Abstract 489: Multi-omic single-cell combinatorial indexing of gRNA, epitopes, and transcriptome uncovers modulators of drug sensitivity in K562 cells.

Abstract Identifying genes that modulate drug response is critical for understanding therapeutic resistance and discovering new targets to improve cancer therapy. Conventional pooled CRISPR screens, based on bulk measurements of guide RNA (gRNA) abundance, provide limited resolution and cannot capture transcriptomic or proteomic changes associated with gene perturbations. To overcome these limitations, we developed Single-cell combinatorial Guide RNA, Epitope, and Transcriptome Mapping Of Signals Across Integrated Cellular omics (scGET-MOSAIC) sequencing, a Cas13-based single-cell CRISPR screening platform that simultaneously captures gRNA identity, transcriptome, and surface protein expression from individual cells. This approach integrates the scalability of pooled screening with the molecular depth of single-cell multi-omics, enabling comprehensive functional interrogation of large druggable gene libraries. Compared to traditional bulk CRISPR screens, scGET-MOSAIC provides not only broader gRNA coverage but also multi-modal phenotypic profiles that reveal how each perturbation alters cellular states. Furthermore, the platform overcomes gene library size constraints found in other single-cell CRISPR methods, such as CROP-seq, allowing a substantially higher number of perturbations to be analyzed in a single experiment. We applied scGET-MOSAIC sequencing to the chronic myeloid leukemia cell line K562 treated with the tyrosine kinase inhibitor imatinib. Single-cell analysis across thousands of perturbed cells revealed distinct transcriptional and surface protein signatures associated with drug response. Through integrative analysis, we identified gene X as a critical modulator that enhances imatinib sensitivity, suggesting a potential combinatorial target for overcoming drug resistance. In summary, scGET-MOSAIC sequencing, powered by Cas13-mediated RNA targeting, establishes a versatile framework for large-scale, high-content CRISPR screening that connects genetic perturbations to transcriptomic and proteomic phenotypes. By directly perturbing RNA, this platform enables the exploration of both coding and non-coding gene functions, expanding the capacity of functional genomics to uncover novel therapeutic vulnerabilities in cancer. Citation Format: Sangwon Kang, Su-Hyeon Lee, Byungjin Hwang. Multi-omic single-cell combinatorial indexing of gRNA, epitopes, and transcriptome uncovers modulators of drug sensitivity in K562 cells abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 489.