Bioinformatics Combined With Biological Experiments to Identify the Pathogenetic Link of Type 2 Diabetes for Breast...

Area of Science:

• Oncology
• Endocrinology
• Genetics

Background:

• Type 2 diabetes mellitus (T2DM) is a significant risk factor for breast cancer (BC), increasing incidence and worsening patient prognosis.
• Women with both T2DM and BC face poorer outcomes and treatment resistance, highlighting the need to understand their comorbidities.

Purpose of the Study:

• To identify key pathogenic molecules linking T2DM and BC.
• To elucidate potential therapeutic targets for improving BC outcomes in diabetic patients.

Main Methods:

• Bioinformatic analyses including weighted gene co-expression network analysis (WGCNA), differentially expressed gene (DEG) analysis, and machine learning.
• Single-cell RNA sequencing and biological experiments (CCK-8, colony formation, wound healing, transwell assays, immunohistochemistry, immunofluorescence) were employed.

Main Results:

• 27 common hub genes were identified between T2DM and BC, enriched in pathways like focal adhesion and MAPK signaling.
• CCNB2, XRCC2, and CENPI were identified as key genes associated with poor BC prognosis and elevated in BC tissues from diabetic patients.
• Hyperglycemia increased CCNB2, XRCC2, and CENPI expression in BC cells, promoting proliferation and migration, effects partially reversed by gene knockdown.

Conclusions:

• CCNB2, XRCC2, and CENPI are proposed as critical mediators linking T2DM and BC progression.
• Targeting CCNB2, XRCC2, and CENPI may offer a strategy to mitigate the negative impact of T2DM on BC outcomes.