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Application of group of genes related to ovarian cancer prognosis

A technology of ovarian cancer and genes, applied in the direction of recombinant DNA technology, microbial measurement/testing, DNA/RNA fragments, etc., can solve problems that plague patients and doctors, and achieve the effect of avoiding excessive medical treatment

Active Publication Date: 2019-12-10
BERKELEY NANJING MEDICAL RES CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there is currently no similar genetic testing for ovarian cancer that can be used to guide the selection of treatment options. We know that ovarian cancer is a tumor type that is largely caused by genetic factors, and it is a huge challenge for patients and doctors.

Method used

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  • Application of group of genes related to ovarian cancer prognosis
  • Application of group of genes related to ovarian cancer prognosis
  • Application of group of genes related to ovarian cancer prognosis

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Experimental program
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Effect test

Embodiment 1

[0052] There have been studies in the prior art literature using expression differences to show the correlation between genes or polygenomes and the prognosis of ovarian cancer. We compared the 11 gene scoring system with the existing single gene or genome system. We first performed univariate Cox regression analysis and showed that the 232 single genes from GSE described above had only weak overall survival for ovarian cancer. Associated. Then we used the previously reported 5-gene ovarian cancer prognostic signature (Liu LW et al., A Five-Gene Expression Signature Predicts Clinical Outcome of Ovarian Serous Cystadenocarcinoma. Biomed Res Int. 2016: 6945304.) to calculate the prediction score. We used the multivariate Cox regression analysis method to analyze its 5 genes in the previous 100 training sets, and calculated the corresponding coefficients of each gene with the same method and averaged them, and calculated the TCGA 307 ovarian cancer patients with the same formula ...

Embodiment 2

[0054] Predict the prognostic effect of patients with clinical serous ovarian cancer:

[0055] Collect the tumor tissues of ovarian cancer patients received clinically and extract RNA. 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:

[0056]

[0057] After calculating the patient’s predicted score, the doctor predicts the patient’s prognosis based on the score, such as the 5-year survival rate. At present, we have established the model through retrospective research and successfully verified it in different databases (Table 3). By calculating the prognostic scores of all patients in the database, the patients are ranked acco...

Embodiment 3

[0059] Predict the response of clinical ovarian cancer patients to targeted therapy such as PARP inhibitors (such as but not limited to olaparib, rucaparib and niraparib);

[0060] As a prognostic and predictive biomarker, 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. In order to reduce ineffective or excessive use of targeted drugs and reduce medical costs, the present invention predicts that patients with clinical ovarian cancer will be exposed to PARP inhibitors (such as but not limited to olaparib) through the following implementations. ), the reaction of rucaparib and niraparib); tumor tissues were collected from clinically accepted ovarian cancer patients and RNA was extracted. The tumor tissues can include fresh biopsy tissue, postoperative tissue, and fixed Tissue and paraffin-embedded tissue. Then use...

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Abstract

Based on the discovery of a group of 11 prognostic related gene profiles in serous ovarian cancer and the detection of the expression level of the 11 prognostic related gene profiles in clinical tumorsamples, the prognostic score of a patient is calculated according to the prognostic correlation coefficient of a group of the genes to evaluate the clinical prognosis of ovarian cancer patients andrelated application of the clinical prognosis. The system can assist in evaluating the response of the ovarian cancer patients to treatment interventions, thus whether the patients benefit from chemical or targeted treatments or not is judged, treatment choice is conducted, excessive medical treatment is avoided, and the purpose of personalized treatment is achieved. According to the system and different detection technology platforms, corresponding 11 gene expression measurement kits are designed and developed.

Description

Technical field [0001] 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. Background technique [0002] 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 mortality rate ranks fifth among malignant tumors, and ranks first among gynecological tumors. According to the latest annual report of the well-known journal CA: a cancerjournal 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. Therefore, the early di...

Claims

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Application Information

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IPC IPC(8): C12Q1/6886C12N15/11
CPCC12Q1/6886C12Q2600/118
Inventor 赵玥王频安托万·M·斯内德毛建华杭渤
Owner BERKELEY NANJING MEDICAL RES CO LTD
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