Bioinformatic Approach to Identify Positive Prognostic <i>TGFB2</i>-Dependent and Negative Prognostic <i>TGFB2</i>-Independent Biomarkers for Breast Cancers.

ABSTRACT: Breast cancer is highly heterogeneous, with multiple subtypes that differ in molecular and clinical characteristics. It remains the most common cancer among women worldwide. We conducted a hypothesis-generating study using a bioinformatics approach in order to identify potential prognostic biomarkers for breast cancer patients across multiple molecular subtypes. Given the influential role of the transforming growth factor beta (TGFB) pathway in shaping the immune microenvironment, we focused on the isoform, transforming growth factor beta 2 (TGFB2), which is upregulated in tumors, to identify TGFB2-dependent and -independent biomarkers for breast cancer patients' overall survival (OS) responses. We evaluated the impact of TGFB2 mRNA expression, in conjunction with othe

SUBMITTER: Qazi S 

PROVIDER: S-EPMC12692321 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature