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Novel Prognostic Biomarkers in Gastric Cancer: CGB5, MKNK2, and PAPPA2

INTRODUCTION: Gastric cancer is one of the most common malignant tumors of the digestive tract. However, there are no adequate prognostic markers available for this disease. The present study used bioinformatics to identify prognostic markers for gastric cancer that would guide the clinical diagnosi...

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Autores principales: Qin, Min, Liang, Zhihai, Qin, Heping, Huo, Yifang, Wu, Qing, Yang, Huiying, Tang, Guodu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8252917/
https://www.ncbi.nlm.nih.gov/pubmed/34222004
http://dx.doi.org/10.3389/fonc.2021.683582
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author Qin, Min
Liang, Zhihai
Qin, Heping
Huo, Yifang
Wu, Qing
Yang, Huiying
Tang, Guodu
author_facet Qin, Min
Liang, Zhihai
Qin, Heping
Huo, Yifang
Wu, Qing
Yang, Huiying
Tang, Guodu
author_sort Qin, Min
collection PubMed
description INTRODUCTION: Gastric cancer is one of the most common malignant tumors of the digestive tract. However, there are no adequate prognostic markers available for this disease. The present study used bioinformatics to identify prognostic markers for gastric cancer that would guide the clinical diagnosis and treatment of this disease. MATERIALS AND METHODS: Gene expression data and clinical information of gastric cancer patients along with the gene expression data of 30 healthy samples were downloaded from the TCGA database. The initial screening was performed using the WGCNA method combined with the analysis of differentially expressed genes, which was followed by univariate analysis, multivariate COX regression analysis, and Lasso regression analysis for screening the candidate genes and constructing a prognostic model for gastric cancer. Subsequently, immune cell typing was performed using CIBERSORT to analyze the expression of immune cells in each sample. Finally, we performed laboratory validation of the results of our analyses using immunohistochemical analysis. RESULTS: After five screenings, it was revealed that only three genes fulfilled all the screening requirements. The survival curves generated by the prognostic model revealed that the survival rate of the patients in the high-risk group was significantly lower compared to the patients in the low-risk group (P-value < 0.001). The immune cell component analysis revealed that the three genes were differentially associated with the corresponding immune cells (P-value < 0.05). The results of immunohistochemistry also support our analysis. CONCLUSION: CGB5, MKNK2, and PAPPA2 may be used as novel prognostic biomarkers for gastric cancer.
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spelling pubmed-82529172021-07-03 Novel Prognostic Biomarkers in Gastric Cancer: CGB5, MKNK2, and PAPPA2 Qin, Min Liang, Zhihai Qin, Heping Huo, Yifang Wu, Qing Yang, Huiying Tang, Guodu Front Oncol Oncology INTRODUCTION: Gastric cancer is one of the most common malignant tumors of the digestive tract. However, there are no adequate prognostic markers available for this disease. The present study used bioinformatics to identify prognostic markers for gastric cancer that would guide the clinical diagnosis and treatment of this disease. MATERIALS AND METHODS: Gene expression data and clinical information of gastric cancer patients along with the gene expression data of 30 healthy samples were downloaded from the TCGA database. The initial screening was performed using the WGCNA method combined with the analysis of differentially expressed genes, which was followed by univariate analysis, multivariate COX regression analysis, and Lasso regression analysis for screening the candidate genes and constructing a prognostic model for gastric cancer. Subsequently, immune cell typing was performed using CIBERSORT to analyze the expression of immune cells in each sample. Finally, we performed laboratory validation of the results of our analyses using immunohistochemical analysis. RESULTS: After five screenings, it was revealed that only three genes fulfilled all the screening requirements. The survival curves generated by the prognostic model revealed that the survival rate of the patients in the high-risk group was significantly lower compared to the patients in the low-risk group (P-value < 0.001). The immune cell component analysis revealed that the three genes were differentially associated with the corresponding immune cells (P-value < 0.05). The results of immunohistochemistry also support our analysis. CONCLUSION: CGB5, MKNK2, and PAPPA2 may be used as novel prognostic biomarkers for gastric cancer. Frontiers Media S.A. 2021-06-15 /pmc/articles/PMC8252917/ /pubmed/34222004 http://dx.doi.org/10.3389/fonc.2021.683582 Text en Copyright © 2021 Qin, Liang, Qin, Huo, Wu, Yang and Tang 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 Oncology
Qin, Min
Liang, Zhihai
Qin, Heping
Huo, Yifang
Wu, Qing
Yang, Huiying
Tang, Guodu
Novel Prognostic Biomarkers in Gastric Cancer: CGB5, MKNK2, and PAPPA2
title Novel Prognostic Biomarkers in Gastric Cancer: CGB5, MKNK2, and PAPPA2
title_full Novel Prognostic Biomarkers in Gastric Cancer: CGB5, MKNK2, and PAPPA2
title_fullStr Novel Prognostic Biomarkers in Gastric Cancer: CGB5, MKNK2, and PAPPA2
title_full_unstemmed Novel Prognostic Biomarkers in Gastric Cancer: CGB5, MKNK2, and PAPPA2
title_short Novel Prognostic Biomarkers in Gastric Cancer: CGB5, MKNK2, and PAPPA2
title_sort novel prognostic biomarkers in gastric cancer: cgb5, mknk2, and pappa2
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8252917/
https://www.ncbi.nlm.nih.gov/pubmed/34222004
http://dx.doi.org/10.3389/fonc.2021.683582
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