WO2006124022A1 - Microarray gene expression profiling in subtypes of clear cell renal cell carcinoma - Google Patents

Abstract

A nucleic acid probe or a novel set of such probes in a microarray is provided. The probe or probe set is useful in the prognosis of patients with clear cell renal cell carcinoma (CC-RCC), wherein aggressive and non-aggressive CC-RCC tumor types are characterized by differential expression profiles of genes that hybridize with one or more of these probes. Microarrays and kits for carrying out expression profiling of tumor and normal tissue and methods of using them are disclosed.

Description

MICROARRAY GENE EXPRESSION PROFILING IN SUBTYPES OF CLEAR CELL RENAL CELL CARCINOMA

FIELD OF THE INVENTION

[0001] This invention relates to the field of molecular biology and medicine, including gene expression profiling for cancer, specifically, clear cell renal cell carcinoma. BACKGROUND OF THE INVENTION

[0002] Renal cell carcinoma (RCC) is the tenth most common cancer in the United

States. A. Jemal et al, CA Cancer J CHn 54, 8 (2004). The most common subtype is clear cell renal cell carcinoma (CC-RCC), constituting more than 80% of kidney cancers. J. C. Cheville, C. M. Lohse, H. Zincke, A. L. Weaver, M. L. Blute, Am J Surg Pathol 27, 612 (2003).

[0003] CC-RCC is caused by neoplasia of proximal renal tubular epithelium; and is a prime example of a clinically heterogeneous disease for which treatment options are largely ineffective for advanced stage tumors. The cancer is more common in men than women, especially men over 55 years of age. It affects approximately 3/10,000 people; 18,000 new cases arise in the U.S. annually, of which about 8,000 result in death; worldwide fatalities were estimated to exceed 100,000 in 2001. CC-RCC represents 2% of all malignancies and 2% of all cancer-related deaths. Approximately 30% of patients present with metastatic disease and life expectancies averaging only nine months.

[0004] The CC-RCC tumor can be one centimeter in diameter when discovered (usually incidentally), or as bulky as several kilograms. Most often it manifests with pain, as a palpable mass or with hematuria; a variety of paraneoplastic syndromes have been described. CC-RCC may first manifest with metastases after being clinically silent for years. The characteristic gross appearance of the tumor is solid, lobulated, and yellow, with variegation due to necrosis and hemorrhage. Tumor may be well circumscribed, or may invade the perirenal adipose tissue or the renal vein. Cystic degeneration is common, though some tumors are predominantly cystic. Hartman et al, Urology 28:145- 153 (1986). Of the 70% of patients with initially non-metastatic disease, approximately 30% relapse after surgery and usually succumb. Levy et al., J. Urolog. 159:1163-1167 (1999); Ljungberg, B et al, BJU Intl. 84:405-411 (1999).

[0005] Conventional treatment of primary CC-RCC is surgical excision. However, metastasis limits long term survival. In patients with symptomatically advanced CC- RCC, palliative nephrectomy and other tumor excisions may be the only therapeutic option. Ljungberg et al, supra. Radiotherapy appears to have only limited palliative effects, as CC-RCCs appear to be relatively radio-resistant. Chemotherapy, usually with vinblastine, hydroxyurea and/or BCNU₅ also shows limited efficacy and response rates to prolonged infusion of 5-fluorouracil range from <10% to 20% decrease in tumor size. Dutcher et al, Proc Annu Meet Am Soc Clin Oncol 15:A725 (1996). Hormonal therapy has also yielded disappointing results. Bukowski, Cancer 80:1198-1220 (1997). Immunotherapy with cytokines such as interferons and interleukin-2 (Proleukin® from Chiron), and combinations of these agents is considered an encouraging area of therapeutic development.

[0006] Relapse occurs frequently following nephrectomy for clinically localized RCC, and the overall prognosis for metastatic RCC is poor, immunotherapy yielding only modest benefits. There is substantial heterogeneity in survival within staging groups, and individual outcome remains difficult to predict.

[0007] The Union Internationale Contre Ie Cancer (UICC) recently developed an improved system for classifying CC-RCC known as the "TNM" classification (referring to tumor, lymph node, and metastasis). T, N, and M categories are determined by physical examination and imaging. Sobin, L.H. et al, eds., TNM classification of malignant tumors. 5^th ed. (John Wiley & Sons, New York 1997). This system is set forth in Table 1 below. Approximately one-third of initially diagnosed CC-RCC patients present with metastatic disease, and 40% of individuals undergoing surgical resection or radical nephrectomy will eventually develop metastasis. Among individuals with metastatic disease, approximately 75% exhibit lung metastasis, 36% have lymph node and/or soft tissue involvement, 20% have bone involvement, and 18% have liver involvement. The literature also reports low incidences of metastasis in contralateral adrenal glands, brain, uvula, diaphragm, and digits. Levy et al, supra. Spontaneous regressions of metastases after nephrectomy occurs primarily in men with pulmonary metastasis and are not equated with long-term cure. The frequency of spontaneous regression is only 0.4% and may reflect the development and/or enhancement of immune responses.

[0008] Table 1

TNM Clinical Classification T— Primary Tumor

TX Primary tumor cannot be assessed

TO No evidence of primary tumor Tl Tumor is <7.0 cm in greatest dimension, limited to the kidney T2 Tumor is >7.0 cm in greatest dimension, limited to the kidney T3 Tumor extends into major veins or invades adrenal or perinephric tissues but not beyond Gerota fascia

T3a Tumor invades adrenal gland or perinephric tissues but not beyond Gerota fascia

T3b Tumor grossly extends into renal vein(s) or vena cava below diaphragm T3c Tumor grossly extends into vena cava above diaphragm

T4 Tumor invades beyond Gerota fascia

N — Regional Lymph Nodes (hilar, abdominal vara-aortic. and paracaval)

NX Regional lymph nodes cannot be assessed

NO No regional lymph node metastasis

Nl Metastasis in a single regional lymph node

N2 Metastasis in more than one regional lymph node

M — Distant Metastasis

MX Distant metastasis cannot be assessed MO No distant metastasis Ml Distant metastasis present

pTNM Pathological Classification: corresponds to the T, N, and M categories.

G — Histopathological Grading

GX Grade of differentiation cannot be assessed

Gl Well differentiated

G2 Moderately differentiated

G3, 4 Poorly differentiated/undifferentiated Stage Grouping

M N M

Stage I Tl NO MO

Stage II T2 NO MO

Stage m Tl Nl MO

T2 Nl MO

T3 NO, Nl MO

Stage N T4 NO₅ Nl MO

Any T N2 MO

Any T Any N Ml

[0009] Some of the inventors have previously identified that CC-RCC may exist as two distinct subtypes: aggressive and non-aggressive. M. Takahashi et al, Proc. Natl. Acad. ScL U S A 98, 9754 (2001). In the aggressive form, the primary tumor grows more rapidly, tends to metastasize sooner, the metastases grow more rapidly, and the patients die sooner. Patients manifesting the aggressive subtype typically manifest Stages III or rV. Non-aggressive RC patients typically manifest at Stages I or II. However, predicting individual survival in CC-RCC is challenging based on clinico-pathologic parameters. Thus, an understanding of the genetic mechanisms underlying the variability in CC-RCC behavior is a key priority for oncology. R. J. Motzer, J Clin Oncol 21, 1193 (2003).

[00010] Because of the high incidence of initially diagnosed CC-RCC patients with metastatic disease and the high percentage of individuals developing metastasis after undergoing surgical resection or radical nephrectomy, identifying the aggressive subtype of CC-RCC will be useful to inform physicians which patients require aggressive treatment, as well as those patients for which aggressive treatment may not be appropriate.

[00011] Most attention has centered upon the roles of hypoxia and angiogenesis in tumor progression, because von Hippel-Lindau (VHL) gene mutations occur in about 40-50% of CC-RCC tumors - the VHL protein is a key regulator of the hypoxia-inducible factor (HIF) signaling pathway, which in turn regulates angiogenesis and cell survival. W. G. Kaelin, Jr., Clin Cancer Res 10, 6290S (2004). It is a prevailing belief that hypoxia and tumor aggressiveness are directly correlated in RCC (P. Staller et al, Nature 425, 307

(2003)), and considerable research efforts have been devoted to developing CC-RCC as a model for basic and clinical studies aimed at investigating hypoxia-response and angiogenesis pathways. W. G. Kaelin, Jr., Clin Cancer Res 10, 6290S (2004). Although increased angiogenesis and hypoxia (J. M. Brown, W. R. Wilson, Nat Rev Cancer 4, 437 (2004)) are generally correlated to poorer prognosis in cancer, the prognostic significance of VHL mutations in patient samples has been more controversial. M. Yao et al., J Natl Cancer Inst 94, 1569 (2002); P. Schraml et al, J. Pathol. 196, 186 (2002). Accordingly, a better understanding of the relationship between tumor aggressiveness and angiogenesis is needed.

[00012] Genetic markers of particular interest

[00013] Members of the Aurora kinase family (Aurora kinase A, B and C) are key mitotic regulators required for genomic stability. They are involved in multiple steps of mitosis, including centrosome duplication, formation of a bipolar mitotic spindle, chromosome alignment on the mitotic spindle, and the fidelity monitoring spindle checkpoint. While this gene has been previously studied in simpler organisms, and in other types of cancers such as breast, colon and lung cancer, overexpression of these genes has not been previously studied in kidney cancer. Therefore, the inventors were interested in the role and expression of these genes and their mediated pathways both in terms of tumor formation (cancer versus non-cancer) and tumor progression and prognosis (good- prognosis tumors versus poor-prognosis tumors). The biology and mechanisms of this group of three genes are described in a recent authoritative review. Carmena M, Earnshaw WC. Nature Rev. MoI. Cell. Biol. 4, 842-54 (2003).

SUMMARY OF THE INVENTION

[00014] Using a clinically well-characterized patient population, the inventors correlated the global gene expression profiling of CC-RCC with tumor progression and clinical outcome, even in the absence of known cellular or molecular characteristics of these tumors. The inventors identified common features of renal cell tumorigenesis, including, genes that were upregulated when comparing aggressive CC-RCC tumors (poor prognosis) to non-aggressive CC-RCC tumors (good prognosis), thus enabling the inventors to identify specific molecular signatures of aggressive and non-aggressive subtypes of CC-RCC tumors. The discovery of a set of differentially expressed genes for each subtype provides a basis for explaining the differences in aggressiveness and clinical outcome. [00015] Additionally, the methods and compositions described herein permit identification of proteins whose detection provide an early diagnostic approach to CC-RCC proteins as well as drug targets for the products of these genes. Thus, by discovering that a particular gene is differentially regulated in aggressive CC-RCC, one can focus on developing drugs that suppress up-regulation, act directly on the protein product, or bypass the step in a cellular pathway mediated by the product of this gene.

[00016] The present inventors have discovered expressed nucleic acid markers through statistical clustering analysis, namely, fully supervised principal components and unsupervised two-means clustering to derive optimal oligonucleotide predictors that yielded both continuous and discrete survival predictions. In multivariable analysis, the predictors were independently significant of all combinations of up to two clinical pathological parameters studied. Further, the inventors validated their studies across different microarray platforms and experimental designs.

[00017] The present invention provides a nucleic acid probe or set of probes (preferably between two and 266 in number) and a microarray comprising these DNA markers as probes for the gene expression levels that are characteristic of CC-RCC tumor tissue. In one embodiment, the presence and levels of mRNA in a tissue being analyzed are screened using methods known in the art (i.e., Southern/Northern/Western blotting, gel electrophoresis, RFLP, SSCP). The invention is further directed to a method of implementing a microarray technology for disease prognosis (aggressive versus non- aggressive CC-RCC) thereby supplementing currently available prognostic techniques and pathological classification.

[00018] Use of the accurate, objective molecular methods described herein will inform physicians about which patients require heightened observation and additional, e.g., adjuvant therapies — for example, patients presenting with low stage CC-RCCs that appear on their face to be non-aggressive by conventional criteria, but that have the aggressive type molecular signatures as described herein. Moreover, in the case of patients presenting with higher stage CC-RCCs that might mistakenly be diagnosed as aggressive, but which have the non-aggressive molecular signature disclosed herein, this invention facilitates withholding of unnecessarily aggressive treatment while maintaining appropriate vigilance.

[00019] The present invention also is directed to a prognostic microarray composition of at least one oligonucleotide or polynucleotide probe from a set of probes immobilized to a solid surface in a predetermined order such that a row of pixels corresponds to replicates of one distinct probe from the set. The probes are complementary to nucleic acid sequences expressed differentially in aggressive as compared to non-aggressive types of CC-RCC. The probes are preferably any of SEQ ID NOS.: 1-266 inclusive. The nucleic acid sequences hybridize to the probes under high stringency conditions.

[00020] The microarray may comprise at least about ten probes, or in another embodiment, at least seventy-five probes; in another embodiment at least 114 probes; in another embodiment at least fifty probes; and in another embodiment at least twenty-seven probes, which probes are complementary to nucleic acid sequences expressed differentially in aggressive as compared to non-aggressive types of CC-RCC. These probes are preferably at least about fifteen nucleotides in length.

[00021] The present invention also includes a kit comprising the inventive composition; means for carrying out hybridization of the nucleic acid to the probe(s); and means for reading hybridization data. In one embodiment of the invention, the kit includes the inventive microarray, reagents that facilitate hybridization of the nucleic acid to the immobilized probes, and a computer- readable storage medium comprising logic which enables a processor to read data representing detection of hybridization. These kits are useful for determining the prognosis of a patient having CC-RCC.

[00022] The present invention also includes a method for assessing the aggressiveness of

CC-RCC in a renal rumor tissue sample. In this method, the relative expression of genes in a subject's CC-RCC tumor tissue is compared to the same genes in a population of renal tumor tissue samples. The genes are selected from the group consisting of SEQ ID NOS.1-266. In one embodiment, there is at least a twofold difference in the relative expression of the genes comparing the subject's renal tumor tissue sample with the same genes in the population of renal tumor tissue samples.

[00023] Another method discovered by the inventors includes evaluating the aggressiveness of CC-RCC in a patient by detecting the level of expression in a renal tumor tissue sample of two or more genes from Table 7, wherein differential expression of the genes in Table 7 indicates whether the CC-RCC is aggressive or non-aggressive. In another embodiment of this method invention, the genes in Table 8 are evaluated for aggressiveness of CC-RCC in a patient, hi a further embodiment, the genes in Table 9 are evaluated for aggressiveness of CC-RCC in a patient.

[00024] The invention also includes a diagnostic portfolio of nucleic acid sequences selected from the group consisting of SEQ ID NOS.: 1-266. More preferably, the diagnostic profile is in a matrix suitable for identifying the differential expression of the genes contained therein. [00025] The present invention provides a nucleic acid probe or a set of probes (preferably between 2 and 314 in number) and a microarray comprising these DNA markers as probes for the gene expression levels that are characteristic of CC-RCC tumor tissue compared to normal tissue from the same kidney. In one embodiment, the presence and levels of mRNA in a tissue being analyzed are screened using methods known in the art (i.e., Southern/Northern/Western blotting, gel electrophoresis, RFLP, SSCP).

[00026] The microarray of the present invention can be used to assay expressed nucleic acid samples (representing genes differentially expressed in normal kidney versus CC- RCC tumor tissue) for one or more individual subject's tumor or normal tissue, wherein each sample from an individual subject's tumor or normal tissue is spotted column- wise on the pixels of the microarray probes. The microarray can comprise at least 10, or, in another embodiment, at least about 314 probes.

[00027] The differentially expressed nucleic acid sequences detected by the probes may be ones that are up-regulated or down-regulated in one form of CC-RCC compared to normal tissue or compared to the other form of CC-RCC (aggressive versus non- aggressive).

[00028] The above probes are typically of mammalian, preferably human, origin.

[00029] hi the above methods, the nucleic acids from the tumor and the tissue are detectably labeled, preferably with a fluorescent label prior to the hybridization. With fluorescent labels, hybridization is detected as a fluorescent signal bound to the probe. [00030] In one embodiment of the above method, the probes are immobilized to a solid surface of a microarray as pixels arranged in rows, and the expressed nucleic acids from the tumor tissue or normal tissue samples are spotted column-wise onto the probe pixels. [00031] Also provided is a method for the early diagnosis of a CC-RCC tumor in a subject prior to physical or radiological evidence of the tumor. In this method, a protein product of at least one gene is selected based on its expression being up-regulated in a majority of CC-RCC patients. This protein product is preferably a secreted protein or a cell surface protein expressed in tissue readily accessible for assay. The presence or quantity of the protein product in a body fluid or a tissue or cell sample from the subject is determined. An increased level of the protein product compared to the level in a normal subject's fluid, tissue, or cells (or another reference normal value) is indicative of the presence of a CC-RCC tumor in the subject. [00032] This invention also provides a method for diagnosing the recurrence of a CC-RCC tumor in a subject in whom a CC-RCC primary tumor has been excised or otherwise treated. In this method, a protein product of at least one gene is selected based on its expression being up-regulated in a majority of CC-RCC patients. This protein product is preferably a secreted protein or a cell surface protein expressed in tissue readily accessible for assay. The presence or quantity of the protein product in a body fluid or a tissue or cell sample from the subject is determined. An increase in the level of the protein product compared to the level in a normal subject's fluid, tissue, or cells (or another reference normal value) is indicative of the presence of a recurrent CC-RCC tumor in the subject.

[00033] In both methods of early diagnosis and diagnosis of recurrence, the gene is preferably one that hybridizes with any one or more of SEQ ID NOS: 240-553. BRIEF DESCRIPTION OF THE DRAWINGS

[00034] Figures 1A-1C show good prognosis (non-aggressive) and poor prognosis

(aggressive) survival curves for fifty-nine primary tumors for two CC-RCC subgroups derived by employing a fully supervised principal components (PC) predictor, a reduced supervised PC predictor, and a two-means predictor (Figs. IA, IB, and 1C, respectively).

[00035] Figures 2A-2C show good prognosis (non-aggressive) and poor prognosis

(aggressive) survival curves for thirteen metastatic tumors for two CC-RCC subgroups derived by employing a fully supervised PC predictor, a reduced supervised PC predictor, and a two-means predictor (Figs. 2A, 2B, and 2C, respectively).

[00036] Figure 3 shows images of forty-five formalin-fixed paraffin-embedded CC-RCC samples by CD 31 immunostaining in good prognosis (non-aggressive) and poor prognosis (aggressive) tumors (Figs. 3A and 3B, respectively).

[00037] Figure 4A shows a comparative genomic microarray analysis from gene expression ratios derived from a ninety-two tumor oligonucleotide data set and twelve oligonucleotide expression profiles of non-cancerous kidney cortical samples.

[00038] Figure 4B shows a comparative genomic microarray analysis inferred fom cytogenetic profiles of thirteen metastatic tumors.

[00039] Figure 5A is a heat map showing two distinct clusters (good prognosis and poor prognosis) formed by a hierarchical clustering of thirty-four informative cDNA clones corresponding to a reduced supervised PC predictor. Figure 5B shows corresponding survival curves for the two distinct clusters.

[00040] Figure 6 is a heat map showing four distinct subclusters of good-prognosis tumors with a significantly high prevalence of VHL gene mutations formed by hierarchical clustering of thirty-seven transcripts corresponding to a two-means predictor. [00041] Figure 7 is a heat map showing co-regulation of Aurora kinase pathway genes.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[00042] The preferred embodiments of the present invention may be understood more readily by reference to the following detailed description of specific embodiments and the Examples, Tables, and Sequence Listing included hereinafter.

[00043] The Sequence Listing contained on "MICROARRAY GENE EXPRESSION

PROFILING IN SUBTYPES OF CLEAR CELL RENAL CARCINOMA." with file title "Clear cell Sequence Listing.ST25.txt" is incorporated-by-reference. This compact disc was created on May 12, 2005, and is 1,782,781 bytes.

[00044] Definitions

[00045] As used in the present application, "a" can mean one or more, depending on the context with which it is used; the acronym "PCR" is used interchangeably with "polymerase chain reaction"; and the term "oligonucleotide" refers to primers, probes, and oligomer fragments.

[00046] As used in the present application, "nucleic acid" and "polynucleotide" are interchangeable and refer to both DNA and RNA (as well as peptide nucleic acids). The term "oligonucleotide" is not intended to be limited to a particular number of nucleotides and therefore overlaps with polynucleotide. Probes for gene expression analysis include those comprising ribonucleotides, deoxyribonucleotides, both or their analogues as described below. They may be poly- or oligonucleotides, without limitation of length.

[00047] The present invention uses both oligonucleotide microarrays and cDNA microarrays to probe for, and to determine the relative expression of target genes of interest in a tissue sample of CC-RCC.

[00048] As used in the present application, the term "specifically hybridize to" refers to the binding, duplexing, or hybridizing of a molecule only to a particular nucleotide sequence under stringent conditions when that sequence is present in a complex mixture (e.g., total cellular) DNA or RNA. The term "stringent conditions" refers to conditions under which a probe will hybridize to its target subsequence, but to no other sequence. Stringent conditions are sequence-dependant and will be different in different circumstances. One skilled in the art knows how to select such conditions. Longer sequences hybridize specifically at higher temperatures. Generally, stringent conditions are selected to be about 5 degrees Celsius lower than the thermal melting point (Tm) for the specific sequence at a defined ionic strength and pH. The Tm is the temperature

(under defined ionic strength, pH, and nucleic acid concentration) at which 50% of the probes complementary to the target sequence hybridize to the target sequence at equilibrium. (As the target sequences are generally present in excess, at Tm, 50% of the probes are occupied at equilibrium). Typically, stringent conditions will be those in which the salt concentration is at least about 0.01 ato 1.0 M Na ion concentration (or other salts) at pH 7.0 to 8.3 and the temperature is at least about 3.0 degrees Celsius for short probes (e.g., 10 to 50 nucleotides). Stringent conditions may also be achieved with the addition of destabilizing agents such as formamide.

[00049] Microarrays are orderly arrangements of spatially resolved samples or probes (in the present invention oligonucleotides and cDNAs of known sequence) that allow for massively parallel gene expression and gene discovery studies (Lockhart DJ et at, Nature (2000) 405 (6788):827-836).

[00050] The underlying concept of the microarray depends on base-pairing (hybridization) between purine and pyrimidine bases following the rules of Watson-Crick base pairing. DNA microarrays (DNA "chips") are fabricated by high-speed robotics. Microarray technology adds automation to the process of resolving nucleic acids of particular identity and sequence present in an analyte sample by labeling, preferably with fluorescent labels, and subsequent hybridization to their complements immobilized to a solid support in microarray format. An experiment with a single DNA chip can provide simultaneous information on thousands of genes- a dramatic increase in throughput (Reichert et ah (2000) Anal. Chem. 72:6025-6029) when compared to traditional methods.

[00051] Array experiments employ common solid supports such as glass slides, microplates or standard blotting membranes, and can be created by photolithographic synthesis by robotic deposition of samples. Photolithography generally involves attaching synthetic linkers (modified with photochemically removable protecting groups) to a glass substrate and directing light through a photolithographic mask to deprotect specific areas on the surface. The first of a series of hydroxyl-protected deoxynucleotides is incubated with the surface, and chemical binding occurs at the sites previously illuminated. Using a new mask, light then is directed to different regions of the substrate, and the chemical cycle repeated. Probes may be synthesized either in situ (on-chip) or by conventional synthesis followed by on-chip immobilization. Sample spot sizes in microarrays are typically <200 μm in diameter, and these arrays usually contain thousands of spots.

[00052] Microarrays require specialized robotics and imaging equipment that generally are commercially available and well-known in the art. Microarray analysis generally involves injecting a fluorescently tagged nucleic acid sample into a chamber to hybridize with complementary oligonucleotides on the microarray slide; laser excitation at the interface of the array surface and the tagged sample; collection of fluorescence emission by a lens; optical filtration of the fluorescence emissions; fluorescence detection; and quantification of hybridization intensity. Lipshutz, Robert J., Fodor, Stephen P.A., Gingeras, Thomas R., Lockhart, David J. High density synthetic oligonucleotide arrays. Nature Genetics Supplement. 21:20-23 (1999).

[00053] Oligonucleotide arrays are based on sequence information and are targeted to monitor the expression levels of many genes. Using as little as 200 to 300 bases of a gene, cDNA, or EST sequence, independent 25-mer oligonucleotides are selected (non- overlapping or minimally overlapping) as detectors. Probe selection is based upon several factors: complementarity of the probe to a selected gene, cDNA, or EST sequence; uniqueness relative to family members and other genes; and an absence of near-complementarity to other common RNAs that may be in the sample. The overall selection of probes is based on "probe redundancy," i.e., using multiple oligonucleotides having different sequences but designed to hybridize to different regions of the same RNA. In the overall probe mix, additional redundancy involves the use of "mismatch control probes" that are identical to their "perfect match" partners except for a single base difference in a central position. Even with low concentrations of RNA, hybridization to the perfect match/mismatch pairs yields identifiable fluorescence patterns. The strength of these patterns indicates the concentration of the RNA in the sample. Lipshutz, Robert J., Fodor, Stephen P.A., Gingeras, Thomas R., Lockhart, David J. High density synthetic oligonucleotide arrays. Nature Genetics Supplement. 21:20-23 (1999).

[00054] Format I: a cDNA probe (500-5,000 bases) is immobilized to a solid surface such as glass using robotic spotting and exposed to a set of targets either separately or in a mixture. This method, traditionally called "DNA microarray," is considered to have been developed at Stanford University (Ekins, R et at, Trends in Biotech (1999) 17:217-218).

[00055] Format II: an array of probes that are "natural" oligo- or polynucleotides

(oligomers of 20~80 bases), oligonucleotide analogues e.g., with phosphorothioate, methylphosphonate, phosphoramidate, or 3'-aminopropyl backbones), or peptide-nucleic acids (PNA).

[00056] The array is (1) exposed to an analyte comprising a detectable labeled, preferably fluorescent, sample nucleic acid (typically DNA), (2) allowed to hybridize, and (3) the identity and/or abundance of complementary sequences is determined.

[00057] For analysis of the target nucleic acid of primary tumor tissue, the preferred analyte of this invention is isolated from tissue biopsies before they are stored or from fresh-frozen tumor tissue of the primary tumor which may be stored and/or cultured in standard culture media. For expression studies, total RNA or poly(A)-containing mRNA is isolated using commercially available reagents and kits, e.g., from Invitrogen, Oligotex, or Qiagen. The mRNA is reverse transcribed into cDNA in the presence of labeled nucleotides. cDNA is generally synthesized using reverse transcriptase (e.g., Superscript II reverse-transcription kit from GEBCO-BRL). This may be directly or indirectly labeled by conjugation with a fluorescent dye.

[00058] The materials for a particular application of microarray technology are not necessarily available in convenient in kit form. The present invention provides microarrays and kits useful for analysis and prognosis of CC-RCC samples. Namely, the present invention includes microarrays comprising one or more nucleic acid probes having hybridizable fragments of any length (from about 15 bases to full coding sequence) for the genes whose expression is to be analyzed. For purposes of the analysis, the full length sequence must not necessarily be known, as those of skill in the art will know how to obtain the full length sequences using the sequence of a given EST and known data mining, bioinformatics, and DNA sequencing methodologies without undue experimentation. Those skilled in the art will appreciate that the probe of choice for a particular gene can be the full length coding sequence or any fragment thereof having at least about 15 nucleotides. Thus, when the full length sequence is known, the practitioner can select any appropriate fragment of that sequence. When the original results are obtained using partial sequence information (e.g., an EST probe), and when the full length sequence of which that EST is a fragment becomes available (e.g., in a genome database), the skilled artisan can select a longer fragment than the initial EST, as long as the length is at least about 15 nucleotides.

[00059] The polynucleotide or oligonucleotide probes of the present invention may be native DNA or RNA molecules or analogues of DNA or RNA or portions thereof. The present invention is not limited to the use of any particular DNA or RNA analogue or portion thereof; rather any one is useful provided that it is capable of adequate hybridization to the complementary DNA (or mRNA) in a test sample, has adequate resistance to nucleases and stability in the hybridization protocols employed. DNA or RNA may be made more resistant to nuclease degradation in vivo by modifying internucleosite linkages (e.g., methylphosphonates or phosphorothioates) or by incorporating modified nucleosides (e.g., 2'-0-methylribose or l'-α-anomers) as described below.

[00060] A poly- or oligonucleotide may comprise at least one modified base moiety, for example, 5-fluorouracil, 5-bromouracil, 5-chlorouracil, 5-iodouracil, hypoxanthine, xanthine, 4-acetylcytosine, 5-(carboxyhydroxylmethyl)uracil, 5- carboxymethylaminomethyl-ω-thiouridine, 5-carboxymethyl-aminomethyl uracil, dihydrouracil, β-D-galactosylqueosine, inosine, N6-isopentenyladenine, 1-methylguanine, 3-methyl-cytosine, 5-methylcytosine, N6-adenine, 7-methylguanine, 5- methylaminomethyluracil, 5 -methoxyamino-methyl-2-thiouracil, β-D-mannosylqueosine, 5-methoxy-carboxymethyluracil, 5-methoxyuracil-2-methyltliio-N6-iso-pentenyladenine, uracil-5-oxyacetic acid, butoxosine, pseudouracil, queuosine, 2-thio-cytosine, 5-methyl-2- thiouracil, 2-thiouracil, 4-thiouracil, 5-methyluracil, uracil-5-oxyacetic acid methylester, uracil-t-oxyacetic acid, 5-methyl-2-thiouracil, 3(3-amino-3-N-2-carboxypropyl) uracil and 2,6-diaminopurine.

[00061] The poly- or oligonucleotide may comprise at least one modified sugar moiety including, but not limited, to arabinose, 2-flourarabinose, xylulose, and hexose.

[00062] In yet another embodiement, the poly- or oligonucleotide probe comprises a modified phosphate backbone synthesized from a nucleotide having, for example, one of the following structures: a phosphorothioate, a phosphoridothioate, a phosphoramidothioate, a phosphoramidate, a phosphordiimidate, a methylsphosphonate, an alkyl phosphotriester, 3'-aminopropyl and a formacetal or analog thereof. [00063] In yet another embodiment, the poly- or oligonucleotide probe is an α-anomeric oligonucleotide which forms specific double-stranded hybrids with complementary RNA in which, contrary to the usual β-units, the strands run parallel to each other (Gautier et al,, 1987, Nucl. Acids Res. 15:6625-6641).

[00064] An oligonucleotide may be conjugated to another molecule, e.g., a peptide, a hybridization triggered cross-linking agent, a hybridization-triggered cleavage agent, etc., all of which are well-known in the art.

[00065] Oligonucleotides of this invention may be synthesized by standard methods known in the art, e.g., by use of an automated DNA synthesizer (such as are commercially available from Biosearch, Applied Biosystems, etc.). As examples, phosphorothioate oligonucleotides may be synthesized by the method of Stein et al, (Nucl. Acids Res. (1998) 16:3209, methylphosphonate oligonucleotides can be prepared by use of controlled pore glass polymet supports (Sarin et al, Proc. Natl. Acad. ScL USA (1988) 85:7448-7451), etc.

[00066] Detectable Labels for Oligo- or Polynucleotide Probes

[00067] Preferred detectable labels include radionuclides, fluorescers, fluourogens, a chromophore, a chromogen, a phosphoescer, a chemiluminescer or a bioluminescer. Examples of fluorescers or fluorogens are i fluorescein, rhodamine, dansyl, phycoerythrin, phycocyanin, allophycocyanin, o-phthaldehyde, fluorescamine, a fluorescein derivative, Oregon Green, Rhodamine Green, Rhodol Green or Texas Red. [00068] Common fluorescent labels include fluorescein, rhodamine, dansyl, phycoerythrin, phycocyanin, allophycocyanin, o-phthaldehyde and fluorescamine. Most preferred are the labels described in the Examples, below.

[00069] The fluorophore must be excited by light of a particular wavelength to flouresce.

See, for example, Haugland, Handbook of Fluorescent Probes and Research Chemicals, Sixth Ed., Molecular Probes, Eugene, OR., 1996).

[00070] Fluorescein, fluorescein derivatives and fluorescein-like molecules such as

Oregon Green™ and its derivatives, Rhodamine Green™ and Rhodol Green™, are coupled to amine groups using the isothiocyanate, succinimidyl ester or dichlorotriazinyl- reactive groups. Similarly, fluorophores may also be coupled to thiols using maleimide, iodoacetamide, and aziridine-reactive groups. The long wavelength rhodamines, which are basically Rhodamine Green™ derivatives with substituents on the nitrogens, are among the most photostable fluorescent labeling reagents known. Their spectra are not affected by changes in pH between 4 and 10, an important advantage over the fluouresceins for many biological applications. This group includes the tetramethylrhodamines, X-rhodamines and Texas Red™ derivatives. Other preferred fluorophores are those which are excited by ultraviolet light. Examples include cascade blue, coumarm derivatives, naphthalenes (of which dansyl chloride is a member), pyrenes and pyridyloxazole derivatives.

[00071] The present invention serves as a basis for even broader implementation of microarrays and gene expression in deducing critical pathways implicated in cancer, hi the case of CC-RCC, which is the focus of the present invention, a database of known patient genetic profiles can be used to categorize each new CC-RCC patient. The gene expression profile of the newly diagnosed CC-RCC patient is compared to the known CC-RCC molecular database of patients, such as that described herein based on 110 patients in whom complete clinical follow up information is available,. This database will grow with each patient who is subjected to the present analysis as soon as his clinical outcome information becomes available. If the newly diagnosed patient's gene expression profile most closely resembles the profile of aggressive CC-RCC, as described herein, that patient will be so classified and treated accordingly, i.e., with more aggressive measures. Correspondingly, if a newly diagnosed patient's profile is that of the non- aggressive type, he will be treated accordingly, e.g., with less aggressive measures and careful clinical follow-up.

[00072] The composition of the present invention may be used in diagnostic, prognostic, or research procedures in conjunction with any appropriate cell, tissue, organ or biological sample of the desired animal species. By the term "biological sample" is intended any fluid or other material derived from the body of a normal or diseased subject, such as blood, serum, plasma, lymph, urine, saliva, tears, cerebrospinal fluid, milk, amniotic fluid, bile, ascites fluid, pus and the like. Also included within the meaning of this term is an organ or tissue extract and a culture fluid in which any cells or tissue preparation from the subject has been incubated.

[00073] Drug Discovery Based on Gene Expression Profiling

[00074] The molecular profiling information described herein is also harnessed for the purpose of discovering drugs that are selected for their ability to correct or bypass the molecular alterations or derangements that are characteristic of CC-RCC, particularly those that are associated with its aggressive form. A number of approaches are available.

[00075] In one embodiment, CC-RCC cell lines are prepared from tumors using standard methods and are profiled using the present methods. Preferred cell lines are those that maintain the expression profile of the primary tumor from which they were derived. One or several CC-RCC cells lines may be used as a "general" panel; alternatively or additionally, cell lines from individual patients may be prepared and used. These cell lines are used to screen compounds, preferably by high-throughput screening (HTS) methods, for their ability to alter the expression of selected genes. Typically, small molecule libraries available from various commercial sources are tested by HTS protocols.

[00076] The molecular alterations in the cell line cells can be measured at the mRNA level

(gene expression) applying the methods disclosed in detail herein. Alternatively, one may assay the protein product(s) of the selected gene(s). Thus, in the case of secreted or cell- surface proteins, expression can be assessed using immunoassay or other immunological methods including enzyme immunoassays (EIA), radioimmunoassay (RIA), immunofluorescence microscopy or flow cytometry. EIAs are described in greater detail in several references. Butler, J.E., Ih: Structure of Antigens, Vol. 1 (Van Regenmortel, M., CRC Press, Boca Raton (1992), pp. 209-259; Butler, J.E., "ELISA," In: van Oss, CJ. et al. (eds), Immunochemistry, Marcell Dekker, Inc., New York, 1994, pp. 759-803; Butler, J.E. (ed.), Immunochemistry of Solid-Phase Immunoassay, CRC Press, Boca Raton, (1991). RIAs are discussed in Kirkjam and Hunter (eds.), Radioimmune Assay Methods, E. & S. Livingstone, Edinburgh, 1970.

[00077] In another approach, antisense RNAs or DNAs that specifically inhibit the transcription and/or translation of the targeted genes can be screened for specificity and efficacy using the present methods. Antisense compositions would be particularly useful for treating tumors in which a particular gene is up-regulated (e.g., the genes in Tables 2 and 3).

[00078] Diagnostic Methods

[00079] The protein products of genes that are upregulated in most cases of CC-RCC (e.g.,

Table 12 in Examples) are targets for ealy diagnostic assays of CC-RCC if the proteins can be detected by some assay means, e.g., immunoassay, in some accessible body fluid or tissue. The most useful diagnostic targets are secreted proteins which reach a measurable level in a body fluid before the tumor presents by other criteria discussed in the Background section. Thus, a sample of a body fluid such as plasma, serum, urine, saliva, cerebrospinal fluid, et cetera, is obtained from the subject being screened. The sample is subject to any known assay for the protein analyte. Alternatively, cells expressing the protein on their surface may be obtained, e.g., blood cells, by simple, conventional means. If the protein is a receptor or other cell surface structure, it can be detected and quantified by well-known methods such as flow cytometry, immunofluorescence, immunocytochemistry or immunohistochemistry, and the like.

[00080] Preferably, an antibody or other protein or peptide ligand for the target protein to be detected is used. In another embodiment where the gene product is a receptor, a peptidic or small molecule ligand for the receptor may be used in known assays as the basis for detection and quantitation.

[00081] In vivo methods with appropriately labeled binding partners for the protein targets, preferably antibodies may also be used for diagnosis and prognosis, for example to image occult metastatic foci or for other types of in situ evaluations. These methods utilize include various radiographic, scintigraphic, and other imaging methods well-known in the art (MRI, PET, et cetera).

[00082] Suitable detectable labels include radioactive, fluorescent, fluorogenic, chromogenic, or other chemical labels. Useful radiolabels, which are detected simply by gamma counter, scintillation counter, or autoradiography include ³H, ¹²⁵I, ¹³¹I₅ ³⁵S, and ¹⁴C.

[00083] Common fluorescent labels include fluorescein, rhodamine, dansyl, phycoerythrin, phycocyanin, allophycocyanin, ø-phthaldehyde and fluorescamine. The fluorophore, such as the dansyl group, must be excited by light of a particular wavelength to fluoresce. See, Haugland, Handbook of Fluorescent Probes and Research Chemicals, Sixth Ed., Molecular Probes, Eugene, OR, 1996. Fluorescein, fluorescein derivatives and fluorescein-like molecules such as Oregon Green™ and its derivatives, Rhodamine Green™ and Rhodol Green™, are coupled to amine groups using the isothiocyanate, succinimidyl ester or dichlorotriazinyl-reactive groups. Fluorophores may also be coupled to thiols using maleimide, iodoacetamide, and aziridine-reactive groups. The long wavelength rhodamines include the tetramethykhodamines, X-rhodamines and Texas Red™ derivatives. Other preferred fluorophores for derivatizing the protein binding partner are those which are excited by ultraviolet light. Examples include cascade blue, coumarin derivatives, naphthalenes (of which dansyl chloride is a member), pyrenes and pyridyloxazole derivatives.

[00084] The protein (antibody or other ligand) can also be labeled for detection using fluorescence-emitting metals such as ¹⁵²Eu, or others of the lanthanide series. These metals can be attached to the protein using metal chelating groups such as diethylenetriaminepentaacetic acid (DTPA) or ethylenediaminetetraacetic acid (EDTA). [00085] For in vivo diagnosis, radionuclides may be bound to protein either directly or indirectly using a chelating agent such as DTPA and EDTA which is chemically conjugated, coupled, or bound (which terms are used interchangeably) to the protein. The chemistry of chelation is well known in the art. The key limiting factor on the chemistry of coupling is that the antibody or ligand must retain its ability to bind the target protein. A number of references disclose methods and compositions for complexing metals to macromolecules including description or useful chelating agents. The metals are preferably detectable metal atoms, including radionuclides, and are complexed to proteins and other molecules. See, for example, U.S. 5,627,286, U.S. 5,618,513, U.S. 5,567,408, U.S. 5,443,816, U.S. 5,561,220, all of which are incorporated by reference herein.

[00086] Any radionuclide having diagnostic (or therapeutic value) can be used. In a preferred embodiment, the radionuclide is a γ-emitting or a β-emitting radionuclides, for example, one selected from the lanthanide or actinide series of the elements. Positron- emitting radionuclides, e.g., ⁶⁸Ga or ⁶⁴Cu, may also be used. Suitable γ-emitting radionuclides include those which are useful in diagnostic imaging applications. The gamma-emitting radionuclides preferably have a half-life of from one hour to forty days, preferably from twelve hours to three days. Examples of suitable γ-emitting radionuclides include ⁶⁷Ga, ¹¹¹In, ^99mTc, ¹⁶⁹Yb and ¹⁸⁶Re. Examples of preferred radionuclides (ordered by atomic number) are ⁶⁷Cu, ⁶⁷Ga, ⁶⁸Ga, ⁷²As, ⁸⁹Zr, ⁹⁰Y, ⁹⁷Ru, ⁹⁹Tc, ¹¹¹In₅ ¹²³1, ¹²⁵1, ¹³¹1, ¹⁶⁹Yb, ¹⁸⁶Re, and ²⁰¹Tl. Though limited work has been done with positron-emitting radiometals as labels, certain proteins, such as transferrin and human serum albumin, have been labeled with ⁶⁸Ga.

[00087] A number of metals (not radioisotopes) useful for MRI include gadolinium, manganese, copper, iron, gold, and europium. Gadolinium is most preferred. Dosage can vary from 0.01 mg/kg to 100 mg/kg.

[00088] In situ detection of the labeled protein may be accomplished by removing a histological specimen from a subject and examining it by microscopy under appropriate conditions to detect the label. Those of ordinary skill will readily perceive that any of a wide variety of histological methods (such as staining procedures) can be modified in order to achieve such in situ detection.

[00089] An alternative diagnostic approach utilizes cDNA probes that are complementary to and thereby detect cells in which a gene associated with CC-RCC is upregulated by in situ hybridization with mRNA in these cells. The present invention provides methods for localizing target mRNA in cells using fluorescent in situ hybridization (FISH) with labeled cDNA probes having a sequence that hybridizes with the mRNA of an upregulated gene. The basic principle of FISH is that DNA or RNA in the prepared specimens are hybridized with the probe nucleic acid that is labeled non-isotopically with, for example, a fluorescent die, biotin, or digoxigenin. The hybridized signals are then detected by fluorimetric or by enzymatic methods, for example, by using a fluorescence or light microscope. The detected signal and image can be recorded on light sensitive film.

[00090] An advantage of using a fluorescent probe is that the hybridized image can be readily analyzed using a powerful confocal microscope or an appropriate image analysis system with a charge-coupled device (CCD) camera. As compared with radioactive methods, FISH offers increased sensitivity. In addition to offering positional information, FISH allows better observation of cell or tissue morphology. Because of the nonradioactive approach, FISH has become widely used for localization of specific DNA or mRNA in a specific cell or tissue type.

[00091] The in situ hybridization methods and the preparations useful herein are described in Wu, W. et al., eds., Methods in Gene Biotechnology, CRC Press, 1997, chapter 13, pages 279-289. This book is incorporated by reference in its entirety, as are the references cited therein. A number of patents and papers that describe various in situ hybridization techniques and applications, also incorporated by reference, are: 5,912,165; 5,906,919; 5,885,531; 5,880,473; 5,871,932; 5,856,097; 5,837,443; 5,817,462; 5,784,162; 5,783,387; 5,750,340; 5,759,781; 5,707,797; 5,677,130; 5,665,540; 5,571,673; 5,565,322; 5,545,524; 5,538,869; and 5,501,954; 5,225,326; 4,888,278. Other related references include Jowett, T., Methods Cell. Biol; 59:63-85 (1999), Pinkel, et al, Cold Spring Harbor Symp. Quant. Biol. LI: 151-157 (1986); Pinkel, D. et al, Proc. Natl. Acad. ScL (USA) 83:2934-2938 (1986); Gibson, et al, Nucl. Acids Res. 15:6455-6467 (1987); Urdea et al, Nucl Acids Res. 16:4937-4956 (1988); Cook et al, Nucl. Acids Res. 16:4077-4095 (1988); Telser et al, J. Am. Chem. Soc. 111:6966-6976 (1989); Allen et al, Biochemistry 28:4601-4607 (1989); Nederlof, P.M., et al, Cytometry 10:20-27 (1989); Nederlof, P.M. et al, Cytometry 11:126-131 (1990); Seibl, R. et al, Biol Chem. Hoppe-Seyler 371:939- 951 (Oct. 1990); Wiegant, J. et al, Nucl Acids Res. 19:3237-3241 (1991); McNeil J.A., et al, Genet. Anal. Tech. Appl. 8:41-58 (1991); Komminoth et al, Diagnostic Molecular Biology 1:85-87 (1992); Dauwerse, J.G., et al, Hum. MoI. Genet. 1:593-598 (1992); Ried, T. et al, Proc. Natl. Acad. ScL (USA) 89:1388-1392 (1992); Wiegant, J. et al, Cytogenet. Cell Genet. 63:73-76 (1993); Glaser, V., Genetic Eng. News, 16:1, 26 (1996); Speicher, M.R., Nature Genet. 12:368-375 (1996). [00092] Detection of "Unknown" Gene Product

[00093] In an extreme case, in which an upregulated DNA "X" is identified but its protein product "Y" is unknown, one would first examine the expressed DNA X sequence. The full length gene sequence may be obtained by accessing a human genomic database such as that of Celera. In either case, examination of the coding sequence for appropriate motifs will indicate whether the encoded protein Y is secreted protein or a transmembrane protein. If no antibodies specific for protein Y are already available, the peptides of protein Y can be designed and synthesized using known principles of protein chemistry and immunology. The object is to create a set of immunogenic peptides that elicit antibodies specific for epitopes of the protein that reside on its surface. Alternatively, the coding DNA or portions thereof can be expression-cloned to produce a polypeptide or peptide epitope thereof. That protein or peptide can be used as an immunogen to immunize animals for the production of antisera or to prepare monoclonal antibodies (mAbs). These polyclonal sera or mAbs can then be applied in an immunoassay, preferably an EIA, to detect the presence of protein Y or measure its concentration in a body fluid or cell/tissue sample.

[00094] Therapeutic Methods

[00095] Taking the lead from the drug discovery methods described above, one can exploit the present invention to treat CC-RCC based on the knowledge of the genes that are either up- or down- regulated in a highly predictable manner across CC-RCC cases (see Tables 12 and 13 in Examples). Based on the nature of the deduced protein product, on can devise a menas to inhibit the action of, or remove and upregulated protein, hi the case of a receptor, one would treat the upregulated receptor with an antagonist, a soluble receptor or a "decoy" ligand binding site of a receptor. Gershoni J.M., et al, Proc. Natl. Acad. ScL USA, 1988 85:4087-9; U.S. Patent No. 5,770,572.

[00096] For an under-expressed receptor, an agonist or mimetic would be administered to maximize binding and activation of those receptor molecules which are expressed.

[00097] As for the set of genes that are shown here to be down-regulated in CC-RCC, one can devise a therapy targeted specifically at this form of the cancer, that would be used alone or in combination with known therapeutic approaches as discussed above. A preferred approach would be to stimulate production of the protein by administering an agent that promoted production, enhanced its stability or inhibited its degradation or metabolism. Alternatively, one could design means to bypass the metabolic step or signal pathway step that was affected by this down-regulation. This could be achieved by stimulating downstream steps in such pathways. If a receptor was involved, then, as above, agonists or mimics could be used to heighten responses of cells expressing too little of the receptor.

[00098] Moreover, for the down-regulated genes, gene therapy methods could be used to introduce more copies of the affected gene or more actively expressed genes operatively linked to strong promoters, e.g., inducible promoters, such as an estrogen inducible system. Braselmann, S. et al, Proc. Natl. Acad. ScL USA (1993) 90:1657-1661. Also known are repressible systems driven by the conventional antibiotic, tetracycline. Gossen, M. et al, Proc. Natl. Acad. ScL USA 89:5547-5551 (1992).

[00099] One can exploit the present invention to treat CC-RCC based on the knowledge of the genes that are upregulated in a highly predicable manner across CC-RCC cases (see Tables 6-9 and 12 in Examples). Based on the nature of the deduced protein product, one can devise a means to inhibit the action of, or remove an upregulated protein. In the case of a receptor, one would treat the upregulated receptor with an antagonist, a soluble receptor or a "decoy" ligand binding site of a receptor (Gershoni J.M. et al, Proc. Natl. Acad. Set USA, 1988 85:408709; U.S. Patent No. 5,770,572).

[000100] Antibodies may be administered to a patient to bind and inactivate (or compete with) secreted protein products or expressed cell surface products or upregulated genes.

[000101] In the case of upregulated genes, gene therapy methods could be used to introduce antisense oligonucleotide or polynucleotide constructs that would inhibit gene expression in a highly specific manner. Such constructs could be operatively linked to strong promoters, e.g., inducible promoters, such as an estrogen inducible system (Braselmann, S. et al,. Proc. Natl. Acad. Sd. USA (1993) 90:1657-1661). Also known are repressible systems driven by the conventional antibiotic, tetracycline (Gossen, M. et al, Proc. Natl. Acad. ScL USA 89:5547-5551 (1992)). Multiple antisense constructs specific for different upregulated genes could be employed together. The sequences of the upregulated genes described herein are used to design the antisense oligonucleotides (Hambor, J.E. et al., J. Exp. Med. 168:1237-1245 (1988); Holt, J.T. et al., Proc. Natl Acad. ScL 83:4794-4798 (1986); Izant LG. et al., Cell 36:1007-1015 (1984); Izant, LG. et al, Science 229:345- 352 (1985); De Benedetti, A. et al, Proc. Natl. Acad. ScL USA 84:658-662 (1987)). The antisense oligonucleotides may range from 6 to 50 nucleotides, and may be as large as

100 or 200 nucleotides. The oligonucleotides can be DNA or RNA or chimeric mixtures or derivatives or modified versions thereof, sing-stranded or double-stranded. The oligonucleotides can be modified at the base moiety, sugar moiety, or phosphate backbone (as discussed above). The oligonucleotide may include other appending groups such as peptides, or agents facilitating transport across the cell membrane (see., e.g., Letsinger et al, 1989, Proc. Natl. Acad. Sci. USA 84:684-652; PCT Publication No. WO 88/09810, published December 15, 1988) or blood-brain barrier (e.g., PCT Publication No. WO 89/10134, published April 25, 1988), hybridization-triggered cleavage agents (e.g., Krol et al, 1988, BioTechniques 6:958-976) or intercalating agents (e.g., Zon, 1988, Pharm. Res. 5:539-549).

[000102] The therapeutic methods that require gene transfer and targeting may include virus-mediated gene transfer, for example, with retroviruses (Nabel, E.G. et al, Science 244:1342 (1989), Antiviruses, and recombinant adenovirus vectors (Horowitz, M.S., In: Virology, Fields, B.N. et al, eds. Raven Press, New York, 1990, p. 1679, or current edition; Berkner, K.L., Biotechniques 6:616-919, 1988), Straus, S.E., In: The Adenoviruses, Ginsberg, H.S., ed., Plenum Press, New York, 1984, or current edition). Adeno-associated virus (AAV) also is also useful for human gene therapy (Samulski, RJ., et al., EMBO J. 10:3941 (1991); Lebkowskie, J.S. et al, MoI. Cell Biol. (1988) 8:3988-3996; Kotin, R.M. et al., Proc. Natl. Acad. Sci. USA (1990) 87:2211-2215; Hermonat, PL et al, J. Virol. (1984) 51: 329-339). Improved efficiency is attained by the used of promoter enhancer elements in the plasmid DNA constructs (Philip R., et al, J. Biol. Chem. (1993) 268:16087-16090).

[000103] In addition to virus-mediated gene transfer in vivo, physical means well-known in the art can be used for direct gene transfer, including administration of plasmid DNA, and particle-bombardment mediated gene transfer, originally described in the transformation of plant tissue (Klein, T.M. et al, Nature 327:70 (1987); Christou, P. et al, Trends Biotechnol. 6:145 (1990)) but also applicable to mammalian tissues in vivo, ex vivo or in vitro (Yang, N.S. et al, Proc. Natl. Acad. Sci USA 87:9568 (1990); Williams, R.S. et al, Proc. Natl. Acad. Sd. USA 88: 2726 (1991); Zelenin A.v. et al, FEBS Lett. 280:94 (1991); Zwelenin A.v. et al, FEBS Lett. 244:65 (1989); Johnston, S.A., et al, In Vitro Cell Dev. Biol. 27:11 (1991)). Furthermore, electroporation, a well-known means to transfer genes into cell in vitro, can be used to transfer DNA molecules according to the present invention to tissues in vivo (Titomirov, A.V. et al, Biochim. Biophys. Acta 1088:131 (1991)). [000104] Gene transfer can also be achieved using "carrier mediated gene transfer" (Wu,

CH. et al, J. Biol. Chem. 264: 16985 (1989); Wu, G.Y et al, J. Biol. Chem. 263:14621 (1988); Soriano, P. et al, Proc. Natl. Acad. Sci. USA 80:7128 (1983); Wang, CY. et al, Proc. Natl. Acad. ScL USA 84:7851 (1982); Wilson, J. M et al, J. Biol. Chem. 267:963 (1992)). Preferred carriers are targeted liposomes (Nicolau, C. et al, Proc. Natl. Acad. Sci. USA 80:1068 (1983); Soriano, et al, supra) such as immunoliposomes, which can incorporate acylated monoclonal antibodies into the lipid bilayer (Wang, et al, supra), or polycations such as asialogycoprotein/polylysine (Wu, et al., 1989, supra). Liposomes have been used to encapsulate and deliver a variety of materials to cells, including nucleic acids and viral particles (Faller, D. V. et al, J. Virol. (1984) 49:269-272).

[000105] Preformed liposomes that contain synthetic cationic lipids form stable complexes with polyanionic DNA (Feigner, P.L. et al, Proc. Natl. Acad. Sci. USA (1987) 84:7413- 7417). Cationic liposomes, liposomes comprising some cationic lipid, that contained a membrane fusion-promoting lipid dioctadecyldimethyl-ammonium-bromide (DDAB) have efficiently transferred heterologous genes into eukaryotic cells (Rose, J.K. et al, Biotechniques (1991) 10:520-525). Cationic liposomes can mediate high level cellular expression of transgenes, or mRNA, by delivering them into a variety of cultured cell lines (Malone, R., et al, Proc. Natl. Acad. Sci. USA (1989) 86:6077-6081).

[000106] RT-PCR

[000107] hi addition to microarray analysis of patient tissue samples, other techniques known in the art can be used to assay expression individually of any one of the identified genes. For example, expression level can be detected by reverse transcription PCR if the the sample DNA is in formalin-fixed paraffin-embedded tissue.

EXAMPLES

[000108] The present invention is more particularly described in the following Examples, which are intended as illustrative only, since modifications and variations therein will be apparent to those skilled in the art.

[000109] Example 1- Patients and tumor samples

[000110] To identify potential genetic programs driving tumor aggressiveness, the inventors performed gene expression profiling for 110 sporadic primary CC-RCC samples and thirteen metastatic CC-RCC samples from eight institutions in the U.S.A. and Japan. Primary tumor tissue samples were acquired from patients diagnosed with sporadic CC- RCC who had undergone primary nephrectomy. Metastatic tumor tissue samples were acquired from patients with a history of localized CC-RCC, who had relapsed with metastases after primary nephrectomy. Baseline patient characteristics are presented (Table 2). Survival analysis was performed by Cox regression analysis. Median follow-up in patients with primary RCC was 5.0 years in surviving patients, and 2.4 years in all patients. Table 2

Table 2- Baseline Characteristics of Patients

to

ON

to

-r¹

do

O

* 24 cases were profiled on both the oligonucleotide and the spotted cDNA array platforms. f 27 USA cases underwent both profiling and CD31 immunostaining.

J Patients with metastatic RCC at surgery who received adjuvant immunotherapy.

The total percentage count for each category may not total to 100 due to rounding.

[000112] A total of 146 primary tumor and thirteen metastatic tissue specimens from independent patients were received from eight centers (six in the U.S.A., two in Japan). Each tumor sample was grossly dissected, flash frozen following resection and stored at - 80⁰C at each center until transport. Thirty-six of 146 primary tumor samples were degraded on quality assessment of RNA by denaturing gel electrophoresis. Baseline characteristics of viable and non- viable tissue did not significantly differ (Table 2).

[000113] Representative tissue sections were cut and stained with hematoxylin-eosin for the diagnosis of clear cell renal cell carcinoma (CC-RCC), and histological diagnosis was confirmed by central pathological review. AU samples had at least 60% tumor tissue. Tumor staging and grading were obtained from review of the pathology reports and evaluation of the case notes by individual clinicians. Node status was either assessed intraoperatively by inspection or by pathological evaluation. Tumors with sarcomatoid change were classified as grade four tumors. Functional status at the point of surgery, expressed by Eastern Cooperative Oncology Group (ECOG) performance status was derived by individual clinicians either at the point of initial evaluation, or by retrospective evaluation of the case notes. Response to immunotherapy was determined by Response Evaluation Criteria in Solid Tumors (RECIST) criteria (A. Jemal et al., CA Cancer J CHn 54, 8 (2004)) six months after completion of therapy. Tumor size was defined as the maximum tumor dimension upon measurement after resection.

[000114] Example 2- Microarray analysis

[000115] Ninety-two primary tumor samples underwent expression profiling with whole- genome oligonucleotide arrays containing 54,675 probe sets (HGU133 Plus 2.0, Affymetrix, CA). A prespecified external validation approach was used, where samples from Japan were designated as the training set (n=33) and those from the USA as the test set (n=59). The inventors employed supervised principal components (PC) (E. Bair, R. Tibsbirani, PLoS Biol 2, E108 (2004)) and unsupervised two-means clustering to derive optimal oligonucleotide predictors that yielded both continuous and discrete survival predictions (Table 3, Figs. IA, IB₅ and 1C). [000116] Table 3

Oligonucleotide Survival Predictor Performance

[000117] Oligonucleotide array profiling

[000118] For oligonucleotide array gene profiling, the inventors extracted total RNA from homogenized samples using Trizol reageant (Invitrogen, CA) according to manufacturer's recommendations. Total RNA was subsequently purified with an RNEasy kit (Qiagen, CA). Ninety-two primary CC-RCC specimens, thirteen metastatic specimens, and twelve non-cancerous unmatched cortical specimens were profiled using oligonucleotide array gene profiling. The HGUl 33 Plus 2.0 GeneChips contains 54,675 probe sets, representing approximately 47,000 transcripts and variants. 5 - 20 μg of total RNA was used to prepare antisense biotinylated RNA. A subset of cases were spiked with external poly-A RNA positive controls (Affymetrix). Synthesis of single-stranded and double-stranded complementary DNA was performed with the use of T7-oligo(dT) primer (Affymetrix). In-vitro transcription was performed using Enzo Bioarray Transcript Labelling Kit (Enzo, NY). The biotinylated cRNA was subsequently fragmented, and ten μg was hybridized to each array at 45⁰C over sixteen hours. Scanning was performed in a GeneChip 3000 scanner. Quality assessment was performed in GeneChip Operating System (GCOS) 1.1.1 (Affymetrix) using global scaling to a target signal of 500. Quality assessment was performed using denaturing gel electrophoresis. The manufacturer's recommended protocol (GeneChip Expression Analysis Technical Manual, Affymetrix, April 2003) was followed for expression profiling. All quality indices indicated a high overall array and RNA quality: mean percentage present (± SD) of 47.4 ± 3.1%, mean background of 56.4 ± 9.4, mean scaling factor of 3.45 ± 0.71 and a mean GADPH 375' ratio of 1.02 ± 0.14. All expression and clinical data have been uploaded to the Gene Expression Omnibus.

[000119] Data analysis

[000120] Statistical analyses were performed in the statistical environment R 1.9.1 , utilizing packages from the Bioconductor project. R. C. Gentleman et al., Genome Biol 5, R80 (2004). Packages used include Affy version 1.4.32 (L. Gautier, L. Cope, B. M. Bolstad, R. A. Mzarry, Bioinformatics 20, 307 (2004)), Survival version 2.11-5, Design version 2.0-9 (F. E. Harrell, Programs available from biostat.mc.vanderbilt.edu/s/Design.html (2003)) and Superpc 1.0 (E. Bair, R. Tibshirani, PLoS Biol 2, E108 (2004)). The default unsupervised analysis approach was hierarchical clustering using complete linkage clustering with a Euclidean distance metric. The default supervised analysis approach was prediction analysis of microarrays (PAM) with ten-fold cross validation over thirty thresholds and an offset percentage of 50%. R. Tibshirani, T. Hastie, B. Narasimhan, G. Chu, Proc. Natl. Acad. ScL U S A 99, 6567 (2002). The default significance threshold was 0.05. For the Affymetrix data, the robust multichip average (RMA) algorithm was the default method used to perform pre-processing of the CEL files, including background adjustment, quantile normalization and summarization. Following pre-processing, fifty- six transcripts corresponding to Affymetrix external spike-in controls were eliminated from the data sets. Two sets of data were pre-processed with RMA for survival analysis: (1) primary tumor samples only (n=92) and (2) primary and metastatic tumor samples (n=105). The expression values of the metastatic tumor samples (n=13) were derived from the second data set.

[000121] For supervised principal components (PC) (E. Bair, R. Tibshirani, PLoS Biol 2,

El 08 (2004)), the inventors used ten-fold cross-validation over fifty Cox score thresholds to obtain an optimal significant threshold for the Cox scores of each gene within the training set. This threshold was 2.540206. The first principal component of genes with absolute Cox scores exceeding that threshold was used as a gene predictor of continuous outcome; discrete classification was obtained by dividing the outcomes in two groups. For derivation of the reduced supervised PC signature, the inventors computed an importance score for each feature equal to its correlation with the supervised PC predictor. Shrinkage over sixty thresholds was performed, and the maximal shrinkage threshold corresponding to a significant likelihood ratio was selected. This corresponded to 77 transcripts. Validation of this reduced signature was performed on the test set.

[000122] A two-means clustering predictor was generated by the initial application of two- means clustering on the training set, followed by the derivation of a shrunken gene predictor with a minimum misclassification error by PAM. Multiple thresholds with a minimum misclassification error of 3% were noted, corresponding to 1, 3, 5, 12, 22, 37, 3733, 5412 and 11809 transcripts. Upon fitting to a Cox proportional hazards model, the first group of thresholds (1 to 37 transcripts) generated marginally superior results (R² = 0.276; p-value = 3.27 x 10^"3 versus R² = 0.241; 6.38 10^"3) in the training set upon fitting in comparison to the second group of thresholds (3733 - 11809 transcripts). The inventors thus selected the thirty-seven transcript predictor as the most conservative shrinkage threshold within the former group of thresholds.

[000123] For evaluation of co-expression, hierarchical clustering was performed on expression values corresponding to the reduced supervised PC signature. The reduced supervised PC predictor was used for matching because gene coexpression is likely to be biologically more meaningful. E. Bair, R. Tibshirani, PLoS Biol 2, El 08 (2004). 34 matching clones were identified as being informative for more than 50% of samples. Oligonucleotide probe sets were matched to cDNA clones by gene symbol, and hierarchical clustering was performed on the expression set, resulting in two clusters of samples.

[000124] Survival analysis

[000125] All survival analyses were performed by fitting the data to a Cox proportional hazards model, and the end point of interest was disease-specific mortality. Overall survival time in both patient groups (primary tumors and metastatic relapses) was defined as the time from nephrectomy to the date of death or the last known date of contact with provider. The level of significance was calculated with the likelihood ratio test. Goodness of fit is reported as Nagelkerke's R² values (N. J. D. Nagelkerke, Biometrika 78, 691 (1991)), where a value of one represents a perfect fit. Adjusted analyses were undertaken with the ninety-two-tumor oligonucleotide array data set. Case deletion was used for missing data. Variables adjusted for included age, gender, tumor stage, metastatic status at surgery, tumor maximum dimension, tumor grade, ECOG performance status, UCLA Integrated Staging System (UISS) status and VHL mutation status. The UISS is an externally validated aggregate variable composed of tumor stage, grade and ECOG performance status (A. Zisman et al, J Clin Oncol 19, 1649 (2001); A. Zisman, A. J. Pantuck, R. A. Figlin, A. S. Belldegrun, J Clin Oncol 19, 3792 (2001)). In the light of having thirty-one outcome events of interest in ninety-two patients, the inventors avoided underpowered Cox proportional hazards models by entering a maximum of three variables (corresponding to one variable per ten outcomes of interest) into the model. The inventors adjusted for all thirty-six possible combinations of two variables drawn from the nine available variables (Table 4).

[000126] In multivariable analysis, the predictors were independently significant of all combinations of up to two clinico-pathologic parameters studied (Table 4).

[000127] Table 4

Table 4- Multivariable analysis

ECOG PS: Eastern Cooperative Oncology Group Performance Status, VHL: von Hippel-Lindau gene mutation status, UISS: UCLA Integrated Staging System, a composite of Stage, Grade and ECOG

T⁴

OO

[000128] Example 3- Validation by spotted cDNA array profiling

[000129] For additional validation, the inventors established utility for the predictors across different microarray platforms and experimental designs. Two-channel spotted cDNA gene expression profiles (21,103 clones) were generated from patient-matched tumor and noncancerous kidney samples from forty-two patients, of whom eighteen were independent patients. As the differing data structures precluded the direct application of the prediction models, we used hierarchical clustering of well-measured (<50% missing data) expression values of cDNA clones matching gene symbols in the reduced supervised PC predictor (Table 5).

[000130] Table 5

List of Informative cDNA Clones Matching Reduced Supervised PC predictor

[000131] The resulting two clusters of tumors (Figs. 5A and 5B) were fitted to a Cox proportional hazards model, yielding good survival predictions (R² =0.416, p- value = 8.64 x 10^'6). For the twenty-four samples profiled on both oligonucleotide and spotted cDNA platforms, there was good concordance between group labels (83%) in the oligonucleotide data set (discrete prediction by reduced supervised PC predictor) and the spotted data set (hierarchical clustering).

[000132] Spotted cDNA array profiling

[000133] For spotted cDNA microarray gene profiling, forty-two additional sample pairs of patient-matched tumor and non-cancerous cortical samples were profiled (twenty-four biological replicates firom the training set, and eighteen independent samples). A separate analysis of twenty-eight of these spotted arrays has been previously reported, together with the protocols involved. M. Takahashi et al, Proc. Natl. Acad. Sd. U S A 98, 9754 (2001). Microarray experiments were performed with spotted cDNA arrays from different print runs with a total of 21,103 different cDNA clones. 2 μg of messenger RNA from each kidney tumor and patient-matched normal kidney tissue were used in a direct- labeling protocol for preparation of Cy5- and Cy3 cDNA probe.

[000134] Example 4- Comparative genomic microarray analysis/regional expression biases

[000135] In view of the distinct prognostic subtypes of RCC defined on unsupervised and semi-supervised analysis, the inventors sought to identify the characteristic chromosomal aberrations involved with comparative genomic microarray analysis (CGMA). Regional expression biases are genetic intervals where gene expression is coordinately changed (K. A. Furge et al, Cancer Res 64, 4117 (2004)), and correspond well with cytogenetic aberrations detected by comparative genomic hybridization. K. A. Furge et al, in preparation. Cytogenetic profiles of the ninety-two tumor oligonucleotide data set were inferred by identifying regional expression biases from gene expression ratios derived from the ninety-two-tumor oligonucleotide data set and twelve oligonucleotide expression profiles of non-cancerous kidney cortical samples (Fig. 4A). Each block corresponding to a single chromosome represents the chromosomal expression profiles of a group of samples, and each sample is represented by a single vertical line in each block. Samples have been arranged from left to right within each block by progressively worsening prognosis as predicted in a continuous fashion by the reduced supervised PC predictor. This technique identified distinct regional expression biases corresponding to common cytogenetic abnormalities in CC-RCC (G. Kovacs et al, Proc. Natl. Acad. Sd. USA S5, 1571 (1988)), such as deletions of chromosomes 3p, 6q, 9pq and 14q, as well as amplifications of chromosomes 1, 3q, 5q, 8q and 12. The profiles were consistent with previous reports of associations between deletions of 9pq and 14q and poor prognosis. A. M. Meloni-Ehrig, Am. J. Med. Genet. 115, 164 (2002). Other known cytogenetic aberrations not previously linked to survival, such as amplification of Iq, 3q and deletion of 6q, were highlighted as being of potential prognostic value.

[000136] Mutation analysis [000137] Genomic DNA was extracted from ninety-seven tumor tissue samples with either Trizol reageant (Invitrogen, CA) or the Wizard Genomic DNA Purification Kit (Promega, WI). Mutation screening was performed on exons 1 to 3 of the VHL gene. Primer sequences and protocols are available on request.

[000138] Regional gene expression biases [000139] The general approach to identify regional expression biases has been previously described. K. A. Furge et al, Cancer Res 64, 4117 (2004). In this study, a refinement of the algorithm was applied to increase the resolution of the detection method. Relative expression profiles (R) are generated from the single channel tumor expression profiles (T) and the mean expression values of the twelve single channel kidney cortical expression profiles (N) such that R = Iog₂(7) - log₂(N). Regional expression biases are identified using a unweighted, multiple span, running binomal estimator. Briefly, gene expression values are separated into chromosome subsets and ordered based on gene mapping information. The hgul33plus2 annotation package 1.5.1 was used. A sliding window algorithm is applied to each ordered gene expression subset such that within each window span a binomial test is applied under the assumption that the probability (p) of the appearance of a positive relative gene expression value equals the probability (q) of the appearance of a negative expression value. A z-score for the span is computed using the normal approximation of the binomal distrubution. As such, a positive z-score indicates that within the span expression was relatively higher in the tumor profile and a negative z-score indictates that expression within the span was relatively lower in the tumor profile. Rather then use data generated from a single window span, data generated from multiple spans is collected and an average z-score at each gene location is computed. More formally, given a set of ordered gene expression values g_j for genes j = 1, 2, ...m, let Xy denote expression bias approximations for genes 7 = 1, 2, ...m using spans

i = 25, 26, 27, ...mil where n denotes the number of spans. Let

z+2 >j ≥ i where t denotes the number of non-zero and r the number of positive values within the span {g_hgk±u ■■■gkή-i-i}- To not discard regions, xy is tapered wheny < i such

Xij ₌ If 2r-t that J ^k=l vt 3J₁(J analogously tapered wheny > m-i+2. Regional expression bias

estimates (^Xj ) are computed such that

. Limiting the minimum window span to 25 provides assurance the approximated z-scores are reasonably accurate and limiting the maximum window span to mil prevents the generation of redundant bias estimations.

[000140] Example 5- Oligonucleotide predictors [000141] The inventors noted from inspection of the predictors (Tables 6-9) that high expression of genes classically involved in angiogenesis, hypoxia-response and endothelial cell formation optimally predicted longer patient survival. Identified genes included vascular endothelial growth factor (VEGF), endothelial PAS domain protein 1/ hypoxia inducible factor-2 (HIF-2), kinase insert domain receptor/ VEGF receptor 2, and many others.

[000142] Table 6 Table 6- Oligonucleotide predictors

*

CΛ

4

Table 7

oo

in

9

Ut

Table 8

Table 8- Reduced supervised principal components factor

**This score measures how well individual genes correlate with the fully supervised PC predictor.

HIGH EXPRESSION IN GOOD PROGNOSIS (non-aggressive) tumors

PROBE ID GENE SYMBOL GENE TITLE IMPORTANCE RAW COX ShQ ID

LU

Table 9

Table 9- Two-Means clustering predictor

OO

VO

[000143] Individual predictors are fiilly described in Tables 7 to 9. All transcripts have been placed in descending order of discriminatory ability as defined by each statistical approach, and duplicate transcripts in a single group correspond to multiple oligonucleotide probe sets for a single gene. Referring to Table 8, informative clones in the cDNA spotted array corresponding to the asterisked genes (i.e., having less than 50% missing data) were used for hierarchical clustering.

[000144] Example 6- Patient Case Example

[000145] Patient X, whose sample was prospectively collected, underwent nephrectomy in

2001. He died of cancer approximately 1 year after surgery. He did not receive any adjuvant therapy. Following gene expression profiling, the statistical methods applied yielded the following results:

[000146] Using the continuous supervised PC predictor, his expression profile scored (on a continuous scale) -0.329, based on the expression values of the corresponding 58 transcripts. For the 92 cases, good prognosis tumors ranged between a score of -0.83 to - 0.53. Poor prognosis tumors ranged between a score of -0.51 to -0.23. This case clearly classified as a poor-prognosis tumor by the continuous full supervised PC predictor.

[000147] Using the reduced supervised PC predictor, his expression profile scored -19.7 based on the expression values of the corresponding 77 transcripts. For the 92 cases, good prognosis tumors ranged between a score of -25.74 to -21.82. Poor prognosis tumors ranged between a score of -21.61 to -17.92. This case clearly classified as a poor- prognosis tumor by the reduced supervised PC predictor.

[000148] Using the two means clustering predictor, his expression profile was classified directly as a poor prognosis class tumor, based on the expression values of the corresponding thirty-seven transcripts. For the 92 cases, calculation of class was based on derivation of linear discriminant scores by standard methodology previously described in the initial description of nearest shrunken centroids methodology. Tibshirani R, Hastie T, Narasimhan B, Chu G. Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proa Natl. Acad. ScL USA. 2002 May 14;99(10):6567-72. [000149] Example 7- Pathway analysis

[000150] Pathway analysis was performed on the reduced supervised PC predictor with a curated database. A single key network of gene interaction was identified and corresponding canonical signal pathways were ranked by the number of nodes involved (Table 10). The VEGF canonical signaling pathway, predominantly activated in good- prognosis tumors, was the highest ranked pathway distinguishing good- from poor- prognosis tumors.

[000151] Table 10

Pathway Ranking of Network Analysis

[000152] The reduced supervised PC analysis was analyzed because correlation with the full supervised PC predictor is likely to select for coexpressed genes that are more biologically more coherent. Importance scores were used to score the genes for pathway analysis. The Ingenuity Pathways database Summer 2004 build was used for analysis. Thirty genes were identified from the 77 transcripts as being eligible for generating networks. 73 of 77 transcripts were mapped to a known gene. Duplicate transcripts corresponding to a single gene were recorded. The Ingenuity pathways analysis software identified a single key network with a score of 35, with eighteen focus genes involved. In comparison, all other identified networks had a score of two or less, with only one focus gene each. Canonical pathways in this network were ranked by the number of nodes included in this network (Table 10).

[000153] Example 8- Aurora Kinase Pathway Analysis

[000154] In a demonstration that the Aurora Kinase pathway is likely to be particularly active in renal cell carcinoma, and poor-prognosis renal cell carcinoma in particular, the inventors surveyed several genes previously reported to physically and functionally participate within this pathway. The inventors found the Aurora kinases A, B and C overexpressed in renal cell tissue relative to non-cancerous glomerular cortex. Further, the inventors found distinct co-regulation of genes - that is, tumors with higher expression of Aurora kinase A showed higher expression of Aurora kinase B, TPX2, survivin (Figure

7).

[000155] In an additional step, the inventors found Aurora Kinase pathway genes overexpressed in poor-prognosis renal cell carcinoma relative to good-prognosis renal cell carcinoma. This was particularly highlighted by the presence of STK6/STK15/Aurora- kinase A, and non-metastatic cell 1 protein (NM23A) within the optimal reduced supervised PC predictor of prognosis (Table 8, with the reduced supervised predictor). The individual expression of genes within this pathway is described at Table 11.

Table 11

[000157] Using comparative genomic microarray analysis, the inventors demonstrated that upregulation of the region of 20ql 3 (a region corresponding to STK6 / aurora kinase A) was present in poor prognosis RCC, consistent with amplification, a phenomenon previously observed in breast cancer (Figs. 4A and 4B).

[000158] The Aurora Kinase pathway group of genes are of potential use as therapeutic targets in renal cell carcinoma. This therapy may take a form of pharmacological or genetic inhibition of the pathway. Pharmacological inhibition may include, but is not limited to, small molecule inhibitors, monoclonal antibodies, and other forms of targeted therapies. Genetic inhibition may include, but is not limited to, include techniques such as RNA inhibition (RNAi) or the expression of dominant-negative mutants.

[000159] Example 9- CDSl immunostaining analysis

[000160] The inventors used conventional CD31 immunostaining to assess tissue angiogenesis in 45 formalin-fixed paraffin-embedded CC-RCC samples (Figs. 3A and 3B). For Figs. 3 A and 3B, images of selected hot spots in good-prognosis (3A) and poor- prognosis tumors (3B) from the test set indicate that microvessel density is relatively higher in good-prognosis tumors. The differences in grade are also visible from the photomicrographs. Mean microvessel density (MVD) was calculated from interactive image analysis of three-by-three 20Ox fields per slide. The inventors used the median MVD (65 vessels/ field) as a cutoff. Univariate analysis demonstrated that increased MVD was significantly correlated with prolonged survival (R²=0.167, p-value= 0.01). For a subset of 27 tumors for which both expression profiling and immunohistochemistry were performed, there was good correlation between MVD and log-transformed mean HIF-2 mRNA expression (r=0.7, 95% C.I. 0.43 - 0.85), as well as between MVD and log-transformed mean VEGF mRNA expression (r=0.54, 95% C.I. 0.2 - 0.76). These results are consistent with previous reports that RCC vascularity is correlated with expression of HIF-2 rnRNA (K. J. Turner et al, Cancer Res 62, 2957 (2002)) and VEGF rnRNA. A. Takahashi et al, Cancer Res 54, 4233 (1994). The inventors also noted an interesting lack of consensus in a literature review of previous immunohistochemical studies correlating survival and angiogenesis in CC-RCC, contrasting with the situation in most other cancers where angiogenesis is directly correlated with tumor aggressiveness. N. Weidner, J. Pathol. 189, 297 (1999).

[000161] To the knowledge of the inventors: five studies have shown a direct correlation between increasing MVD and prolonged survival time. B. Delahunt, P. B. Bethwaite, A. Thornton, Br J Urol 80, 401 (1997); C. Herbst et al, J. Cancer Res. Clin. Oncol. 124, 141 (1998); N. Rioux-Leclercq et al, Hum Pathol 32, 1209 (2001); E. Sabo et al, Clin Cancer Res 7, 533 (2001); T. Imao, M. Egawa, H. Takashima, K. Koshida, M. Namiki, Int J Urol 11, 948 (2004). Five studies have shown an inverse relationship. S. Yoshino, M. Kato, K. Okada, Anticancer Res 20, 591 (2000); O. Nativ et al, Urology 51, 693 (1998); Y. Dekel, R. Koren, V. Kugel, P. M. Livne, R. Gal, Pathol Oncol Res 8, 129 (2002); H. J. Joo, D. K. Oh, Y. S. Kim, K. B. Lee, S. J. Kim, BJU Int 93, 291 (2004); V. Paradis et al, Virchows Arch 436, 351 (2000). Five studies have shown no significant correlation. G. T. MacLennan, D. G. Bostwick, Urology 46, 27 (1995); A. B. GeIb, D. Sudilovsky, C. D. Wu, L. M. Weiss, L. J. Medeiros, Cancer 80, 1768 (1997); J. W. Slaton et al, Am J. Pathol. 158, 735 (2001); P. Schraml et al, J. Pathol 196, 186 (2002); Y. Imazano et al., JClin Oncol 15, 2570 (1997).

[000162] CD31 is an endothelium specific transmembrane protein expressed in vascular and lymphatic endothelium, and is a commonly used standard for assessment of microvessel density (MVD). Automated CD31 immunostaining was performed on 45 formalin-fixed paraffin embedded tissue specimens with pepsin pre-digestion, and with an incubation of mouse anti-human monoclonal antibody, clone JC/70A (M0823) at a concentration of 1:25. The Envision system (DAKO, Denmark) was used for detection. One slide was stained per specimen. In view of the high tissue heterogeneity and vascularity of RCC, the inventors used a strategy optimized to maximize correlation between mRNA expression in bulk tissue and the immunohistochemical staining. Nine fields for each slide were captured at a magnification of x 200 in a 3 x 3 arrangement with the widest possible distribution across the slide. Digital image capture was performed with a Spot Insight Camera on a Nikon Eclipse E600, and each field was 0.2596 mm² in size. Interactive image analysis was performed using Cytometrix, an in-house program for quantitative analysis of histologic images. Immunostaining, image capture and analysis were performed independently by blinded individuals. CD31 immunostained plasma cells were eliminated from the analysis. A countable microvessel was defined as a stained endothelial cell cluster with or without a lumen distinct from other cell clusters. Structures which were contiguous or anastomosing were considered as a single microvessel. To define two groups, the inventors used the median number of vessels as a cutoff (an MVD of 65 vessels or less versus an MVD more than 65). The inventors correlated the log-transformed mean expression values of the oligonucleotide probe sets corresponding to EPAS1/HIF2 (n=2) and VEGF (n=4) with MVD using Pearson's product moment correlation.

[000163] Example 10- Analysis of VHL-mutant CC-RCC tumors

[000164] As the VHL protein is a key regulator of the HIF pathway, the inventors asked if

VHL mutation was associated with survival or gene expression patterns that could further define its role in angiogenesis and hypoxia-response. A mutation prevalence of 34% was determined in 97 primary tumors. No prognostic significance for VHL mutation status was found in the full data set (HR=0.81, p-value = 0.59). However, a non-significant correlation was observed between VHL mutation and longer survival in localized tumors (HR=0.20, p=0.13) but not in metastatic tumors, in line with a previous study. M. Yao et al., J Natl Cancer Inst 94, 1569 (2002). A class comparison approach using prediction analysis of microarrays (PAM) (R. Tibshirani, T. Hastie, B. Narasimhan, G. Chu, Proa Natl. Acad. ScL U S A 99, 6567 (2002)) did not yield a specific gene classifier corresponding to VHL gene mutation. However, preliminary analysis using a modified class discovery strategy identified a subcluster of good-prognosis (non-aggressive) tumors with a significantly higher prevalence of VHL gene mutations (Fig. 6). Samples are clustered along columns, and transcripts along the rows below. Subcluster four has a significantly higher percentage of VHL mutations (p-value=0.002). Subcluster four is a good-prognosis subcluster.

[000165] The observation that different types of VHL mutations exert diverse effects in vitro (W. J. Hansen et al., MoI Cell Biol 22, 1947 (2002); S. C. Clifford et al, Hum MoI Genet 10, 1029 (2001)) and result in different phenotypes in familial VHL syndromes suggested that VHL-mutant CC-RCC tumors may be heterogeneous in gene expression. Since VHL is a mediator of the HIF signaling pathway, and many genes of the predictors are linked to HIF-signaling and angiogenesis, the inventors evaluated the possibility that distinct subclusters within the major prognostic tumor groups might be characterized by high incidences of VHL mutations. The inventors pursued a modified class-discovery strategy, performing hierarchical clustering on expression values of transcripts corresponding to the two-means clustering predictor to discover subclusters with varying degrees of expression of the prognostic genes (Fig. 6). Two major clusters were noted: one cluster was a poor prognosis cluster (aggressive tumors); the other cluster demonstrated three distinct subclusters, two of which were good prognosis subclusters (non-aggressive clusters), and one of which was a poor prognosis subcluster. One subcluster of good-prognosis tumors was distinguished by a significantly high prevalence of VHL mutations (14/19), as compared to the other good-prognosis subcluster (8/21) and the two poor-prognosis subclusters (3/11 and 3/13) (2-sided Fisher's exact test, p- value=0.002). Grouping these subclusters as good-prognosis and poor-prognosis tumors yielded excellent survival predictions (R2 = 0.295, p-value = 4.65 x lO^'8).

[000166] The heatmap demonstrated distinct patterns of expression corresponding to each subcluster, with progressive gradations of gene expression in the four groups (Fig. 6). The majority of prognostic genes identified in the predictor was upexpressed in good- prognosis tumors (34/37) and many of these genes are angiogenesis-linked. The VHL mutant-predominant subcluster had lower expression of these genes relative to the other good-prognosis subcluster, and higher expression of the same genes relative to the two poor prognosis subclusters. The VHL mutations characterizing this subcluster were not distinctive. This interesting finding requires validation in an external set, and should be considered preliminary.

[000167] Example 11- Analysis of metastatic tumors resected after relapse

[000168] The inventors investigated a direct prediction of this hypothesis: expression profiles from tumor tissue separated from primary tumor by space (metastasis) and time (relapse) should be expected to exhibit the same correlation between expression signature and overall survival, as well as similar cytogenetic aberrations. The inventors applied the predictors from the primary tumor data set to an oligonucleotide data set of metastatic CC-RCC samples (n=13) resected from a variety of distant sites after relapse, and obtained good survival predictions (Figs. 2A, 2B, 2C, Table 3). CGMA of these profiles yielded similar regional gene expression biases linked to poor-prognosis (aggressive tumors), including downregulation of 9pq and 14q (Fig. 4B). The results account for clinical observations where metastatic CC-RCC may be startlingly indolent in a small group of patients. An in vitro study provides support for this concept by demonstrating an independent gene signature for metastasis superimposed upon a poor prognostic gene set in a breast cancer cell line. Y. Kang et ah, Cancer Cell 3, 537 (2003).

[000169] Example 12- Identification of Probes for Up-Regulated and Down-Regulated

Genes

[000170] The inventors obtained a group of 830 transcripts that discriminated between CC-

RCC tumor tissue and normal noncancerous tumor tissue, and defined this group using significance analysis of microarrays (two class unpaired analysis of 10,000 permutations). The inventors found 830 genes with a false discovery rate of 0.01 at a delta cutoff of 10. The inventors selected to top 50 up- and top 50 down-regulated transcripts ordered by magnitude of fold-change (Table 12 and Table 13, respectively) and by magnitude of d. value (a modified tstatistic) (Table 14 and Table 15, respectively).

[000171] Table 12

Table 12 - TOP 50 UP Regulated Genes in Terms of Magnitude of Difference

Table 13

Table 13 - Top 50 Down Regulated Genes in Terms of Magnitude of Difference

Table 14

Table 14 - Top 50 Up Regulated Genes in Terms of Specificity of Difference

Table 15

Table 15 - Top 50 Down Regulated Genes in Terms of Specificity of Difference

<So

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[000172] The identified genes may serve as a means for therapeutic inhibition by chemical or genetics means, resulting in a novel therapy. Alternatively, the individual detection of these genes in formalin-fixed paraffin-embedded tissue using methods such as real-time reverse transcription PCR or microarrays may serve as a means of diagnosis. Also, their detection using microarrays may serve as a means of diagnosis.

[000173] The gene products (taken from serum, urine, saliva, or other abundant body fluid rather than kidney tissue) of the up-regulated expressed nucleic acids (Table 12) can be assayed using in immunoassays known in the art (i.e., ELISA, immunocytochemistry, sandwich assays, et cetera) for the purpose of diagnosing patients with CC-RCC but do not discriminate between the heterogeneous disease severity.

Claims

What is claimed is:

1. A microarray useful as a prognostic composition, comprising a matrix of at least one probe from a set of probes immobilized to a solid surface in predetermined order such that a row of pixels corresponds to replicates of one distinct probe from the set, the probes being any of SEQ ID NO: 1- SEQ ID NO: 266, inclusive; and

(a) wherein the probes are complementary to nucleic acid sequences expressed differentially in aggressive as compared to non-aggressive types of clear cell renal cell carcinoma (CC-RCC), which nucleic acid sequences hybridized to the probes under stringent conditions.

2. The microarray of claim 1, wherein the set of probes comprises at least 75 probes, which probes have the sequence SEQ ID NO: 1-SEQ ED NO: 75.

3. The microarray of claim 1, wherein the set of probes comprises at least 114 probes, which probes have the sequence SEQ ID NO: 76-SEQ ID NO: 189.

4. The microarray of claim 1, wherein the set of probes comprises at least 50 probes, which probes have the sequence SEQ ED NO: 190- SEQ ID NO: 239.

5. The microarray of claim 1 , wherein the set of probes comprises at least 27 probes, which probes have the sequence SEQ ID NO: 240- SEQ ID NO: 266.

6. The microarray of any of claims 1-5, wherein the one or more probes comprise nucleotides having at least one modified phosphate backbone selected from a phosphorothioate, a phosphoridothioate, a phosphoramidothiate, a phosphoamidate, a phosphordiimidate, a methylsphosphonate, an alkyl phosphotriester, 3'aminoprσpyl, a formacetal, or an analogue thereof.

7. The microarray of claim 1 or 6, wherein each probes comprises at least 15 nucleotides.

8. The microarray of any of claims 1-7, further comprising one or more nucleic acid samples representing expressed genes, each sample from an individual subject's tumor tissue, each sample spotted column-wise on the pixels of the microarray probes.

9. The microarray of claim 8, which has further been subjected to nucleic acid hybridization under stringent conditions such that the nucleic acid samples are hybridized with the immobilized probes on which the samples have been spotted.

10. A composition comprising a set of two or more oligonucleotide or polynucleotide probes each of which specifically hybridize with part of all of a coding sequence that is differentially expressed in an aggressive type of CC-RCC compared to a non-aggressive type of CC-RCC.

11. The composition of claim 10 comprising a set of at least 75 of the probes.

12. The composition of claim 10 comprising a set of at least 114 of the probes.

13. The composition of claim 10 comprising a set of at least 50 of the probes.

14. The composition of claim 10 comprising a set of at least 27 of the probes.

15. The composition of any of claims 10-14, wherein the coding sequence is up- regulated in the aggressive CC-RCC compared to the non-aggressive CC-RCC.

16. The composition of any of claims 10-14, wherein the coding sequence is up- regulated in the non-aggressive CC-RCC compared to the aggressive CC-RCC.

17. The composition of any of claims 10-14, wherein the probes are or mammalian origin.

18. The composition of claim 17 wherein the probes are of human origin.

19. A kit comprising:

(a) the microarray of any of claims 1 -9 ; (b) reagents that facilitate hybridization of the nucleic acid to the immobilized probes; and

(c) a computer readable storage medium comprising logic which enables a processor to read data representing detection of hybridization.

20. The kit of claim 19 wherein the reagents are ones that facilitate detection of fluorescence.

21. A kit comprising:

(a) the composition of any of claims 10-18;

(b) means for carrying out hybridization of the nucleic acid to the probes; and

(c) means for reading hybridization data.

22. The kit of claim 21, wherein the hybridization data is in the form of fluorescence data.

23. The kit of claims 21-22 wherein the probes are immobilized to the microarray.

24. A method of assessing aggressive CC-RCC in a renal tumor tissue sample comprising identifying differential modulation of each gene (relative to the expression of the same genes in a population of non-aggressive renal tumor tissue samples) in a combination of genes selected from the group consisting of SEQ ID NO: 1-SEQ ID NO: 266.

25. The method of claim 24 wherein there is at least a two-fold difference in the expression of the modulated genes.

26. A method of assessing non-aggressive CC-RCC in a renal tumor tissue sample comprising identifying differential modulation of each gene (relative to the expression of the same genes in a population of aggressive renal tumor tissue samples) in a combination of genes selected from the group consisting of SEQ ID NO: 1-SEQ. ID NO: 266.

27. The method of claim 25 wherein there is at least a two-fold difference in the expression of the modulated genes.

28. A prognostic portfolio comprising isolated nucleic acid sequences, their complements, or portions thereof of a combination of genes selected from the group consisting SEQ ID NOS: 1-266.

29. The prognostic portfolio of claim 28, in a matrix suitable for identifying the differential expression of the genes contained therein.

30. The prognostic portfolio of claim 29, wherein said matrix is employed in a microarray.

31. The prognostic portfolio of claim 30, wherein said microarray is a cDNA microarray.

32. A method of evaluating the aggressiveness of CC-RCC in a patient, comprising detecting the level of expression in a renal tumor tissue sample of two or more genes from Table 7; wherein differential expression of the genes in Table 7 indicates whether the CC- RCC is aggressive or non-aggressive.

33. A method of evaluating the aggressiveness of CC-RCC in a patient, comprising detecting the level of expression in a renal tumor tissue sample of two or more genes from Table 8; wherein differential expression of the genes in Table 8 indicates whether the CC- RCC is aggressive or non-aggressive.

34. A method of evaluating the aggressiveness of CC-RCC in a patient, comprising detecting the level of expression in a renal tumor tissue sample of two or more genes from Table 9; wherein differential expression of the genes in Table 9 indicates whether the CC- RCC is aggressive or non-aggressive.

35. A method of evaluating the aggressiveness of CC-RCC in a patient, comprising detecting the level of expression in a renal tumor tissue sample of two or more genes from Table 11; wherein differential expression of the genes in Table 11 indicates whether the CC-RCC is aggressive or non-aggressive. άd. A method of assessing the aggressiveness of CC-RCC, the method comprising the steps of:

(a) providing a biological sample from a patient having CC-RCC;

(b) analyzing the expression of a set of genes selected from the group consisting of alpha-2-macroglobulin angiopoietin 2 aquaporin 1 (channel-forming integral protein, 28kDa)

Rho guanine nucleotide exchange factor (GEF) 17 butyrophilin-like 9 chromosome 14 open reading frame 27 chromosome 20 open reading frame 160 chromosome 20 open reading frame 24 chromobox homolog 7

CD34 antigen cadherin 5, type 2, VE-cadherin (vascular epithelium) brain specific protein collagen, type XXI, alpha 1 chondroitin sulfate proteoglycan 4 (melanoma-associated) cysteine and tyrosine-rich 1 hypothetical protein DKFZp434F0318 endothelin receptor type B endothelial PAS domain protein 1/ hypoxia inducible factor-2 alpha endothelial cell adhesion molecule hypothetical protein FLJ20898 hypothetical protein FLJ39370 fms-related tyrosine kinase 1/ vascular endothelial growth factor receptor 1 precursor forkhead box F1

FYN oncogene related to SRC, FGR, YES guanine nucleotide binding protein (G protein), alpha 11 (Gq class)

G protein-coupled receptor 4 growth factor receptor-bound protein 10 hairy/enhancer-of-split related with YRPW motif 2 insulin receptor integrin, alpha 1 potassium voltage-gated channel, Isk-related family, member 3 kinase insert domain receptor/vascular endothelial growth factor receptor 2 precursor

KIAA1912 protein LIM and senescent cell antigen-like domains 2 insulin receptor tyrosine kinase substrate hypothetical protein MGC20460 similar to 2010300C02Rik protein multimerin 2 non-metastatic cells 1, protein (NM23A)

Notch homolog 4 (Drosophila) ornithine decarboxylase antizyme 2 olfactomedin-like 2A palmdelphin platelet derived growth factor D phosphoinositide-3-kinase, regulatory subunit, polypeptide 3 (p55, gamma) placenta-specific 9 plasmalemma vesicle associated protein phosphatide acid phosphatase type 2A protein tyrosine phosphatase, receptor type, B

RAS guanyl releasing protein 3 (calcium and DAG-regulated) retinol binding protein 7, cellular response gene to complement 32 regulator of G-protein signalling 5 selenoprotein P, plasma, 1

SPARC-like 1 (mastθ, hevin) serine/threonine kinase 6

T-box 2 vascular endothelial growth factor von Willebrand factor

Transcribed sequences

; and

(c) identifying the CC-RCC as aggressive or non-aggressive based on the expression of the set of genes.

37. A composition comprising a set of two or more oligonucleotide or polynucleotide probes each of which specifically hybridizes with part of all of a coding sequence that is differentially expressed in CC-RCC tumors compared to normal kidney tissue, wherein the set includes at least 77 probes.

38. A composition comprising a set of two or more oligonucleotide or polynucleotide probes each of which specifically hybridizes with part of all of a coding sequence that is differentially expressed in CC-RCC tumors compared to normal kidney tissue, wherein the set includes at least 58 probes.

39. A composition comprising a set of two or more oligonucleotide or polynucleotide probes each of which specifically hybridizes with part of all of a coding sequence that is differentially expressed in CC-RCC tumors compared to normal kidney tissue, wherein the set includes at least 83 probes.

40. A composition comprising a set of two or more oligonucleotide or polynucleotide probes each of which specifically hybridizes with part of all of a coding sequence that is differentially expressed in CC-RCC tumors compared to normal kidney tissue, wherein the set includes at least 69 probes.

41. A composition comprising a set of two or more oligonucleotide or polynucleotide probes each of which specifically hybridizes with part of all of a coding sequence that is differentially expressed in CC-RCC tumors compared to normal kidney tissue, wherein the set includes at least 27 probes.

42. A composition comprising a set of two or more oligonucleotide or polynucleotide probes each of which specifically hybridizes with part of all of a coding sequence that is differentially expressed in CC-RCC tumors compared to normal kidney tissue, wherein the set includes at least 314 probes.

43. The composition of any of claims 37-42, wherein the probes are of mammalian origin.

44. The composition of claim 43, wherein the probes are of human origin.

45. A method for early diagnosis of a CC-RCC tumor in a subject prior to physical or radiological evidence of the tumor, comprising the steps of: (a) selecting a protein product of at least one gene the expression of which is up-regulated in a majority of CC-RCC patients, which protein is a secreted protein or is expressed on cell surfaces in a tissue that is readily accessible for assay; and

(b) deterrnining the presence or measuring the quantity of the protein product in a body fluid or a tissue or cell sample from the subject, wherein, an increased level of the protein product compared to

(i) the level in a normal subject's fluid, tissue or cells, or

(ii) another reference normal value is indicative of the presence of a CC-RCC tumor in the subject, and wherein the gene is one that hybridizes with any one or more of SEQ ID NO: 267-343 and SEQ ID NOS: 402-484.

46. A method for diagnosing the recurrence of a CC-RCC tumor in a subject in whom a CC-RCC primary tumor has been excised or otherwise treated, comprising the steps of:

(a) selecting a protein product of at least one gene the expression of which is up-regulated in a majority of CC-RCC patients, which protein is a secreted protein or is expressed on cell surfaces in a tissue that is readily accessible for assay; and

(b) determining the presence or measuring the quantity of the protein product in a body fluid or a tissue or cell sample from the subject, wherein, an increased level of the protein product compared to

(i) the level in a normal subject's fluid, tissue or cells, or (ii) another reference normal value, is indicative of the presence of a recurrent CC-RCC tumor in the subject, and wherein the gene is one that hybridizes with any one or more of SEQ ID NO: 267-

343 and SEQ ID NOS: 402-484.

47. A kit comprising:

(a) the composition of any of claims 37-44;

(b) reagents that facilitate hybridization of the nucleic acid to the immobilized probes; and

(c) a computer readable storage medium comprising logic which enables a processor to read data representing detection of hybridization.

48. The kit of claim 47 wherein the reagents are ones that facilitate detection of fluorescence