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Comprehensive analysis of prognostic genes in gastric cancer
Background: Gastric cancer is associated with high mortality, and effective methods for predicting prognosis are lacking. We aimed to identify potential prognostic markers associated with the development of gastric cancer through bioinformatic analyses. Methods: Gastric cancer-associated gene expres...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580339/ https://www.ncbi.nlm.nih.gov/pubmed/34686626 http://dx.doi.org/10.18632/aging.203638 |
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author | Huang, Shaohua Ma, Liping Lan, Biyang Liu, Ning Nong, Wenwei Huang, Zhihu |
author_facet | Huang, Shaohua Ma, Liping Lan, Biyang Liu, Ning Nong, Wenwei Huang, Zhihu |
author_sort | Huang, Shaohua |
collection | PubMed |
description | Background: Gastric cancer is associated with high mortality, and effective methods for predicting prognosis are lacking. We aimed to identify potential prognostic markers associated with the development of gastric cancer through bioinformatic analyses. Methods: Gastric cancer-associated gene expression profiles were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The key genes involved in the development of gastric cancer were obtained by differential expression analysis, coexpression analysis, and short time-series expression miner (STEM) analysis. The potential prognostic value of differentially expressed genes was further evaluated using a Cox regression model and risk scores. Hierarchical clustering was applied to validate the impact of key genes on the overall survival of gastric cancer patients. Results: A total of 1381 genes were consistently dysregulated in the development of gastric cancer. Among them, 186 genes affected the overall survival of gastric cancer patients. The following genes had areas under the receiver operating characteristic curve greater than 0.9 in both datasets and were therefore considered key genes: ADAM12, CEP55, LRFN4, INHBA, ADH1B, DPT, FAM107A, and LOC100506388. LRFN4, DPT, and LOC100506388 were identified as potential prognostic genes for gastric cancer through a nomogram. Overexpression of LRFN4 and LOC100506388 was associated with a higher risk of gastric cancer. Finally, we found that tumors were infiltrated with high levels of Th2 cells and mast cells, and the infiltration levels were associated with overall survival in gastric cancer patients. Conclusions: We found that key dysregulated genes may have a prognostic value for the development of gastric cancer. |
format | Online Article Text |
id | pubmed-8580339 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-85803392021-11-15 Comprehensive analysis of prognostic genes in gastric cancer Huang, Shaohua Ma, Liping Lan, Biyang Liu, Ning Nong, Wenwei Huang, Zhihu Aging (Albany NY) Research Paper Background: Gastric cancer is associated with high mortality, and effective methods for predicting prognosis are lacking. We aimed to identify potential prognostic markers associated with the development of gastric cancer through bioinformatic analyses. Methods: Gastric cancer-associated gene expression profiles were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The key genes involved in the development of gastric cancer were obtained by differential expression analysis, coexpression analysis, and short time-series expression miner (STEM) analysis. The potential prognostic value of differentially expressed genes was further evaluated using a Cox regression model and risk scores. Hierarchical clustering was applied to validate the impact of key genes on the overall survival of gastric cancer patients. Results: A total of 1381 genes were consistently dysregulated in the development of gastric cancer. Among them, 186 genes affected the overall survival of gastric cancer patients. The following genes had areas under the receiver operating characteristic curve greater than 0.9 in both datasets and were therefore considered key genes: ADAM12, CEP55, LRFN4, INHBA, ADH1B, DPT, FAM107A, and LOC100506388. LRFN4, DPT, and LOC100506388 were identified as potential prognostic genes for gastric cancer through a nomogram. Overexpression of LRFN4 and LOC100506388 was associated with a higher risk of gastric cancer. Finally, we found that tumors were infiltrated with high levels of Th2 cells and mast cells, and the infiltration levels were associated with overall survival in gastric cancer patients. Conclusions: We found that key dysregulated genes may have a prognostic value for the development of gastric cancer. Impact Journals 2021-10-22 /pmc/articles/PMC8580339/ /pubmed/34686626 http://dx.doi.org/10.18632/aging.203638 Text en Copyright: © 2021 Huang et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Huang, Shaohua Ma, Liping Lan, Biyang Liu, Ning Nong, Wenwei Huang, Zhihu Comprehensive analysis of prognostic genes in gastric cancer |
title | Comprehensive analysis of prognostic genes in gastric cancer |
title_full | Comprehensive analysis of prognostic genes in gastric cancer |
title_fullStr | Comprehensive analysis of prognostic genes in gastric cancer |
title_full_unstemmed | Comprehensive analysis of prognostic genes in gastric cancer |
title_short | Comprehensive analysis of prognostic genes in gastric cancer |
title_sort | comprehensive analysis of prognostic genes in gastric cancer |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580339/ https://www.ncbi.nlm.nih.gov/pubmed/34686626 http://dx.doi.org/10.18632/aging.203638 |
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