Research On The Relationship Between The Prognosis Of Triple Negative Breast Cancer And Platinum Target Based On Gene Coexpression Network Analysis

Objective: As a routine neoadjuvant chemotherapy regimen,the mechanism by which platinum exerts its effect in triple-negative breast cancer remains unclear.The prediction of a platinum marker gene signature in triple-negative breast cancer is of great significance and can be useful for screening patients with appropriate platinum drugs.,to improve the therapeutic effect of platinum drugs.This study intends to construct a gene co-expression network to screen the gene signatures of platinum drugs affecting the prognosis of triple-negative breast cancer,and to sort out the regulatory mechanism of platinum drugs in this process.Methods: Breast cancer gene expression data and corresponding clinical data were downloaded from the TCGA database,and the mclust clustering algorithm was used to identify the three negative breast cancer samples.The samples were subjected to three negative/non-three negative and three negative/normal two-level differential expression analysis using the edge R and DESeq2 methods.Furthermore,a weighted gene coexpression network analysis(WGCNA)method was used to construct a co-expression network of differentially-expressed genes in triple-negative breast cancer.On this basis,combined with text mining methods to predict the platinum response target in triplenegative breast cancer,and interpret the transcriptional regulation mechanism with the help of the competitive endogenous RNA(ce RNA)hypothesis.Results: A total of 176 triple-negative breast cancer samples were identified in this study and 3,045 triple-negative breast cancers were differentially expressed by differential analysis.In the gene co-expression network constructed,the turquoise module contains 481 genes and is significantly associated with prognosis.Seventeen potential platinum drugs were screened for gene markers that influence the prognosis of triple-negative breast cancer,and a ce RNA network was constructed.Conclusion: Combining bioinformatics and text mining,we identified a prognosticConclusion: Combining bioinformatics and text mining,we identified a prognostic model of triple-negative breast cancer,predicted potential platinum response targets affecting the prognosis of triple-negative breast,revealed the regulatory mechanism of the transcriptional level of the process,and analyzed The results were verified.This study provided a basis for screening platinum-sensitive patients with triple-negative breast cancer to further study the relationship between prognosis-related genes and platinumresponsive targets in triple-negative breast cancer.