An In Silico Analysis Identified FZD9 as a Potential Prognostic Biomarker in Triple-Negative Breast Cancer Patients

Daniel Rodrigues de BASTOS, Mércia Patrícia Ferreira Conceição, Ana Paula Picaro Michelli, Jean Michel Rocha Sampaio Leite, Rafael André da Silva, Ricardo Cesar Cintra, Jeniffer Johana Duarte Sanchez, Cesar Augusto Sam Tiago Vilanova-Costa, Antonio Márcio Teodoro Cordeiro Silva

Abstract

Objective: Breast cancer (BC) is the main cause of cancer-related deaths in women across the world. It can be classified into different subtypes, includingtriple-negative (TN), which is characterized by the absence of hormone receptors for estrogen and progesterone and the lack of the human epidermal growthfactor receptor 2. These tumors have high heterogeneity, acquire therapeutic resistance, and have no established target-driven treatment yet.The identification of differentially expressed genes in TN breast tumors and the in silico validation of their prognostic role in these tumors.Materials and Methods: We employed a microarray dataset and, by using the GEO2R tool, we identified a list of differentially expressed genes. The insilico validation was conducted using several online platforms including the KM Plotter, cBioPortal, bc-GenExMiner, Prognoscan, and Roc Plotter.Results: We observed that FZD9 was among the top differentially expressed genes in a cohort of patients with different TNBC subtypes. The FZD9expression was significantly different in TN breast tumors than in non-TN (nTN) breast tumors (p