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Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets

Tumor microenvironment and heterogeneity play vital roles in the development and progression of gastric cancer (GC). In the past decade, a considerable amount of single-cell RNA-sequencing (scRNA-seq) studies have been published in the fields of oncology and immunology, which improve our knowledge o...

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Autores principales: Wei, Xujin, Liu, Jie, Hong, Zhijun, Chen, Xin, Wang, Kang, Cai, Jianchun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9421061/
https://www.ncbi.nlm.nih.gov/pubmed/36046240
http://dx.doi.org/10.3389/fgene.2022.896064
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author Wei, Xujin
Liu, Jie
Hong, Zhijun
Chen, Xin
Wang, Kang
Cai, Jianchun
author_facet Wei, Xujin
Liu, Jie
Hong, Zhijun
Chen, Xin
Wang, Kang
Cai, Jianchun
author_sort Wei, Xujin
collection PubMed
description Tumor microenvironment and heterogeneity play vital roles in the development and progression of gastric cancer (GC). In the past decade, a considerable amount of single-cell RNA-sequencing (scRNA-seq) studies have been published in the fields of oncology and immunology, which improve our knowledge of the GC immune microenvironment. However, much uncertainty still exists about the relationship between the macroscopic and microscopic data in transcriptomics. In the current study, we made full use of scRNA-seq data from the Gene Expression Omnibus database (GSE134520) to identify 25 cell subsets, including 11 microenvironment-related cell types. The MIF signaling pathway network was obtained upon analysis of receptor–ligand pairs and cell–cell interactions. By comparing the gene expression in a wide variety of cells between intestinal metaplasia and early gastric cancer, we identified 64 differentially expressed genes annotated as immune response and cellular communication. Subsequently, we screened these genes for prognostic clinical value based on the patients’ follow-up data from The Cancer Genome Atlas. TMPRSS15, VIM, APOA1, and RNASE1 were then selected for the construction of LASSO risk scores, and a nomogram model incorporating another five clinical risk factors was successfully created. The effectiveness of least absolute shrinkage and selection operator risk scores was validated using gene set enrichment analysis and levels of immune cell infiltration. These findings will drive the development of prognostic evaluations affected by the immune tumor microenvironment in GC.
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spelling pubmed-94210612022-08-30 Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets Wei, Xujin Liu, Jie Hong, Zhijun Chen, Xin Wang, Kang Cai, Jianchun Front Genet Genetics Tumor microenvironment and heterogeneity play vital roles in the development and progression of gastric cancer (GC). In the past decade, a considerable amount of single-cell RNA-sequencing (scRNA-seq) studies have been published in the fields of oncology and immunology, which improve our knowledge of the GC immune microenvironment. However, much uncertainty still exists about the relationship between the macroscopic and microscopic data in transcriptomics. In the current study, we made full use of scRNA-seq data from the Gene Expression Omnibus database (GSE134520) to identify 25 cell subsets, including 11 microenvironment-related cell types. The MIF signaling pathway network was obtained upon analysis of receptor–ligand pairs and cell–cell interactions. By comparing the gene expression in a wide variety of cells between intestinal metaplasia and early gastric cancer, we identified 64 differentially expressed genes annotated as immune response and cellular communication. Subsequently, we screened these genes for prognostic clinical value based on the patients’ follow-up data from The Cancer Genome Atlas. TMPRSS15, VIM, APOA1, and RNASE1 were then selected for the construction of LASSO risk scores, and a nomogram model incorporating another five clinical risk factors was successfully created. The effectiveness of least absolute shrinkage and selection operator risk scores was validated using gene set enrichment analysis and levels of immune cell infiltration. These findings will drive the development of prognostic evaluations affected by the immune tumor microenvironment in GC. Frontiers Media S.A. 2022-08-15 /pmc/articles/PMC9421061/ /pubmed/36046240 http://dx.doi.org/10.3389/fgene.2022.896064 Text en Copyright © 2022 Wei, Liu, Hong, Chen, Wang and Cai. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Wei, Xujin
Liu, Jie
Hong, Zhijun
Chen, Xin
Wang, Kang
Cai, Jianchun
Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets
title Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets
title_full Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets
title_fullStr Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets
title_full_unstemmed Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets
title_short Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets
title_sort identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell rna-sequencing datasets
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9421061/
https://www.ncbi.nlm.nih.gov/pubmed/36046240
http://dx.doi.org/10.3389/fgene.2022.896064
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