It is demonstrated that integrated Perturb-seq experiments spanning diverse contexts enable hypotheses about gene function specific to tissue types or cancer subtypes – suggesting large-scale, genome-wide datasets would offer invaluable insight into the highly context-dependent nature of cancer biology.
Abstract
Background CRISPR-mediated viability assays in diverse cancer cell lines have informed cancer biology and precision medicine, but cell fitness is not the only cancer-relevant phenotype. Gene expression profiling provides insight into cellular stress, inflammation, and differential state, while still identifying activation of cell-death pathways. Perturb-seq allows scalable functional genomics screening of expression phenotypes at single-cell resolution, however existing datasets cover only a small number of work-horse cell lines. Results We produced a proof-of-concept Perturb-seq dataset targeting 100 genes in 16 diverse cancer cell lines. In the process, we established methods to address single-cell technical artifacts, identified Cas9-mediated chromosomal aberrations and assessed screen quality. Even with a limited library, we observed common signatures of deleting essential genes as well as context-specific responses based on intrinsic genomic properties of the models. For example, we inferred a previously undescribed relationship between dependence on the ER-golgi transport gene immediate early response 3 interacting protein 1 (IER3IP1) and oxidative stress, demonstrating the potential of integrated Perturb-seq for hypothesis generation. Conclusions We established a framework for building a comprehensive map of post-perturbational transcriptional phenotypes using parallel Perturb-seq experiments across multiple cell lines. We demonstrated that integrated Perturb-seq experiments spanning diverse contexts enable hypotheses about gene function specific to tissue types or cancer subtypes – suggesting large-scale, genome-wide datasets would offer invaluable insight into the highly context-dependent nature of cancer biology.
Perturb-seq enables pooled genetic screens with rich single-cell profiling readouts, but genome-scale profiling remains costly and may not be associated with other established functional characteristics. Moreover, as screens grow in size and complexity, interpreting the resulting data comprehensively is challenging and slow. Here, we introduce Perturb-seq with Marker Enrichment (Perturb-ME), which combines genome-scale CRISPR screening, phenotype-based enrichment and multimodal single-cell profiling. Applied to MHC-I cell surface protein expression in melanoma, Perturb-ME profiled HLA-low and HLA-high cells with matched RNA, surface-protein and guide measurements. A regulatory model with 221 impactful regulators affecting 1,998 responsive genes recovered seven coherent co-functional regulatory modules governing nine gene programs, including the canonical IFNγ-MHC-I axis regulating an antigen-presentation and interferon-response program. Agentic interpretation of the entire model with an AI co-scientist linked additional modules to trafficking, proteostasis and chromatin regulation. Perturb-ME, along with agentic interpretation, provide a scalable framework for comprehensive functional discovery from phenotype-enriched genetic screens.
Hanchen Wang, Jiacheng Gu, Chris J. Frangieh et al.· bioRxiv· 0 citations
Genome-wide CRISPR screens have systematically identified genes required for cancer cell survival, yet these studies are typically performed under standardized conditions that do not fully recapitulate the physiological stresses encountered within the tumor microenvironment. In a recent issue of Nature Genetics, Cheruiyot and colleagues perform genome-wide loss-of-function screens under inflammatory conditions induced by interferon-β (IFN-β), interferon-γ (IFN-γ), and tumor necrosis factor (TNF), revealing that distinct cytokines impose different genetic requirements for tumor cell survival. The study shows that inflammatory signaling reshapes genetic dependency landscape in a cytokine-specific manner. Mechanistic analyses identify the glycosylphosphatidylinositol (GPI) transamidase complex and FITM2 as representative examples of genes that become selectively required under inflammatory stress by maintaining membrane protein maturation, endoplasmic reticulum homeostasis, and resistance to oxidative stress. These findings broaden our understanding of how inflammatory cytokines influence tumor cell biology beyond transcriptional regulation and immune recognition. More broadly, the study highlights the value of incorporating physiologically relevant conditions into functional genetic screens, suggesting that conventional dependency maps capture only part of the genetic requirements for tumor survival. Applying similar approaches to other microenvironmental stresses-including hypoxia, metabolic competition, extracellular matrix remodeling, and stromal signaling-may uncover additional therapeutic opportunities for cancer immunotherapy.
Zihan Ning, Guangchuan Wang· Cancer Research· 0 citations
Key methodological steps for achieving high-efficiency lentiviral transduction and selection are described, enabling the successful application of EPIKOL CRISPR screens in chemoresistant TNBC models.
O. Yedier-Bayram, Elif Ayca Guvener, T. Bagci-Onder· Journal of Visualized Experi...· 0 citations
It is proposed that integrating precise editing, in vivo screening, single-cell multi-omics, and emerging artificial intelligence (AI)-assisted design may provide information and a design basis for future combined strategies that simultaneously target vulnerabilities in senescent cells and malignant populations.
Bo Fan, Aiwei Wu, Xue Pan et al.· Ageing and Cancer Research &...· 0 citations
Patient‐derived organoids (PDOs) have emerged as physiologically relevant cancer models that preserve key genetic, histological, and functional features of the tumors from which they are derived. In parallel, CRISPR‐based perturbation technologies have transformed functional genomics by enabling scalable interrogation of gene function. Their integration provides a powerful framework for identifying cancer dependencies, modeling oncogenic evolution, and investigating mechanisms of drug response and resistance in patient‐relevant settings. This review examines how CRISPR knockout, CRISPR interference/activation, and precision editing approaches have been applied in PDO systems to uncover context‐specific vulnerabilities, reconstruct mutational trajectories, and study tumor heterogeneity. We further compare pooled and arrayed screening formats and discuss what is uniquely enabled by performing CRISPR screens in organoids rather than conventional 2D models. Particular emphasis is placed on the technical and analytical constraints of organoid‐based screening, including variable editing efficiency, clonal bottlenecks, biological heterogeneity, and limited scalability. We argue that the major value of organoid‐based CRISPR screening lies in its ability to identify functionally actionable cancer vulnerabilities in a patient‐contextualized model, while also introducing methodological challenges that must be addressed for robust clinical translation.
J. du Plessis, Aadilah Omar· Cancer Medicine· 0 citations
The N-glycosylation module is demonstrated as a recurrent hub of context-dependent genetic interactions and combinatorial CRISPR screening as a scalable approach for identifying therapeutic targets and resistance mechanisms in oncogene-driven cancers.
Subin Kim, Chen-Chu Lin, Sabriyeh Alibai et al.· Clinical Cancer Research· 0 citations
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