Abstract
Breast cancer has become one of the most common malignant tumors in women. Although the emergence of molecular typing has greatly improved the prognosis of breast cancer patients, some patients still face drug resistance, recurrence and metastasis. At present, the development of effective biomarkers is still an important direction of breast cancer research. This study aims to provide new ideas for individualized treatment of breast cancer by identifying new biomarkers and constructing models to predict the prognosis of breast cancer patients. In this study, seven tumor-dependent genes associated with tumor proliferation were identified through the combined analysis of bulk-RNA sequencing and CRISPR-CAS9, and the mechanism of their potential promotion of tumor proliferation was initially analyzed. Immune infiltration analysis suggested these genes may be associated with the formation of immunosuppressive microenvironment. In addition, we constructed a gene signature based on seven genes that can predict prognostic risk in patients with breast cancer. The group with higher signature scores was associated with more GATA3 somatic mutations. Finally, we screened potential drugs suitable for high-risk groups to improve their outcomes. Our study provides potential therapeutic targets as well as individualized treatment strategies for breast cancer.