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Spike-in normalization for single-cell RNA-seq reveals dynamic global transcriptional activity mediating anti-cancer drug response

ABSTRACT: The transcriptional plasticity of cancer cells promotes intercellular heterogeneity in response to anti-cancer 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 sequencing (scRNA-seq) to examine transcriptomic profiles of cancer cells treated with chemotherapy drug paclitaxel, anti-inflammatory drug celecoxib, and the combination of the two drugs. By normalizing the expression of endogenous genes to spike-in molecules, we found that global mRNA abundance shows dynamic regulation across single cells 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 at variable levels across single cells. Interestingly, the combination of the two drugs resulted in transcriptional amplification and hyperactivation of the mitochondrial oxidative phosphorylation pathway, which is linked to enhanced cell killing efficiency. Finally, we identified a regulatory module enriched with metabolism and inflammatory genes that was activated in a subpopulation of paclitaxel-treated cells, the expression of which predicted paclitaxel efficacy across human cancer cell lines and in vivo patient samples. Our study highlights the dynamic global transcriptional activity driving single-cell heterogeneity during drug response. The results also emphasize the importance of adding spike-in molecules to study gene expression regulation using scRNA-seq experiments.

ORGANISM(S): Homo sapiens

PROVIDER: GSE162256 | GEO | 2021/05/25

REPOSITORIES: GEO

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Project description:This a model from the article: Transient heterogeneity in extracellular protease production by Bacillus subtilis. Veening JW, Igoshin OA, Eijlander RT, Nijland R, Hamoen LW, Kuipers OP Mol. Syst. Biol. 2008 ; Volume: 4 : 184 18414485, Abstract: The most sophisticated survival strategy Bacillus subtilis employs is the differentiation of a subpopulation of cells into highly resistant endospores. To examine the expression patterns of non-sporulating cells within heterogeneous populations, we used buoyant density centrifugation to separate vegetative cells from endospore-containing cells and compared the transcriptome profiles of both subpopulations. This demonstrated the differential expression of various regulons. Subsequent single-cell analyses using promoter-gfp fusions confirmed our microarray results. Surprisingly, only part of the vegetative subpopulation highly and transiently expresses genes encoding the extracellular proteases Bpr (bacillopeptidase) and AprE (subtilisin), both of which are under the control of the DegU transcriptional regulator. As these proteases and their degradation products freely diffuse within the liquid growth medium, all cells within the clonal population are expected to benefit from their activities, suggesting that B. subtilis employs cooperative or even altruistic behavior. To unravel the mechanisms by which protease production heterogeneity within the non-sporulating subpopulation is established, we performed a series of genetic experiments combined with mathematical modeling. Simulations with our model yield valuable insights into how population heterogeneity may arise by the relatively long and variable response times within the DegU autoactivating pathway. This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2009 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.

Project description:Background: Drug-eluting stents (DES) have rapidly become a standard therapy for treatment of obstructive coronary artery disease. Differences exist in therapeutic responses to different DES formulations, and mechanisms to predict drug responses in the preclinical setting have not been standardized. Results: We have used gene expression profiling to characterize the patterns of gene regulation within cultures of rat aortic smooth muscle cells (RASMC) treated with rapamycin or paclitaxel, the two drugs widely used in commercially available DES. These studies further validate the use of the in vitro RASMC culture system as a model of insulin resistance. Gene expression profiles easily distinguish RASMC grown under normal or high glucose conditions, and we therefore followed this approach in order to understand the activity of these drugs under conditions that approximate those seen in type 2 diabetics. Remarkably, although both drugs are used to arrest smooth muscle proliferation when delivered by DES, there were major differences in gene regulatory responses. Paclitaxel caused marked changes in expression of tubulin-related genes, and also caused striking changes in the transcription of VEGF, PDGF, JAG-1 and their respective receptors, suggesting an important effect on paracrine and autocrine response to mitogens. However, the gene expression signatures elicited by paclitaxel showed little variation under different cell culture conditions. In contrast, these gene expression responses to rapamycin varied considerably depending on the glycemic conditions of culture, and rapamycin had a dramatic dose- and metabolic status- dependent effect on the transcription of key members of the AKT signaling axis, providing a transcriptional explanation for the paradoxical proliferative effect of rapamycin at low dose in the setting of high glucose concentrations and insulin resistance. Conclusions: Gene expression signatures for drugs eluted from coronary stents vary dramatically in ways that correlate with known differences in biological activities of these drugs. Gene expression profiling may provide a useful preclinical method to characterize the activities of candidate drugs for stent impregnation and to understand their biological activities. Keywords: Cardiovascular disease, drug eluting stent, vascular smooth muscle, rapamycin, paclitaxel

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Spike-in normalization for single-cell RNA-seq reveals dynamic global transcriptional activity mediating anti-cancer drug response

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