Meta-analysis of single-cell RNA-seq data reveals phenotypic switching of immune cells in severe COVID-19 patients

Hasan, Zobaer; Islam, Syful; Matsumoto, Kenichi; Kawai, Taro

doi:10.1016/j.compbiomed.2021.104792

Cited by 26 publications

(20 citation statements)

References 49 publications

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“…Several lung single-nuclei and single-cell efforts have been published throughout the COVID-19 pandemic (Delorey et al 2021; J. Xu et al 2020; Hasan et al 2021; Melms et al 2021). To assess the quality and scope of the CTA, we compared our data to the comprehensive lung atlas generated by the Broad Institute (Delorey et al 2021).…”

Section: Resultsmentioning

confidence: 99%

Comprehensive characterization of the transcriptional response to COVID-19 in multiple organs reveals shared signatures across tissues

Granados

Bucher

Agrawal

et al. 2022

Preprint

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Infection by Coronavirus SARS-CoV2 is a severe and often deadly disease that has implications for the respiratory system and multiple organs across the human body. While the effects in the lung have been extensively studied, less is known about COVID-19 cellular impact across other organs. Here we contribute a single-nuclei RNA sequencing atlas comprising six human organs across 20 autopsies where we analyzed the transcriptional changes due to COVID-19 in multiple cell types. Computational cross-organ analysis for endothelial cells and macrophages identified systemic transcriptional changes in these cell types in COVID-19 samples. In addition, analysis of signaling pathways from multiple datasets showed several systemic dysregulations of signaling interaction in different cell types. Altogether, the COVID tissue atlas enables the investigation of both cell type-specific and cross-organ transcriptional responses to COVID-19, providing insights into the molecular networks affected by the disease and highlighting novel potential targets for therapies and drug development.

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Section: Resultsmentioning

confidence: 99%

Comprehensive characterization of the transcriptional response to COVID-19 in multiple organs reveals shared signatures across tissues

Granados

Bucher

Agrawal

et al. 2022

Preprint

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“…Hasan et al . further substantiated this claim in their meta-analysis, finding that inflammatory monocytes and macrophages were significantly increased in severe and deceased COVID-19 patients compared to those who had milder forms of the disease [ 46 ]. While the analyses are limited by small numbers of tissues, it suggests that at least in refractory cases, monocyte-derived macrophages with features similar to “profibrotic macrophages” in pulmonary fibrosis accumulate in COVID-19 lungs.…”

Section: Introductionmentioning

confidence: 84%

“…[ 33 ] 19 severe COVID-19, 8 healthy controls 116,000 10X Genomics 3’ v3.1 Chromium system (single nuclei) IHC, multiplexed microscopy, imaging mass cytometry GEO GSE171524 Travaglini et al , [ 7 ] 3 nonsmoker and smoker controls ~ 75,000 10X Genomics 3’ Chromium system (65,662 cells) and Smart-Seq2 (9,404 cells) ISH, flow cytometry https://www.synapse.org/#!Synapse:syn21041850 https://hlca.ds.czbiohub.org/ European Genome-Phenome Archive EGAS00001004344 Hasan et al . [ 46 ] 3 moderate COVID-19, 12 severe COVID-19, 5 decreased COVID-19, 6 healthy controls (meta-analysis) Not reported 10X Genomics 5’ and 3’ NA GEO GSE1618215, GSE169471, GSE145926 (lungs) Schupp et al . [ 47 ] 73 healthy controls (meta-analysis) ~ 15,000 vascular cells 10X Genomics IF, ISH, IHC GEO GSE164829, www.lungendothelialcellatlas.com Delorey et al .…”

Section: Introductionmentioning

confidence: 99%

From COVID to fibrosis: lessons from single-cell analyses of the human lung

2022

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The increased resolution of single-cell RNA-sequencing technologies has led to major breakthroughs and improved our understanding of the normal and pathologic conditions of multiple tissues and organs. In the study of parenchymal lung disease, single-cell RNA-sequencing has better delineated known cell populations and identified novel cells and changes in cellular phenotypes and gene expression patterns associated with disease. In this review, we aim to highlight the advances and insights that have been made possible by applying these technologies to two seemingly very different lung diseases: fibrotic interstitial lung diseases, a group of relentlessly progressive lung diseases leading to pulmonary fibrosis, and COVID-19 pneumonia, an acute viral disease with life-threatening complications, including pulmonary fibrosis. We discuss changes in cell populations and gene expression, highlighting potential common features, such as alveolar cell epithelial injury and aberrant repair and monocyte-derived macrophage populations, as well as relevance and implications to mechanisms of disease and future directions.

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“…Finally, all analyses in this study focus on bulk sequencing data. Fourthly, it might be better to study the role of CCDC134 using single cell sequencing to avoid cell heterogeneity using methods like single cell clustering (35)(36)(37)(38).…”

Section: Discussionmentioning

confidence: 99%

CCDC134 as a Prognostic-Related Biomarker in Breast Cancer Correlating With Immune Infiltrates

et al. 2022

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BackgroundThe expression of Coiled-Coil Domain Containing 134(CCDC134) is up-regulated in different pan-cancer species. However, its prognostic value and correlation with immune infiltration in breast cancer are unclear. Therefore, we evaluated the prognostic role of CCDC134 in breast cancer and its correlation with immune invasion.MethodsWe downloaded the transcription profile of CCDC134 between breast cancer and normal tissues from the Cancer Genome Atlas (TCGA). CCDC134 protein expression was assessed by the Clinical Proteomic Cancer Analysis Consortium (CPTAC) and the Human Protein Atlas. Gene set enrichment analysis (GSEA) was also used for pathway analysis. Receiver operating characteristic (ROC) curve was used to differentiate breast cancer from adjacent normal tissues. Kaplan-Meier method was used to evaluate the effect of CCDC134 on survival rate. The protein-protein interaction (PPI) network is built from STRING. Function expansion analysis is performed using the ClusterProfiler package. Through tumor Immune Estimation Resource (TIMER) and tumor Immune System Interaction database (TISIDB) to determine the relationship between CCDC134 expression level and immune infiltration. CTD database is used to predict drugs that inhibit CCDC134 and PubChem database is used to determine the molecular structure of identified drugs.ResultsThe expression of CCDC134 in breast cancer tissues was significantly higher than that of CCDC134 mRNA expression in adjacent normal tissues. ROC curve analysis showed that the AUC value of CCDC134 was 0.663. Kaplan-meier survival analysis showed that patients with high CCDC134 had a lower prognosis (57.27 months vs 36.96 months, P = 2.0E-6). Correlation analysis showed that CCDC134 mRNA expression was associated with tumor purity immune invasion. In addition, CTD database analysis identified abrine, Benzo (A) Pyrene, bisphenol A, Soman, Sunitinib, Tetrachloroethylene, Valproic Acid as seven targeted therapy drugs that may be effective treatments for seven targeted therapeutics. It may be an effective treatment for inhibiting CCDC134.ConclusionIn breast cancer, upregulated CCDC134 is significantly associated with lower survival and immune infiltrates invasion. Our study suggests that CCDC134 can serve as a biomarker of poor prognosis and a potential immunotherapy target in breast cancer. Seven drugs with significant potential to inhibit CCDC134 were identified.

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Meta-analysis of single-cell RNA-seq data reveals phenotypic switching of immune cells in severe COVID-19 patients

Cited by 26 publications

References 49 publications

Comprehensive characterization of the transcriptional response to COVID-19 in multiple organs reveals shared signatures across tissues

Comprehensive characterization of the transcriptional response to COVID-19 in multiple organs reveals shared signatures across tissues

From COVID to fibrosis: lessons from single-cell analyses of the human lung

CCDC134 as a Prognostic-Related Biomarker in Breast Cancer Correlating With Immune Infiltrates

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