Abstract
Abstract Drug discovery continues to be refined to enhance efficiency, yet >80% of new drugs fail in the clinical trial stage. It is apparent that a novel approach is needed. COMPASS is a transomic analysis platform that integrates data across multiple omics layers; genomics, transcriptomics, proteomics, and phosphoproteomics. This analysis allows us to interpret complex biological relationships and provide a functional map of the biochemical drivers of disease. We have used EGFR inhibitor (EGFRi) resistance as a case study. EGFRi have been successful in treating non-small cell lung cancer (NSCLC) patients with activating EGFR mutations (EGFRm), however, this success is temporary. The emergence of resistance is a problem and limits long-term treatment for many patients, even with osimertinib, a third-generation inhibitor and current standard of care. As resistance to EGFRi occurs through mutations in EGFR we adopted a novel strategy using COMPASS to identify and validate alternative, non-EGFR targets that could potentially recapitulate the pharmacological effects of EGFRi in EGFRm NSCLC. The transomic signatures of EGFRi were generated using a NSCLC cell line containing the activating mutation ex19del. The drug concentration required to inhibit cell growth (IC50) was first determined. For transomic analyses, cells were incubated for 24 h with the drug IC50 concentration and harvested for genomic, transcriptomic, proteomic, and phosphoproteomic analyses. We have previously shown transomics analysis can differentiate between EGFRi that have been designed to treat EGFRm NSCLC with the transomics signature for osimertinib being significantly different from comparator drugs that failed during drug development. We employed our proprietary target prioritization algorithm to further analyze the omics data to identify and rank novel targets. Targets were then filtered to select those with an available pharmacological tool compound (PTC). The PTCs were used to evaluate the targets in a xenograft model of osimertinib resistant NSCLC, PC9-Del19/T790M/C797S; which contains the activating EGFR mutation (ex19del), and two mutations conferring EGFRi resistance, T790M gatekeeper mutation, and C797S which confers resistance to osimertinib. Of the targets tested 82% (9/11) were associated with >25% inhibition of tumor growth. Furthermore, 36% (4/11) targets were associated with >50% inhibition by the PTCs, with inhibition of one target giving >85% inhibition resulting in stasis of tumor growth. Future work will investigate targets using gene silencing, as PTCs were not available for many of the novel high-ranked targets. These data show that using COMPASS transomic analysis, it is possible to identify novel drug targets to treat difficult-to-treat cancers such as EGFRi-resistant NSCLC and provides validation of this discovery platform by disease-relevant in vivo pharmacology. Further validation studies are ongoing against other difficult-to-treat cancers to identify novel clinical targets and drug candidates. Citation Format: Christopher J Nicholson, Samuel J Roth, Arudhir Singh, Caitlin Brown, Simon P Fricker, Jon Hu, Samantha Dale Strasse. Circumventing EGFR inhibitor resistance in NSCLC using transomics [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr C052.
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