Identification of chromatin remodeling-related gene signature to predict the prognosis in breast cancer

Growing evidence highlights the critical role of chromatin remodeling in tumor development and progression. This study explores the relationship between chromatin remodeling-related genes (CRRGs) and breast cancer (BRCA). Public databases were used to retrieve the TCGA-BRCA and GSE20685 datasets. CRRGs were sourced from prior studies. Prognosis-associated CRRGs were identified using univariate Cox regression analysis. TCGA-BRCA BRCA samples were grouped into CRRG-related subtypes through consensus clustering analysis. Differential expression analysis was conducted in TCGA-BRCA (BRAC vs. control) and among subtypes to identify differentially expressed genes (DEGs). Candidate genes were obtained through the intersection of these DEGs. Prognostic genes were selected using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. Independent prognostic factors were identified, and a nomogram model was developed. Functional enrichment, immune infiltration, clinical relevance, and drug sensitivity analyses were subsequently performed. TCGA-BRCA BRCA samples were classified into two CRRG-related subtypes (clusters 1 and 2) based on prognosis-associated CRRGs. A total of 141 candidate genes were identified by intersecting 250 DEGs (cluster 1 vs. cluster 2) with 3,145 DEGs (BRCA vs. control). Five prognostic genes-LHX5, ZP2, GABRQ, APOA2, and CLCNKB-were selected, and a prognostic risk model was developed. In clinical samples, APOA2 (P = 0.0290) and GABRQ (P = 0.0132) expression were significantly up-regulated, CLCNKB (P < 0.0001) and ZP2 (P = 0.0445) expression were significantly down-regulated, while LHX5 (P = 0.1508) expression did not present a significant difference. A nomogram was created, and calibration and Receiver Operating Characteristic (ROC) curves demonstrated its superior predictive ability for BRCA. Gene Set Variation Analysis (GSVA) revealed 16 pathways, such as "mTORC1 signaling" and "E2F targets," were enriched in the high-risk group, while 9 pathways, including "estrogen response early" and "myogenesis," were enriched in the low-risk group. Additionally, significant differences in immune cell types, including CD8⁺ T cells and follicular helper T cells, were observed between the two risk groups. The risk score was also significantly associated with six drugs, including AZD1332 1463 and SB505124 1194. This study presents a prognostic model based on five genes (LHX5, ZP2, GABRQ, APOA2, and CLCNKB) for BRCA, offering a novel perspective on the link between CRRGs and BRCA.