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

Authors :
Andrea Viale
I-Lin Ho
Timothy P. Heffernan
Wantong Yao
Chieh-Yuan Li
Giannicola Genovese
Annette Machado
Johnathon L. Rose
Sanjana Srinivasan
Eiru Kim
Anirban Maitra
Sahil Seth
Angela K. Deem
Michael P. Kim
Mustafa Syed
Traver Hart
Christopher A. Bristow
Eugene J. Koay
Giulio Draetta
Paola A. Guerrero
Michael Peoples
Alessandro Carugo
Joseph R. Daniele
Jaewon J. Lee
Publication Year :
2020
Publisher :
Cold Spring Harbor Laboratory, 2020.

Abstract

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.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........9ce47526dedf618984cae35b8b3ff12b
Full Text :
https://doi.org/10.1101/2020.09.17.302034