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Identification of key genes and pathways in gastric signet ring cell carcinoma based on transcriptome analysis
BACKGROUND: Gastric signet ring cell carcinoma (GSRCC) is one of the most malignant tumors. It has the features of high invasiveness, rapid progression, and resistance to chemotherapy. However, systematic analyses of mRNAs have not yet been performed for GSRCC. AIM: To identify key mRNAs and signali...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052547/ https://www.ncbi.nlm.nih.gov/pubmed/32149050 http://dx.doi.org/10.12998/wjcc.v8.i4.658 |
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author | Zhao, Zi-Tong Li, Yang Yuan, Hong-Yu Ma, Fu-Hai Song, Yong-Mei Tian, Yan-Tao |
author_facet | Zhao, Zi-Tong Li, Yang Yuan, Hong-Yu Ma, Fu-Hai Song, Yong-Mei Tian, Yan-Tao |
author_sort | Zhao, Zi-Tong |
collection | PubMed |
description | BACKGROUND: Gastric signet ring cell carcinoma (GSRCC) is one of the most malignant tumors. It has the features of high invasiveness, rapid progression, and resistance to chemotherapy. However, systematic analyses of mRNAs have not yet been performed for GSRCC. AIM: To identify key mRNAs and signaling pathways in GSRCC. METHODS: A transcriptome analysis of two GSRCC and two non-GSRCC samples was performed in this study. Differentially expressed mRNAs and pathways were identified based on the KEGG and PANTHER pathway annotations. The interactive relationships among the differential genes were mapped with the STRING database. Quantitative real-time polymerase chain reaction was used to validate the key gene expression in GSRCC. RESULTS: About 1162 differential genes (using a 2-fold cutoff, P < 0.05) were identified in GSRCC compared with non-GSRCC. The enriched KEGG and PANTHER pathways for the differential genes included immune response pathways, metabolic pathways, and metastasis-associated pathways. Ten genes (MAGEA2, MAGEA2B, MAGEA3, MAGEA4, MAGEA6, MUC13, GUCA2A, FFAR4, REG1A, and REG1B) were identified as hub genes in the protein-protein interaction network. The expression levels of five genes (MAGEA2, MAGEA3, MAGEA4, MAGEA6, and REG1B) showed potential clinical value. CONCLUSION: We have identified the potential key genes and pathways in GSRCC, and these hub genes and pathways could be diagnostic markers and therapeutic targets for GSRCC. |
format | Online Article Text |
id | pubmed-7052547 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-70525472020-03-06 Identification of key genes and pathways in gastric signet ring cell carcinoma based on transcriptome analysis Zhao, Zi-Tong Li, Yang Yuan, Hong-Yu Ma, Fu-Hai Song, Yong-Mei Tian, Yan-Tao World J Clin Cases Clinical and Translational Research BACKGROUND: Gastric signet ring cell carcinoma (GSRCC) is one of the most malignant tumors. It has the features of high invasiveness, rapid progression, and resistance to chemotherapy. However, systematic analyses of mRNAs have not yet been performed for GSRCC. AIM: To identify key mRNAs and signaling pathways in GSRCC. METHODS: A transcriptome analysis of two GSRCC and two non-GSRCC samples was performed in this study. Differentially expressed mRNAs and pathways were identified based on the KEGG and PANTHER pathway annotations. The interactive relationships among the differential genes were mapped with the STRING database. Quantitative real-time polymerase chain reaction was used to validate the key gene expression in GSRCC. RESULTS: About 1162 differential genes (using a 2-fold cutoff, P < 0.05) were identified in GSRCC compared with non-GSRCC. The enriched KEGG and PANTHER pathways for the differential genes included immune response pathways, metabolic pathways, and metastasis-associated pathways. Ten genes (MAGEA2, MAGEA2B, MAGEA3, MAGEA4, MAGEA6, MUC13, GUCA2A, FFAR4, REG1A, and REG1B) were identified as hub genes in the protein-protein interaction network. The expression levels of five genes (MAGEA2, MAGEA3, MAGEA4, MAGEA6, and REG1B) showed potential clinical value. CONCLUSION: We have identified the potential key genes and pathways in GSRCC, and these hub genes and pathways could be diagnostic markers and therapeutic targets for GSRCC. Baishideng Publishing Group Inc 2020-02-26 2020-02-26 /pmc/articles/PMC7052547/ /pubmed/32149050 http://dx.doi.org/10.12998/wjcc.v8.i4.658 Text en ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. |
spellingShingle | Clinical and Translational Research Zhao, Zi-Tong Li, Yang Yuan, Hong-Yu Ma, Fu-Hai Song, Yong-Mei Tian, Yan-Tao Identification of key genes and pathways in gastric signet ring cell carcinoma based on transcriptome analysis |
title | Identification of key genes and pathways in gastric signet ring cell carcinoma based on transcriptome analysis |
title_full | Identification of key genes and pathways in gastric signet ring cell carcinoma based on transcriptome analysis |
title_fullStr | Identification of key genes and pathways in gastric signet ring cell carcinoma based on transcriptome analysis |
title_full_unstemmed | Identification of key genes and pathways in gastric signet ring cell carcinoma based on transcriptome analysis |
title_short | Identification of key genes and pathways in gastric signet ring cell carcinoma based on transcriptome analysis |
title_sort | identification of key genes and pathways in gastric signet ring cell carcinoma based on transcriptome analysis |
topic | Clinical and Translational Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052547/ https://www.ncbi.nlm.nih.gov/pubmed/32149050 http://dx.doi.org/10.12998/wjcc.v8.i4.658 |
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