Koay, E. J. | Search bioRxiv

bioRxiv2025

A spatial atlas of chemoradiation therapy in pancreatic cancer identifies cellular and microenvironmental determinants of persister populations

The molecular pathways involved in the response to radiation therapy in pancreatic ductal adenocarcinoma (PDAC) remain poorly understood. We aimed to elucidate the adaptive mechanisms and cellular interactions within PDAC to radiation therapy (RT). We constructed a transcriptomic landscape of the cellular subtypes and spatially resolved neighborhoods from 50 patient samples, including 16 longitudinally matched single cell RNA sequencing and 34 spatial transcriptomics specimens. To resolve shortcomings of cell-type mixtures in spatial data, we developed a novel statistical method called SpaCCI (spatially aware analysis of cell-cell interactions) to profile cell-cell interactions and ligand-receptor enrichment. This revealed CXCL12/TGF{beta}-driven persister cell niches where activated fibroblasts reprogram tumor- associated macrophages and spatially exclude stress-response CD8 T cells after RT. Persister cancer cells displayed transcriptional evidence of recalcitrance to metal-induced cell death pathways of ferroptosis and cuproptosis which were recapitulated in preclinical models. Our study reveals the selective pressures experienced by PDAC following RT that may help provide insight for future multimodal therapeutic strategies.

cancer biology↗

bioRxiv2020

Diversity Across the Pancreatic Ductal Adenocarcinoma Disease Spectrum Revealed by Network-Anchored Functional Genomics

Cancers are highly complex ecosystems composed of molecularly distinct sub-populations of tumor cells, each exhibiting a unique spectrum of genetic features and phenotypes, and embedded within a complex organ context. To substantially improve clinical outcomes, there is a need to comprehensively define inter- and intra-tumor phenotypic diversity, as well as to understand the genetic dependencies that underlie discrete molecular subpopulations. To this end, we integrated CRISPR-based co-dependency annotations with a tissue-specific co-expression network developed from patient-derived models to establish CoDEX, a framework to quantitatively associate gene-cluster patterns with genetic vulnerabilities in pancreatic ductal adenocarcinoma (PDAC). Using CoDEX, we defined multiple prominent anticorrelated gene-cluster signatures and specific pathway dependencies, both across genetically distinct PDAC models and intratumorally at the single-cell level. Of these, one differential signature recapitulated the characteristics of classical and basal-like PDAC molecular subtypes on a continuous scale. Anchoring genetic dependencies identified through functional genomics within the gene-cluster signature defined fundamental vulnerabilities associated with transcriptomic signatures of PDAC subtypes. Subtype-associated dependencies were validated by feature-barcoded CRISPR knockout of prioritized basal-like-associated genetic vulnerabilities (SMAD4, ILK, and ZEB1) followed by scRNAseq in multiple PDAC models. Silencing of these genes resulted in a significant and directional clonal shift toward the classical-like signature of more indolent tumors. These results validate CoDEX as a novel, quantitative approach to identify specific genetic dependencies within defined molecular contexts that may guide clinical positioning of targeted therapeutics.

cancer biology↗