Xiao He ¹ Xianjie Cheng ² Zhun Zhang ³ Lanhui Chen ⁴ Changjun Xie ⁵ Mengjie Tang ^4*

• ¹ The Second Department of Breast Surgery, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University / Hunan Cancer Hospital, Changsha, China
• ² Department of Breast and Thyroid, the Xiangya Boai Rehabilitation Hospital, Changsha, China
• ³ Department of Breast and Thyroid Surgery, The Third Xiangya Hospital, Central South University, Changsha, China
• ⁴ Department of Pathology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University / Hunan Cancer Hospital, Changsha, China
• ⁵ Department of Oncology, the Second Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, China

Breast cancer (BRCA) has a high incidence among women, with poor prognosis and high mortality. Efferocytosis is a process of phagocytosis of abnormal cells and is of great value in tumor research. Our study seeks to create a predictive model for BRCA using efferocytosis-related genes (ERGs) to explore the significance of efferocytosis in this disease. In this research, we employed differential analysis along with univariate Cox regression to identify genes linked to prognosis in BRCA patients. We then categorized BRCA patients into distinct groups using consensus clustering based on prognosis genes. We performed survival analysis, PCA, and t-SNE to verify these groups. We evaluated the enrichment of metabolic pathways within the detected clusters using GSVA and GSEA. Additionally, ssGSEA was used to examine changes in immune infiltration and enrichment. We constructed a risk prognostic model utilizing multivariable Cox regression and LASSO analyses, and subsequently validated its predictive accuracy by stratifying patients according to the median risk score. Ultimately, we pinpointed crucial independent prognostic genes and explored their expression, roles, and immune characteristics in both laboratory and live models. Findings revealed 52 DEGs, of which 21 were significantly linked to BRCA outcomes. These 21 genes were utilized for consensus clustering to categorize BRCA patients into two subtypes. Subtype B was linked to a worse prognosis compared to Subtype A, though both subtypes were distinguishable. The enriched pathways were mainly concentrated in Subtype A and were actively expressed in this group. Following this, a prognostic risk model was constructed using five risk genes, which were proven to possess significant predictive value. A significant link was identified between the immune microenvironment and the risk-associated genes and scores. IL33 was identified as an independent prognostic gene with important research value. Its in vivo expression results aligned with the data analysis findings, showing low expression in BRCA. Furthermore, the overexpression of IL33 significantly suppressed the growth and movement of BRCA cells, while also enhancing their vulnerability to destruction by activated CD8+ T cells. This study has significant guiding value for the clinical treatment and prognosis of BRCA.