Telomere-Associated Gene Signatures Correlate with Prognosis, Tumor Microenvironment, and Chemosensitivity in Breast Cancer.

Abstract

BACKGROUND Telomeres are strongly associated with cancer, as their shortening over time is associated with an increased risk of tumor growth and progression. However, the prognostic value of telomere-related genes (TRGs) in breast cancer has not been systematically elucidated. MATERIAL AND METHODS The transcriptome and clinical data of breast cancer were downloaded from TCGA and GEO databases, and prognostic TRGs were identified by differential expression analysis and univariate and multivariate Cox regression analyses. Gene set enrichment analysis (GSEA) of different risk groups was performed. Molecular subtypes of breast cancer were constructed by consensus clustering analysis, and the differences in immune infiltration and chemotherapy sensitivity between subtypes were analyzed. RESULTS Differential expression analysis revealed 86 significantly differentially expressed TRGs in breast cancer, of which 43 were significantly associated with breast cancer prognosis. A predictive risk signature consisting of 6 tumor-related genes (TRGs) was developed, which can accurately stratify patients with breast cancer into 2 distinct groups with significantly different prognoses. Significantly different risk scores were found among different racial groups, treatment groups, and pathological features groups. GSEA results showed that patients in the low-risk group had activated immune responses and repressed cilium-related biological processes. Consistent clustering analysis based on these 6 TRGs obtained 2 molecular models with significant prognosis differences, which revealed distinct immune infiltration and chemotherapy sensitivity. CONCLUSIONS This study conducted a systematic investigation of the expression pattern of TRGs in breast cancer and its prognostic and clustering implications, thereby offering a reference for utilizing it to predict prognosis and evaluate treatment response.