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

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.