Understanding the consequences of single amino acid substitutions in cancer driver genes remains an unmet need. High-throughput mutagenesis is emerging as a powerful tool to probe the varying consequences of different amino acid substitutions across the length of a protein or protein domain, however it is currently limited to specific functional readouts such as target protein abundance or functional assays. Studying the effects of genetic perturbations on cellular programs and fitness has been challenging using traditional pooled screens. Over the last few years, there has been a surge of interest in Perturb-seq style assays to measure the transcriptional consequences of genetic perturbations ranging from whole gene knockout to amino acid substitutions in single cells. While providing greater function insight, these sequencing-based methods are not yet scalable to exhaustive mutagenesis, necessitating selection of target mutations. In this work, we hypothesized that examining the consequences of perturbing distinct protein interactions could provide a useful abstraction of the phenotypic space reachable by individual amino acid substitutions. To explore this hypothesis, we employed a Perturb-seq style approach to generate mutations at physical interfaces of the transcription factor RUNX1, with the potential to perturb different interactions, and therefore produce transcriptional readouts implicating different aspects of the RUNX1 regulon. We analyzed these readouts to identify functionally distinct groups of RUNX1 mutations, characterize their effects on cellular programs and study the implications for cancer mutations. Our work demonstrates the potential of targeting protein interaction interfaces to better define the landscape of prospective phenotypes reachable by amino acid substitutions. Citation Format: Kivilcim Ozturk, Rebecca Panwala, Jeanna Sheen, Prashant Mali, Hannah Carter. Interface-guided phenotyping of coding variants [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB065.

Understanding the consequences of single amino acid substitutions in cancer driver genes remains an unmet need. Perturb-seq provides a tool to investigate the effects of individual mutations on cellular programs. Here we deploy SEUSS, a Perturb-seq like approach, to generate and assay mutations at physical interfaces of the RUNX1 Runt domain. We measured the impact of 115 mutations on RNA profiles in single myelogenous leukemia cells and used the profiles to categorize mutations into three functionally distinct groups: wild-type (WT)-like, loss-of-function (LOF)-like and hypomorphic. Notably, the largest concentration of functional mutations (non-WT-like) clustered at the DNA binding site and contained many of the more frequently observed mutations in human cancers. Hypomorphic variants shared characteristics with loss of function variants but had gene expression profiles indicative of response to neural growth factor and cytokine recruitment of neutrophils. Additionally, DNA accessibility changes upon perturbations were enriched for RUNX1 binding motifs, particularly near differentially expressed genes. Overall, our work demonstrates the potential of targeting protein interaction interfaces to better define the landscape of prospective phenotypes reachable by amino acid substitutions.