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Exploring TCGA database for identification of potential prognostic genes in stomach adenocarcinoma

BACKGROUND: Stomach adenocarcinoma (STAD) is the fifth most prevalent cancer in the world and ranks third among cancer-related deaths worldwide. The tumour microenvironment (TME) plays an important role in tumorigenesis, development, and metastasis. Hence, we calculated the immune and stromal scores...

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Autores principales: Zhou, Lin, Huang, Wei, Yu, He-Fen, Feng, Ya-Juan, Teng, Xu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7310509/
https://www.ncbi.nlm.nih.gov/pubmed/32581654
http://dx.doi.org/10.1186/s12935-020-01351-3
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author Zhou, Lin
Huang, Wei
Yu, He-Fen
Feng, Ya-Juan
Teng, Xu
author_facet Zhou, Lin
Huang, Wei
Yu, He-Fen
Feng, Ya-Juan
Teng, Xu
author_sort Zhou, Lin
collection PubMed
description BACKGROUND: Stomach adenocarcinoma (STAD) is the fifth most prevalent cancer in the world and ranks third among cancer-related deaths worldwide. The tumour microenvironment (TME) plays an important role in tumorigenesis, development, and metastasis. Hence, we calculated the immune and stromal scores to find the potential prognosis-related genes in STAD using bioinformatics analysis. METHODS: The ESTIMATE algorithm was used to calculate the immune/stromal scores of the STAD samples. Functional enrichment analysis, protein–protein interaction (PPI) network analysis, and overall survival analysis were then performed on differential genes. And we validated these genes using data from the Gene Expression Omnibus database. Finally, we used the Human Protein Atlas (HPA) databases to verify these genes at the protein levels by IHC. RESULTS: Data analysis revealed correlation between stromal/immune scores and the TNM staging system. The top 10 core genes extracted from the PPI network, and primarily involved in immune responses, extracellular matrix, and cell adhesion. There are 31 genes have been validated with poor prognosis and 16 genes were upregulated in tumour tissues compared with normal tissues at the protein level. CONCLUSIONS: In summary, we identified genes associated with the tumour microenvironment with prognostic implications in STAD, which may become potential therapeutic markers leading to better clinical outcomes.
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spelling pubmed-73105092020-06-23 Exploring TCGA database for identification of potential prognostic genes in stomach adenocarcinoma Zhou, Lin Huang, Wei Yu, He-Fen Feng, Ya-Juan Teng, Xu Cancer Cell Int Primary Research BACKGROUND: Stomach adenocarcinoma (STAD) is the fifth most prevalent cancer in the world and ranks third among cancer-related deaths worldwide. The tumour microenvironment (TME) plays an important role in tumorigenesis, development, and metastasis. Hence, we calculated the immune and stromal scores to find the potential prognosis-related genes in STAD using bioinformatics analysis. METHODS: The ESTIMATE algorithm was used to calculate the immune/stromal scores of the STAD samples. Functional enrichment analysis, protein–protein interaction (PPI) network analysis, and overall survival analysis were then performed on differential genes. And we validated these genes using data from the Gene Expression Omnibus database. Finally, we used the Human Protein Atlas (HPA) databases to verify these genes at the protein levels by IHC. RESULTS: Data analysis revealed correlation between stromal/immune scores and the TNM staging system. The top 10 core genes extracted from the PPI network, and primarily involved in immune responses, extracellular matrix, and cell adhesion. There are 31 genes have been validated with poor prognosis and 16 genes were upregulated in tumour tissues compared with normal tissues at the protein level. CONCLUSIONS: In summary, we identified genes associated with the tumour microenvironment with prognostic implications in STAD, which may become potential therapeutic markers leading to better clinical outcomes. BioMed Central 2020-06-23 /pmc/articles/PMC7310509/ /pubmed/32581654 http://dx.doi.org/10.1186/s12935-020-01351-3 Text en © The Author(s) 2020 Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Primary Research
Zhou, Lin
Huang, Wei
Yu, He-Fen
Feng, Ya-Juan
Teng, Xu
Exploring TCGA database for identification of potential prognostic genes in stomach adenocarcinoma
title Exploring TCGA database for identification of potential prognostic genes in stomach adenocarcinoma
title_full Exploring TCGA database for identification of potential prognostic genes in stomach adenocarcinoma
title_fullStr Exploring TCGA database for identification of potential prognostic genes in stomach adenocarcinoma
title_full_unstemmed Exploring TCGA database for identification of potential prognostic genes in stomach adenocarcinoma
title_short Exploring TCGA database for identification of potential prognostic genes in stomach adenocarcinoma
title_sort exploring tcga database for identification of potential prognostic genes in stomach adenocarcinoma
topic Primary Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7310509/
https://www.ncbi.nlm.nih.gov/pubmed/32581654
http://dx.doi.org/10.1186/s12935-020-01351-3
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