{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T05:24:59Z","timestamp":1787117099727,"version":"build-2736575974"},"reference-count":35,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T00:00:00Z","timestamp":1787097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Oncol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Triple-negative breast cancer (TNBC) shows marked intratumoral heterogeneity and variable responses to neoadjuvant chemotherapy (NAC), but the cellular determinants of treatment response remain incompletely defined.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We analyzed the scRNA-seq dataset GSE161529 to characterize TNBC cellular states and used bulk cohorts, including GSE25066 and GSE58812, for NAC response-related signature evaluation and clinical validation. Cell types and subtypes were identified by t-SNE clustering. A permutation-based NACR score estimated chemotherapy-response potential. Differentiation hierarchies were reconstructed using CytoTRACE 2 and Monocle 2, and cell-cell communication was inferred with CellChat. Prognostic value was evaluated by Kaplan-Meier analysis, drug sensitivity was predicted using pRRophetic\/GDSC, and\n                      <jats:italic>in vitro<\/jats:italic>\n                      validation used MDA-MB-231-derived C2-like sensitive and C4-like resistant TNBC models.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Nine major cell populations were identified, with cancer cells (49.3%) showing the highest NACR scores. Four cancer cell subtypes were delineated: C2 was enriched in predicted NACR-high groups, whereas C3\/C4 correlated with low predicted response. Three tumor-associated macrophage (TAM) subtypes were identified, with TAMs + SLPI associated with high predicted NACR and TAMs + CXCL9 with low predicted NACR. Pseudotime analysis revealed increasing NACR scores along the cancer cell trajectory (C4 to C2) and decreasing scores along the TAM trajectory. Predicted NACR-high tumors showed dominant CAF-cancer cell interactions, whereas predicted NACR-low tumors showed endothelial cell-CAF\/TAM communication via PDGFB-PDGFRB and ICAM2-ITGAM\/ITGB2. The NACR signature was associated with overall survival (log-rank p = 0.034).\n                      <jats:italic>In vitro<\/jats:italic>\n                      experiments confirmed a 12.81-fold IC50 difference between C2-like and C4-like models and validated subtype markers.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This integrative analysis identifies response-associated cancer cell and TAM states and nominates PDGFB-PDGFRB signaling as a candidate resistance-associated pathway, providing potential biomarkers and therapeutic targets for precision TNBC therapy.<\/jats:p>\n                  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