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A kind of breast cancer prognosis risk prediction marker composition and application

A technology for risk prediction and breast cancer, applied in the field of gene technology and medicine, to achieve good prediction utility, improve performance, and intuitive prognosis judgment

Active Publication Date: 2022-02-18
GUANGZHOU UNIVERSITY OF CHINESE MEDICINE
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

It can be seen that the existing breast cancer prognostic markers are only applicable to specific breast cancers and have certain limitations.

Method used

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  • A kind of breast cancer prognosis risk prediction marker composition and application
  • A kind of breast cancer prognosis risk prediction marker composition and application
  • A kind of breast cancer prognosis risk prediction marker composition and application

Examples

Experimental program
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Effect test

Embodiment 1

[0047] Example 1 Establishment of a breast cancer prognosis risk prediction model based on depression-related genes and its application in predicting the prognosis of breast cancer patients

[0048] (1) Collect the mRNA expression data matrix and clinical information of breast cancer patients from the Cancer Genome Atlas (TCGA) database, which includes 1096 tumor samples and 113 normal samples as a test data set (test set); from the GEO database The mRNA profiles and clinical characteristics of 2969 breast cancer patients were collected in the GSE96058 dataset as a validation dataset (validation set).

[0049] (2) Screening of differentially expressed genes: Search the Genecard database with "depression" or "depressive" as the key word, and obtain a depression-related gene set (8479 genes). Use the Wilcox rank sum test to screen the differentially expressed genes related to depression in breast cancer samples and normal samples, set the threshold |logfoldChange|=2, padj=0.01, ...

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Abstract

The invention discloses a breast cancer prognosis risk prediction marker composition and its application. The present invention screens out 10 differentially expressed genes MT3, SORBS1, IGFALS, AMH, IL12B, TP53AIP1, PXDNL, MC5R, FOXD1, LHX1 that are closely related to the survival rate of breast cancer, which can be used for detection in tumors and have high predictive accuracy Molecular markers of breast cancer prognosis. Based on these 10 genes, the present invention also constructs a breast cancer patient prognosis death risk prediction model, which can predict the prognosis death risk of breast cancer patients, and can also calculate the one-year, three-year, and five-year survival rates of breast cancer patients. The prognosis prediction of cancer patients provides an effective prediction tool and provides new ideas for guiding clinicians to formulate individualized treatment plans.

Description

technical field [0001] The invention relates to the fields of gene technology and medicine, in particular to a breast cancer prognosis risk prediction marker composition and its application. Background technique [0002] Breast cancer is the most common cancer among women and the leading cause of cancer death in women. Breast cancer treatment has achieved some success due to advances in early screening and treatment methods, but prognostic assessment remains challenging due to the heterogeneity of the disease. Especially as the morbidity and mortality of breast cancer continue to increase and tend to be younger, the curative effect and prognosis of breast cancer patients are still not optimistic at this stage. Therefore, it is particularly important to monitor the prognosis of patients in time. There are many factors affecting the prognosis of breast cancer, and there is still a lack of specific molecular biomarkers for treatment sensitivity and prognosis. Therefore, it i...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): C12Q1/6886G16B25/10G16B40/00
CPCC12Q1/6886G16B25/10G16B40/00C12Q2600/118C12Q2600/158
Inventor 王志宇王玄王能
Owner GUANGZHOU UNIVERSITY OF CHINESE MEDICINE
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