Development and validation of a novel bone metastasis-associated prognostic model for breast cancer

Abstract Background Bone is the main location where breast cancer spreads, which can greatly impact the outlook and well-being of those affected by the disease. Novel targets are crucial in clinical practice as traditional treatment for breast cancer patients with bone metastases is mostly futile. Current therapy for bone metastases in breast cancer patients is hindered by a lack of understanding of the root causes. Methods We created a prognostic bone metastasis signature called PABMS. The Prognostic Analysis of Bone metastases Score (PABMS) utilised genes associated with bone metastases to forecast the overall prognosis of breast cancer patients. The clinical significance and immunological environments of the signature were exhaustively examined. Results Differentially expressed genes (DEGs) associated with bone metastasis were identified by utilising data from the GSE14666 database in order to distinguish disseminated tumour cells (DTCs) from metastatic tumour cells (MTCs). The bone metastasis-related signature (PABMS), comprised of four genes (ZER, SBK1, L1CAM, and CXCL1), was identified. This signature exhibited a robust correlation with the overall survival of patients diagnosed with breast cancer. This was ascertained through the analysis of transcriptome data from a specific cohort of patients. The efficacy of the four-gene signature in distinguishing bone metastases was validated through the examination of protein levels in an independent cohort. There was a significant correlation between a high-risk score and an extremely adverse patient outcome, according to the findings. Stratification analysis and multivariate Cox regression demonstrated that the PABMS functioned independently as a prognostic factor. Risk score was found to positively correlate with the antigen-presenting process, inflammatory response, and expression levels of many immunosuppressive checkpoint molecules (PD-1, B7-H4, galectin-9, and FGL-1). The findings suggested that patients at high risk exhibited inhibition of the immune response. Conclusion This work created a practical signature using differentially expressed genes associated with bone metastases. This attribute has the potential to function as a highly effective predictive instrument and contribute to the enhancement of the cancer therapy methodology.