A trajectory-coupled network bottleneck governs gemcitabine resistance in 3D PDAC tissue models

Abstract PDAC exhibits rapid chemoresistance, yet how drug-tolerant states arise remains unclear. Existing approaches miss how network topology evolves across cell-state transitions under drug pressure. A 3D PANC-1 tissue model on decellularized intestinal matrix was used for scRNA-seq across four conditions (control, GEM, TGF-β1, GEM+TGF-β1). Pseudotime trajectory inference was combined with dynamic PPI network analysis. Findings were cross-examined in a PDAC atlas (726,107 cells, 231 patients; Loveless et al., 2025). GEM resistance involved E2F1, mTOR, CDK1, AURKA, TPX2, TOP2A, and BIRC5. TGF-β1 drove EMT resistance via KRAS, glycolysis, and hypoxia, inducing SPOCK1, MBOAT2, COL5A1, ADAMTS6, THBS1, and FN1. Trajectory-coupled network analysis revealed an emergent bottleneck when G1→S and TGF-β1-induced EMT co-occurred: CDK1 centrality spiked selectively, with CDKN1A as critical regulator. This CDK1–CDKN1A–WEE1 axis defines an “S-phase persistence” state enriched for GEM survivors. Atlas cross-examination confirmed 8.7-fold metastatic enrichment of triple-positive cells and EMT–cell-cycle coupling. Trajectory-coupled network topology analysis identifies CDK1–CDKN1A–WEE1 as a chemoresistance bottleneck corroborated in 726,107 patient cells. The framework generalizes to drug resistance across cancer types.