Dandekar, G. | bioRxiv Science

bioRxiv2026

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

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-{beta}1, GEM+TGF-{beta}1). 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-{beta}1 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-{beta}1-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.

systems biology↗

bioRxiv2021

Pan-cancer mapping of single T cell profiles reveals a TCF1:CXCR6-CXCL16 regulatory axis essential for effective anti-tumor immunity

Unleashing cytotoxic CD8+ T cells for effective cancer treatment requires understanding T cell states across different tumor microenvironments. Here, we developed an algorithm to recover both shared and tumor type specific programs and used it to analyze a scRNA-seq compendium of 38,852 CD8+ T cells from 141 patients spanning nine different human cancers. We uncovered a pan-cancer T cell dysfunction program that was predictive of clinical responses to immunotherapy and highlighted CXCR6 as a pan-cancer marker of dysfunctional T cells. In mouse models, CXCR6 increased following checkpoint blockade and was repressed by TCF1. Its ligand, CXCL16, was expressed primarily by myeloid cells, and was co-regulated with antigen presentation genes. CXCR6 deletion decreased Tox, CX3CR1, and Bcl2 expression, predisposing dysfunctional PD-1+Tim3+CD8+ T cells to apoptosis, and compromising tumor growth control. Our approach discovered a TCF1:CXCR6-CXCL16 regulatory axis essential for effective anti-tumor immunity, revealing a new perspective on T cell dysfunction and new opportunities for modulating this cell state.

immunology↗