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Bridging the gap between cancer cell line models and tumours using gene expression data


Cancer cell line models are a cornerstone of cancer research, yet our understanding of how well they represent the molecular features of patient tumours remains limited. Our recent work provides a computational approach to systematically compare large gene expression datasets to better understand which cell lines most closely resemble each tumour type, as well as identify potential gaps in our current cancer models.

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J.N., F.V. and J.M.M. drafted and revised the paper.

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Correspondence to James M. McFarland.

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Competing interests

F.V. receives research support from Novo Ventures. All authors were partially funded by the Cancer Dependency Map Consortium, but no consortium member was involved in or influenced the study.

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This work was supported by the Cancer Dependency Map Consortium.

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Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Noorbakhsh, J., Vazquez, F. & McFarland, J.M. Bridging the gap between cancer cell line models and tumours using gene expression data. Br J Cancer (2021).

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