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 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.

单细胞RNA测序（single-cell RNA sequencing，scRNA-seq）已成为肿瘤研究领域的核心工具，可实现单个细胞水平下分子复杂性的系统解析。其为肿瘤研究的推进提供了全新的技术路径，有望取得重大突破。然而，从scRNA-seq数据中挖掘有价值的生物学信息仍面临诸多挑战，尤其在细胞注释与肿瘤亚群鉴定方面。解析癌症复杂的生物学过程亟需高效的算法支撑。为应对上述挑战，构建基准数据集以验证聚焦于肿瘤学单细胞组学分析的生物信息学工具至关重要。本研究提供一项基于10XGenomics平台的scRNA-seq实验数据集，通过使用7种携带不同驱动基因（EGFR、ALK、MET、ERBB2、KRAS、BRAF、ROS1）的肺癌细胞系构建了可控的异质性环境，上述驱动基因的功能通路存在部分重叠。此外，本研究还对健康供体的外周血单个核细胞（peripheral blood mononuclear cell，PBMC）进行了测序，纳入的细胞系具体信息如下：PC9（携带EGFR Del19激活突变，PubMed文献编号PMID: 21167064）、A549（携带KRAS p.G12S突变，参与细胞生长与增殖过程，PMID: 20358631）、NCI-H596（HTB178，携带MET Del14突变，可增强细胞抗凋亡能力与迁移能力，PMID: 35636967）、NCI-H1395（CRL5868，携带BRAF p.G469A突变，为功能获得性突变，对所有测试的MEK±BRAF抑制剂均耐药，PMID: 32540409）、DV90（携带ERBB2 p.V842I突变，可增强激酶活性，PMID: 23220880）、HCC78（携带SLC34A2-ROS1融合基因，ROS1抑制剂可发挥抗增殖作用，PMID: 22919003）以及CCL.185.IG（携带EML4-ALK融合基因的A549同基因细胞系，来源：https://www.atcc.org/products/ccl-185ig）；同时包含从健康供体白膜层分离得到的白细胞（即PBMC）。所有细胞系均按照供应商说明书的要求进行购买与培养，本研究采用10XGenomics平台完成scRNA-seq实验。