Abstract Background: TNBC represents approximately 20% of all breast cancers, and is an aggressive subtype. The KEYNOTE-522 trial established neoadjuvant pembrolizumab with chemotherapy as the standard of care for early-stage TNBC, significantly improving pathological complete response (pCR) rates. However, approximately 30-45% do not achieve a pCR, and the biological mechanisms that determine response remain unclear. Identifying a robust predictive immune biomarker is essential for patient (pt) selection and developing new strategies to overcome resistance. Therefore, this study aimed to discover circulating determinants of pCR in TNBC receiving neoadjuvant chemo-immunotherapy. Methods: Blood samples were collected from 41 TNBC pts receiving neoadjuvant chemo-immunotherapy at baseline (BL), on cycle 3 day 1, and post-surgery. Peripheral Blood Mononuclear Cells (PBMCs) were isolated using standard density gradient centrifugation. High-parameter flow cytometry (HPFC) was performed to characterize immune cell subsets and phenotypes. Single-cell RNA sequencing was conducted using the Parse Biosciences platform (pipeline split-pipe v1.2.0) to enable high-throughput transcriptomic profiling at single-cell resolution. Transcriptomic data from single-cell sequencing was processed and analyzed using Seurat pipeline to identify differentially expressed genes and explore cellular pathways across pt samples. Concurrently, plasma samples were analyzed using the Olink® platform to quantify cytokine levels and explore biomarkers associated with responders. Results: Of the 41pts included, 22 achieved pCR (defined as ypT0/isN0, 53.6%) and 13 (31.7%) had residual disease (rd+). At BL, HPFC analysis showed increased levels of immature activated neutrophils (CD15+CD16-CD86+CD80+, 50.4% vs. 2.1%) among pts who achieved a pCR whereas higher levels of mature neutrophils with an immunosuppressive phenotype (CD15+CD16+CD163+CX3CR1+, 24% vs. 6%) and exhausted T-cells (CD57+LAG3+TIGIT+TIM3+, 9% vs. 2%) were observed among rd+ pts. Single-cell transcriptomic analysis showed BL pCR pts had more B-cells (7.5% vs. 5.1%) and fewer classical monocytes (15.9% vs. 22.4%). Dynamic changes from BL to post-surgery revealed opposing trajectories: pCR pts showed decreases in CD4+ (26.9%→23.3%), CD8+ (19.6%→17.4%), and regulatory T-cells (1.9%→1.7%), with increases in NK cells (8%→9.3%) and classical monocytes (15.9%→22.1%), while rd+ pts showed opposite trends. Pathway analysis identified a higher BL interferon state (lymphocyte-driven) in pCR pts. On-treatment, pCR pts had a myeloid-driven TNFA/NFKB inflammatory response; rd+ pts mounted an ineffective interferon response with TNFA/NFKB downregulation. Proteomics analysis revealed higher levels of CCL23, CDCP1, and ANXA4 in rd+ pts. Machine learning models identified TRAIL and NADK as positive BL predictors of pCR, while DNER, LIF-R, and KYAT1 were identified as negative predictors. Volcano plots confirmed responders' proteomes underwent far greater dynamic changes during treatment. Conclusions: This multi-omic analysis reveals that response to immunotherapy in TNBC may be largely predetermined by the baseline immune state. Pts with a pCR exhibited an immune profile characterized by accumulation of active T-cell reserves and a pro-immune proteomic milieu (e.g., high TRAIL), allowing for an effective anti-tumor response to be induced upon treatment. Conversely, residual disease was associated with a pre-existing anti-immune state characterized by the accumulation of both suppressive myeloid cells and secreted factors (e.g., CCL23, ANXA4), leading to dysfunctional T-cell activity. These findings support developing a predictive baseline biomarker panel to guide pt selection and identify those who may require novel strategies to overcome resistance. Citation Format: N. Stabellini, P. B. Parthasarathy, I. Gautam, J. Bassit, P. A. Rayman, M. Patel, A. Moen, B. Race, E. Mundell, A. Trevino, J. Powers, P. G. Pavicic, B. Moftakhar, T. Mizukami, C. Owusu, T. J. Alban, V. Makarov, T. A. Chan, A. J. Montero, M. C. Diaz-Montero. Circulating determinants of response to immunotherapy in triple negative breast cancer (TNBC) 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 PD7-01.
Stabellini et al. (Tue,) studied this question.