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Single-cell RNA transcriptome reveals the intra-tumoral heterogeneity and regulators underlying tumor progression in metastatic pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is the most frequent and aggressive pancreatic tumor characterized by high metastatic risk and special tumor microenvironment. To comprehensively delineate the complex intra-tumoral heterogeneity and the underlying mechanism during metastatic lesions malignant...

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Autores principales: Xu, Qianhui, Chen, Shaohuai, Hu, Yuanbo, Huang, Wen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8566471/
https://www.ncbi.nlm.nih.gov/pubmed/34732701
http://dx.doi.org/10.1038/s41420-021-00663-1
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author Xu, Qianhui
Chen, Shaohuai
Hu, Yuanbo
Huang, Wen
author_facet Xu, Qianhui
Chen, Shaohuai
Hu, Yuanbo
Huang, Wen
author_sort Xu, Qianhui
collection PubMed
description Pancreatic ductal adenocarcinoma (PDAC) is the most frequent and aggressive pancreatic tumor characterized by high metastatic risk and special tumor microenvironment. To comprehensively delineate the complex intra-tumoral heterogeneity and the underlying mechanism during metastatic lesions malignant progression, single-cell RNA sequencing (scRNA-seq) was employed. PCA and TSNE were used for dimensionality reduction analysis and cell clustering. Find All Markers function was used to calculate differential genes in each cluster, and Do Heatmap function was used to plot the distribution of differential genes in each cluster. GSVA was employed to assign pathway activity estimates to individual cells. Lineage trajectory progression was inferred by monocle. CNV status was inferred to compare the heterogeneity among patients and subtypes by infercnv. Ligand-receptor interactions were identified by CellPhoneDB, and regulons network of cells was analyzed by SCENIC. Through RNA-sequencing of 6236 individual cells from 5 liver metastatic PDAC lesions, 10 major cell clusters are identified by using unbiased clustering analysis of expression profiling and well-known cell markers. Cells with high CNV level were considered as malignant cells and pathway analyses were carried out to highlight intratumor heterogeneity in PDAC. Pseudotime trajectory analysis revealed that components of multiple tumor-related pathways and transcription factors (TFs) were differentially expressed along PDAC progression. The complex cellular communication suggested potential immunotherapeutic targets in PDAC. Regulon network identified multiple candidates for promising cell-specific transcriptional factors. Finally, metastatic-related genes expression levels and signaling pathways were validated in bulk RNA Sequencing data. This study contributed a comprehensive single-cell transcriptome atlas and contributed into novel insight of intratumor heterogeneity and molecular mechanism in metastatic PDAC.
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spelling pubmed-85664712021-11-16 Single-cell RNA transcriptome reveals the intra-tumoral heterogeneity and regulators underlying tumor progression in metastatic pancreatic ductal adenocarcinoma Xu, Qianhui Chen, Shaohuai Hu, Yuanbo Huang, Wen Cell Death Discov Article Pancreatic ductal adenocarcinoma (PDAC) is the most frequent and aggressive pancreatic tumor characterized by high metastatic risk and special tumor microenvironment. To comprehensively delineate the complex intra-tumoral heterogeneity and the underlying mechanism during metastatic lesions malignant progression, single-cell RNA sequencing (scRNA-seq) was employed. PCA and TSNE were used for dimensionality reduction analysis and cell clustering. Find All Markers function was used to calculate differential genes in each cluster, and Do Heatmap function was used to plot the distribution of differential genes in each cluster. GSVA was employed to assign pathway activity estimates to individual cells. Lineage trajectory progression was inferred by monocle. CNV status was inferred to compare the heterogeneity among patients and subtypes by infercnv. Ligand-receptor interactions were identified by CellPhoneDB, and regulons network of cells was analyzed by SCENIC. Through RNA-sequencing of 6236 individual cells from 5 liver metastatic PDAC lesions, 10 major cell clusters are identified by using unbiased clustering analysis of expression profiling and well-known cell markers. Cells with high CNV level were considered as malignant cells and pathway analyses were carried out to highlight intratumor heterogeneity in PDAC. Pseudotime trajectory analysis revealed that components of multiple tumor-related pathways and transcription factors (TFs) were differentially expressed along PDAC progression. The complex cellular communication suggested potential immunotherapeutic targets in PDAC. Regulon network identified multiple candidates for promising cell-specific transcriptional factors. Finally, metastatic-related genes expression levels and signaling pathways were validated in bulk RNA Sequencing data. This study contributed a comprehensive single-cell transcriptome atlas and contributed into novel insight of intratumor heterogeneity and molecular mechanism in metastatic PDAC. Nature Publishing Group UK 2021-11-03 /pmc/articles/PMC8566471/ /pubmed/34732701 http://dx.doi.org/10.1038/s41420-021-00663-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Xu, Qianhui
Chen, Shaohuai
Hu, Yuanbo
Huang, Wen
Single-cell RNA transcriptome reveals the intra-tumoral heterogeneity and regulators underlying tumor progression in metastatic pancreatic ductal adenocarcinoma
title Single-cell RNA transcriptome reveals the intra-tumoral heterogeneity and regulators underlying tumor progression in metastatic pancreatic ductal adenocarcinoma
title_full Single-cell RNA transcriptome reveals the intra-tumoral heterogeneity and regulators underlying tumor progression in metastatic pancreatic ductal adenocarcinoma
title_fullStr Single-cell RNA transcriptome reveals the intra-tumoral heterogeneity and regulators underlying tumor progression in metastatic pancreatic ductal adenocarcinoma
title_full_unstemmed Single-cell RNA transcriptome reveals the intra-tumoral heterogeneity and regulators underlying tumor progression in metastatic pancreatic ductal adenocarcinoma
title_short Single-cell RNA transcriptome reveals the intra-tumoral heterogeneity and regulators underlying tumor progression in metastatic pancreatic ductal adenocarcinoma
title_sort single-cell rna transcriptome reveals the intra-tumoral heterogeneity and regulators underlying tumor progression in metastatic pancreatic ductal adenocarcinoma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8566471/
https://www.ncbi.nlm.nih.gov/pubmed/34732701
http://dx.doi.org/10.1038/s41420-021-00663-1
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