Prognosis-related MRNA Of Breast Cancer Based On TCGA Data Mining

Objective: Breast cancer is the most common malignant tumor in women.At present,despite the continuous advancement of breast cancer diagnosis and treatment methods,due to its characteristics of easy metastasis and recurrence after operation,the mortality,mortality and disability rate of female patients in my country always high.Therefore,early diagnosis and treatment of breast cancer is particularly important for female patients.Biomarkers that have the potential to predict the survival of breast cancer patients or help make treatment decisions,and their heterogeneity in treatment and prognosis are essential for individualized treatment.So,studying the early pathogenesis and prognostic factors of breast cancer and finding potential new therapeutic targets for the early diagnosis,treatment,and prognosis of breast cancer have become a hot project of clinical research.This article is based on public databases and aims to find mRNAs that can be used as biomarkers of breast cancer.Methods: To use the transcriptome sequencing data set of the Cancer Genome Atlas and the Gene Expression Omnibus for differential analysis to obtain mRNAs that are both up-regulated and down-regulated in breast cancer.Then we perform functional enrichment analysis on the co-upregulated and downregulated mRNAs,that is,targeted functional analysis,and construct a protein interaction network.We use the least absolute contraction and selection operation LASSO model to perform regression analysis to construct a prognostic model to identify high-risk prognostic cases and low-risk cases,and use the validation set to verify the effect.Results: A total of 176 up-regulated mRNAs and 562 down-regulated mRNAs were identified.Mitosis and amoebic cell migration are the main enrichment pathways for up-regulation and down-regulation,respectively.The PPI network is mainly composed of 6 modules.The risk prognosis model consists of 16 mRNAs including ATP5 B,DCUN1D4,FAM47E-STBD1,INPP5 A,MMGT1,MRO,MURC,PGK1,RPL29,SDCBP2,SIPA1L1,STXBP5,TARS,TMEM233,WWOX and ZNF674.The area under the receiver operating characteristic curve for the training set and the validation set for one,three and five years are 0.820,0.792,0.747 and 0.741,0.747,0.699 respectively.Conclusion: The expression of mRNA is related to the postoperative condition of female tumor patients.The research results provide candidate biomarkers for the diagnosis and prognosis of breast cancer.A breast cancer prognostic model constructed from 16 mRNAs,it can be used to guide the prognosis of breast cancer patients,and at the same time,it provides a bioinformatics basis for further elucidating the molecular pathological mechanism of breast cancer.