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Identification of the angiogenesis related genes for predicting prognosis of patients with gastric cancer
INTRODUCTION: Angiogenesis is a key factor in promoting tumor growth, invasion and metastasis. In this study we aimed to investigate the prognostic value of angiogenesis-related genes (ARGs) in gastric cancer (GC). METHODS: mRNA sequencing data with clinical information of GC were downloaded from Th...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8017607/ https://www.ncbi.nlm.nih.gov/pubmed/33794777 http://dx.doi.org/10.1186/s12876-021-01734-4 |
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author | Zheng, Sheng Zhang, Zizhen Ding, Ning Sun, Jiawei Lin, Yifeng Chen, Jingyu Zhong, Jing Shao, Liming Lin, Zhenghua Xue, Meng |
author_facet | Zheng, Sheng Zhang, Zizhen Ding, Ning Sun, Jiawei Lin, Yifeng Chen, Jingyu Zhong, Jing Shao, Liming Lin, Zhenghua Xue, Meng |
author_sort | Zheng, Sheng |
collection | PubMed |
description | INTRODUCTION: Angiogenesis is a key factor in promoting tumor growth, invasion and metastasis. In this study we aimed to investigate the prognostic value of angiogenesis-related genes (ARGs) in gastric cancer (GC). METHODS: mRNA sequencing data with clinical information of GC were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The differentially expressed ARGs between normal and tumor tissues were analyzed by limma package, and then prognosis‑associated genes were screened using Cox regression analysis. Nine angiogenesis genes were identified as crucially related to the overall survival (OS) of patients through least absolute shrinkage and selection operator (LASSO) regression. The prognostic model and corresponding nomograms were establish based on 9 ARGs and verified in in both TCGA and GEO GC cohorts respectively. RESULTS: Eighty-five differentially expressed ARGs and their enriched pathways were confirmed. Significant enrichment analysis revealed that ARGs-related signaling pathway genes were highly related to tumor angiogenesis development. Kaplan–Meier analysis revealed that patients in the high-risk group had worse OS rates compared with the low-risk group in training cohort and validation cohort. In addition, RS had a good prognostic effect on GC patients with different clinical features, especially those with advanced GC. Besides, the calibration curves verified fine concordance between the nomogram prediction model and actual observation. CONCLUSIONS: We developed a nine gene signature related to the angiogenesis that can predict overall survival for GC. It’s assumed to be a valuable prognosis model with high efficiency, providing new perspectives in targeted therapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-021-01734-4. |
format | Online Article Text |
id | pubmed-8017607 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-80176072021-04-02 Identification of the angiogenesis related genes for predicting prognosis of patients with gastric cancer Zheng, Sheng Zhang, Zizhen Ding, Ning Sun, Jiawei Lin, Yifeng Chen, Jingyu Zhong, Jing Shao, Liming Lin, Zhenghua Xue, Meng BMC Gastroenterol Research Article INTRODUCTION: Angiogenesis is a key factor in promoting tumor growth, invasion and metastasis. In this study we aimed to investigate the prognostic value of angiogenesis-related genes (ARGs) in gastric cancer (GC). METHODS: mRNA sequencing data with clinical information of GC were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The differentially expressed ARGs between normal and tumor tissues were analyzed by limma package, and then prognosis‑associated genes were screened using Cox regression analysis. Nine angiogenesis genes were identified as crucially related to the overall survival (OS) of patients through least absolute shrinkage and selection operator (LASSO) regression. The prognostic model and corresponding nomograms were establish based on 9 ARGs and verified in in both TCGA and GEO GC cohorts respectively. RESULTS: Eighty-five differentially expressed ARGs and their enriched pathways were confirmed. Significant enrichment analysis revealed that ARGs-related signaling pathway genes were highly related to tumor angiogenesis development. Kaplan–Meier analysis revealed that patients in the high-risk group had worse OS rates compared with the low-risk group in training cohort and validation cohort. In addition, RS had a good prognostic effect on GC patients with different clinical features, especially those with advanced GC. Besides, the calibration curves verified fine concordance between the nomogram prediction model and actual observation. CONCLUSIONS: We developed a nine gene signature related to the angiogenesis that can predict overall survival for GC. It’s assumed to be a valuable prognosis model with high efficiency, providing new perspectives in targeted therapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-021-01734-4. BioMed Central 2021-04-01 /pmc/articles/PMC8017607/ /pubmed/33794777 http://dx.doi.org/10.1186/s12876-021-01734-4 Text en © The Author(s) 2021 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 | Research Article Zheng, Sheng Zhang, Zizhen Ding, Ning Sun, Jiawei Lin, Yifeng Chen, Jingyu Zhong, Jing Shao, Liming Lin, Zhenghua Xue, Meng Identification of the angiogenesis related genes for predicting prognosis of patients with gastric cancer |
title | Identification of the angiogenesis related genes for predicting prognosis of patients with gastric cancer |
title_full | Identification of the angiogenesis related genes for predicting prognosis of patients with gastric cancer |
title_fullStr | Identification of the angiogenesis related genes for predicting prognosis of patients with gastric cancer |
title_full_unstemmed | Identification of the angiogenesis related genes for predicting prognosis of patients with gastric cancer |
title_short | Identification of the angiogenesis related genes for predicting prognosis of patients with gastric cancer |
title_sort | identification of the angiogenesis related genes for predicting prognosis of patients with gastric cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8017607/ https://www.ncbi.nlm.nih.gov/pubmed/33794777 http://dx.doi.org/10.1186/s12876-021-01734-4 |
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