WO2021036620A1 - Application d'un groupe de gènes liés au pronostic du cancer de l'ovaire - Google Patents

Application d'un groupe de gènes liés au pronostic du cancer de l'ovaire Download PDF

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WO2021036620A1
WO2021036620A1 PCT/CN2020/104023 CN2020104023W WO2021036620A1 WO 2021036620 A1 WO2021036620 A1 WO 2021036620A1 CN 2020104023 W CN2020104023 W CN 2020104023W WO 2021036620 A1 WO2021036620 A1 WO 2021036620A1
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ovarian cancer
genes
gene
prognosis
related genes
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PCT/CN2020/104023
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Chinese (zh)
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赵玥
王频
安托万·M·斯内德
毛建华
杭渤
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伯克利南京医学研究有限责任公司
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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
    • C12Q2600/118—Prognosis of disease development

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  • the invention belongs to the technical field of tumor gene detection, and specifically relates to a group of serous ovarian cancer-related genes and applications thereof.
  • Ovarian cancer is a major disease that seriously threatens women’s health. Its incidence ranks second among malignant tumors of the female reproductive system, and its fatality rate ranks fifth among malignant tumors, and ranks first among gynecological tumors.
  • journal CA a cancer journal for clinicians, there are more than 295,000 new cases of ovarian cancer and more than 185,000 deaths worldwide each year, and the number of patients and deaths is on the rise. The anatomical location of the ovary is hidden, and the early symptoms of ovarian cancer are not obvious. At present, there is no effective and beneficial method for early diagnosis or extensive screening in the population.
  • the early diagnosis rate of ovarian cancer is very low, as high as 70%-80% Of patients are in the advanced stage when they see a doctor.
  • ovarian cancer is called the "silent killer" of women, which shows its significant clinical and social importance.
  • the recurrence rate is still as high as 75%.
  • the current treatment effect and prognosis of ovarian cancer are both poor, and the 5-year survival rate is only about 20%. Therefore, establishing early diagnosis methods, finding effective treatment targets, and accurately assessing prognosis to guide clinical intervention are important challenges for improving the survival rate of ovarian cancer patients.
  • ovarian cancer surgery technology has been continuously improved, new chemotherapy drugs have been continuously put into use, and chemotherapy regimens have been continuously optimized.
  • chemotherapy regimens have been continuously optimized.
  • PARP inhibitor therapy for patients with BRCA mutations, molecular targeted therapy such as folate receptors, immunotherapy, anti-angiogenesis drug therapy, and weekly paclitaxel chemotherapy regimens.
  • ovarian tumors are histologically divided into epithelial tumors, sex cord-stromal tumors, germ cell tumors, etc., and each category is subdivided into many subcategories, such as epithelial tumors.
  • Ovarian cancer is divided into serous carcinoma, mucinous carcinoma, endometrioid carcinoma, clear cell carcinoma, serous-mucinous carcinoma and so on.
  • Serous ovarian cancer (Serous Ovarian Carcinoma, SOC) is the most important of epithelial ovarian cancer, accounting for 70-80% of ovarian cancer mortality.
  • SOCs can be divided into four subtypes: mesenchymal, immunoreactive, differentiated, and proliferative.
  • Serous ovarian cancer is characterized by genetic changes, including hereditary BRCA gene mutations, TP53 mutations, DNA damage, chromosomal instability, and changes in RNA and miRNA expression and methylation status.
  • Ovarian cancer like other tumors, is a "systemic and systemic disease with multi-factor origin and multi-step development". Even the same type of ovarian cancer, there is a high degree of heterogeneity at the molecular level among different individuals. Therefore, simple histological classification has limited guiding value for clinical intervention. Different tumor patients, even if their pathological types, stages, grades, and even the treatments they receive are the same, their survival times will still show differences. Tumor heterogeneity includes the heterogeneity between different patients of the same type of tumor and the heterogeneity between cells in individual tumors.
  • each patient’s tumor is unique, and this uniqueness can extend from the macroscopic to the microscopic to the different cell clones in individual tumors, and this is present in almost all types of tumors. unique.
  • different genetic backgrounds, internal factors and environmental factors constitute the macroscopic tumor heterogeneity among patients.
  • intratumoral heterogeneity has become a research hotspot in the field of tumors. It is the inevitable trend of future medical development to provide individualized precision treatment for the difference in the molecular level of each individual tumor. At present, the most successful work in this area is breast cancer.
  • Oncotype DX Genemic Health Company in the United States
  • MammaPrint Genedia Company in Norway
  • Oncotype DX Genemic Health Company in the United States
  • MammaPrint Genedia Company in Norway
  • the above methods have been maturely applied to the clinic and have obtained significant curative effects. At present, these two tests have been approved by the US FDA for marketing.
  • Oncotype DX has also been recommended by the NCCN guidelines and is covered by the US medical insurance, which has completely realized the transformation from basic research to clinical application.
  • the purpose of the present invention is to perform genetic diagnosis such as prognosis prediction and treatment plan evaluation for patients with ovarian cancer.
  • the sample in the present invention is the tumor tissue of a patient with ovarian cancer.
  • mRNA is isolated from the tumor tissue sample of the patient, the expression level of ovarian cancer-related genes is determined, and the prognosis of serous ovarian cancer is evaluated by the multi-gene expression profile and scoring system for evaluating the prognosis of ovarian cancer.
  • the expression level of related genes in clinical samples is detected, and the clinical prognosis of the patient is predicted by calculating the prognostic score.
  • the present invention provides a set of 11 ovarian cancer-related genes in the preparation of ovarian cancer prognostic prediction reagents
  • the above-mentioned 11 ovarian cancer-related genes are (1) homologous recombination repair genes: RAD51AP1; (2) ) Genes encoding biological enzymes: MTHFD2, GALNT10, PYCR1; (3) Signal transduction-related genes: CADPS2, DSE, ITGB8, PDE10A, SNX1; (4) Other genes: C9orf16, ARL4; and (5) Control genes: GAPDH , ACTB, GUSB and TFRC.
  • the ovarian cancer is serous ovarian cancer.
  • the present invention provides a set of gene probes or primers designed for the application of the 11 ovarian cancer-related genes of claim 1 in preparing reagents for predicting the prognosis of ovarian cancer.
  • the gene probes can pass Molecular hybridization combines with the 11 ovarian cancer-related genes to generate hybridization signals, and the primers can amplify the 11 ovarian cancer-related genes through PCR-based technology.
  • the present invention provides a composition for predicting the prognosis of ovarian cancer, which includes the above-mentioned gene probe or primer.
  • the present invention provides a diagnostic kit for predicting the prognosis of ovarian cancer, which comprises the above-mentioned composition.
  • the above 11 ovarian cancer-related genes can be detected by real-time fluorescent quantitative PCR, gene chip, second-generation high-throughput sequencing, Panomics or Nanostring technology.
  • real-time fluorescent quantitative PCR, gene chip, second-generation high-throughput sequencing, Panomics or Nanostring technology can be used to detect the mRNA expression levels of the above 11 related genes in ovarian cancer.
  • gene probe and “primer” used in this specification refer to oligonucleotides, preferably single-stranded deoxyribonucleotides, including naturally occurring dNMP (dAMP, dGMP, dCMP and dTMP), and variants. Nucleotides or non-natural nucleotides, in addition, ribonucleotides may also be included.
  • the gene probes and primers used in the present invention contain hybridizing nucleotide sequences complementary to the target position of the target nucleic acid.
  • complementary means that under hybridization conditions, primers or probes are fully complementary to the target nucleic acid sequence selectively hybridizing, including substantially complementary and perfectly complementary. The meaning of is preferably completely complementary.
  • substantially complementary sequence used in this specification includes not only completely identical sequences, but also sequences that can function as primers on a specific target sequence and are partially inconsistent with the sequence to be compared.
  • sequences of gene probes and primers do not need to have sequences that are completely complementary to a part of the template sequence, as long as they have sufficient complementarity within a range that can hybridize to the template and exert its inherent functions. Therefore, the gene probes and primers in the present invention do not need to have a sequence that is completely complementary to the aforementioned nucleotide sequence as a template, as long as they have sufficient complementarity within a range that can hybridize to the template to exert its inherent function.
  • the design of primers and gene probes is a skill mastered by those skilled in the art. For example, a program for primer design (for example, the PRIMER 3 program) can be used.
  • the mRNA expression level of the present invention can be determined by methods known in the art, including but not limited to real-time fluorescent quantitative PCR, gene chip, second-generation high-throughput sequencing, Panomics or Nanostring technology.
  • the invention provides a diagnostic reagent and kit containing the gene probe or primer of the invention for predicting the prognosis of ovarian cancer.
  • the reagents and kits of the present invention may additionally contain tools known in the art for PCR reactions, RNA isolation of samples, and cDNA synthesis. And/or reagents.
  • the kit of the present invention may additionally contain a tube for mixing the components, a microplate, and instruction materials describing the method of use, etc., as necessary.
  • the present invention successfully finds a group of 11 important biomarker genes for predicting the overall survival of patients with ovarian cancer by using multiple omics data, and establishes a prognostic scoring system based on 11 gene markers for the first time. We have also confirmed that the prediction score of the system can accurately distinguish the different clinical prognosis of patients with ovarian cancer.
  • This invention can be used to assist in predicting the response of patients with ovarian cancer to therapeutic interventions, to determine whether the patients benefit from chemotherapy and targeted therapy, to make treatment choices, to avoid excessive medical treatment, and to achieve the purpose of individualized medical treatment.
  • Figure 1 Kaplan-Meier survival curve example of representative genes in serous ovarian cancer gene tags. The p value is obtained by comparing the log-rank test between the two groups.
  • Figure 2 Co-expression network diagram of 232 overall survival related genes used in ovarian cancer of the present invention.
  • Figure 3 The first 20 highly enriched gene function groups in ovarian cancer of the present invention.
  • Figure 4A Kaplan-Meier survival curves of two representative test sets in which ovarian cancer patients with different prognosis are divided into three groups: good, middle and poor according to the present invention.
  • Figure 4B Hazard ratio (HR) in 100 test sets and its 95% HR confidence interval.
  • Figure 5 Kaplan-Meier survival curve shows that the prognostic score of the present invention can accurately predict the prognosis of ovarian cancer patients in multiple databases.
  • Figure 6 The present invention's assessment of the prognosis of patients with ovarian cancer is significantly better than the reported prognostic signatures of 5 genes.
  • the present invention applies the international general tumor database and adopts a multi-step bioinformatics analysis method to firstly confirm 488 genes with significant differences in expression in normal ovarian tissue and serous ovarian cancer tissue.
  • survival analysis 232 genes are found Significantly related to overall survival (OS).
  • the biological functions of these 232 genes involve processes such as cell division, epithelial cell differentiation, p53 signaling pathway, blood vessel formation, and drug metabolism.
  • TCGA The Cancer Genome Atlas
  • a multi-step bioinformatics analysis method was used to compare the gene expression between normal ovarian tissue and ovarian cancer tissue to determine the significantly differentially expressed genes in each data set.
  • a total of 397 samples (349 cases of ovarian cancer, 48 cases of normal ovarian) Organization) included in the analysis.
  • These 6 data sets have 24049, 11262, 37330, 17903, 11959, and 6733 differentially expressed genes (probe ID) that meet our standard (fold change (FC) ⁇ 1.5, corrected p value ⁇ 0.05), and then The intersection of these 6 groups of differentially expressed genes, a total of 590 genes (probe ID) were selected.
  • 562 genes have the same trend of expression changes in the 6 data sets (the expressions are all up-regulated or all down-regulated in the 6 data sets), of which 260 genes (probe ID) are down-regulated, and 302 genes ( probe ID) expression is up-regulated; according to the chip gene probe, the corresponding 488 genes were found.
  • the expression trend of these genes in the 6 data sets is the same (all up-regulated or all down-regulated in the 6 data sets), of which 222 The expression of two genes was down-regulated, and the expression of 266 genes was up-regulated.
  • Figure 1 shows the effect of 4 representative gene expression levels on the prognosis and survival of patients.
  • 232 genes 82 genes have a hazard ratio (HR) ⁇ 1 (higher gene expression is associated with a good prognosis), which are called protective genes; while the other 150 genes have HR>1 (higher gene expression is associated with poor prognosis).
  • HR hazard ratio
  • Prognosis-related prognosis-related
  • prognostic scoring system for serous ovarian cancer.
  • These genes include: (1) homologous recombination repair gene: RAD51AP1; (2) encoding biological enzyme genes: MTHFD2, GALNT10, PYCR1; (3) signal transduction related genes: CADPS2, DSE, ITGB8, PDE10A, SNX1; ( 4) Other genes: C9orf16, ARL4.
  • Each gene is a sequence of each gene known in the art or a synonym sequence of each gene, preferably a sequence of each gene derived from humans, more preferably RAD51AP1 is the sequence described in Genbank accession number NM_006479, and MTHFD2 is Genbank The sequence described in accession number NM_006636, GALNT10 is the sequence described in Genbank accession number NM_198321, PYCR1 is the sequence described in Genbank accession number NM_006907, CADPS2 is the sequence described in Genbank accession number NM_017954, DSE is the sequence described in Genbank accession number NM_013352 Sequence, ITGB8 is the sequence described in Genbank registration number NM_002214, PDE10A is the sequence described in Genbank registration number NM_001130690, SNX1 is the sequence described in Genbank registration number NM_003099, C9orf16 is the sequence described in Genbank registration number NM_024112, ARL4 is the sequence recorded in
  • the above-mentioned serous ovarian cancer prognosis scoring system uses predictive scores to calculate the survival probability of patients.
  • the scoring system is defined as a linear combination of gene expression levels based on a canonical discriminant function. Calculated as follows:
  • the prognostic score of each patient can be used to assess their overall survival and risk of death. Sort the patients in the training group according to their prognostic scores, and divide the patients into three groups of the same number according to their scores, record the prognostic scores corresponding to the corresponding cut-off points, and take the average of the scores of each cut-off point as the true cut-off point According to the scores of these two cut-off points, patients in the test group are divided into three groups (prognosis) of "good”, "medium” and "poor”.
  • the sample is a tumor tissue of an ovarian cancer patient.
  • the above-mentioned ovarian cancer patient sometimes contains a part of normal cells, including but not limited to fresh biopsy tissue, postoperative tissue, fixed tissue, and paraffin-embedded tissue.
  • the diagnostic tags for ovarian cancer prognosis prediction of the present invention can be detected by different detection technology platforms, including but not limited to real-time fluorescent quantitative PCR, gene chips, second-generation high-throughput sequencing, Panomics and Nanostring technologies, and are aimed at different technology platforms. Designed corresponding gene primers (real-time fluorescent quantitative PCR) and probes (gene chip, second-generation high-throughput sequencing, Panomics and Nanostring technology).
  • a preferred solution is the detection of the expression level of the target gene, and more preferably the quantitative detection of the expression level of the target gene.
  • RNA needs to be isolated from the sample tissue, and methods known in the art for isolating RNA from the sample can be used.
  • the calculation method of the forecast score we defined is as above, but the absolute value of the forecast score and the demarcation of the score can be different according to different technology platforms and need to be determined separately.
  • the present invention provides a composition for predicting the prognosis of ovarian cancer, which contains a gene probe or primer as an effective ingredient, and the gene probe or primer is directed against the above-mentioned 11-gene markers (RAD51AP1, MTHFD2, GALNT10, PYCR1, CADPS2, DSE, ITGB8, PDE10A, SNX1, C9orf16, ARL4).
  • 11-gene markers RAD51AP1, MTHFD2, GALNT10, PYCR1, CADPS2, DSE, ITGB8, PDE10A, SNX1, C9orf16, ARL4
  • the present invention provides a diagnostic kit for predicting the prognosis of ovarian cancer, which includes the above-mentioned composition.
  • the tumor tissues can include fresh biopsy tissues, postoperative tissues, fixed tissues and paraffin-embedded tissues. Then use the kit developed by the present invention and the corresponding instrument to quantitatively detect the expression levels of 11 genes in the prognosis scoring system. Input the expression level of 11 genes into the prognostic scoring formula established in the present invention:
  • the doctor predicts the patient's prognosis based on the score value, such as the 5-year survival rate.
  • the score value such as the 5-year survival rate.
  • the prognostic scores of all patients in the database the patients are ranked according to their scores. Kaplan-Meier was used to analyze significant differences between patient groups with "good” and “poor” prognosis. We found that patients with high prognostic scores had significantly shorter OS than those with low scores (p ⁇ 0.05) (Figure 5). The HR value ranges from 1.54 to .9.76, confirming that the 11-gene prognostic scoring system can repeatedly predict the overall survival rate of patients with ovarian cancer. We have also begun to implement prospective studies to further improve the scoring system.
  • PARP inhibitors such as but not limited to olaparib, rucaparib and niraparib
  • BRCA1/BRCA2 mutations are a larger risk factor for ovarian cancer (lifetime risk 40%).
  • the response rate of olaparib in people without germ cell BRCA mutations is 30%. 50% of platinum-based drug-sensitive populations.
  • the present invention predicts that patients with clinical ovarian cancer will respond to PARP inhibitors (such as but not limited to olaparib) through the following implementations. ), the reaction of rucaparib and niraparib); tumor tissues are collected from clinically accepted ovarian cancer patients and RNA is extracted.
  • the tumor tissues can include fresh biopsy tissue, postoperative tissue, and fixed Tissue and paraffin-embedded tissue. Then use the kit developed by the present invention and the corresponding instrument to quantitatively detect the expression level of the 11 genes of the prognosis scoring system. Input the expression level of 11 genes into the prognostic scoring formula established in the present invention:
  • the doctor After calculating the predictive score of the patient, the doctor considers whether the patient should receive targeted therapy with PARP inhibitors based on the score value. For patients whose predicted scores indicate a good prognosis, doctors can be advised to consider the necessity of PARP inhibitor targeted therapy as appropriate, so as to avoid excessive medication, reduce medical costs, and finally achieve the purpose of precise or individualized medical treatment.
  • Predicting the response of clinical ovarian cancer patients to the chemotherapy drug paclitaxel At present, the recurrence rate of ovarian cancer chemotherapy is high, and the effective rate is low.
  • the present invention uses the following schemes to predict clinical ovarian cancer patients’ response to chemotherapy drugs
  • Paclitaxel response Collect tumor tissue and extract RNA from clinically accepted ovarian cancer patients.
  • the tumor tissue can include fresh biopsy tissue, postoperative tissue, fixed tissue and paraffin-embedded tissue. Then use the kit developed by the present invention and the corresponding instrument to quantitatively detect the expression level of the 11 genes of the prognosis scoring system. Input the expression level of 11 genes into the prognostic scoring formula established in the present invention:
  • the doctor After calculating the predictive score of the patient, the doctor considers whether the patient should receive paclitaxel chemotherapy based on the score value. For patients whose predicted scores indicate a good prognosis, doctors can be advised to consider the necessity of paclitaxel treatment as appropriate, and for patients whose predicted scores indicate a poor prognosis, doctors can be advised to increase the treatment intensity of paclitaxel or other chemotherapeutics as appropriate.

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Abstract

Sur la base de la découverte d'un groupe de 11 profils de gènes associés à un pronostic dans le cancer de l'ovaire séreux et la détection du niveau d'expression des 11 profils géniques associés au pronostic dans des échantillons de tumeur clinique, le score pronostique d'un patient est calculé en fonction du coefficient de corrélation pronostique d'un groupe des gènes pour évaluer le pronostic clinique de patients atteints d'un cancer de l'ovaire et l'application associée du pronostic clinique.
PCT/CN2020/104023 2019-08-23 2020-07-24 Application d'un groupe de gènes liés au pronostic du cancer de l'ovaire WO2021036620A1 (fr)

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* Cited by examiner, † Cited by third party
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CN114686590A (zh) * 2022-04-25 2022-07-01 重庆大学附属肿瘤医院 一种检测ahctf1表达水平的试剂在制备判断卵巢癌干性程度的试剂中的应用
CN114752673A (zh) * 2022-04-30 2022-07-15 重庆大学附属肿瘤医院 一种检测isyna1表达水平的试剂在制备卵巢癌干性鉴别试剂中的应用

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110551819B (zh) * 2019-08-23 2023-05-16 伯克利南京医学研究有限责任公司 一组卵巢癌预后相关基因的应用
CN111139300B (zh) * 2020-02-19 2021-08-17 伯克利南京医学研究有限责任公司 一组结肠癌预后相关基因的应用
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013152301A1 (fr) * 2012-04-05 2013-10-10 H. Lee Moffitt Cancer Center And Research Institute, Inc. Signature du cancer de l'ovaire par voie o-glycane
WO2018162596A1 (fr) * 2017-03-07 2018-09-13 Elypta Ab Biomarqueurs du cancer
CN110551819A (zh) * 2019-08-23 2019-12-10 伯克利南京医学研究有限责任公司 一组卵巢癌预后相关基因的应用

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20090071603A (ko) * 2006-09-19 2009-07-01 노파르티스 아게 Ｒａｆ 억제제에 대한 표적 조절, 효능, 진단 및/또는 예후의 바이오마커
WO2009009890A1 (fr) * 2007-07-16 2009-01-22 University Health Network Biomarqueurs du cancer de l'ovaire
US20140045915A1 (en) * 2010-08-31 2014-02-13 The General Hospital Corporation Cancer-related biological materials in microvesicles
EP2906724A4 (fr) * 2012-10-12 2016-12-14 Agency Science Tech & Res Méthode de pronostic et de stratification du cancer de l'ovaire
US9771620B2 (en) * 2013-05-20 2017-09-26 Duke University Biomarkers of high-grade serous ovarian carcinomas
CN105531590A (zh) * 2013-09-17 2016-04-27 利兰斯坦福初级大学董事会 卵巢癌生物标志物
CN106706915A (zh) * 2016-12-30 2017-05-24 山东大学齐鲁医院 Susd2在制备高级别浆液性卵巢癌诊断和/或预后判断的试剂盒中的应用
CN106771248B (zh) * 2016-12-30 2018-05-15 山东大学齐鲁医院 高级别浆液性卵巢癌诊断和/或预后判断的标志物
US20210254056A1 (en) * 2017-05-05 2021-08-19 Camp4 Therapeutics Corporation Identification and targeted modulation of gene signaling networks
WO2019008412A1 (fr) * 2017-07-03 2019-01-10 Datar Rajan Utilisation d'une analyse d'expression génique fondée sur le sang pour la prise en charge du cancer
CN108508212B (zh) * 2018-04-19 2020-11-03 山东大学齐鲁医院 高级别浆液性卵巢癌靶向治疗和预后判断的标志物

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013152301A1 (fr) * 2012-04-05 2013-10-10 H. Lee Moffitt Cancer Center And Research Institute, Inc. Signature du cancer de l'ovaire par voie o-glycane
WO2018162596A1 (fr) * 2017-03-07 2018-09-13 Elypta Ab Biomarqueurs du cancer
CN110551819A (zh) * 2019-08-23 2019-12-10 伯克利南京医学研究有限责任公司 一组卵巢癌预后相关基因的应用

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
CHUDASAMA DIMPLE, BO VALERIA, HALL MARCIA, ANIKIN VLADIMIR, JEYANEETHI JEYAROOBAN, GREGORY JANE, PADOS GEORGE, TUCKER ALLAN, HARVE: "Identification of cancer biomarkers of prognostic value using specific gene regulatory networks (GRN): a novel role of RAD51AP1 for ovarian and lung cancers", CARCINOGENESIS, vol. 39, no. 3, 8 November 2017 (2017-11-08), pages 407 - 417, XP055786296, ISSN: 0143-3334, DOI: 10.1093/carcin/bgx122 *

Cited By (4)

* Cited by examiner, † Cited by third party
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CN114686590A (zh) * 2022-04-25 2022-07-01 重庆大学附属肿瘤医院 一种检测ahctf1表达水平的试剂在制备判断卵巢癌干性程度的试剂中的应用
CN114686590B (zh) * 2022-04-25 2023-07-28 重庆大学附属肿瘤医院 一种检测ahctf1表达水平的试剂在制备判断卵巢癌干性程度的试剂中的应用
CN114752673A (zh) * 2022-04-30 2022-07-15 重庆大学附属肿瘤医院 一种检测isyna1表达水平的试剂在制备卵巢癌干性鉴别试剂中的应用
CN114752673B (zh) * 2022-04-30 2023-07-28 重庆大学附属肿瘤医院 一种检测isyna1表达水平的试剂在制备卵巢癌干性鉴别试剂中的应用

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