Abstract 5658: Genome-scale CRISPR screen in 3D tumor models identifies EGFR-TKI resistance mechanisms in human NSCLC
Authors: Pranay Agarwal, Soon Youn Choi, Xin Liu, Jina Song, Maya Tureez, Aashka Mehta, Un Jae Baek, Kyuho Han, Hong-Pyo Lee
Journal: Cancer Research (2024)

Abstract INTRODUCTION: Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are the primary treatment for EGFR-mutated non-small-cell lung cancer (NSCLC). Despite Osimertinib, an FDA-approved EGFR-TKI, showing high selectivity for EGFR-activating mutations, resistance inevitably arises, leading to disease progression. The influence of genes within cancer on Osimertinib response remains unclear. To tackle this challenge, CRISPR screens have been extensively used. However, current CRISPR screens investigating EGFR TKI resistance heavily rely on 2D monolayer cell models, lacking the ability to replicate in vivo tumors accurately. In response, we conducted a genome-scale loss-of-function CRISPR screening employing 3D tumor models embedded in an extracellular matrix across various NSCLC cell lines. Utilizing a comprehensive panel of CRISPR screens in both 3D tumor models and 2D monolayer models, we systematically assessed how genetic alterations impact cell resistance and transformation against treatment with Osimertinib, in diverse cellular contexts. METHOD: Genome-scale CRISPR-Cas9 screens in 10 NSCLC cell lines used 3D tumor models and 2D cells to pinpoint genes pivotal for EGFR TKI resistance. Cas9-expressing cell lines were transduced with a lentivirus carrying 60,000 sgRNAs targeting ~20,000 human genes. Cells were cultured in both models and treated with optimized Osimertinib or DMSO, inducing 20-30% cell growth inhibition for 3 days. Post-treatment, cells were recovered for 4 days. This treatment cycle was repeated 3-4 times in 3D models and 2-3 times in 2D cells. The sgRNA composition in each pool was analyzed using Next Generation Sequencing after treatment cycles in both models. RESULTS: Upon analyzing CRISPR screening data across 10 distinct cell lines to assess drug phenotypes, we confirmed the enrichment of established resistance pathways like PI3K/AKT/mTOR, Hippo, and MAPK signaling pathways in both 2D monolayer cells and 3D tumor models. However, notable discrepancies in EGFR TKI resistance mechanisms were evident between these two models. Specifically, CRISPR screens conducted with 3D tumor models unveiled unique resistance mechanisms, notably the LKB1/AMPK/mTOR pathway (STK11, GSK3B), Ubiquitination (RNF7, ARIH2), and stabilization of E-cadherin adherens junction (NCKAP1, EXOC4) differing from those identified in conventional 2D monolayer model. Furthermore, the 3D tumor models exhibited significantly heightened enrichment of the MAPK and Hippo signaling pathways compared to their drug phenotype score in 2D monolayer cells. CONCLUSION: This study underscores the significance of employing the 3D tumor model in drug phenotype CRISPR screen. This approach recapitulates unique gene dependency patterns and interactions linked to EGFR-TKI resistance in a 3D tumor context, revealing potential targetable vulnerabilities context-dependent. Citation Format: Pranay Agarwal, Soon Youn Choi, Xin Liu, Jina Song, Maya Tureez, Aashka Mehta, Un Jae Baek, Kyuho Han, Hong-Pyo Lee. Genome-scale CRISPR screen in 3D tumor models identifies EGFR-TKI resistance mechanisms in human NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5658.