Inferred Ancestral Origin of Cancer Cell Lines Associates with Differential Drug Response

Nguyen, Phong; Ohnmacht, Alexander J; Sharifli, Samir; Garnett, Mathew J.; Menden, Michael P.

doi:10.3390/ijms221810135

Cited by 3 publications

(3 citation statements)

References 34 publications

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“…We systematically cataloged local ancestral haplotypes across the genomes of commonly used cancer cell lines, focusing on the 994 (out of 1829 total) cell line models in the Cancer Cell Line Encyclopedia collection for which publicly available Affymetrix SNP6 germline variant data have been analyzed 8 . While previous reports have evaluated cell line genetic ancestry at genome scale [8][9][10][11][12] , we hypothesized that such global assessments may preclude the discovery of regional germline associations with dependencies. We therefore leveraged germline variants from 10,345,968 SNPs genome-wide to infer local ancestry.…”

Section: Main Textmentioning

confidence: 99%

Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries

Misek

Fultineer

Kalfon

et al. 2022

Preprint

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Reducing disparities is critical to promote equity of access to precision treatments for all patients with cancer. While socioenvironmental factors are a major driver behind such disparities, biological differences also are likely to contribute. The prioritization of cancer drug targets is foundational for drug discovery, yet whether ancestry-related signals in target discovery pipelines exist has not been systematically explored due to the absence of data at the appropriate scale. Here, we analyzed data from 611 genome-scale CRISPR/Cas9 viability experiments in human cell line models as part of the Cancer Dependency Map to identify ancestry-associated genetic dependencies. Surprisingly, we found that most putative associations between ancestry and dependency arose from artifacts related to germline variants that are present at different frequencies across ancestry groups. In 2-5% of genes profiled in each cellular model, germline variants in sgRNA targeting sequences likely reduced cutting by the CRISPR/Cas9 nuclease. Unfortunately, this bias disproportionately affected cell models derived from individuals of recent African descent because their genomes tended to diverge more from the consensus genome typically used for CRISPR/Cas9 guide design. To help the scientific community begin to resolve this source of bias, we report three complementary methods for ancestry-agnostic CRISPR experiments. This report adds to a growing body of literature describing ways in which ancestry bias impacts cancer research in underappreciated ways.

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Section: Main Textmentioning

confidence: 99%

Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries

Misek

Fultineer

Kalfon

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…(B) The Affymetrix SNP6.0 arrays genotyping dataset contains 994 cancer cell lines that are deposited in the European Genome-Phenome Archive. Analysis of this dataset found that 633 of the cell lines were of European ancestry, 248 were of East Asian ancestry, 56 were of African ancestry, 47 were of American ancestry and ten were of South Asian ancestry ( Nguyen et al, 2021 ). (C) Of 853 samples in the NCI patient-derived models repository, 135 had unreported ancestry, 645 were of European ancestry, 39 were of African ancestry, 25 were of mixed ancestry, eight were of East Asian ancestry, and one was of American ancestry (NCI-Frederick).…”

Section: The Promise and Shortfall Of Cell Lines To Diversify Genetic...mentioning

confidence: 99%

“…Disappointingly, but not surprisingly, analysis of datasets from over 1000 commonly used cancer cell lines demonstrated that 63% of them had European ancestry ( Fig. 2 ) ( Nguyen et al, 2021 ). In an attempt to better recapitulate the genetic heterogeneity and diversity of cancer patients, the NCI moved towards a patient-derived models repository (NCI-Frederick) that includes xenografts, in vitro tumor cell cultures and organoids.…”

Section: The Promise and Shortfall Of Cell Lines To Diversify Genetic...mentioning

confidence: 99%

How inclusive are cell lines in preclinical engineered cancer models?

Raghavan

2022

Disease Models &Amp; Mechanisms

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Diverse factors contribute to significant and dire disparities in cancer risk and treatment outcomes. To address this, there was a call for inclusion of sex as a biological variable, which resulted in more instances of careful inclusion of sex in preclinical studies of cancer. Another variable in cancer treatment is genetic ancestry. Although this is considered explicitly in clinical research, it is considerably neglected in preclinical studies. Preclinical research can use several 3D in vitro model systems, such as spheroids/organoids, xenografts, or other bioengineered systems that combine biomaterials and cellular material. Ultimately, the cellular base for all of these in vitro model systems is derived from human cell lines or patient samples, to investigate mechanisms of cancer and screen novel therapeutics, all of which aim to maximize successful outcomes in clinical trials. This in itself offers an opportunity to potentiate effective treatments for many groups of people, when diverse variables like genetic ancestry are consciously included into study design. This Perspective highlights the need for conscious inclusion of genetic ancestry in preclinical cancer tissue engineering, especially when it pertains to determining therapeutic outcomes.

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Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries

Misek,

Fultineer,

Kalfon

et al. 2024

Nat Commun

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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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Inferred Ancestral Origin of Cancer Cell Lines Associates with Differential Drug Response

Cited by 3 publications

References 34 publications

Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries

Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries

How inclusive are cell lines in preclinical engineered cancer models?

Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries

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