diagnosis of Acute Rejection of Renal Allografts", Current Opinion in Organ Transplantation, vol. 15, No. 1, Feb. 2010, pp. 35-41.
Hauge; et al., "Characterization of the FAM110 gene family", Genomics (May 2007), 90:14-27.
Hauser; et al., "Prediction of Acute Renal Allograft Rejection by Urinary Monokine Induced by IFn-gamma (MIG)", The American Society of Nephrology (Jan. 2005), 16(6):1849-1858.
Hernandez-Fuentes; et al., "Immunologic monitoring", Immunological Reviews (Dec. 2003), 196:247-264.
Hidalgo; et al., "The Transcriptome of Human Cytotoxic T Cells: Measuring the Burden of CTL-Associated Transcripts in Human Kidney Transplants", American Journal of Transplantation (Mar. 2008), 8(3):637-646.
Hillier; et al., "Generation and annotation of the DNA sequences of human chromosomes 2 and 4", Nature (2005), 434:724-731.
Hopfner R. et al., Cancer Research 60, 121-128, Jan. 1, 2000.
Horwitz; et al., "Detection of Cardiac Allograft Rejection and Response to Immunosuppressive Therapy with Peripheral Blood Gene Expression", Circulation (Dec. 2004), 110:3815-3821.
Ismail; "Important fluorinated drugs in experimental and clinical use", Journal of Fluorine Chemistry (Dec. 2002), 118(1):27-33.
Jevnikar; et al., "Late Kidney Allograft Loss: What We Know About It, and What We Can Do About It", Clin J Am Soc Nephrol (Mar. 2008), 3(S56-S67).
Joosten; et al., "Antibody response against the glomerular basement membrane protein agrin in patients with transplant glomerulopathy", American Journal of Transplantation (Feb. 2005), 5(2):383-93.
Joosten; et al., "Chronic Renal Allograft Rejection: Pathophysiologic Considerations", Kidney International (Jul. 2005), 68:1-13.
Kalil; et al., "Meta-analysis: the efficacy of strategies to prevent organ disease by cytomegalovirus in solid organ transplant recipients", Ann Intern Med (Dec. 2005), 143(12):870-880.
Kaposztas; et al., "Impact of rituximab therapy for treatment of acute humoral rejection", Clin Transplant (Jan.-Feb. 2009), 23(1):63-73.
Kazutoshi Takahashi et al: "Induction of Pluripotent Stem Cells from Adult Human Fibroblasts by Defined Factors", Cell, Cell Press, US, vol. 131, No. 5, Nov. 30, 2007 (Nov. 30, 2007), pp. 861-872.
Lang; et al. "DUSP meet immunology: dual specificity MAPK phosphatases in control of the inflammatory response", J Immunol (Dec. 2006), 177(11)1497-504.
Lee et al., "Expression profiling of murine double-negative regularoty T cells suggest mechanisms for prolonged cardiac allograft survival", J. Immunol. (Apr. 2005), 174(8):4535-4544.
Li; et al., "A Peripheral Blood Diagnostic Test for Acute Rejection in Renal Transplantation", American Journal of Transplantation (Oct. 2012), 12(10):2710-2718.
Li; et al., "Identifying compartment-specific non-HLA targets after renal transplantation by integrating transcriptome and "antibodyome" measures", PNAS (Mar. 2009), 106(11):4148-4153.
Ling; et al. "Integrative urinary peptidomics in renal transplantation identifies biomarkers for acute rejection", J Am Soc Nephrol (Apr. 2010), 21(4):646-653.
List of cDNA clones on the Lymphochip (2000), truncated from the fullist available online at https://llmpp.nih.gov/lymphoma/data/clones.xls, one printed page.
MANSFIELD ELAINE S, SARWAL MINNIE M: "Arraying the orchestration of allograft pathology.", AMERICAN JOURNAL OF TRANSPLANTATION, BLACKWELL MUNKSGAARD,, DK, vol. 4, no. 6, 1 June 2004 (2004-06-01), DK, pages 853 - 862, XP002473233, ISSN: 1600-6135, DOI: 10.1111/j.1600-6143.2004.00458.x
Mansfield, Elaine S.; et al., "Arraying the Orchestration of Allograft Pathology", American Journal of Transplantation, Jun. 2004, 4(6):853-62, XP002473233 ISSN:1600-6135.
Marsden, "Predicting Outcomes after Renal Transplantation—New Tools and Old Tools", The New England Journal of Medicine (Jul. 2003), 349(2):182-184.
Martinez-Llordella; et al., "Using transcriptional profiling to develop a diagnostic test of operational tolerance in liver transplant recipients", The Journal of Clinical Investigations (Aug. 2008), 118(8):2845-2857.
Matsuki; et al., "Novel regulation of MHC class II function in B cells", The EMBO Journal (Jan. 2007), 26:846-854.
McMorrow; et al., "New intra-renal graft genes associated with tolerance or rejection", Kidney International, symp. 1 (Jan. 2002), 61: 885-S93.
Medbury; et al., "The Cytokine and Histological Response in Islet Xenograft Rejection is Dependent Upon Species Combination", Transplantation (Nov. 1997), 64(9):1307-1314.
Mengel; et al., "Scoring Total Inflammation Is Superior to the Current Banff Inflammation Score in Predicting Outcome and the Degree of Molecular Disturbance in Renal Allografts", American Journal of Transplantation (Aug. 2009), 9(8):1859-1867.
Metz; et al., "Application of proteomics in the discovery of candidate protein biomarkers in a diabetes autoantibody standardization program sample subset", J Proteome Res (Feb. 2008), 7(2):698-707.
Midha; et al., "Chemokine Expression in Nerve Allografts", Neurosurgery (Jun. 2004), 54(6):1472-149.
Mizutani; et al., "Frequency of MIC antibody in rejected renal transplant patients without HLA antibody", Human Immunology (Mar. 2006), 67(3):223-9.
Morgun; et al., "Molecular Profiling Improves Diagnoses of Rejected and Infection in Transplanted Organs", Circulation Research (Jun. 2006), 98(12):e74-83.
NCB I Gene output for UHRF1, from https://www.ncbi .nlm.nih.gov/gene/29128, printed on May 1, 2018, pp. 1-10.
Nesslinger; et al., "A viral vaccine encoding prostate-specific antigen induces antigen spreading to a common set of self-proteins in prostate cancer patients", Clinical Cancer Research (Aug. 2010), 16(15):4046-4056.
O'Riordan; et al., "Bioinformatic Analysis of the Urine Proteome of Acute Allograft Rejection", Journal of American Society of Nephrology (Dec. 2004), 15:3240-3248.
Patil et al. "Bronchoalveolar Lavage Cell Gene Expression in Acute Lung Rejection: Development of a Diagnostic Classifier", Transplantation, Jan. 27, 2008, vol. 85, No. 2, pp. 224-231.
Roedder; et al., "The pits and pearls in translating operational tolerance biomarkers into clinical practice", Current Opinion in Organ Transplantation (Dec. 2012), 17(6):655-662.
Rotondi; et al. "High pretransplant serum levels of CXCL9 are associated with increased risk of acute rejection and graft failure in kidney graft recipients", Transpl Int (May 2010), 23(5):465-475.
Saint-Mezard; et al., "Analysis of independent microarray datasets of renal biopsies identifies a robust transcript signature of acute allograft rejection", Transplant International (Mar. 2009), 22(3):293-302.
Sarwal; et al., "Integrative Genomics to Identify Non-HLA Allogenic Kidney-Specific Targets after Kidney Transplantation", Transplantation (2008), 86(2S):13, Oral Abstracts, downloaded Apr. 6, 2010.
Sarwal; et al., "Molecular Heterogeneity in Acute Renal Allograft Rejection Identified by DNA Microarray Profiling", New England Journal of Medicine (Jul. 2003), 349:125-138.
Sato; et al. "Aberrant CD3- and CD3-mediated signaling events in cord blood T Cells are associated with dysfunctional regulation of Fas ligand-mediated cytotoxicity", The Journal of Immunology (Apr. 1999), 162 (8):4464-4471.
SCHERER A, ET AL.: "EARLY PROGNOSIS OF THE DEVELOPMENT OF RENAL CHRONIC ALLOGRAFT REJECTION BY GENE EXPRESSION PROFILING OF HUMAN PROTOCOL BIOPSIES", TRANSPLANTATION, WILLIAMS AND WILKINS, GB, vol. 75, no. 08, 27 April 2003 (2003-04-27), GB, pages 1323 - 1330, XP009045201, ISSN: 0041-1337, DOI: 10.1097/01.TP.0000068481.98801.10
Scherer Andreas; et al., "Early Prognosis of the Development of Renal Chronic Allograft Rejection by Gene Expression Profiling of Human Protocol Biopsies", Transplantation, Apr. 27, 2003, 75(8):1323-30, XP009045201 ISSN: 0041-1337.
Serody; et al., "T-lymphocyte production of macrophage inflammatory protein-lalpha is critical to the recruitment of CD8(+) T cells to the liver, lung, and spleen during graft-versus-host disease", Blood (Nov. 2000), 96(9):2973-2980.
Shi; et al., "[Clinical significance of Rantes and MIP-1 alpha in acute rejection episode in kidney transplantation]", Zhongguo Yi Xue Ke Xue Yuan Xue Bao (Feb. 2004), abstract.
Shiro, "Organ Transplant and Molecular Pathology", Journal of the Japan Society for Transplantation, (2004), 39, [2], p. 138-144.
Sigdel; et al. "Shotgun proteomics identifies proteins specific for acute renal transplant rejection", Proteomics Clin Appl (Jan. 2010), 4(1):32-47.
Sigdel; et al., "Profiling of autoantibodies in IgA nephropathy, an integrative antibiomics approach", Clin J Am Soc Nephrol (Dec. 2011), 6(12):2775-2784.
Simon; et al., "Serial Peripheral Blood Perforin and Granzyme B Gene Expression Measurements for Prediction of Acute Rejection in Kidney Graft Recipients", American Journal of Transplantation (Sep. 2003), 3:1121-1127.
Teramoto; et al., "DNA Synthesis in Hepatocytes During Liver Allograft Rejection in Rats", Transplantation (Aug. 1990), 50(2):199-201.
Thomson; et al., "Monitoring the Patient Off Immunosuppression", Transplantation (Oct. 2001), 72(8):S13-S22.
Voshol; et al. "Evaluation of biomarker discovery approaches to detect protein biomarkers of acute renal allograft rejection", J Proteome Res (Jul.-Aug. 2005), 4(4):1192-1199.
Wakui; et al., "Genes Highly Expressed in the Early Phase of Murine Graft-Versus-Host Reaction", Biochemical and Biophysical Communications (Mar. 2001), 282:200-206.
Whitfield; et al., "Systemic and Cell Type-Specific Gene Expression Patterns in Scleroderma Skin", Proc. Natl. Acad Sci. (Oct. 2003), 100(21):12319-12324.
Wu, "Analysing Gene Expression Data From DNA Microarrays to Identify Candidate Genes", Journal of Pathology (Sep. 2001), 195:53-65.
Zhang; et al., "Microarray Analysis of Gene Expression in Peripheral Blood Mononuclear Cells Derived From Long-Surviving Renal Recipients", Transplantation Proceedings (Aug. 2002), 34:1757-1759.

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10538813B2 (en) 2009-01-15 2020-01-21 The Board Of Trustees Of The Leland Stanford Junior University Biomarker panel for diagnosis and prediction of graft rejection
US11768208B2 (en) 2010-03-25 2023-09-26 The Board Of Trustees Of The Leland Stanford Junior University Protein and gene biomarkers for rejection of organ transplants

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