Abstract The transcriptional plasticity of cancer cells promotes intercellular heterogeneity in response to anticancer drugs and facilitates the generation of subpopulation surviving cells. Characterizing single-cell transcriptional heterogeneity after drug treatments can provide mechanistic insights into drug efficacy. Here, we used single-cell RNA-seq to examine transcriptomic profiles of cancer cells treated with paclitaxel, celecoxib and the combination of the two drugs. By normalizing the expression of endogenous genes to spike-in molecules, we found that cellular mRNA abundance shows dynamic regulation after drug treatment. Using a random forest model, we identified gene signatures classifying single cells into three states: transcriptional repression, amplification and control-like. Treatment with paclitaxel or celecoxib alone generally repressed gene transcription across single cells. Interestingly, the drug combination resulted in transcriptional amplification and hyperactivation of mitochondrial oxidative phosphorylation pathway linking to enhanced cell killing efficiency. Finally, we identified a regulatory module enriched with metabolism and inflammation-related genes activated in a subpopulation of paclitaxel-treated cells, the expression of which predicted paclitaxel efficacy across cancer cell lines and in vivo patient samples. Our study highlights the dynamic global transcriptional activity driving single-cell heterogeneity during drug response and emphasizes the importance of adding spike-in molecules to study gene expression regulation using single-cell RNA-seq.
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Defining mammary basal cell transcriptional states using single-cell RNA-sequencing
Abstract Breast cancer is a heterogenous disease that can be classified into multiple subtypes including the most aggressive basal-like and triple-negative subtypes. Understanding the heterogeneity within the normal mammary basal epithelial cells holds the key to inform us about basal-like cancer cell differentiation dynamics as well as potential cells of origin. Although it is known that the mammary basal compartment contains small pools of stem cells that fuel normal tissue morphogenesis and regeneration, a comprehensive yet focused analysis of the transcriptional makeup of the basal cells is lacking. We used single-cell RNA-sequencing and multiplexed RNA in-situ hybridization to characterize mammary basal cell heterogeneity. We used bioinformatic and computational pipelines to characterize the molecular features as well as predict differentiation dynamics and cell–cell communications of the newly identified basal cell states. We used genetic cell labeling to map the in vivo fates of cells in one of these states. We identified four major distinct transcriptional states within the mammary basal cells that exhibit gene expression signatures suggestive of different functional activity and metabolic preference. Our in vivo labeling and ex vivo organoid culture data suggest that one of these states, marked by Egr2 expression, represents a dynamic transcriptional state that all basal cells transit through during pubertal mammary morphogenesis. Our study provides a systematic approach to understanding the molecular heterogeneity of mammary basal cells and identifies previously unknown dynamics of basal cell transcriptional states.
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- Award ID(s):
- 1763272
- NSF-PAR ID:
- 10322209
- Date Published:
- Journal Name:
- Scientific Reports
- Volume:
- 12
- Issue:
- 1
- ISSN:
- 2045-2322
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1038/s41598-022-08870-1
