Beyondcell: targeting cancer therapeutic heterogeneity in single-cell RNA-seq

Fustero-Torre, C.; Jimenez-Santos, M. J.; Garcia-Martin, S.; Carretero-Puche, C.; Garcia-Jimeno, L.; Di Domenico, T.; Gomez-Lopez, G.; Al-Shahrour, F.

doi:10.1101/2021.04.08.438954

bioRxiv · 10.1101/2021.04.08.438954

Beyondcell: targeting cancer therapeutic heterogeneity in single-cell RNA-seq

Fustero-Torre, C.·Jimenez-Santos, M. J.·Garcia-Martin, S.·Carretero-Puche, C.·Garcia-Jimeno, L.·Di Domenico, T.·Gomez-Lopez, G.·Al-Shahrour, F.

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Abstract

We present Beyondcell (https://gitlab.com/bu_cnio/beyondcell/), a computational methodology for identifying tumour cell subpopulations with distinct drug responses in single-cell RNA-seq data and proposing cancer-specific treatments. Our method calculates an enrichment score in a collection of drug signatures, delineating therapeutic clusters (TCs) within cellular populations. Additionally, Beyondcell determines therapeutic differences among cell populations, and generates a prioritised ranking of the differential sensitivity drugs between chosen conditions to guide drug selection. We performed Beyondcell analysis in four single-cell datasets to validate our score and to demonstrate that TCs can be exploited to target malignant cells both in cancer cell lines and tumour patients.

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Fustero-Torre, C., Jimenez-Santos, M. J., Garcia-Martin, S., Carretero-Puche, C., Garcia-Jimeno, L., Di Domenico, T., Gomez-Lopez, G., Al-Shahrour, F.. 2021-04-09. Beyondcell: targeting cancer therapeutic heterogeneity in single-cell RNA-seq. https://doi.org/10.1101/2021.04.08.438954

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