Enabling Single-Cell Drug Response Annotations from Bulk RNA-Seq Using SCAD
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
---|---|
Article number | 2204113 |
Journal / Publication | Advanced Science |
Volume | 10 |
Issue number | 11 |
Online published | 10 Feb 2023 |
Publication status | Published - 14 Apr 2023 |
Link(s)
DOI | DOI |
---|---|
Attachment(s) | Documents
Publisher's Copyright Statement
|
Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85147589309&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(468f181f-b9c4-482f-927b-d154f71a7f5d).html |
Abstract
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. © 2023 The Authors. Advanced Science published by Wiley-VCH GmbH.
Research Area(s)
- drug response annotation, single-cell sequencing, transfer learning
Citation Format(s)
Enabling Single-Cell Drug Response Annotations from Bulk RNA-Seq Using SCAD. / Zheng, Zetian; Chen, Junyi; Chen, Xingjian et al.
In: Advanced Science, Vol. 10, No. 11, 2204113, 14.04.2023.
In: Advanced Science, Vol. 10, No. 11, 2204113, 14.04.2023.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Download Statistics
No data available