Comparative bioinformatics analysis of the Wnt pathway in breast cancer: Selection of novel biomarker panels associated with ER status.

Abstract

Breast cancer (BC) is a major global health concern, ranking among the most common neoplasms and representing one of the leading causes of cancer-related deaths worldwide. Early recognition and classification of BC subtypes are crucial for improving patient outcomes. Therefore, identifying novel biomarkers with diagnostic and prognostic significance is of great importance. The Wnt signaling pathway plays a significant role in BC by influencing various cell cycle regulation processes and stem cell renewal. This study aims to identify novel Wnt-associated biomarker panels for BC patients, composed of multiple molecular factors. A series of bioinformatical analyses have been employed, including weighted gene co-expression network analysis, differential expression analysis, Kaplan-Meier survival analysis, logistic regression model evaluation, and receiver operating characteristic construction. Thus, this study revealed potential diagnostic and prognostic signatures based on comprehensive analyses of BC patient data sourced from The Cancer Genome Atlas database. Consequently, four gene signatures were constructed: two differentiate ER+ from ER-BC: TTC8, SLC5A7, and PLCH1 for overall survival (OS); ZNF695, SLC7A5, and PLCH1 for disease free survival (DFS), while the other two effectively distinguish tumor from normal samples: SPC25, ANLN, KPNA2, SLC7A5 for OS; SPC25, KIF20A, SKA3, DTL, CDCA3, ANLN, TTK, RAD54L, MYBL2, ZNF695, and SLC7A5 for DFS.