Discovering Breast Cancer Biomarkers Candidates through mRNA Expression Analysis Based on The Cancer Genome Atlas Database.

Abstract

Background: Research on the discovery of tumor biomarkers based on big data analysis is actively being conducted. This study aimed to secure foundational data for identifying new biomarkers of breast cancer via breast cancer datasets in The Cancer Genome Atlas (TCGA). Methods: The mRNA profiles of 526 breast cancer and 60 adjacent non-cancerous breast tissues collected from TCGA datasets were analyzed via MultiExperiment Viewer and GraphPad Prism. Diagnostic performance was analyzed by identifying the pathological grades of the selected differentially expressed (DE) mRNAs and the expression patterns of molecular subtypes. Results: Via DE mRNA profile analysis, we selected 14 mRNAs with downregulated expression (HADH, CPN2, ADAM33, TDRD10, SNF1LK2, HBA2, KCNIP2, EPB42, PYGM, CEP68, ING3, EMCN, SYF2, and DTWD1) and six mRNAs with upregulated expression (ZNF8, TOMM40, EVPL, EPN3, AP1M2, and SPINT2) in breast cancer tissues compared to that in non-cancerous tissues (p < 0.001). Conclusions: In total, 20 DE mRNAs had an area under cover of 0.9 or higher, demonstrating excellent diagnostic performance in breast cancer. Therefore, the results of this study will provide foundational data for planning preliminary studies to identify new tumor biomarkers.