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WO2024067848A1 - 血液胞外囊泡miRNA在卵巢癌诊断中的应用 - Google Patents

血液胞外囊泡miRNA在卵巢癌诊断中的应用 Download PDF

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Publication number
WO2024067848A1
WO2024067848A1 PCT/CN2023/122823 CN2023122823W WO2024067848A1 WO 2024067848 A1 WO2024067848 A1 WO 2024067848A1 CN 2023122823 W CN2023122823 W CN 2023122823W WO 2024067848 A1 WO2024067848 A1 WO 2024067848A1
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mir
hsa
mirna
ovarian cancer
benign
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PCT/CN2023/122823
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English (en)
French (fr)
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张大东
张继扬
许晓雅
张付闯
陈灏
陈升
年宝宁
李志宽
杨旻
张亚楠
李雷
梁智勇
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上海思路迪生物医学科技有限公司
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Publication of WO2024067848A1 publication Critical patent/WO2024067848A1/zh

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/112—Disease subtyping, staging or classification
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/178—Oligonucleotides characterized by their use miRNA, siRNA or ncRNA

Definitions

  • the present invention belongs to the field of biomedicine. Specifically, the present invention relates to a combination of blood extracellular vesicle miRNA for diagnosing ovarian cancer and its application.
  • Ovarian cancer is one of the three major malignant tumors of the female reproductive system. Its incidence is relatively low, but its mortality rate ranks first among gynecological tumors. It has become one of the malignant diseases that seriously threaten women's health.
  • the five-year survival rate of patients with early ovarian cancer is 80-95%, while the five-year survival rate of patients with advanced ovarian cancer is only 10-30%.
  • the ovaries are located deep in the pelvic cavity. Due to the lack of specific symptoms in the early stages of ovarian cancer, early lesions are difficult to detect. More than two-thirds of ovarian cancer patients have progressed to the late stage at the time of diagnosis. If it can be detected early, tumor cell reduction surgery and combined chemotherapy mainly based on platinum can be performed, and the 5-year survival rate of ovarian cancer can be increased to 40%-50%. Therefore, early diagnosis of ovarian cancer is crucial to prolonging the survival of patients.
  • the main diagnostic methods for ovarian cancer include imaging examination, tumor marker determination, cytology and histopathology. Since the ovaries are completely intraperitoneal organs, it is impossible to diagnose ovarian cancer without surgery. At present, histopathological biopsy is the gold standard for diagnosing ovarian cancer. Taking tissue samples from suspicious areas and observing them under a microscope is the only way to confirm ovarian cancer. However, puncture biopsy should be avoided for early ovarian tumors because cancer cells can easily spread to the peritoneal cavity and puncture can promote peritoneal metastasis. Therefore, puncture biopsy is suitable for patients who are not suitable for surgery due to advanced cancer or other serious diseases. For patients with abdominal effusion, abdominal effusion can be taken for analysis to see if there are cancer cells in it.
  • the present invention aims to develop an independent liquid biopsy technology that can be used for the diagnosis of ovarian cancer by discovering and verifying a highly accurate serum exosomal miRNA diagnostic biomarker model, so as to make up for the deficiencies of existing imaging examinations, serum tumor marker determination and tissue biopsy in the diagnosis of ovarian cancer, provide the clinic with a low-invasive diagnostic technology, reduce the pain of patients and improve their quality of life.
  • the present invention provides a combination of biomarkers, which can be used to clinically diagnose ovarian cancer, especially to distinguish between benign and malignant ovarian tumors.
  • the present invention also provides a chip and a kit which can be used for clinical diagnosis of ovarian cancer, especially for distinguishing benign and malignant ovarian tumors.
  • the present invention also provides a method for diagnosing ovarian cancer using the biomarker, especially for distinguishing benign and malignant ovarian tumors.
  • the present invention provides a use of blood extracellular vesicle miRNA in preparing a chip, a detection reagent or a detection kit for diagnosing ovarian cancer, wherein the miRNA is
  • miRNAs selected from the group consisting of hsa-miR-1-3p, hsa-miR-1246, hsa-miR-141-3p, hsa-miR-200a-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, hsa-miR-203a-3p, hsa-miR-3679-5p and hsa-miR-429; or
  • the "plurality” is 2, 3, 4, 5, 6, 7, 8 or 9.
  • the diagnosis of ovarian cancer is an early diagnosis of ovarian cancer; preferably, the early diagnosis of ovarian cancer is to distinguish between benign and malignant ovarian tumors.
  • the miRNA is one or more miRNAs selected from the group consisting of hsa-miR-1246, hsa-miR-141-3p, hsa-miR-200a-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, hsa-miR-203a-3p and hsa-miR-429.
  • the "plurality” is 2, 3, 4, 5, 6 or 7.
  • the present invention provides a miRNA chip, wherein the miRNA chip comprises:
  • Oligonucleotide probes are sequentially fixed on the solid phase carrier, and the oligonucleotide probes specifically bind to miRNA;
  • the miRNA is the miRNA described in the first aspect.
  • the oligonucleotide probe comprises:
  • a linker region connected to a solid support.
  • the miRNA chip is used for early diagnosis of ovarian cancer; preferably for distinguishing benign and malignant ovarian tumors.
  • the miRNA is blood extracellular vesicle miRNA.
  • the present invention provides a use of the miRNA chip described in the second aspect for preparing a detection kit for diagnosing ovarian cancer.
  • the diagnosis of ovarian cancer is an early diagnosis of ovarian cancer; preferably, the early diagnosis of ovarian cancer is the differentiation of benign and malignant ovarian tumors.
  • the present invention provides a detection kit, wherein the detection kit contains a detection reagent for detecting miRNA;
  • the miRNA is the miRNA described in the first aspect
  • the detection kit is equipped with the miRNA chip described in the second aspect.
  • the detection kit is used for early diagnosis of ovarian cancer; preferably for distinguishing benign and malignant ovarian tumors.
  • the miRNA is blood extracellular vesicle miRNA.
  • the present invention provides a miRNA isolated from extracellular vesicles of blood for the diagnosis of ovarian cancer:
  • the miRNA is:
  • miRNAs selected from the group consisting of hsa-miR-1-3p, hsa-miR-1246, hsa-miR-141-3p, hsa-miR-200a-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, hsa-miR-203a-3p, hsa-miR-3679-5p and hsa-miR-429; or
  • the "plurality” is 2, 3, 4, 5, 6, 7, 8 or 9.
  • the diagnosis of ovarian cancer is an early diagnosis of ovarian cancer; preferably, the early diagnosis of ovarian cancer is to distinguish between benign and malignant ovarian tumors.
  • the miRNA is one or more miRNAs selected from the group consisting of hsa-miR-1246, hsa-miR-141-3p, hsa-miR-200a-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, hsa-miR-203a-3p and hsa-miR-429.
  • the "plurality” is 2, 3, 4, 5, 6 or 7.
  • the diagnosis of ovarian cancer is an early diagnosis of ovarian cancer; preferably, it is to distinguish between benign and malignant ovarian tumors.
  • the miRNA is blood extracellular vesicle miRNA.
  • the present invention provides a method for diagnosing ovarian cancer, comprising the steps of:
  • the miRNA expression level of the object to be tested is used as a variable, combined with the reference value, and when the risk value is less than or equal to the reference value, the object is judged to be benign, otherwise it is malignant ovarian cancer;
  • the miRNA is:
  • miRNAs selected from the group consisting of miRNAs: hsa-miR-1-3p, hsa-miR-1246, hsa-miR-141-3p, hsa-miR-200a-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, hsa-miR-203a-3p, hsa-miR-3679-5p and hsa-miR-429; or
  • the "plurality” is 2, 3, 4, 5, 6, 7, 8 or 9.
  • the diagnosis of ovarian cancer is an early diagnosis of ovarian cancer; preferably, the ovarian Early diagnosis of ovarian cancer is to distinguish between benign and malignant ovarian tumors.
  • the miRNA is one or more miRNAs selected from the group consisting of hsa-miR-1246, hsa-miR-141-3p, hsa-miR-200a-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, hsa-miR-203a-3p and hsa-miR-429.
  • the "plurality” is 2, 3, 4, 5, 6 or 7.
  • the reference value is 0.2.
  • the diagnosis of ovarian cancer is an early diagnosis of ovarian cancer; preferably, it is to distinguish between benign and malignant ovarian tumors, wherein the control sample is a benign ovarian lesion sample.
  • the miRNA is blood extracellular vesicle miRNA.
  • the present invention provides a miRNA isolated from extracellular vesicles of blood, wherein the miRNA is:
  • miRNAs selected from the group consisting of miRNAs: hsa-miR-1-3p, hsa-miR-1246, hsa-miR-141-3p, hsa-miR-200a-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, hsa-miR-203a-3p, hsa-miR-3679-5p and hsa-miR-429; or
  • the "plurality” is 2, 3, 4, 5, 6, 7, 8 or 9.
  • the miRNA is one or more miRNAs selected from the group consisting of hsa-miR-1246, hsa-miR-141-3p, hsa-miR-200a-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, hsa-miR-203a-3p and hsa-miR-429.
  • the "plurality” is 2, 3, 4, 5, 6 or 7.
  • the present invention provides an isolated or artificially constructed precursor miRNA, wherein the precursor miRNA can be cleaved and expressed into the miRNA in human cells.
  • the present invention provides an isolated polynucleotide, wherein the polynucleotide can be transcribed into a precursor miRNA by a human cell, and the precursor miRNA can be cleaved and expressed into the miRNA in a human cell.
  • the polynucleotide has a structure shown in Formula I: Seq Forward -X-Seq Reverse I
  • Seq forward is a nucleotide sequence that can be expressed as the miRNA in human cells
  • Seq reverse is a nucleotide sequence that is substantially complementary or completely complementary to Seq forward;
  • X is a spacer sequence located between Seq forward and Seq reverse , and the spacer sequence is not complementary to Seq forward and Seq reverse ;
  • Seq forward , Seq reverse and X are defined as above,
  • the present invention provides a vector, wherein the vector contains the miRNA or the polynucleotide.
  • Figure 1 shows the identification results of exosomes by transmission electron microscopy
  • Figure 2 shows the expression of characteristic proteins of exosomes
  • Figure 3 shows the ROC curve for the training cohort
  • Figure 4 shows the ROC curve for the test cohort
  • Figure 5 shows the ROC curves for the validation cohort.
  • Transvaginal ultrasound is quick, economical, non-invasive, and repeatable, and is the preferred method for diagnosing ovarian cancer.
  • CT computed tomography
  • the clinical application of computed tomography (CT) technology has greatly improved the spatial resolution of images. It can clearly show the degree of tumor infiltration into the surrounding area and whether there is pelvic and abdominal metastasis.
  • CT computed tomography
  • Magnetic resonance imaging (MRI) has high soft tissue resolution, can be imaged in multiple planes, and is non-invasive.
  • PET-CT has low sensitivity and specificity for ovarian tumors and is generally not recommended for initial diagnosis. However, its imaging can reflect changes in tumor cell metabolism. When ovarian cancer recurrence is suspected clinically, PET-CT should be used as the preferred imaging examination method.
  • the detection of serum tumor markers has been used in the early diagnosis of ovarian cancer in the clinic.
  • serum markers of ovarian cancer approved by the U.S. Food and Drug Administration (FDA) for clinical use include tumor antigen 125 (CA125) and human epididymis protein 4 (HE4). Both are of high value in the detection of postoperative efficacy of ovarian cancer patients, but lack sufficient sensitivity and specificity for the early diagnosis of ovarian cancer.
  • the present invention uses serum samples from clinical patients and a small RNA sequencing detection method to disclose a liquid biopsy technology for the detection of serum exosome microRNA (miRNA) for ovarian cancer diagnosis.
  • the present invention has made contributions to the field in the following two aspects:
  • Exosomes are a type of small extracellular vesicles (EVs), which are membrane vesicles with a diameter of about 30-150nm. They are derived from vesicles of late endosomes (multivesicular bodies, MVBs). The endosome membrane of the cell is concave inward to form a multivesicular body containing multiple small vesicles. This multivesicular body fuses with the cell membrane and is released into the extracellular matrix. The contents carried by extracellular vesicles include proteins, lipids, mRNA, rRNA, miRNA, etc. Cells can secrete extracellular vesicles under normal and pathological conditions, which can participate in the transmission of information between cells.
  • EVs small extracellular vesicles
  • extracellular vesicles can characterize certain physiological and pathological conditions.
  • diseases such as malignant tumors, immune diseases, etc.
  • free exosomes in peripheral blood have received extensive attention and in-depth research as an important form of liquid biopsy.
  • Other studies have identified differences in blood exosomal miRNAs between healthy people and ovarian cancer patients.
  • next-generation sequencing technology to explore blood exosomal miRNAs as diagnostic biomarkers in ovarian cancer, and no biomarkers that can be used to improve the specificity of early diagnosis of ovarian cancer have been found and verified.
  • the present invention adopts various clinical techniques to comprehensively detect the serum of patients suspected of ovarian cancer as research samples, applies the exosome extraction reagent L3525 independently developed by Shanghai Silidi Biomedical Technology Co., Ltd. to extract serum exosomes, and further uses the second-generation sequencing technology small RNA sequencing to detect the expression of serum exosome miRNA.
  • the serum exosome miRNA biomarker diagnostic model that can be used for the diagnosis of ovarian cancer was discovered, tested and verified in three independent cohorts.
  • ovarian cancer the imaging examinations and laboratory serological tests used in the diagnosis of ovarian cancer in clinical practice have certain limitations and poor accuracy.
  • the only way to confirm ovarian cancer is a histopathological biopsy, but puncture biopsy should be avoided for early ovarian tumors because cancer cells can easily spread to the peritoneal cavity and puncture can promote peritoneal metastasis. It is only suitable for patients with advanced cancer or other serious diseases who are not suitable for surgery.
  • the advantage of the present invention is that it has developed a liquid biopsy technology based on serum exosome miRNA biomarkers that can be used for the diagnosis of ovarian cancer.
  • the technology is non-invasive and avoids the side effects of histopathological biopsy due to sampling.
  • the present invention uses the independently developed extraction reagent L3525 to extract serum exosomes, and further uses small RNA sequencing to detect the expression of serum exosome miRNA, and finally discovers and verifies the highly effective serum exosome miRNA diagnostic biomarker.
  • the present invention proposes and verifies for the first time that serum exosome miRNA can be used as a biomarker for the diagnosis of ovarian cancer, avoiding the risks brought by puncture biopsy.
  • the inventors have discovered a class of blood extracellular vesicle miRNAs, which can be used to diagnose ovarian cancer, especially for early diagnosis of ovarian cancer.
  • the blood extracellular vesicle miRNA of the present invention is:
  • the “plurality” is 2, 3, 4, 5, 6, 7, 8 or 9.
  • next-generation sequencing to identify the expression of blood exosomal miRNAs for diagnostic biomarkers to distinguish between benign and malignant ovarian tumors.
  • the inventors first used small RNA sequencing technology to confirm that the discovered serum exosomal miRNA combination has a good effect in distinguishing benign and malignant ovarian tumors in three independent groups (training group, test group and validation group), and its AUC can reach 0.913 (training group), 0.973 (test group) and 0.924 (validation group).
  • one or more miRNAs selected from the following group are preferably used: hsa-miR-1246, hsa-miR-141-3p, hsa-miR-200a-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, hsa-miR-203a-3p and hsa-miR-429.
  • the "plurality" is 2, 3, 4, 5, 6 or 7.
  • the blood extracellular vesicle miRNA can be used to prepare a chip, a detection reagent or a detection kit for diagnosing ovarian cancer, especially for early diagnosis of ovarian cancer, preferably for distinguishing benign ovarian tumors from malignant tumors.
  • the miRNA chip can include a solid phase carrier; and oligonucleotide probes fixed in order on the solid phase carrier, and the oligonucleotide probes specifically bind to the miRNA.
  • the oligonucleotide probe contains a complementary binding region; and/or a connection region connected to the solid phase carrier.
  • the present invention further provides a detection kit, wherein the detection kit is equipped with a detection reagent for detecting the miRNA, or the detection kit is equipped with the miRNA chip.
  • the present invention selects one of the contents of serum exosomes, miRNA, to identify diagnostic biomarkers and construct an ovarian cancer diagnostic model.
  • contents in exosomes such as proteins, mRNA, LncRNA, etc. These contents can also be used as biomarkers and achieve similar effects as miRNA.
  • components in patient serum such as ctDNA (Circulating tumor DNA), CTC (Circulating tumor cell), protein and other substances. These substances may be found to be diagnostic biomarkers for ovarian cancer and developed into independent liquid biopsy diagnostic technology.
  • the present invention also provides various methods for utilizing the miRNA.
  • the present invention provides a method for diagnosing ovarian cancer, comprising the steps of:
  • the miRNA expression level of the object to be tested is used as a variable, combined with the reference value.
  • the risk value is less than or equal to the reference value, the object is judged to be benign, otherwise it is malignant ovarian cancer.
  • the diagnosis of ovarian cancer is an early diagnosis of ovarian cancer; preferably, it is to distinguish between benign and malignant ovarian tumors.
  • the control sample is a sample of benign ovarian lesions.
  • the reference value is 0.2.
  • the present invention proposes to use serum exosome miRNA combination as a biomarker to establish a high-accuracy diagnostic model to distinguish between benign and malignant ovarian tumors, thereby improving the accuracy of ovarian cancer diagnosis.
  • the present invention uses a variety of benign ovarian disease samples in the real world as control samples.
  • the benign controls have strong heterogeneity, which is different from the healthy population or the mixed samples of healthy population and benign diseases used as controls in the published screening studies.
  • the results obtained by the design adopted by the present invention can better reflect the real-world situation.
  • the present invention uses the exosome (exosome) extraction reagent L3525 independently developed by Shanghai Siludi Biomedical Technology Co., Ltd. to extract serum exosomes and conduct subsequent exosome miRNA detection.
  • the present invention adopted a multivariate logistic regression model statistical analysis method to discover 7 serum exosomal miRNAs, including: hsa-miR-1246, hsa-miR-141-3p, hsa-miR-200a-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, hsa-miR-203a-3p and hsa-miR-429, and constructed a high-accuracy risk prediction model for benign and malignant ovarian tumors.
  • the present invention used data from two other independent cohorts (test group and validation group) to confirm the high accuracy of the risk prediction model of 7 serum exosomal miRNAs.
  • the supernatant was divided into 1 ml tubes and stored in a refrigerator at minus 80 degrees.
  • the serum samples were taken out and placed in a 37°C metal bath for incubation until completely melted, centrifuged at 12000g for 10min at 4°C, and 500 ⁇ l of supernatant was transferred to a 0.45 ⁇ m tube filter (Costar, CLS8163-100EA, Corning, USA), centrifuged at 12000g for 5min at 4°C, and the filtrate was transferred to a 0.22 ⁇ m tube filter (Costar, CLS8161-100EA, USA) at 12000g for 5min at 4°C.
  • the filtrate was transferred to a 1.5ml centrifuge tube and 1/4 volume of L-type exosome precipitant (L3525, 3DMed, Shanghai, China) was added. After mixing, the samples were incubated at 4°C for 30min, centrifuged at 4700g for 30min at 4°C, and the supernatant was discarded and 200 ⁇ l PBS (phosphate buffer saline) was added to suspend the exosome precipitate.
  • L-type exosome precipitant L3525, 3DMed, Shanghai, China
  • the present invention uses transmission electron microscopy to detect the morphology of exosomes, and further uses immunohybridization experiments to detect the expression level of characteristic proteins of exosomes.
  • Identification of exosome morphological characteristics First, the isolated extracellular vesicles are resuspended with PBS, and then 4% paraformaldehyde is added to fix the extracellular vesicles, and then the exosomes are transferred to a carbon-coated 200-mesh electron microscope copper grid.
  • the copper grid is washed twice with PBS, freshly prepared with PBS containing glycine (50mM) and the copper grid is washed for 3min, and freshly prepared with PBS containing 0.5% BSA to wash the copper grid again for 10min, and finally stained with 2% uranyl acetate. After staining, the exosome morphology is characterized by transmission electron microscopy (H-7650, Hitachi High-Technologies, Japan).
  • Exosomes were precipitated with N-type exosome precipitant (N3525, 3DMed, Shanghai, China), and then lysed on ice for 30 min with RIPA lysis buffer (P0013B, Beyotime, Shanghai, China). 4%-20% SDS-PAGE gel (#4561095, Bio-Rad, USA) was used for constant voltage electrophoresis for about 1 h, PVDF membrane (Millipore) was electrophoresed at a constant current for 45 min, and 5% skim milk powder was used for overnight blocking.
  • N-type exosome precipitant N3525, 3DMed, Shanghai, China
  • RIPA lysis buffer P0013B, Beyotime, Shanghai, China
  • SDS-PAGE gel #4561095, Bio-Rad, USA
  • TSG101 (1:1000diluted, ab125011, Abcam, England), CD63 (1:1000diluted, ab216130, Abcam, England), CD9 (1:1000diluted, ab92726, Abcam, England), Alix (1:1000diluted, 2171, Cell Signaling Technology, Danvers, MA, USA), Syntenin (1:1000diluted, ab216130, Abcam, England), The sections were incubated with 24-nitropropene (luted, ab19903, Abcam, England) and calnexin (1:1000diluted, 2679, Cell Signaling Technology, Danvers, MA, USA) antibodies at room temperature for 2 h, washed four times with TBST for 10 min each, incubated with rabbit secondary antibody (A0208, Beyotime) or mouse secondary antibody (A0216, Beyotime) at room temperature for 1 h, washed four times with TBST for 10 min each, and developed with a chemiluminescence system (Tanon-5200 Multi, Shanghai, China).
  • the present invention uses the exosome extraction reagent L3525 independently developed by Shanghai Siludi Biomedical Technology Co., Ltd. to extract serum exosomes.
  • exosome extraction reagent L3525 independently developed by Shanghai Siludi Biomedical Technology Co., Ltd. to extract serum exosomes.
  • those skilled in the art are aware of other alternatives, including but not limited to: a. ultracentrifugation; b. density gradient centrifugation; c. ultrafiltration centrifugation; d. immunomagnetic bead method; e. other commercial exosome extraction reagents.
  • the miRNeasy Serum/Plasma Kit (217184, QIAGEN, Shanghai, China) was used to separate serum exosome miRNA.
  • the specific operation procedures were in accordance with the product manual.
  • the Agilent 2100 analyzer with the corresponding chip 5067-1548, Agilent, USA was used for miRNA quantification and fragment distribution detection.
  • the present invention uses small RNA sequencing to detect the expression level of serum exosomal miRNA.
  • the NEBNext, Multiplex Small RNA Library Prep Set for Illumina (E7300L, NEB, USA) kit is used for library construction, and the specific operation process is in accordance with the product manual.
  • the loading amount of miRNA for each serum sample is 100 ng, and the total volume does not exceed 6 ⁇ l.
  • Connect the 3' adapter hybridize the reverse transcription primer, connect the 5' adapter, reverse transcribe, add Illumina index primers, and amplify PCR for 18 cycles.
  • the present invention uses the second generation sequencing technology - small RNA sequencing to detect the expression of serum exosome miRNA.
  • the second generation sequencing technology small RNA sequencing to detect the expression of serum exosome miRNA.
  • those skilled in the art are aware of other alternatives, including but not limited to: a. Q-PCR detection; b. chip detection; c. other second generation sequencing methods; d. third generation sequencing methods.
  • miRNA annotation The miRNAs were annotated using the Gencode v25 and miRBase v21 databases, and those annotated as known mature miRNAs were retained for subsequent analysis.
  • miRNA filtering For the training cohort, mature miRNAs with a length of less than or equal to 30 nt and at least 2 reads per sample in the training cohort data were retained for subsequent analysis; for the test cohort and validation cohort, miRNAs screened by the training cohort and at least 2 reads per sample in the test cohort and validation cohort data were retained for subsequent analysis.
  • TMM M-values
  • limma-voom methods in the limma analysis package in R language were used to standardize the miRNA expression of the training cohort samples, the test cohort samples, and the validation cohort samples.
  • the tissue type the data in GSE53829 were divided into two groups, 15 normal ovarian tissues and 48 malignant ovarian cancer tissues.
  • the t-test (Student's t test) method in R language was used to analyze the miRNAs with different expression levels between the two groups of data.
  • the miRNAs with a change of more than 2 times between the two groups and a test result P value of less than or equal to 0.05 were selected as candidate molecular markers.
  • a total of 296 candidate molecular markers were used for subsequent analysis.
  • the analysis method used in the present invention - the Least Absolute Shrinkage and Selection Operator (LASSO) Shrinkage and Selectionator operator) model.
  • LASSO Least Absolute Shrinkage and Selection Operator
  • those skilled in the art are aware of other alternatives, including but not limited to: a. linear regression; b. support vector machine; c. Bayesian classifier; d. neural network.
  • Model parameters In the training cohort, seven molecular markers were used as variables, and the 10-fold cross-validation method was repeated 100 times to obtain the model calibration parameters and model coefficients of molecular markers.
  • Risk-Score is the benign or malignant risk prediction value
  • Gi represents the expression value of the i-th miRNA
  • ⁇ i represents the risk scoring model coefficient of the i-th miRNA
  • i 1, 2...n
  • n is the total number of molecular markers predicting benign or malignant
  • ⁇ represents the model correction value.
  • Reference value When the risk value is less than or equal to the reference value, the sample is predicted to be benign; otherwise, it is predicted to be malignant. According to the risk value and pathological test results of each patient in the training cohort, the ROC curve of the training cohort is drawn. Based on the ROC curve results, the reference value is determined while ensuring that the specificity value is greater than 0.5 and the sensitivity value is greater than 0.5.
  • Model performance evaluation Based on the reference value of 0.2, the training cohort samples were divided into a low-risk group (i.e., predicted to be benign lesions) and a high-risk group (i.e., predicted to be malignant tumors). The pathological test results were used as the true value to evaluate the model prediction performance.
  • the model prediction performance evaluation methods include AUC (value range 0-1), specificity (value range 0-1) and sensitivity (value range 0-1). The higher the value, the better the effect.
  • the model's ability to predict benign or malignant tumors was verified based on the risk scoring model and reference values determined in the training cohort. The process is as follows:
  • Model performance verification Based on the reference value of 0.2, the patients in the test cohort and validation cohort were divided into a low-risk group (same as the training cohort) and a high-risk group. The pathological test results were used as the true value to draw the ROC curves of the test cohort and validation cohort to evaluate the predictive performance of the model, including AUC, specificity, and sensitivity. The higher the value, the better the effect.
  • the types of malignant tumor samples include low-grade and high-grade serous carcinomas and mucinous carcinomas.
  • the types of benign tumor samples include ovarian serous cystadenoma, ovarian mucinous cystadenoma, ovarian fallopian tube abscess, endometrial atypical hyperplasia, etc.
  • Table 1 shows the clinical information of patient age and pathological diagnosis. The analysis results showed that there was no significant difference in the age and proportion of benign and malignant patients between the two groups of patients.
  • Table 1 Clinical information of ovarian cancer patients.
  • exosome extraction reagents L3525 and N3525 independently developed by Shanghai Siludi Biomedical Technology Co., Ltd. were used to extract exosomes from the serum of ovarian cancer patients.
  • the morphology of exosomes was detected by transmission electron microscopy, and the expression level of exosome characteristic proteins was further detected by immunoblotting experiments.
  • the transmission electron microscopy results show that the typical "horseshoe-shaped" morphology of exosomes can be seen (see Figure 1).
  • the test results show that the characteristic exosome proteins TSG101, CD63, CD9, Alix and Syntenin are expressed in the representative samples extracted by this patent, and the exosome negative protein Calnexin is not expressed (see Figure 2).
  • small RNA sequencing was used to detect the expression levels of serum exosomal miRNA in patients with benign and malignant ovarian tumors. Based on the expression levels of miRNAs in the training cohort, the samples were grouped according to the pathological test results, and statistical methods were used to discover miRNAs that can be used to distinguish between benign and malignant ovarian tumors as biomarkers.
  • Biomarkers candidate molecular markers, including hsa-miR-1-3p, hsa-miR-1246, hsa-miR-141-3p, hsa-miR-200a-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, hsa-miR-203a-3p, hsa-miR-3679-5p and hsa-miR-429, a total of 9, were used for subsequent analysis. Subsequently, according to the GSE53829qRT-PCR miRNA expression profile data in the NCBI GEO public database.
  • the data in GSE53829 were divided into two groups, and statistical methods were used to discover miRNAs that can be used to distinguish normal ovarian tissue from malignant ovarian cancer tissue as candidate molecular markers.
  • the intersection of the candidate molecular markers in the training cohort and the candidate molecular markers in the GSE53829 dataset was selected as the molecular marker.
  • miRNAs were selected as molecular markers, including hsa-miR-1246, hsa-miR-141-3p, hsa-miR-200a-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, hsa-miR-203a-3p and hsa-miR-429, for the subsequent construction of risk scoring models for benign and malignant ovarian tumors.
  • the miRNA expression data of the training cohort was used, 7 molecular markers were used as variables, based on the multivariate logistic regression model, and combined with the pathological test results, a risk scoring model for benign and malignant ovarian tumors was constructed.
  • the model consists of three parts: parameters, model formulas, and reference values.
  • the 100-fold cross-validation method was repeated 100 times to obtain the model correction parameters and model coefficients of the molecular markers (Table 2) and the risk scoring model formula.
  • the risk scoring model and the expression levels of the 7 molecular markers in each sample the risk value of each sample can be obtained, and the high or low risk value can reflect the benign or malignant nature of the sample.
  • the receiver operating characteristic curve (ROC curve) of the training cohort was drawn ( Figure 3).
  • the reference value was determined to be 0.2 while ensuring that the specificity value was greater than 0.5 and the sensitivity value was greater than 0.5.
  • the pathological test results were taken as the true value to evaluate the model prediction efficiency.
  • the model prediction efficiency evaluation method including AUC (value range 0-1), specificity (value range 0-1) and sensitivity (value range 0-1), was 0.913 ( Figure 3), 92.3% and 87.5% (Table 3), respectively.
  • the results showed that in the training cohort, this risk prediction model had high AUC, specificity and sensitivity, and the model prediction efficiency was better.
  • the model predicts the efficacy of benign and malignant according to the risk score model and reference value determined in the training cohort. Based on the reference value of 0.2, the test cohort and the validation cohort patients were divided into a low-risk group (same as the training cohort) and a high-risk group. In the test cohort, the pathological test results were taken as the true value, and the ROC curve ( Figure 4) was drawn to evaluate the model prediction efficiency, including AUC ( Figure 4), specificity and sensitivity, which were 0.973, 100% and 86.7% (Table 3) respectively.

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Abstract

本发明公开了一个或多个血液胞外囊泡miRNA可以作为卵巢癌的诊断、早期诊断、尤其是区分卵巢肿瘤良恶性的生物标志物，从而能够用于制备卵巢癌的诊断、早期诊断，尤其是区分卵巢肿瘤良恶性的芯片、检测试剂或检测试剂盒。利用所述一个或多个miRNA作为生物标志物能够提高卵巢癌诊断、早期诊断的特异性，降低其假阳性，从而对卵巢病变的良恶性鉴别以及卵巢癌的诊断、早期诊断具有潜在的良好临床应用价值。

Description

血液胞外囊泡miRNA在卵巢癌诊断中的应用 技术领域
本发明属于生物医药领域。具体地说，本发明涉及用于诊断卵巢癌的血液胞外囊泡miRNA的组合及其应用。
背景技术
卵巢癌(ovarian cancer，OC)是女性生殖系统三大恶性肿瘤之一，其发病率相对较低，但病死率位居妇科肿瘤之首，已成为严重威胁女性健康的恶性疾病之一。早期卵巢癌患者五年生存率为80～95％，而晚期卵巢癌患者五年生存率仅为10～30％。卵巢位于盆腔深部，早期阶段的卵巢癌由于缺乏特异性的症状，使得早期病变不易发现，超过2/3的卵巢癌患者在诊断时已进展到晚期。若能早期发现，施以肿瘤细胞减灭术并辅以铂类为主的联合化疗，卵巢癌的5年生存率能提高到40％～50％。因此，早期诊断卵巢癌对延长患者生存期至关重要。
卵巢癌的诊断方法主要有影像学检查，肿瘤标志物测定，细胞学和组织病理学检查。由于卵巢完全是腹膜内器官，不进行手术而诊断出卵巢癌是不可能的。目前，组织病理学活检是确诊卵巢癌的金标准。从可疑区域取组织样本在显微镜下观察，是对卵巢癌进行确诊的唯一方法。但是对于早期卵巢肿瘤应避免穿刺活检，因为癌细胞容易扩散到腹膜腔，穿刺可促进腹膜转移。因而穿刺活检适用于因癌症晚期或者其他严重疾病不适宜进行手术的患者。对于腹部有积液的患者，可以取腹部积液进行分析看其中是否存在癌细胞。目前，卵巢癌的各种检查手段各有利弊，确诊还要结合病史，综合评估。卵巢癌的诊断迫切需要一种低侵入性的诊断生物标志物，以实现对卵巢癌的早期发现和诊断，并探索用于筛查试验的可能性。
发明内容
本发明旨在通过发现和验证高准确性的血清外泌体miRNA诊断生物标志物模型，开发可以用于卵巢癌诊断的独立液体活检技术，以弥补现有影像学检查，血清肿瘤标志物测定和组织活检在卵巢癌诊断上的不足，为临床提供侵入性低的诊断技术，减少患者的痛苦，提高患者的生活质量。
为此，本发明提供了一种生物标志物的组合，这种组合能够在临床上诊断卵巢癌，尤其是区分卵巢肿瘤良恶性。
本发明还提供了能够在临床上诊断卵巢癌，尤其是区分卵巢肿瘤良恶性的芯片和试剂盒。
本发明还提供了利用所述生物标志物来诊断卵巢癌，尤其是区分卵巢肿瘤良恶性的方法。
在第一方面，本发明提供血液胞外囊泡miRNA在制备用于诊断卵巢癌的芯片、检测试剂或检测试剂盒中的用途，其中所述miRNA是
(i)选自下组的一个或多个miRNA：hsa-miR-1-3p、hsa-miR-1246、hsa-miR-141-3p、hsa-miR-200a-3p、hsa-miR-200b-3p、hsa-miR-200c-3p、hsa-miR-203a-3p、hsa-miR-3679-5p和hsa-miR-429；或者
(ii)与(i)所述miRNA序列互补的miRNA。
在优选的实施方式中，所述“多个”是2个、3个、4个、5个、6个、7个、8个或9个。
在具体的实施方式中，所述的诊断卵巢癌是卵巢癌的早期诊断；优选地，所述卵巢癌的早期诊断是区分卵巢肿瘤良恶性。
在具体的实施方式中，所述miRNA是选自下组的一个或多个miRNA：hsa-miR-1246、hsa-miR-141-3p、hsa-miR-200a-3p、hsa-miR-200b-3p、hsa-miR-200c-3p、hsa-miR-203a-3p和hsa-miR-429。
在优选的实施方式中，所述“多个”是2个、3个、4个、5个、6个或7个。
在第二方面，本发明提供一种miRNA芯片，所述的miRNA芯片包括：
固相载体；以及
有序固定在所述固相载体上的寡核苷酸探针，所述的寡核苷酸探针特异性地结合miRNA；
其中，所述的miRNA是第一方面所述的miRNA。
在具体的实施方式中，所述的寡核苷酸探针含有：
互补结合区；和/或
与固相载体相连的连接区。
在具体的实施方式中，所述miRNA芯片用于卵巢癌的早期诊断；优选区分卵巢肿瘤良恶性。
在优选的实施方式中，所述的miRNA是血液胞外囊泡miRNA。
在第三方面，本发明提供第二方面所述的miRNA芯片的用途，用于制备诊断卵巢癌的检测试剂盒。
在具体的实施方式中，所述诊断卵巢癌是卵巢癌的早期诊断；优选地，所述卵巢癌的早期诊断是区分卵巢肿瘤良恶性。
在第四方面，本发明提供一种检测试剂盒，所述的检测试剂盒装有检测miRNA的检测试剂；
其中，所述的miRNA是第一方面所述的miRNA；
或者，所述检测试剂盒装有第二方面所述的miRNA芯片。
在具体的实施方式中，所述检测试剂盒用于卵巢癌的早期诊断；优选用于区分卵巢肿瘤良恶性。
在优选的实施方式中，所述的miRNA是血液胞外囊泡miRNA。
在第五方面，本发明提供一种分离自血液胞外囊泡的miRNA，用于卵巢癌的诊断：
其中，所述的miRNA是：
(i)选自下组的一个或多个miRNA：hsa-miR-1-3p、hsa-miR-1246、hsa-miR-141-3p、hsa-miR-200a-3p、hsa-miR-200b-3p、hsa-miR-200c-3p、hsa-miR-203a-3p、hsa-miR-3679-5p和hsa-miR-429；或者
(ii)与(i)所述miRNA序列互补的miRNA。
在优选的实施方式中，所述“多个”是2个、3个、4个、5个、6个、7个、8个或9个。
在优选的实施方式中，所述的诊断卵巢癌是卵巢癌的早期诊断；优选地，所述卵巢癌的早期诊断是区分卵巢肿瘤良恶性。
在优选的实施方式中，所述miRNA是选自下组的一个或多个miRNA：hsa-miR-1246、hsa-miR-141-3p、hsa-miR-200a-3p、hsa-miR-200b-3p、hsa-miR-200c-3p、hsa-miR-203a-3p和hsa-miR-429。
在优选的实施方式中，所述“多个”是2个、3个、4个、5个、6个或7个。
在优选的实施方式中，所述的卵巢癌的诊断是卵巢癌的早期诊断；优选是区分卵巢良性肿瘤和恶性肿瘤。
在优选的实施方式中，所述的miRNA是血液胞外囊泡miRNA。
在第六方面，本发明提供一种卵巢癌的诊断的方法，包括步骤：
(a)根据训练队列miRNA表达量数据，结合病理检测结果，构建良/恶性分类模型；
(b)以待测对象miRNA表达量为变量，结合参比值，当风险值小于或等于参比值时则判定该对象为良性，否则为恶性卵巢癌；
所述的miRNA是：
(i)选自下组的一个或多个miRNA：miRNA：hsa-miR-1-3p、hsa-miR-1246、hsa-miR-141-3p、hsa-miR-200a-3p、hsa-miR-200b-3p、hsa-miR-200c-3p、hsa-miR-203a-3p、hsa-miR-3679-5p和hsa-miR-429；或者
(ii)与(i)所述miRNA序列互补的miRNA。
在优选的实施方式中，所述“多个”是2个、3个、4个、5个、6个、7个、8个或9个。
在优选的实施方式中，所述的诊断卵巢癌是卵巢癌的早期诊断；优选地，所述卵 巢癌的早期诊断是区分卵巢肿瘤良恶性。
在优选的实施方式中，所述miRNA是选自下组的一个或多个miRNA：hsa-miR-1246、hsa-miR-141-3p、hsa-miR-200a-3p、hsa-miR-200b-3p、hsa-miR-200c-3p、hsa-miR-203a-3p和hsa-miR-429。
在优选的实施方式中，所述“多个”是2个、3个、4个、5个、6个或7个。
在优选的实施方式中，所述参比值为0.2。
在优选的实施方式中，所述的卵巢癌的诊断是卵巢癌的早期诊断；优选是区分卵巢肿瘤良恶性，其中，所述对照样本是卵巢良性病变样本。
在优选的实施方式中，所述的miRNA是血液胞外囊泡miRNA。
在第七方面，本发明提供一种分离自血液胞外囊泡的miRNA，所述的miRNA是：
(i)选自下组的一个或多个miRNA：miRNA：hsa-miR-1-3p、hsa-miR-1246、hsa-miR-141-3p、hsa-miR-200a-3p、hsa-miR-200b-3p、hsa-miR-200c-3p、hsa-miR-203a-3p、hsa-miR-3679-5p和hsa-miR-429；或者
(ii)与(i)所述miRNA序列互补的miRNA。
在优选的实施方式中，所述“多个”是2个、3个、4个、5个、6个、7个、8个或9个。
在优选的实施方式中，所述miRNA是选自下组的一个或多个miRNA：hsa-miR-1246、hsa-miR-141-3p、hsa-miR-200a-3p、hsa-miR-200b-3p、hsa-miR-200c-3p、hsa-miR-203a-3p和hsa-miR-429。
在优选的实施方式中，所述“多个”是2个、3个、4个、5个、6个或7个。
在第八方面，本发明提供一种分离的或人工构建的前体miRNA，所述的前体miRNA能在人细胞内剪切并表达成所述的miRNA。
在第九方面，本发明提供一种分离的多核苷酸，所述的多核苷酸能被人细胞转录成前体miRNA，所述的前体miRNA能在人细胞内被剪切且表达成所述的miRNA。
在优选的实施方式中，所述的多核苷酸具有式I所示的结构：
Seq正向-X-Seq反向  式I
式I中，
Seq正向为能在人细胞中表达成所述的miRNA的核苷酸序列；
Seq反向为与Seq正向基本上互补或完全互补的核苷酸序列；
X为位于Seq正向和Seq反向之间的间隔序列，并且所述间隔序列与Seq正向和Seq反 向不互补；
式I所示的结构在转入人细胞后，形成式II所示的二级结构：
式II中，Seq正向、Seq反向和X的定义如上述，
||表示在Seq正向和Seq反向之间形成的碱基互补配对关系。
在第十方面，本发明提供一种载体，所述载体含有所述的miRNA或所述的多核苷酸。
应理解，在本发明范围内中，本发明的上述各技术特征和在下文(如实施例)中具体描述的各技术特征之间都可以互相组合，从而构成新的或优选的技术方案。限于篇幅，在此不再一一累述。
附图说明
图1显示了外泌体透射电镜的鉴定结果；
图2显示了外泌体特征性蛋白的表达情况；
图3显示了训练队列的ROC曲线；
图4显示了测试队列的ROC曲线；
图5显示了验证队列的ROC曲线。
具体实施方式
经阴道超声检查(TVS)快捷、经济、无创、可重复，是卵巢癌诊断的首选检查方法。但较小的卵巢肿块的形态、内部结构以及与周围组织的关系往往显示不清，不易测出直径＜1cm的实性肿瘤。电子计算机断层扫描(CT)技术的临床应用，使得图像的空间分辨率大大提高。可清楚显示肿瘤向周围的浸润程度以及有无盆、腹腔转移。但卵巢原发性肿瘤和转移瘤在CT上的表现无显著差异。磁共振成像(MRI)软组织分辨率高，能够多平面成像，无创。但MRI的成本也较CT高，有宫内节育器的患者，也要取出后才能做MRI。PET-CT对卵巢肿瘤的敏感度和特异性均不高，一般不推荐用于初次诊断。但其显像能够反映肿瘤细胞代谢变化，临床怀疑卵巢癌复发时，PET-CT应作为首选影像学检查方法。
血清肿瘤标志物的检测已被应用于临床上卵巢癌早期诊断，目前美国食品药品监督管理局(Food and Drug Administration,FDA)批准的可用于临床的卵巢癌血清标志物包括肿瘤抗原125(Cancer antigen 125,CA125)和人附睾蛋白4(Humanepididymis protein 4,HE4)。两者在卵巢癌患者术后疗效检测方面具有很高的价值,但用于卵巢癌的早期诊断缺乏足够的敏感性和特异性。
对此，本发明采用临床患者来源的血清样本和small RNA sequencing检测方法，公开了用于卵巢癌诊断的血清外泌体microRNA(miRNA)检测的液体活检技术。具体地说，本发明在如下两部分为本领域作出了贡献：
(1)研究卵巢癌诊断的血清外泌体miRNA生物标志物及其组合，并构建高准确性的诊断模型；
(2)进一步验证所发现的诊断模型的诊断效果。
通过(1)、(2)发现并验证可用于卵巢癌诊断的基于血清外泌体miRNA生物标志物组合的液体活检技术。
定义
本文所用的科学和技术术语与本领域技术人员常规理解的一致。为便于理解本发明，现对相关术语解释和定义如下：
外泌体是一类小型胞外囊泡(Extracellular vesicles,EVs)，其直径约30-150nm的膜性囊泡。它来源于晚期内吞体(multivesicular bodies,MVB)的囊泡，是细胞内吞泡膜向内凹陷形成含有多个小囊泡的多囊泡体，这种多囊泡体与细胞膜融合，释放到细胞外基质中。胞外囊泡运载的内容物有蛋白质、脂质、mRNA、rRNA、miRNA等。细胞在正常和病理条件下都能分泌胞外囊泡，其可参与细胞间的信息传递。
胞外囊泡的内容物能够表征一定的生理、病理状况。在多种疾病(如恶性肿瘤、免疫性疾病等)中，外周血中游离的外泌体作为一种重要的液体活检形式已得到广泛的关注和深入研究。另有研究鉴定了血液外泌体miRNA在健康人群和卵巢癌患者存在差异。然而，基于二代测序技术探索血液外泌体miRNA作为诊断生物标志物在卵巢癌中的研究较少，也没有发现并验证可用于提高卵巢癌早诊特异性的生物标志物。
本发明采用临床中各种技术综合检测疑似为卵巢癌的患者的血清作为研究样本，应用上海思路迪生物医学科技有限公司自主研发的外泌体提取试剂L3525抽提血清外泌体，进一步采用二代测序技术small RNA sequencing检测血清外泌体miRNA的表达，在三个独立的队列中发现、测试并验证可用于卵巢癌诊断的血清外泌体miRNA生物标志物诊断模型。
本发明的血液胞外囊泡miRNA
目前，临床上应用于卵巢癌诊断的影像学检查和实验室血清学检测都有一定的局限性，准确性差。对卵巢癌进行确诊的唯一方法是组织病理学活检，但是对于早期卵巢肿瘤应避免穿刺活检，因为癌细胞容易扩散到腹膜腔，穿刺可促进腹膜转移，只适用于癌症晚期或者其他严重疾病不适宜进行手术的患者。
本发明的优点就在于开发了可用于卵巢癌诊断的基于血清外泌体miRNA生物标志物的液体活检技术，特点是无创，避免了组织病理学活检因取样而产生的副作用。
现有技术中，关于卵巢癌诊断生物标志物的研究存在如下缺点：a.真正聚焦良、恶性卵巢肿瘤鉴别诊断的研究数量稀少；b.基于二代测序平台的研究数量较少；c.外泌体内容物作为诊断生物标志物且经过另两组数据验证的研究稀少；d.未见到诊断 准确性高的液体活检技术。
针对目前研究的不足，本发明采用自主研发的提取试剂L3525抽提血清外泌体，进一步利用small RNA sequencing检测血清外泌体miRNA的表达，最终发现和验证了效能高的血清外泌体miRNA诊断生物标志物。本发明首次提出并验证了血清外泌体miRNA作为生物标志物可用于卵巢癌的诊断，避免穿刺活检带来的风险。
具体地说，本发明人发现了一类血液胞外囊泡miRNA，所述血液胞外囊泡miRNA能够用于诊断卵巢癌，尤其是用于卵巢癌的早期诊断。在具体的实施方式中，本发明的血液胞外囊泡miRNA是：
(i)选自下组的一个或多个miRNA：hsa-miR-1-3p
(UGGAAUGUAAAGAAGUAUGUAU；SEQ ID NO:1)、hsa-miR-1246
(AAUGGAUUUUUGGAGCAGG；SEQ ID NO:2)、hsa-miR-141-3p
(UAACACUGUCUGGUAAAGAUGG；SEQ ID NO:3)、hsa-miR-200a-3p
(UAACACUGUCUGGUAACGAUGU；SEQ ID NO:4)、hsa-miR-200b-3p
(UAAUACUGCCUGGUAAUGAUGA；SEQ ID NO:5)、hsa-miR-200c-3p
(UAAUACUGCCGGGUAAUGAUGGA；SEQ ID NO:6)、hsa-miR-203a-3p
(GUGAAAUGUUUAGGACCACUAG；SEQ ID NO:7)、hsa-miR-3679-5p
(UGAGGAUAUGGCAGGGAAGGGGA；SEQ ID NO:8)和hsa-miR-429
(UAAUACUGUCUGGUAAAACCGU；SEQ ID NO:9)；或者
(ii)与(i)所述miRNA序列互补的miRNA。
在一优选例中，所述“多个”是2个、3个、4个、5个、6个、7个、8个或9个。
目前，尚未见基于二代测序鉴定血液外泌体miRNA的表达用于区分良、恶性卵巢肿瘤的诊断生物标志物的研究报道。本发明人首次采用small RNA sequecning技术在三组独立人群(训练组、测试组和验证组)中确认了发现的血清外泌体miRNA组合在区分良性和恶性卵巢肿瘤具有较好的效果，其AUC可达到0.913(训练组)、0.973(测试组)和0.924(验证组)。在具体的实施方式中，为区分卵巢肿瘤的良恶性，优选利用选自下组的一个或多个miRNA：hsa-miR-1246、hsa-miR-141-3p、hsa-miR-200a-3p、hsa-miR-200b-3p、hsa-miR-200c-3p、hsa-miR-203a-3p和hsa-miR-429。在优选的实施方式中，所述“多个”是2个、3个、4个、5个、6个或7个。
在进一步的实施方式中，可以利用所述血液胞外囊泡miRNA制备芯片、检测试剂或检测试剂盒以便诊断卵巢癌，尤其是早期诊断卵巢癌，优选是区分卵巢良性肿瘤和恶性肿瘤。例如，所述的miRNA芯片可以包括固相载体；以及有序固定在所述固相载体上的寡核苷酸探针，所述的寡核苷酸探针特异性地结合所述miRNA。在优选的实施方式中，所述的寡核苷酸探针含有互补结合区；和/或，与固相载体相连的连接区。
在具体的实施方式中，本发明还提供一种检测试剂盒，所述的检测试剂盒装有检测所述miRNA的检测试剂，或者，所述检测试剂盒装有所述的miRNA芯片。
本发明选取血清外泌体其中的一个内容物miRNA进行诊断生物标志物的鉴定并构建卵巢癌诊断模型。然而，外泌体的内容还有许多，如蛋白质、mRNA、LncRNA等，这些内容物也可以作为生物标志物并达到与miRNA类似的效果。除此之外，患者血清中还多种成分，如ctDNA(Circulating tumor DNA)、CTC(Circulating tumor cell)、蛋白等物质，这些物质都有可能被发现成为卵巢癌的诊断生物标志物，并开发成独立的液体活检诊断技术。
本发明的方法
基于本发明的血液胞外囊泡miRNA，本发明还提供了利用该miRNA的各种方法。
例如，利用所述miRNA，本发明提供了一种卵巢癌的诊断的方法，包括步骤：
(a)根据训练队列miRNA表达量数据，结合病理检测结果，构建良/恶性分类模型；
(b)以待测对象miRNA表达量为变量，结合参比值，当风险值小于或等于参比值时则判定该对象为良性，否则为恶性卵巢癌。
在优选的实施方式中，所述的诊断卵巢癌是卵巢癌的早期诊断；优选地是区分卵巢肿瘤良恶性。在区分卵巢肿瘤良恶性时，所述对照样本是卵巢良性病变样本。
在优选的实施方式中，所述参比值为0.2。
本发明的优点：
(1)本发明提出采用血清外泌体miRNA组合作为生物标志物建立高准确性诊断模型来区分良、恶性卵巢肿瘤，从而提高卵巢癌诊断的准确性。
(2)本发明采用真实世界中多种良性卵巢疾病样本作为对照样本，良性对照异质性强，不同于已发表的筛查研究所采用的健康人群或者健康人群和良性疾病混合的样本作为对照，本发明所采取的设计所得到的结果更能反映真实世界情况。
(3)本发明应用上海思路迪生物医学科技有限公司自主研发的外泌体(外泌体)提取试剂L3525抽提血清外泌体，并进行后续外泌体miRNA检测。
(4)本发明采用多元logistic回归模型(multivariate logistic regression model)统计分析方法发现了7个血清外泌体miRNAs，包括：hsa-miR-1246、hsa-miR-141-3p、hsa-miR-200a-3p、hsa-miR-200b-3p、hsa-miR-200c-3p、hsa-miR-203a-3p和hsa-miR-429，构建了具有高准确性的良、恶性卵巢肿瘤风险预测模型。
(5)本发明使用另两个独立队列(测试组和验证组)数据确认了7个血清外泌体miRNAs的风险预测模型的高准确性。
下面结合具体实施例，进一步阐述本发明。应理解，这些实施例仅用于说明本发明而不用于限制本发明的范围。下列实施例中未注明具体条件的实验方法，通常按照 常规条件，例如Sambrook等人，分子克隆：实验室手册(Cold Spring Harbor Laboratory Press，2001)中所述的条件，或按照制造厂商所建议的条件。除非另外说明，否则百分比和份数按重量计算。
实施例
材料
以下实施例中利用的材料均属于可商品化购得的。
方法
1.研究队列及临床信息
本研究共纳入三个研究队列共计79例经影像学(如超声检查、腹盆腔CT扫描等)、肿瘤标志物(如CA125、HE4等)、细胞学和组织病理学检查等检测结果为疑似卵巢癌的患者，于术前采集患者的血液样本。每个入组的患者于术后根据病理检查结果给出准确的诊断。
2.血清外泌体的提取和特征鉴定
1)血液收集和血清外泌体的提取
本研究所有的良性和恶性卵巢肿瘤患者血液样本在手术或药物治疗前采集到5ml红盖的真空采血管中(REF367814,BD,USA)，缓慢柔和地上下翻转几次，室温竖直静置1-2小时，待血块凝固收缩后，先常温低速离心，2000g，10min；取离心后判断血样溶血等级，小于4级的样本进行下一步处理。转移上清液到1.5ml离心管中再次离心，8000g，4度，10min。分装上清液每管1ml保存在负80度冰箱。取出血清样本置于37℃金属浴孵育至完全融化，12000g，4℃离心10min，转移500μl上清液到0.45μm tube filter(Costar,CLS8163-100EA,Corning,USA)，12000g，4℃离心5min，转移过滤液到0.22μm tube filter(Costar,CLS8161-100EA,USA)12000g，4℃离心5min。转移过滤液到1.5ml离心管中并加入1/4体积的L型外泌体沉淀剂(L3525,3DMed,Shanghai,China)，混匀后4℃孵育30min，4700g，4℃离心30min，弃上清液加入200μl PBS(phosphate buffer saline)悬浮外泌体沉淀。
2)血清外泌体的特征鉴定
为了检测良性和恶性卵巢肿瘤患者血清外泌体的特征，本发明采用透射电镜检测外泌体形态，进一步利用免疫杂交实验检测外泌体特征蛋白的表达水平。外泌体形态特征鉴定：首先将分离得到的胞外囊泡用PBS重悬，然后加入4％多聚甲醛对胞外囊泡进行固定，之后转移外泌体到碳包覆的200目电子显微镜铜网上。其次用PBS清洗铜网2次，新鲜配置含甘氨酸(50mM)的PBS并清洗铜网3min，新鲜配置含0.5％BSA的PBS再次清洗铜网10min，最后用2％醋酸铀酰对铜网进行染色，染色完成后采用透射电镜(H-7650,Hitachi High-Technologies,Japan)对外泌体形态进行特征分析。
外泌体特征蛋白检测：外泌体用N型外泌体沉淀剂(N3525,3DMed,Shanghai,China)沉淀，然后用RIPA裂解液(P0013B,Beyotime,Shanghai,China)冰上裂解30min。用4％-20％SDS-PAGE gel(#4561095,Bio-Rad,USA)恒压电泳1h左右，PVDF膜(Millipore)恒流电转45min，5％脱脂奶粉过夜封闭。一抗信息：TSG101(1:1000diluted,ab125011,Abcam,England)、CD63(1:1000diluted,ab216130,Abcam,England)、CD9(1:1000diluted,ab92726,Abcam,England)、Alix(1:1000diluted,2171,Cell Signaling Technology,Danvers,MA,USA)、Syntenin(1:1000diluted,ab19903,Abcam,England)和Calnexin(1:1000diluted,2679,Cell Signaling Technology,Danvers,MA,USA)抗体室温孵育2h，TBST洗四次每次10min，兔源二抗(A0208,碧云天)或鼠源二抗(A0216,碧云天)室温孵育1h，TBST洗四次每次10min，用化学发光系统显影(Tanon-5200Multi,Shanghai,China)。
本发明采用上海思路迪生物医学科技有限公司自主研发的外泌体提取试剂L3525抽提血清外泌体。然而，本领域技术人员知晓其它替代方案，包括但不限于：a.超速离心法；b.密度梯度离心法；c.超滤离心法；d.免疫磁珠法；e.其他商品化外泌体的提取试剂。
3.外泌体miRNA抽提和表达量检测
1)血清外泌体miRNA抽提
血清外泌体miRNA的分离选用miRNeasy Serum/Plasma Kit(217184,QIAGEN,Shanghai,China)，具体的操作流程依照产品说明书。用安捷伦2100分析仪配套相应的芯片(5067-1548,Agilent,USA)进行miRNA定量和片段分布检测。
2)血清外泌体的表达检测
本发明采用small RNA sequencing检测血清外泌体miRNA的表达水平。文库的构建选用NEBNext,Multiplex Small RNA Library Prep Set for Illumina(E7300L,NEB,USA)试剂盒，具体的操作流程依照产品说明书。每个血清样本miRNA上样量为100ng总体积不超过6μl，连接3’接头、杂交反转录引物、连接5’接头、反转录、加入Illumina index primers标记PCR扩增18个循环。选用NucleoSpin Gel and PCR Clean-up(740609.50,MACHEREY-NAGEL,Germany)试剂盒纯化PCR产物，用30μl NE缓冲液洗脱DNA。用GX TouchTM HT核酸分析仪及配套的芯片(CLS138948,PerkinElmer,USA)和试剂(CLS760672,PerkinElmer,USA)对DNA定量和片段分布的检测。一般20-25个文库等摩尔比混合包lane测序，选用Illumina HiSeq PE150analyzer测序。
本发明利用二代测序技术-small RNA sequencing检测血清外泌体miRNA的表达。然而，本领域技术人员知晓其它替代方案，包括但不限于：a.Q-PCR检测；b.芯片检测；c.其他二代测序方法；d.三代测序方法。
4.测序数据分析流程
基于small RNA sequencing检测技术，获得患者血清外泌体中miRNA的表达量。测序数据的分析流程如下：
1)测序数据比对。去除small RNA sequencing数据测序接头后，使用BWA软件(版本：0.7.12-r1039)将测序数据比对到人类参考基因组hg19(基因组下载链接：http://hgdownload.soe.ucsc.edu/goldenPath/hg19/bigZips/)，并统计比对到miRNA上的reads数量。
2)miRNA注释。利用Gencode v25和miRBase v21数据库对miRNA进行注释，保留注释为已知的成熟miRNA，用于后续分析。
3)miRNA过滤。对于训练队列，保留长度小于等于30nt且在训练队列数据中的每个样本至少覆盖2条reads的成熟miRNA，用于后续分析；对于测试队列和验证队列，保留由训练队列筛选所得的miRNA且在测试队列和验证队列数据中的每个样本至少覆盖2条reads的成熟miRNA，用于后续分析。
4)miRNA表达量标准化。使用R语言中limma分析包中的M值加权截尾均值方法(TMM，trimmed mean of M-values)及limma-voom方法分别对训练队列样本、测试队列和验证队列样本进行miRNA表达量标准化处理。
5.生物标记物的发掘
基于训练队列中miRNAs的表达量，根据病理检测结果对样本进行分组，使用统计学方法发掘可用于区分良、恶性卵巢肿瘤的miRNA作为生物标志物。过程如下：
1)训练队列分组。依据病理检测结果，将训练队列中患者分为两组，良性肿瘤患者组和恶性肿瘤患者组。
2)候选分子标记物。在训练队列中，使用R语言limma分析包中拟合线性模型(limma-voom)方法分析良恶性两组患者表达量存在差异的miRNA，表达量大于等于4、两组间变化量在2倍以上且检验结果P值小于等于0.05的miRNA，作为候选分子标记物。随后，搜索并下载NCBI GEO公共数据库中GSE53829(下载链接：https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi？acc＝GSE53829)全基因组实时定量聚合酶链反应(qRT-PCR，quantitative real-time polymerase chain reaction)miRNA表达谱数据。依据组织类型，将GSE53829中数据分为两组，15例正常卵巢组织和48例恶性卵巢癌组织数据组。使用R语言中的t检验(Student's t test)方法分析两组数据表达量存在差异的miRNA，两组间变化量在2倍以上且检验结果P值小于等于0.05的miRNA，作为候选分子标记物。候选分子标记物共计296个，用于后续分析。
3)分子标记物。选取训练队列中的候选分子标记物与GSE53829数据集中的候选分子标记物的交集，做为分子标记物。最终选定7个miRNA作为分子标记物用于后续构建良、恶性卵巢肿瘤风险评分模型。
本发明采用的分析方法-最小绝对收缩和选择算子(LASSO，The Least Absolute  Shrinkage and Selectionator operator)模型。然而，本领域技术人员知晓其它替代方案，包括但不限于：a.线性回归；b.支持向量机；c.贝叶斯分类器；d.神经网络。
6.卵巢肿瘤良、恶性风险评分模型
利用训练队列miRNA表达量数据，以7个分子标记物为变量，基于多元logistic回归模型(multivariate logistic regression model)，结合病理检测结果，构建良、恶性卵巢肿瘤风险评分模型。模型由参数、模型公式和参比值三部分组成。过程如下：
1)模型参数。在训练队列中，以7个分子标记物为变量，使用100次重复10折交叉验证法，获得模型校正参数及分子标记物的模型系数。
2)风险评分模型。风险评分模型公式如下:
Risk-Score＝∑Gi*βi+α
其中，Risk-Score是良恶性风险预测值，Gi代表第i位miRNA的表达值，βi代表第i位miRNA的风险评分模型系数，i＝1，2…n，n为预测良恶性分子标记物的总数，α代表模型校正值。使用风险评分模型和每个样本中7个分子标记物的表达量，可以获得每个样本的风险值，风险值的高低可以反映样本的良恶性。
3)参比值。当风险值小于或等于参比值时，该样本被预测为良性；否则预测为恶性。根据训练队列中每个病人的风险值及病理检测结果，绘制训练队列的ROC曲线。依据ROC曲线结果，在保证特异性取值大于0.5及敏感性取值大于0.5的情况下，确定参比值。
4)模型效能评估。以参比值0.2为准，将训练队列样本分为低风险组(即被预测为良性病变)和高风险组(即被预测为恶性肿瘤)。以病理检测结果为真值，评估模型预测效能。模型预测效能评估方法，包括AUC(取值范围0～1)、特异性(取值范围0～1)和敏感性(取值范围0～1)，值越高效果越优。
7.风险评分模型预测效能的测试和验证
在测试队列和验证队列中，根据训练队列中确定的风险评分模型及参比值，对模型预测良恶性的效能进行验证。过程如下：
1)风险值。在测试队列和验证队列中，计算每个样本的风险值。
2)模型效能验证。以参比值0.2为准，分别将测试队列和验证队列患者分为低风险组(同训练队列)和高风险组。以病理检测结果为真值，绘制测试队列和验证队ROC曲线，评估模型预测效能，包括AUC、特异性和敏感性，值越高效果越优。
8.卵巢肿瘤良、恶性风险评分模型的应用
1)采集临床诊断结果疑似为卵巢癌患者的外周血，获得外周血外泌体，使用small RNA sequencing获得生物标志物的表达；
2)使用风险评分模型，获得每一位患者的风险值；
3)将风险值与模型参比值比较，给出每一位患者罹患卵巢癌风险的预测结果。
实施例1.
本实施例共招募了三个研究队列。具体研究队列及临床信息如下所述：
训练队列患者29例，包括13例良性肿瘤患者和16例恶性肿瘤患者(表1)。测试队列患者20例，包括5例良性肿瘤患者和15例恶性肿瘤患者(表1)。验证队列患者30例，包括15例良性肿瘤患者和15例恶性肿瘤患者(表1)。恶性肿瘤样本的种类有低级别、高级别浆液性癌和黏液性癌等。良性肿瘤样本的种类有卵巢浆液性囊腺瘤、卵巢粘液性囊腺瘤、卵巢输卵管脓肿、子宫内膜不典型增生等。表1展示了患者年龄和病理诊断的临床信息。分析结果表明两组患者间的年龄和良、恶性患者比例并无显著差异。
表1.卵巢癌患者临床信息。
实施例2.血清外泌体的提取及其特征鉴定
在本实施例中，应用上海思路迪生物医学科技有限公司自主研发的，外泌体提取试剂L3525和N3525抽提卵巢癌患者血清中的外泌体。为了检测良性与恶性卵巢肿瘤患者血清外泌体的特征，采用透射电镜检测外泌体的形态，进一步利用免疫杂交实验检测外泌体特征蛋白的表达水平。透射电镜检测结果可见到外泌体典型的“马蹄状”形态(见图1)。检测结果表明本专利提取的代表性样本中外泌体特征性蛋白TSG101、CD63、CD9、Alix和Syntenin均有表达，而且外泌体阴性蛋白Calnexin没有表达(见图2)。
实施例3.生物标记物的发掘
在本实施例中，采用small RNA sequencing检测良性与恶性卵巢肿瘤患者血清外泌体miRNA的表达水平。基于训练队列中miRNAs的表达量，根据病理检测结果对样本进行分组，使用统计学方法发掘可用于区分良、恶性卵巢肿瘤的miRNA作为生 物标志物，候选分子标记物，包括hsa-miR-1-3p、hsa-miR-1246、hsa-miR-141-3p、hsa-miR-200a-3p、hsa-miR-200b-3p、hsa-miR-200c-3p、hsa-miR-203a-3p、hsa-miR-3679-5p和hsa-miR-429，共计9个，用于后续分析。随后，根据NCBI GEO公共数据库中GSE53829qRT-PCR miRNA表达谱数据。依据组织类型，将GSE53829中数据分为两组，使用统计学方法发掘可用于区分正常卵巢组织和恶性卵巢癌组织的miRNA作为候选分子标记物。选取训练队列中的候选分子标记物与GSE53829数据集中的候选分子标记物的交集，做为分子标记物。最终选定7个miRNA作为分子标记物，包括hsa-miR-1246、hsa-miR-141-3p、hsa-miR-200a-3p、hsa-miR-200b-3p、hsa-miR-200c-3p、hsa-miR-203a-3p和hsa-miR-429，用于后续构建良、恶性卵巢肿瘤风险评分模型。
实施例4.卵巢肿瘤良、恶性风险评分模型
在本实施例中，利用训练队列miRNA表达量数据，以7个分子标记物为变量，基于多元logistic回归模型(multivariate logistic regression model)，结合病理检测结果，构建良、恶性卵巢肿瘤风险评分模型。模型由参数、模型公式和参比值三部分组成。以7个分子标记物为变量，使用100次重复10折交叉验证法，获得模型校正参数及分子标记物的模型系数(表2)和风险评分模型公式。使用风险评分模型和每个样本中7个分子标记物的表达量，可以获得每个样本的风险值，风险值的高低可以反映样本的良恶性。
根据训练队列中每个病人的风险值及病理检测结果，绘制训练队列的接受者操作特性曲线(ROC曲线，receiver operating characteristic curve)(图3)。依据ROC曲线结果，在保证特异性取值大于0.5及敏感性取值大于0.5的情况下，确定参比值为0.2。当风险值小于或等于参比值时，该样本被预测为良性；否则预测为恶性。以病理检测结果为真值，评估模型预测效能。模型预测效能评估方法，包括AUC(取值范围0～1)、特异性(取值范围0～1)和敏感性(取值范围0～1)，分别为0.913(图3)，92.3％和87.5％(表3)。结果表明：在训练队列中，此风险预测模型具有较高AUC、特异性和敏感性,模型预测效能较优。
表2.以7个miRNA为标记物所构建风险评分模型的参数。
实施例5.风险评分模型预测效能测试和验证
在本实施例中，在测试队列和验证队列中，根据训练队列中确定的风险评分模型及参比值，对模型预测良恶性的效能进行验证。以参比值0.2为准，分别将测试队列和验证队列患者分为低风险组(同训练队列)和高风险组。在测试队列中，以病理检测结果为真值，绘制ROC曲线(图4)，评估模型预测效能，包括AUC(图4)、特异性和敏感性，分别为0.973、100％和86.7％(表3)。在验证队列中，以病理检测结果为真值，绘制ROC曲线(图5)，评估模型预测效能，包括AUC(图5)、特异性和敏感性，分别为0.924、93.3％和86.7％(表3)。结果表明：在测试队列和验证队列中，此风险预测模型同样具有较高AUC、特异性和敏感性，即模型预测效能较优。
表3.七个分子标记模型效能评估
在本发明提及的所有文献都在本申请中引用作为参考，就如同每一篇文献被单独引用作为参考那样。此外应理解，在阅读了本发明的上述讲授内容之后，本领域技术人员可以对本发明作各种改动或修改，这些等价形式同样落于本申请所附权利要求书所限定的范围。

Claims (10)

  1. 血液胞外囊泡miRNA在制备用于诊断卵巢癌的芯片、检测试剂或检测试剂盒中的用途，其中所述miRNA是
    (i)选自下组的一个或多个miRNA：hsa-miR-1-3p、hsa-miR-1246、hsa-miR-141-3p、hsa-miR-200a-3p、hsa-miR-200b-3p、hsa-miR-200c-3p、hsa-miR-203a-3p、hsa-miR-3679-5p和hsa-miR-429；或者
    (ii)与(i)所述miRNA序列互补的miRNA。
  2. 如权利要求1所述的用途，其特征在于，所述的诊断卵巢癌是卵巢癌的早期诊断；优选地，所述卵巢癌的早期诊断是区分卵巢肿瘤良恶性。
  3. 如权利要求1或2所述的用途，其特征在于，所述miRNA是选自下组的一个或多个miRNA：hsa-miR-1246、hsa-miR-141-3p、hsa-miR-200a-3p、hsa-miR-200b-3p、hsa-miR-200c-3p、hsa-miR-203a-3p和hsa-miR-429。
  4. 一种miRNA芯片，所述的miRNA芯片包括：
    固相载体；以及
    有序固定在所述固相载体上的寡核苷酸探针，所述的寡核苷酸探针特异性地结合miRNA；
    其中，所述的miRNA是权利要求1-3中任一项所述miRNA。
  5. 如权利要求4所述的miRNA芯片，其特征在于，所述的寡核苷酸探针含有：
    互补结合区；和/或
    与固相载体相连的连接区。
  6. 如权利要求5所述的miRNA芯片，其特征在于，所述miRNA芯片用于卵巢癌的早期诊断；优选区分卵巢肿瘤良恶性。
  7. 权利要求4-6中任一项所述的miRNA芯片的用途，用于制备诊断卵巢癌的检测试剂盒。
  8. 如权利要求7所述的用途，其特征在于，所述诊断卵巢癌是卵巢癌的早期诊断；优选地，所述卵巢癌的早期诊断是区分卵巢肿瘤良恶性。
  9. 一种检测试剂盒，所述的检测试剂盒装有检测miRNA的检测试剂；
    其中，所述的miRNA是权利要求1-3中任一项所述miRNA；
    或者，所述检测试剂盒装有权利要求4-6中任一项所述的miRNA芯片。
  10. 如权利要求9所述的检测试剂盒，其特征在于，所述检测试剂盒用于卵巢癌的早期诊断；优选用于区分卵巢肿瘤良恶性。
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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101755208A (zh) * 2007-07-25 2010-06-23 路易斯维尔大学研究基金会公司 作为诊断标记物的外来体相关微rna
KR20220052461A (ko) * 2020-10-21 2022-04-28 순천향대학교 산학협력단 난소암 진단 또는 감별진단을 위한 마이크로rna-1246 및 이의 용도

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101755208A (zh) * 2007-07-25 2010-06-23 路易斯维尔大学研究基金会公司 作为诊断标记物的外来体相关微rna
KR20220052461A (ko) * 2020-10-21 2022-04-28 순천향대학교 산학협력단 난소암 진단 또는 감별진단을 위한 마이크로rna-1246 및 이의 용도

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
TAOQIONG LI: "Exosomal transfer of miR-429 confers chemoresistance in epithelial ovarian cancer", AMERICAN JOURNAL OF CANCER RESEARCH, E-CENTURY PUBLISHING CORPORATION, US, vol. 11, no. 5, 1 January 2021 (2021-01-01), US , pages 2124 - 2141, XP093154220, ISSN: 2156-6976 *

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