Multi-omics characterization of cachexia-related genes reveals prognostic signatures and immune landscape in breast cancer.

BACKGROUND

Cancer cachexia is a multifactorial syndrome affecting cancer prognosis and immune microenvironment. However, the roles of cachexia-related genes (CRGs) in breast cancer remain unclear.

METHODS

We performed differential expression analysis and weighted gene co-expression network analysis (WGCNA) on TCGA-BRCA data to identify key CRGs. A prognostic model was constructed using LASSO-Cox regression. Immune infiltration and treatment sensitivity were assessed, and single-cell RNA-seq analyses were conducted to explore gene function and cell-cell interactions.

RESULTS

A total of 82 CRGs were identified, and an 11-gene prognostic model was constructed, showing high predictive accuracy across multiple cohorts. Based on this model, we created a new risk score (Cachexia-related Risk Score for Breast Cancer, CRSBC) to categorize patients into high and low-risk groups. Low-risk patients had a better prognosis and good immune infiltration with higher sensitivity to immunotherapy. Single-cell analysis revealed HCCS as a key gene enriched in epithelial cells (breast cancer cells) and involved in macrophages recruitment via the MIF signaling pathway.

CONCLUSIONS

This study reveals the prognostic and immunological significance of CRGs in breast cancer and highlights HCCS as a potential therapeutic target.