Phagocytosis-Regulators-Based Signature to Predict the Prognosis and Chemotherapy Resistance for Breast Cancer Patients

Abstract

Phagocytosis is crucial in tumor surveillance and immune function. The association between phagocytosis and the outcomes of breast cancer patients has not been well-determined. In this study, data were downloaded from the cancer genome atlas (TCGA) and gene expression omnibus (GEO) databases to investigate the role of phagocytosis in breast cancer. Data from the TCGA and GEO databases were used to investigate the prognostic role of phagocytosis in breast cancer. Then, we performed pathway enrichment analysis, copy number variation (CNV) and single-nucleotide variant (SNV) analyses, immune infiltration analysis, calculation of tumor purity, stromal score, and immune score, and consistent clustering. We also constructed a phagocytosis-regulators-based signature system to examine its association in survival and drug response. The genomic and expression differences in the phagocytosis regulators in breast cancer were systematically analyzed, explaining the widespread dysregulation of phagocytosis regulators. Using the investigated association of phagocytosis regulators with the prognosis and tumor immune environment, we constructed a prognostic model based on phagocytosis regulators. We discovered that patients with high risk scores had a poor prognosis and were negatively associated with immune functions. The model had preferential predictive performance and significantly consistent drug-resistance prediction results. Our findings suggest that the phagocytosis-factors-based scoring system can be used as a novel prognostic factor, serving as a powerful reference tool for predicting prognosis and developing methods against drug resistance.