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LncRNA DIRC1 is a novel prognostic biomarker and correlated with immune infiltrates in stomach adenocarcinoma

The potential application value of Long non-coding RNA disrupted in renal carcinoma 1 (DIRC1) has not yet been explored, the purpose of this study was to explore the relationship between DIRC1 and stomach adenocarcinoma (STAD) based on the cancer genome atlas database. Wilcoxon rank sum test, Chi-sq...

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Autores principales: Lin, Yuning, Zhang, Zhongying, Li, Ying, Chen, Yongquan, Su, Meiying, Zhao, Wenzhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9678523/
https://www.ncbi.nlm.nih.gov/pubmed/36401393
http://dx.doi.org/10.1097/MD.0000000000031839
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author Lin, Yuning
Zhang, Zhongying
Li, Ying
Chen, Yongquan
Su, Meiying
Zhao, Wenzhen
author_facet Lin, Yuning
Zhang, Zhongying
Li, Ying
Chen, Yongquan
Su, Meiying
Zhao, Wenzhen
author_sort Lin, Yuning
collection PubMed
description The potential application value of Long non-coding RNA disrupted in renal carcinoma 1 (DIRC1) has not yet been explored, the purpose of this study was to explore the relationship between DIRC1 and stomach adenocarcinoma (STAD) based on the cancer genome atlas database. Wilcoxon rank sum test, Chi-square test, Fisher test and logistic regression were used to evaluate relationships between clinical-pathologic features and DIRC1 expression. Receiver operating characteristic (ROC) curves were used to describe binary classifier value of DIRC1 using area under curve (AUC) score. Kaplan-Meier method was used to assess the impact of DIRC1 on prognosis and the impact of DIRC1-related hub genes on prognosis. Gene oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to predict the function of differentially expressed genes associated with DIRC1. Gene set enrichment analysis (GSEA) was used to predict biological states or processes associated with DIRC1. Immune infiltration analysis was performed to identify the significantly involved functions of DIRC1. Protein–protein interaction (PPI) networks were established and 10 hub genes identified with Cytoscape software. Real time-polymerase chain reaction (RT-PCR) was used to detect the expression of DIRC1 in Gastric Cancer patients and healthy people. Increased DIRC1 expression in STAD was associated with T stage (P = .004), race (P = .045), histologic grade (P = .029) and anatomic neoplasm subdivision (P = .034). ROC curve suggested the significant diagnostic ability of DIRC1 (AUC = 0.779). High DIRC1 expression predicted a poorer Overall survival (P = .004, hazard ratio: 1.63; 95% confidence interval: 1.17‐2.27; P = .034). GO and KEGG analysis demonstrated that DIRC1 is related to epidermis, collagen-containing extracellular matrix, receptor-ligand activity, protein digestion and absorption, etc. GSEA demonstrated that E2F target, G2M checkpoint, Myc target, interferon γ reaction were differentially enriched in the high DIRC1 expression phenotype. SsGSEA and Spearman correlation revealed the relationships between DIRC1 and macrophages, dendritic cells, and Th1 cells were the strongest. Coregulatory proteins were included in the PPI network, higher expressions of 4 hub genes were associated with worse prognosis in STAD. RT-PCR showed that the expression of DIRC1 in the serum of Gastric Cancer patients was higher than healthy people (P = .027). DIRC1 expression was significantly correlated with poor survival and immune infiltrations in STAD, and it may be a promising prognostic biomarker in STAD.
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spelling pubmed-96785232022-11-22 LncRNA DIRC1 is a novel prognostic biomarker and correlated with immune infiltrates in stomach adenocarcinoma Lin, Yuning Zhang, Zhongying Li, Ying Chen, Yongquan Su, Meiying Zhao, Wenzhen Medicine (Baltimore) 5700 The potential application value of Long non-coding RNA disrupted in renal carcinoma 1 (DIRC1) has not yet been explored, the purpose of this study was to explore the relationship between DIRC1 and stomach adenocarcinoma (STAD) based on the cancer genome atlas database. Wilcoxon rank sum test, Chi-square test, Fisher test and logistic regression were used to evaluate relationships between clinical-pathologic features and DIRC1 expression. Receiver operating characteristic (ROC) curves were used to describe binary classifier value of DIRC1 using area under curve (AUC) score. Kaplan-Meier method was used to assess the impact of DIRC1 on prognosis and the impact of DIRC1-related hub genes on prognosis. Gene oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to predict the function of differentially expressed genes associated with DIRC1. Gene set enrichment analysis (GSEA) was used to predict biological states or processes associated with DIRC1. Immune infiltration analysis was performed to identify the significantly involved functions of DIRC1. Protein–protein interaction (PPI) networks were established and 10 hub genes identified with Cytoscape software. Real time-polymerase chain reaction (RT-PCR) was used to detect the expression of DIRC1 in Gastric Cancer patients and healthy people. Increased DIRC1 expression in STAD was associated with T stage (P = .004), race (P = .045), histologic grade (P = .029) and anatomic neoplasm subdivision (P = .034). ROC curve suggested the significant diagnostic ability of DIRC1 (AUC = 0.779). High DIRC1 expression predicted a poorer Overall survival (P = .004, hazard ratio: 1.63; 95% confidence interval: 1.17‐2.27; P = .034). GO and KEGG analysis demonstrated that DIRC1 is related to epidermis, collagen-containing extracellular matrix, receptor-ligand activity, protein digestion and absorption, etc. GSEA demonstrated that E2F target, G2M checkpoint, Myc target, interferon γ reaction were differentially enriched in the high DIRC1 expression phenotype. SsGSEA and Spearman correlation revealed the relationships between DIRC1 and macrophages, dendritic cells, and Th1 cells were the strongest. Coregulatory proteins were included in the PPI network, higher expressions of 4 hub genes were associated with worse prognosis in STAD. RT-PCR showed that the expression of DIRC1 in the serum of Gastric Cancer patients was higher than healthy people (P = .027). DIRC1 expression was significantly correlated with poor survival and immune infiltrations in STAD, and it may be a promising prognostic biomarker in STAD. Lippincott Williams & Wilkins 2022-11-18 /pmc/articles/PMC9678523/ /pubmed/36401393 http://dx.doi.org/10.1097/MD.0000000000031839 Text en Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC) (https://creativecommons.org/licenses/by-nc/4.0/) , where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.
spellingShingle 5700
Lin, Yuning
Zhang, Zhongying
Li, Ying
Chen, Yongquan
Su, Meiying
Zhao, Wenzhen
LncRNA DIRC1 is a novel prognostic biomarker and correlated with immune infiltrates in stomach adenocarcinoma
title LncRNA DIRC1 is a novel prognostic biomarker and correlated with immune infiltrates in stomach adenocarcinoma
title_full LncRNA DIRC1 is a novel prognostic biomarker and correlated with immune infiltrates in stomach adenocarcinoma
title_fullStr LncRNA DIRC1 is a novel prognostic biomarker and correlated with immune infiltrates in stomach adenocarcinoma
title_full_unstemmed LncRNA DIRC1 is a novel prognostic biomarker and correlated with immune infiltrates in stomach adenocarcinoma
title_short LncRNA DIRC1 is a novel prognostic biomarker and correlated with immune infiltrates in stomach adenocarcinoma
title_sort lncrna dirc1 is a novel prognostic biomarker and correlated with immune infiltrates in stomach adenocarcinoma
topic 5700
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9678523/
https://www.ncbi.nlm.nih.gov/pubmed/36401393
http://dx.doi.org/10.1097/MD.0000000000031839
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