Abstract PS4-01-23: Transcriptomic Profiling and Immune-metabolic Prediction Model Construction for Neoadjuvant Chemotherapy Response in Triple-Negative Breast Cancer Patients

Abstract Background Triple-negative breast cancer (TNBC) had great tumor heterogeneity and lacks effective therapeutic targets. The addition of immunotherapy to neoadjuvant chemotherapy (NAC) has dramatically improved pathologic complete response rates (pCR) in TNBC, but some patients may be overtreated as they could achieve pCR with NAC only. Thus, identifying the molecular features associated with efficacy of NAC and finding robust biomarkers to select patients who are sensitive to chemotherapy was crucial. Patients and Methods: RNA sequencing analysis was performed on paired tumor samples collected before and after neoadjuvant treatment with nab-paclitaxel and carboplatin from 44 TNBC participants enrolled in the prospective NeoPATH clinical trial (ClinicalTrial.gov identifier: NCT0390780). Transcriptomic features were compared in patients with different treatment responses. Changes in molecular biology after treatment were illustrated in matched pre- treatment and post-treatment samples as well. Univariate regression and lasso regression were utilized to construct the predictive signature for NAC. Results The results showed that patients achieving pCR had upregulated immune-related signatures suggesting more active immune response and decreased metabolic signatures indicating less energy production. Increases in both anti-tumor immune cell infiltration and immune molecular expression were observed after neoadjuvant chemotherapy, inferring the activation of immune microenvironment. Multiple immune-related signatures were found to be positively associated with treatment response, while metabolic signatures were negatively associated with the response. Based on these findings, the immune-metabolic predictive signatures were further built and validated to predict the treatment response of neoadjuvant nab-paclitaxel and carboplatin for TNBC (AUC, 0.719 in the train set, 0.787 and 0.717 in the validation sets). Conclusions Overall, our study delineates distinct molecular profiles between pCR and non-pCR TNBC patients following neoadjuvant nab-paclitaxel/carboplatin. The developed immune-metabolic signature effectively identifies treatment-sensitive tumors, while observed transcriptomic changes post-therapy may inform future targeted drug development. Citation Format: S. Ding, J. Wu, D. Liu, Y. Fang, W. Wang, L. Zhu. Transcriptomic Profiling and Immune-metabolic Prediction Model Construction for Neoadjuvant Chemotherapy Response in Triple-Negative Breast Cancer Patients abstract. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS4-01-23.