Enabling Single-Cell Drug Response Annotations from Bulk RNA-Seq Using SCAD.
Zetian ZhengJunyi ChenXingjian ChenLei HuangWeidun XieQiuzhen LinXiangtao LiKa-Chun WongPublished in: Advanced science (Weinheim, Baden-Wurttemberg, Germany) (2023)
The single-cell RNA sequencing (scRNA-seq) quantifies the gene expression of individual cells, while the bulk RNA sequencing (bulk RNA-seq) characterizes the mixed transcriptome of cells. The inference of drug sensitivities for individual cells can provide new insights to understand the mechanism of anti-cancer response heterogeneity and drug resistance at the cellular resolution. However, pharmacogenomic information related to their corresponding scRNA-Seq is often limited. Therefore, a transfer learning model is proposed to infer the drug sensitivities at single-cell level. This framework learns bulk transcriptome profiles and pharmacogenomics information from population cell lines in a large public dataset and transfers the knowledge to infer drug efficacy of individual cells. The results suggest that it is suitable to learn knowledge from pre-clinical cell lines to infer pre-existing cell subpopulations with different drug sensitivities prior to drug exposure. In addition, the model offers a new perspective on drug combinations. It is observed that drug-resistant subpopulation can be sensitive to other drugs (e.g., a subset of JHU006 is Vorinostat-resistant while Gefitinib-sensitive); such finding corroborates the previously reported drug combination (Gefitinib + Vorinostat) strategy in several cancer types. The identified drug sensitivity biomarkers reveal insights into the tumor heterogeneity and treatment at cellular resolution.
Keyphrases
- single cell
- rna seq
- high throughput
- induced apoptosis
- drug resistant
- gene expression
- adverse drug
- healthcare
- small cell lung cancer
- cell cycle arrest
- multidrug resistant
- emergency department
- drug induced
- signaling pathway
- genome wide
- cell death
- squamous cell carcinoma
- mental health
- endoplasmic reticulum stress
- cell proliferation
- pseudomonas aeruginosa
- smoking cessation
- health information
- papillary thyroid
- cell therapy