Identification of microRNAs influencing triple-negative breast cancer through bioinformatics analytical approaches

Introduction Breast cancer (BC) is the most common cause of cancer death in women worldwide. It can be divided into several subtypes, including triple-negative (TN) tumors, a subtype of breast cancer with high heterogeneity and invasiveness, and limited targeted therapies. Early diagnosis of triple-negative breast cancer (TNBC) has been hindered by the lack of important diagnostic and prognostic indicators. Material and method In this study, we aimed to identify genes and regulatory miRNAs associated with TNBC that may provide new insights into the genetic dysregulation in TNBC. We used a microarray dataset from the Gene Expression Omnibus (GEO) database containing approximately ۲۶۵ samples. We used the GEO۲R tool to identify significantly differentially expressed genes (DEGs) between TN and non-TN tumors. To discover core genes in the PPI network, use the cytoHubba plugin in Cytoscape. We used gene expression profile interaction analysis (GEPIA) to identify the expression of hub genes, and the regulated miRNAs of the identified hub genes were provided by targetcan, mirbase, mirwalk, and mirable software. Result According to the analysis of GSE, there were ۵۴,۶۷۶ differentially expressed genes (p values). ۶۳ up-regulated genes and ۱۶۴ down-regulated genes were | ۱.۵ |. Based on the PPI network, EN۱, GABRP, and SHC۴ play important roles in the progression of TN tumors. In our study, comparing TN tumors with non-TN tumors, we found that the hub gene EN۱ was regulated by the decreased expression of hsa-mir-۲۹b-۳p, and hsa-mir۳۳۵-۳p regulated the GABRP gene. Discussion Because TNBC has a high mortality rate, early molecular diagnosis plays an important role in favorable prognosis. To date, numerous miRNAs have been found to be involved in breast cancer development, and newly identified genes and miRNAs may help elucidate the underlying molecular mechanisms of TNBC development and open potential new avenues for personalized treatment. Therefore, bioinformatics analysis may provide new insights into the developmental mechanisms of TNBC and other types of breast cancer. This study suggests that further in vitro analyses are needed to confirm our results.

کلیدواژه ها:

Breast cancer ، triple-negative tumours ، miRNA ، bioinformatic