Abstract 2359: Identifying synergistic master regulators of pancreatic ductal adenocarcinoma tumorigenesis through CRISPR/Cas9 combinatorial genetic screens
Authors: Griffin Aaron T. , Turunen Mikko , Tomassoni Lorenzo , Olive Kenneth P. , Laise Pasquale , Califano Andrea 
Published: June 2022

Abstract
Pancreatic ductal adenocarcinoma (PDAC) is the third-leading cause of cancer-related mortality and is highly resistant to cytotoxic, targeted, and immune therapies. Compared to other cancers, PDAC is remarkable for its relatively uniform set of DNA alterations; unfortunately, these hallmark events are not currently targetable and other mutations known to confer sensitivity to specific drugs are uncommon. Consequently, cytotoxic combinations remain the standard of care, with most patients quickly exhibiting primary or secondary chemoresistance.
Previous studies have shown that transcriptional regulatory proteins can form small, highly interconnected and autoregulated modules that can initiate and maintain malignant tumor cell state, and that the Master Regulator (MR) protein they comprise represent a novel class of non-oncogene dependencies. We used the VIPER algorithm to identify MR proteins representing mechanistic regulators of the transcriptional state for 200 laser microdissected PDAC epithelial compartment samples, collected at Columbia University Irving Medical Center (CUIMC).
To systematically identify synergistic pairs of MRs, we designed a combinatorial CRISPR-Cas9 screen based on the Big Papi dual SaCas9/SpCas9 system which was used to systematically target all possible pairs of the top 50 MRs identified by VIPER analysis across 6 PDAC cell lines (KP4, PATU8988S, PANC1, HPAFII, BXPC3, MIAPACA2) with three guide-RNAs per gene, thus differentiating between potentially idiosyncratic, cell line-specific and highly conserved genetic interactions.
We also developed a novel nonparametric statistical method for inferring genetic interactions from this data based on the use of conditional Mann-Whitney U tests; our new analytical method significantly improved over a previously developed parametric model of synergy inference, demonstrating increased correlation between genetic interactions inferred from biological replicates of the same cell line while simultaneously prioritizing four established synthetic lethal gene pairs in the top 10 gene pairs following integration across all 6 cell lines: BCL2L1-MCL1, BCL2L1-BCL2L2, MAPK1-MAPK3, and SEC23A-SEC23B. The methods also identified 314 additional highly significant (FDR &lt; 0.05), yet never previously reported synthetic lethal interactions that are being validated using an array-based, low-throughput screening platform. We expect that the results of this screen will help elucidate mechanisms controlling the state of PDAC tumor cells and identify potentially druggable gene pairs.
Citation Format: Aaron T. Griffin, Mikko Turunen, Lorenzo Tomassoni, Kenneth P. Olive, Pasquale Laise, Andrea Califano. Identifying synergistic master regulators of pancreatic ductal adenocarcinoma tumorigenesis through CRISPR/Cas9 combinatorial genetic screens [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2359.