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Candidate genes for predicting the survival of patients with gastric cancer: a study based on The Cancer Genome Atlas (TCGA) database
BACKGROUND: Gastric cancer (GC) is the second most frequent cause of cancer-related mortality in the world, and the five-year survival rate for GC remains very low universally. In recent years, it has become a consensus that genetic changes are associated with carcinogenesis of GC, and precision med...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798540/ https://www.ncbi.nlm.nih.gov/pubmed/35117619 http://dx.doi.org/10.21037/tcr.2020.02.82 |
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author | Liu, Xiqiao Gao, Liying Ni, Dongqiong Ma, Chengao Lu, Yuping Huang, Xuan |
author_facet | Liu, Xiqiao Gao, Liying Ni, Dongqiong Ma, Chengao Lu, Yuping Huang, Xuan |
author_sort | Liu, Xiqiao |
collection | PubMed |
description | BACKGROUND: Gastric cancer (GC) is the second most frequent cause of cancer-related mortality in the world, and the five-year survival rate for GC remains very low universally. In recent years, it has become a consensus that genetic changes are associated with carcinogenesis of GC, and precision medicine based on genetic changes is one of the most popular treatments for GC patients. However, the association between some genes and GC-related protein signaling pathways is still not well understood. This study revealed that seven genes were closely related to the survival probability in GC patients. METHODS: We downloaded the gene expression data of GC patients from The Cancer Genome Atlas (TCGA) databases, and integrated bioinformatic analysis was performed, such as differential gene expression analysis, including Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) pathways analyses, as well as survival analysis. The r package “survival” was used to analyze the Kaplan-Meier survival analysis, which showed the associations between specific gene expressions and the outcomes of patients with GC to identify which genes could be potential prognostic biomarkers. RESULTS: This study revealed that seven genes: alcohol dehydrogenase 4 (ADH4), histamine receptor H3 (HRH3), neuropeptide Y2 receptor (NPY2R), apolipoprotein AI (APOA1), N-acetylgalactosaminyltransferase 14 (GALNT14), leucine-rich repeats and IQ motif containing 1 (LRRIQ1), and coiled-coil-domain-containing 57 (CCDC57). These seven genes were closely related to the survival probability of GC patients (P<0.05). CONCLUSIONS: Our study found seven genes which could be considered as candidate prognostic biomarkers and therapeutic targets. |
format | Online Article Text |
id | pubmed-8798540 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-87985402022-02-02 Candidate genes for predicting the survival of patients with gastric cancer: a study based on The Cancer Genome Atlas (TCGA) database Liu, Xiqiao Gao, Liying Ni, Dongqiong Ma, Chengao Lu, Yuping Huang, Xuan Transl Cancer Res Original Article BACKGROUND: Gastric cancer (GC) is the second most frequent cause of cancer-related mortality in the world, and the five-year survival rate for GC remains very low universally. In recent years, it has become a consensus that genetic changes are associated with carcinogenesis of GC, and precision medicine based on genetic changes is one of the most popular treatments for GC patients. However, the association between some genes and GC-related protein signaling pathways is still not well understood. This study revealed that seven genes were closely related to the survival probability in GC patients. METHODS: We downloaded the gene expression data of GC patients from The Cancer Genome Atlas (TCGA) databases, and integrated bioinformatic analysis was performed, such as differential gene expression analysis, including Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) pathways analyses, as well as survival analysis. The r package “survival” was used to analyze the Kaplan-Meier survival analysis, which showed the associations between specific gene expressions and the outcomes of patients with GC to identify which genes could be potential prognostic biomarkers. RESULTS: This study revealed that seven genes: alcohol dehydrogenase 4 (ADH4), histamine receptor H3 (HRH3), neuropeptide Y2 receptor (NPY2R), apolipoprotein AI (APOA1), N-acetylgalactosaminyltransferase 14 (GALNT14), leucine-rich repeats and IQ motif containing 1 (LRRIQ1), and coiled-coil-domain-containing 57 (CCDC57). These seven genes were closely related to the survival probability of GC patients (P<0.05). CONCLUSIONS: Our study found seven genes which could be considered as candidate prognostic biomarkers and therapeutic targets. AME Publishing Company 2020-04 /pmc/articles/PMC8798540/ /pubmed/35117619 http://dx.doi.org/10.21037/tcr.2020.02.82 Text en 2020 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/. |
spellingShingle | Original Article Liu, Xiqiao Gao, Liying Ni, Dongqiong Ma, Chengao Lu, Yuping Huang, Xuan Candidate genes for predicting the survival of patients with gastric cancer: a study based on The Cancer Genome Atlas (TCGA) database |
title | Candidate genes for predicting the survival of patients with gastric cancer: a study based on The Cancer Genome Atlas (TCGA) database |
title_full | Candidate genes for predicting the survival of patients with gastric cancer: a study based on The Cancer Genome Atlas (TCGA) database |
title_fullStr | Candidate genes for predicting the survival of patients with gastric cancer: a study based on The Cancer Genome Atlas (TCGA) database |
title_full_unstemmed | Candidate genes for predicting the survival of patients with gastric cancer: a study based on The Cancer Genome Atlas (TCGA) database |
title_short | Candidate genes for predicting the survival of patients with gastric cancer: a study based on The Cancer Genome Atlas (TCGA) database |
title_sort | candidate genes for predicting the survival of patients with gastric cancer: a study based on the cancer genome atlas (tcga) database |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798540/ https://www.ncbi.nlm.nih.gov/pubmed/35117619 http://dx.doi.org/10.21037/tcr.2020.02.82 |
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