Cancer Stem Cell Characteristics by Network Analysis of Transcriptome Data Stemness Indices in Breast Carcinoma

Area of Science:

• Oncology
• Genomics
• Biomarker Discovery

Background:

• Breast cancer (BC) is a global health concern affecting women worldwide.
• Identifying reliable prognostic biomarkers is crucial for effective breast cancer management.

Purpose of the Study:

• To screen for potential prognostic biomarkers in breast cancer.
• To analyze stemness-related genes for their association with breast cancer outcomes.

Main Methods:

• Utilized RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA).
• Integrated Weighted Gene Co-expression Network Analysis (WGCNA) with BC mRNAsi data.
• Screened key stemness-related genes and analyzed their prognostic value and immune infiltration.

Main Results:

• Significantly higher mRNAsi expression was observed in BC tissues compared to normal samples (P=1.791e-43).
• Identified 38 key genes within the turquoise module, highly correlated with stemness.
• Lower expression of these key genes was significantly associated with longer overall survival, distant metastasis-free survival, and relapse-free survival.

Conclusions:

• This research highlights the significant role of stemness-related genes in breast cancer prognosis.
• The identified key genes show potential as prognostic biomarkers for breast cancer.
• Further clinical validation is recommended to integrate these genes into clinical practice for prognosis evaluation.