Abstract 828: Screen for actionable ERBB3 mutations

Abstract Activating mutations and copy number variations in ERBB genes have been shown to serve as oncogenic driver mutations and predictive biomarkers for ERBB inhibitor drugs. To address whether mutations in ERBB3 can affect the potential of ERBB3 to promote growth or affect sensitivity to ERBB inhibitors, we set up an unbiased functional screen for ERBB3 missense or nonsense mutations in the context of ERBB2/ERBB3 heterodimers. To this end, the iSCREAM (in vitro screen of activating mutations) pipeline, recently developed in our laboratory, was chosen. This platform exploits randomly mutated cDNA libraries of the gene of interest created with error-prone PCR and allows an unbiased assessment of growth-advantage conferred by thousands of mutations in parallel. To set up the model for screening actionable ERBB3 mutations, interleukin-3 (IL-3)-dependent Ba/F3 cells were engineered to express a homodimerization-incompetent ERBB2 V956R mutant together with ERBB3 constructs. The model was validated to serve as a readout for ERBB3's ability in activating ERBB2 kinase by demonstrating that cells expressing known transforming ERBB3 mutations, together with ERBB2 V956R, survived and expanded in the absence of IL-3. In contrast, control cells expressing ERBB2 V956R together with wild-type ERBB3 rapidly died in the absence of IL-3. The cell background with ERBB2 V956R expression was subsequently used as a target for retroviral expression of a cDNA library of randomly mutated ERBB3 constructs. The cells harboring activating ERBB3 mutations were allowed to evolve for 15-48 days. The identity of the mutations was determined from the surviving cell population by ERBB3-targeted next generation sequencing. The discovered activating mutations were validated by cloning them into expression vectors and addressing their activity by Western analyses and growth assays in Ba/F3, NIH-3T3, and MCF10A cell backgrounds. As a demonstration of the validity of the protocol, the well-characterized activating ERBB3 mutation ERBB3 E928G was identified as one of the major hits. These analyses are expected to identify activating ERBB3 mutations that are directly actionable or that provide predictive value for the use of drugs targeting ERBB signaling. Citation Format: Marika K. Koivu, Deepankar Chakroborty, Kari J. Kurppa, Klaus Elenius. Screen for actionable ERBB3 mutations [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 828.