Novel joint lipid score based on longitudinal metabolic remodeling patterns predicts chemotherapy response in luminal breast cancer
Year: 2026
Type: article
Study design: Observational Study
Abstract: Luminal breast cancer typically exhibits low sensitivity to neoadjuvant chemotherapy(NAC). Identifying reliable biomarkers for predicting treatment response is crucial for optimizing individualized therapy. This study aims to clarify the dynamic changes in peripheral blood lipid parameters during chemotherapy and their predictive value for achieving pathological complete response(pCR). Data from 202 Luminal breast cancer patients who underwent standardized chemotherapy regimens were retrospectively collected. Serial measurements of total cholesterol(TC), triglycerides(TG), high-density lipoprotein(HDL), and low-density lipoprotein(LDL) levels at nine time points were obtained. Group-based trajectory modeling was employed to identify distinct metabolic trajectory patterns. Furthermore, a composite lipid score was developed by integrating these four parameters, and its predictive performance for pathological response was validated. Patients who achieved pCR exhibited higher baseline levels of TC and LDL. In contrast, those achieved Non-pCR displayed a progressive increase in lipid parameters during the entire chemotherapy period. The composite lipid score showed superior predictive performance. With an area under the curve of 0.957 (95% CI: 0.917-0.998), this score served as a robust predictor independent of conventional clinicopathological factors. Dynamic changes in lipid metabolism during NAC are strongly correlated with pCR. The composite lipid score facilitates early and accurate evaluation of treatment response in Luminal breast cancer, offering a simple yet effective metabolic tool to aid in clinical decision-making optimization.
Source: BMC Cancer
Institution: Guangzhou Medical University
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,390
OpenAlex ID: W7221645116
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