Breast cancer-related complications affect patients’ quality of life and survival. How to identify and stratify the risks of breast cancer-associated complications? And what are the mechanisms behind breast cancer-associated complications? The project aims to determine breast cancer-related complications, develop risk stratification models, and decode the underlying mechanisms based on multi-omics data. This will help in improving the clinical management and outcomes of breast cancer patients.
Breast cancer is a major public health concern and the most common cancer among women globally. With advancements in diagnosis and treatment, survival rates have improved; however, the multi-system complications caused by anti-tumor treatments cannot be ignored. These complications include various conditions that arise during or after breast cancer therapy, such as dyslipidemia, cognitive decline, osteoporosis, etc. Research indicated that among early-stage breast cancer patients, the proportion of deaths caused by non-cancer factors gradually increased with age, and in some populations, this proportion even exceeded the mortality risk from breast cancer itself. Among these factors, cardiovascular diseases have become the most common non-cancer cause of death in breast cancer patients. Therefore, early detection, and optimal management of breast cancer related complications are necessary. Currently, there is a lack of comprehensive and accurate methods to identify and stratify the risks of these complications. Understanding the mechanisms behind them is also limited. This proposed research project aims to fill these gaps by utilizing multi-omics data, providing a more holistic view of the phenotypic characteristics and biological processes involved in breast cancer associated complications. These insights will be used to build predictive models that stratify patients according to their risk levels.