ArticleNature communications2024
Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- The evolution of AI-integrated genome editing and its challenges.Mammalian genome : official journal of the International Mammalian Genome Society · 2026Review
- Balancing off-target and on-target considerations for optimized CRISPR-Cas9 knockout library design.Cell genomics · 2026Article
- Kinome-Focused CRISPR-Cas9 Screens in African Ancestry Patient-Derived Breast Cancer Organoids Identify Essential Kinases and Synergy of EGFR and FGFR1 Inhibition.Cancer research · 2025Article
- The present and future of the Cancer Dependency Map.Nature reviews. Cancer · 2025Review
- Making gene editing accessible in resource limited environments: recommendations to guide a first-time user.Frontiers in genome editing · 2024Review
- Accounting for diversity in the design of CRISPR-based therapeutic genome editing.Nature genetics · 2023Article
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
Reducing disparities is vital for equitable access to precision treatments in cancer. Socioenvironmental factors are a major driver of disparities, but differences in genetic variation likely also contribute. The impact of genetic ancestry on prioritization of cancer targets in drug discovery pipelines has not been systematically explored due to the absence of pre-clinical data at the appropriate scale. Here, we analyze data from 611 genome-scale CRISPR/Cas9 viability experiments in human cell line models to identify ancestry-associated genetic dependencies essential for cell survival. Surprisingly, we find that most putative associations between ancestry and dependency arise from artifacts related to germline variants. Our analysis suggests that for 1.2-2.5% of guides, germline variants in sgRNA targeting sequences reduce cutting by the CRISPR/Cas9 nuclease, disproportionately affecting cell models derived from individuals of recent African descent. We propose three approaches to mitigate this experimental bias, enabling the scientific community to address these disparities.
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Registered trials
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