Search

Cell-cycle control is accomplished by cyclin-dependent kinases (CDKs), motivating extensive research into CDK targeting small-molecule drugs as cancer therapeutics. Here we use combinatorial CRISPR/Cas9 perturbations to uncover an extensive network of functional interdependencies among CDKs and related factors, identifying 43 synthetic-lethal and 12 synergistic interactions. We dissect CDK perturbations using single-cell RNAseq, for which we develop a novel computational framework to precisely quantify cell-cycle effects and diverse cell states orchestrated by specific CDKs. While pairwise disruption of CDK4/6 is synthetic-lethal, only CDK6 is required for normal cell-cycle progression and transcriptional activation. Multiple CDKs (CDK1/7/9/12) are synthetic-lethal in combination with PRMT5, independent of cell-cycle control. In-depth analysis of mRNA expression and splicing patterns provides multiple lines of evidence that the CDK-PRMT5 dependency is due to aberrant transcriptional regulation resulting in premature termination. These inter-dependencies translate to drug–drug synergies, with therapeutic implications in cancer and other diseases.

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.