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.