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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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.
This work was supported by the Cancer Dependency Map Consortium.
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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 125, 311–312 (2021). https://doi.org/10.1038/s41416-021-01359-0