A single cell RNAseq benchmark experiment embedding "controlled" cancer heterogeneity

Single-cell RNA sequencing (scRNA-seq) has emerged as a vital tool in tumor research, enabling exploration of molecular complexities at the individual cell level. It offers new technical possibilities for advancing tumor research and is anticipated to yield significant breakthroughs. However, deciphering meaningful insights from scRNA-seq data poses challenges, particularly in cell annotation and tumor subpopulation identification. Efficient algorithms are needed to unravel the intricate biological processes of cancer. To address these challenges, benchmarking datasets are essential to validate bioinformatics tools focusing on the analysis of single-cell omics in oncology. Here, we present a 10XGenomics scRNA-seq experiment, providing a controlled heterogeneity environment using lung cancer cell lines characterised by expressing seven different driver genes (EGFR, ALK, MET, ERBB2, KRAS, BRAF, ROS1), which are characterised by the presence of partial overlaps in their functional pathways. Furthermore, PBMC from a healthy donor were also sequenced Overall design: PC9 (EGFR Del19, activating mutation, PMID: 21167064; A549 (KRAS p.G12S, growth and proliferation, PMID: 20358631; NCI-H596 (HTB178, MET Del14 , enhanced protection from apoptosis and cellular migration PMID: 35636967; NCI-H1395 (CRL5868, BRAF p.G469A, gain of function, resistant to all tested MEK +/- BRAF inhibitors, PMID: 32540409; DV90 (ERBB2 p.V842I, increases kinase activity, PMID: 23220880; HCC78 (SLC34A2-ROS1 Fusion, ROS1 inhibitors have antiproliferative effect PMID: 22919003; CCL.185.IG (EML4-ALK Fusion-A549 Isogenic Cell, https://www.atcc.org/products/ccl-185ig); White cell from donor buffy coat (PBMC). All cell lines were purchased and cultured as suggested by the manufacturer. scRNA-seq was done using 10XGenomics platform.