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Application of Cholesterol Production Gene Signature to Prognosis Prediction in Young Breast Cancer Patients

A cholesterol and breast cancer technology, applied in the field of biomedical applications, can solve the problems of young breast cancer patients raised by no scholars

Active Publication Date: 2021-07-27
江门市中心医院
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Looking at the previous literature, no scholars have proposed to establish a model for predicting the prognosis of young breast cancer patients through cholesterol metabolism gene signatures

Method used

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  • Application of Cholesterol Production Gene Signature to Prognosis Prediction in Young Breast Cancer Patients
  • Application of Cholesterol Production Gene Signature to Prognosis Prediction in Young Breast Cancer Patients
  • Application of Cholesterol Production Gene Signature to Prognosis Prediction in Young Breast Cancer Patients

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment 1

[0044] Get breast cancer transcription group data (HTSEQ-FPKM) and clinical data from the TCGA and GEO database. Patients with breast cancer in the age of ≤ 45 years old, using 183 cases of breast cancer specimens and 30 normal specimens construction training sets, compared to the transcriptional expression of cholesterol generation genes by R language, using LIMMA and Pheatmap packets, statistical analysis, Differentially expressed genes (P figure 1 As shown, 97 up-regulated genes and 124 down-regulatory genes were prelimed.

specific Embodiment 2

[0046] By using single variable Cox regression analysis and LASSO regression analysis, it was determined that a gene associated with a prognosis of young breast cancer patients was set, and P figure 2 As shown, 5 pre-rear correlation genes are finally screens, respectively, of GRAMD1C, NFKBIA, INHBA, CD24, and ACSS2. The risk assessment model of the five breast cancer prognosis related genes was used. The model is based on the following formula: -1.169 × Gramd1c-0.992 × NFKBIa + 0.432 × inhba + 0.261 × CD24-0.839 × Acss2; where Gramd1c, NFKBIA, INHBA, CD24 and ACSS2 are mRNA levels of the corresponding gene.

[0047] After removing 4 cases of follow-up information, 179 cases of breast cancer patients were divided into high-risk group (n = 89) and low-risk groups (n = 90), such as the median value of the risk score. figure 2 As shown, Kaplan-Meier survival analysis showed that the prognosis of the low-risk group was significantly better than the high-risk group (P <0.001), and the ...

specific Embodiment 3

[0049] Combined with the risk assessment model of Example 2, single factors and multi-factors analysis were performed on age, clinical staging, surgical mode (labo-breast surgery and breast allocation), T staging, N staging and risk score. Such as image 3 As shown, the risk assessment model is an independent risk factor in the prognosis of young breast cancer patients (P <0.05).

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Abstract

The present invention provides a reliable breast cancer prognostic label, especially for young breast cancer patients, wherein the combination of GRAMD1C, NFKBIA, INHBA, CD24, and ACSS2 is effective in predicting the prognosis of young breast cancer patients, and provides a basis for the development of breast cancer patient prognosis prediction products. a clear idea.

Description

Technical field [0001] The invention belongs to the field of biomedical applications, and in particular, the application of cholesterol generation gene label in prognosis prediction in patients with young breast cancer. Background technique [0002] The increase in working pressure and unhealthy lifestyle caused rapid growth in the incidence of female breast cancer. In the United States, approximately 11% of women under the 45-year-old woman in the United States. In Asia, patients with young breast cancer are as high as 20%, far higher than the US. These evidence suggest that breast cancer is undoubtedly the main cause of cancer-related death for women 45 years or less. Young breast cancer patients have more risk factors than elderly breast cancer patients, including hormone receptor negative, high degree of malignancy, and HER2 positive tumors. Therefore, it is important to understand that its intrinsic mechanism is essential for designing the treatment solution suitable for you...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): C12Q1/6886G01N33/68G01N33/574
CPCC12Q1/6886C12Q2600/118C12Q2600/158G01N33/57415G01N33/57484G01N33/68G01N2333/47G01N2333/70596
Inventor 李晓平周庆华余绮荷胡刘兵张鑫任亮亮
Owner 江门市中心医院