CRISPR Functional Genomics in Precision Oncology: Integrating Single-Cell Multi-Omics for Cancer Vulnerability Discovery

Vollständiger Abstract

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Precision oncology seeks to identify patient-specific therapeutic vulnerabilities; however, conventional genomic profiling is limited by intratumoral heterogeneity and its inability to distinguish functional driver alterations from passenger mutations, often resulting in incomplete prediction of therapeutic response. Recently, the combination of CRISPR functional genomics with single-cell multi-omics has proven to be a paradigm-shifting strategy for understanding context-specific cancer vulnerabilities by causal functional interrogation. The aim of this review is to critically examine recent progress in the integration of these technologies for discovering vulnerabilities in cancer, and introduces a new conceptual model, called the Integrated Functional Precision Oncology (IFPO) Framework, that brings together functional genomic perturbation, single-cell multi-omics, computational systems biology, and clinical translation. Literature was retrieved from Pubmed, Web of Science and Google Scholar and peer reviewed studies published between 2020 and 2025. Key findings from historic and recent research were analyzed to pinpoint methodological innovations, translational studies, limitations, and areas in need of further research. The results reveal that the integrated CRISPR–single-cell platforms, such as Perturb-seq, CROP-seq, and ECCITE-seq, can be used to causally interrogate gene function at the single-cell level, allowing for the identification of context-dependent essential genes, synthetic lethal interactions, regulatory networks, and therapeutic resistance mechanisms. All the evidence suggests that therapeutic response is not merely a function of genomic alterations but also the dynamic interplay between genomic alterations, cellular state, epigenetic plasticity, and the tumor microenvironment. The proposed IFPO Framework integrates these findings into a systems-level model that captures the mechanisms by which these functional perturbations, multimodal molecular profiling, and AI-driven integration of data converge to reveal clinically actionable cancer vulnerabilities. This integrated paradigm transforms precision oncology from descriptive molecular profiling to functional systems oncology and offers directions for further progress of precision cancer treatment based on enhanced biomarker discovery, therapeutic target identification, and prospective clinical translation.