Marker and model for predicting triple-negative breast cancer chemotherapy response

A triple-negative breast cancer, marker technology, applied in the field of precision medicine, can solve the problem of inability to guide TNBC, and achieve the effect of a good treatment plan

Pending Publication Date: 2022-04-26
SHENZHEN LUWEI BIOTECHNOLOGY (BIOMANIFOLD TECH CO) LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] However, on the one hand, a variety of existing genetic detection models including the 21-gene recurrence score cannot be directly used to guide TNBC due to differences in gene expression

Method used

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  • Marker and model for predicting triple-negative breast cancer chemotherapy response
  • Marker and model for predicting triple-negative breast cancer chemotherapy response
  • Marker and model for predicting triple-negative breast cancer chemotherapy response

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0111] Example 1 Screening of TNBC gene diagnostic markers using mRNA expression data of genes

[0112] 1. Data set preparation

[0113] 1. Download the dataset GSE69031 (GPL571) from Gene Expression Omnibus (GEO), and then download the dataset TCGA-BRCA (GPL96, etc.) from TCGA. The data sets are gene chip data of breast cancer slices (Affymetrix platform GPL96, GPL571, etc.). A total of 171 cases were selected only from TNBC patients, of which TCGA-BRCA contributed 150 cases and GSE69031 contributed 21 cases.

[0114] 2. After removing the gene transcriptions with extremely low expression (the number of samples with non-zero expression does not exceed 10), miRNA and lncRNA are removed, and the common genes of the two data sets are selected, and the number of genes is 9524.

[0115] 3. Standardize the data of samples and genes step by step:

[0116] For each sample, the median of all gene expression levels was calculated separately, and the normalized expression of each sam...

Embodiment 2

[0135] Example 2 Cross Validation

[0136] The data set in Example 1 is equally divided according to the population of the target variable, half of which is a training set and the other half is a verification set. The ROC curve analysis is performed on the model obtained in Example 1, and the AUC is calculated. This is repeated N (=20) times, and the statistical characteristics of AUC are calculated. see figure 1 As shown, the minimum value AUC=0.79, the maximum value AUC=0.96, and the median value AUC=0.87. Taking the median AUC value of the cross-validation as an indicator for evaluating the results of the model shows that the model provided by the present invention has excellence.

Embodiment 3

[0137] Example 3 Evaluation of any subset of markers

[0138] For the markers obtained in Example 1, take any subset (the subset includes K genes, K is a positive integer greater than or equal to 1 and less than 19), and evaluate the subset as a biomarker.

[0139] For the case of K=1, evaluate any single gene among the markers as a biomarker, draw its ROC curve and calculate the AUC, the results are shown in image 3 shown.

[0140] For the case of K ≥ 2, randomly select K genes among the markers, rebuild the model and perform cross-validation, draw the ROC curve and calculate the AUC, see some results Figure 4-7 shown.

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Abstract

The invention relates to a marker and a model for predicting chemotherapy response of triple negative breast cancer. The marker comprises one or a combination of more than two of the following genes: AKT2, ARG1, BIRC7, CCR3, CDKN2A, CHGB, CNN1, CYP7A1, FGF5, KMT2A, NME1, NRAS, PCP4, PRC1, PRKCI, SUZ12, VEGFC, WRN and ZBTB16. According to the method, the chemotherapy response is taken as a target function, and the accurate model for predicting the chemotherapy response of the triple-negative breast cancer is established by utilizing the whole transcriptome data of the triple-negative breast cancer slice based on an iterative linear regression algorithm of correlation coefficient layering. By utilizing the model, evaluation can be performed before chemotherapy of a triple-negative breast cancer patient, and the model is used for guiding establishment of a treatment scheme.

Description

technical field [0001] The invention relates to the technical field of precision medicine, in particular to a marker and a model for predicting chemotherapy response of triple-negative breast cancer. Background technique [0002] Triple-negative breast cancer (TNBC) refers to breast cancer that is negative for estrogen receptor (ER), progesterone receptor (PR) and proto-oncogene Her-2 as a result of immunohistochemical examination of cancer tissue, accounting for about 100% of all breast cancers. 20% of cancer. It mostly occurs in young premenopausal women, and the clinical manifestation is an aggressive course of disease, with a higher risk of distant metastasis, visceral metastasis than bone metastasis, and a higher probability of brain metastasis. The risk of distant metastasis in triple-negative breast cancer peaked at 3 years. [0003] In terms of drug treatment, according to NCCN (National Comprehensive Cancer Network) and CSCO (Chinese Society of Clinical Oncology) ...

Claims

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Application Information

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IPC IPC(8): G16H20/40G16B20/00
CPCG16H20/40G16B20/00
Inventor 饶皑炳
Owner SHENZHEN LUWEI BIOTECHNOLOGY (BIOMANIFOLD TECH CO) LTD
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