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

Genome Medicine

María José Jiménez-Santos¹  Luis García-Jimeno¹  Vadym Ivanchuk¹  Santiago García-Martín¹  Tomás Di Domenico¹  Fátima Al-Shahrour¹  Gonzalo Gómez-López¹  Coral Fustero-Torre¹  Carlos Carretero-Puche² 

[1] Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Calle Melchor Fernandez Almagro, 3, 28029, Madrid, Spain;Laboratorio de Oncología Clínico-Traslacional, Unidad de Investigación en tumores Digestivos, Instituto de Investigación I+12, Hospital 12 de Octubre, Av. de Córdoba, 28041, Madrid, Spain;Lung-H120 Group, Spanish National Cancer Research Centre (CNIO), Calle Melchor Fernandez Almagro, 3, 28029, Madrid, Spain;

关键词: Single-cell RNA-seq;    Intratumoural heterogeneity;    Drug repositioning;    Therapeutic clusters;    Personalised therapy;   

DOI  :  10.1186/s13073-021-01001-x

来源: Springer

【 摘 要 】

We present 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 the therapeutic differences among cell populations and generates a prioritised sensitivity-based ranking in order to guide drug selection. We performed Beyondcell analysis in five single-cell datasets and demonstrated that TCs can be exploited to target malignant cells both in cancer cell lines and tumour patients. Beyondcell is available at: https://gitlab.com/bu_cnio/beyondcell.

【 授权许可】

CC BY