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Combining bioinformatics techniques to explore the molecular mechanisms involved in pancreatic cancer metastasis and prognosis
This article aims to explore the underlying molecular mechanisms and prognosis‐related genes in pancreatic cancer metastasis. Pancreatic cancer metastasis‐related gene chip data were downloaded from GENE EXPRESSION OMNIBUS(GEO)database. Differentially expressed genes were screened after R‐package pr...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7754005/ https://www.ncbi.nlm.nih.gov/pubmed/33164330 http://dx.doi.org/10.1111/jcmm.16023 |
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author | Xu, Jia‐Sheng Liao, Kai‐li Wang, Xinlu He, Jiarui Wang, Xiao‐Zhong |
author_facet | Xu, Jia‐Sheng Liao, Kai‐li Wang, Xinlu He, Jiarui Wang, Xiao‐Zhong |
author_sort | Xu, Jia‐Sheng |
collection | PubMed |
description | This article aims to explore the underlying molecular mechanisms and prognosis‐related genes in pancreatic cancer metastasis. Pancreatic cancer metastasis‐related gene chip data were downloaded from GENE EXPRESSION OMNIBUS(GEO)database. Differentially expressed genes were screened after R‐package pre‐treatment. Functional annotations and related signalling pathways were analysed using DAVID software. GEPIA (Gene Expression Profiling Interactive Analysis) was used to perform prognostic analysis, and differential genes associated with prognosis were screened and validated using data from GEO. We screened 40 healthy patients, 40 primary pancreatic cancer and 40 metastatic pancreatic cancer patients, collected serum, designed primers and used qPCR to test the expression of prognosis‐related genes in each group. 109 differentially expressed genes related with pancreatic cancer metastasis were screened, of which 49 were up‐regulated and 60 were down‐regulated. Functional annotation and pathway analysis revealed differentially expressed genes were mainly concentrated in protein activation cascade, extracellular matrix construction, decomposition, etc In the biological process, it is mainly involved in signalling pathways such as PPAR, PI3K‐Akt and ECM receptor interaction. Prognostic analysis showed the expression levels of four genes were significantly correlated with the overall survival time of patients with pancreatic cancer, namely SCG5, CRYBA2, CPE and CHGB. qPCR experiments showed the expression of these four genes was decreased in both the primary pancreatic cancer group and the metastatic pancreatic cancer group, and the latter was more significantly reduced. Pancreatic cancer metastasis is closely related to the activation of PPAR pathway, PI3K‐Akt pathway and ECM receptor interaction. SCG5, CRYBA2, CPE and CHGB genes are associated with the prognosis of pancreatic cancer, and their low expression suggests a poor prognosis. |
format | Online Article Text |
id | pubmed-7754005 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77540052020-12-23 Combining bioinformatics techniques to explore the molecular mechanisms involved in pancreatic cancer metastasis and prognosis Xu, Jia‐Sheng Liao, Kai‐li Wang, Xinlu He, Jiarui Wang, Xiao‐Zhong J Cell Mol Med Original Articles This article aims to explore the underlying molecular mechanisms and prognosis‐related genes in pancreatic cancer metastasis. Pancreatic cancer metastasis‐related gene chip data were downloaded from GENE EXPRESSION OMNIBUS(GEO)database. Differentially expressed genes were screened after R‐package pre‐treatment. Functional annotations and related signalling pathways were analysed using DAVID software. GEPIA (Gene Expression Profiling Interactive Analysis) was used to perform prognostic analysis, and differential genes associated with prognosis were screened and validated using data from GEO. We screened 40 healthy patients, 40 primary pancreatic cancer and 40 metastatic pancreatic cancer patients, collected serum, designed primers and used qPCR to test the expression of prognosis‐related genes in each group. 109 differentially expressed genes related with pancreatic cancer metastasis were screened, of which 49 were up‐regulated and 60 were down‐regulated. Functional annotation and pathway analysis revealed differentially expressed genes were mainly concentrated in protein activation cascade, extracellular matrix construction, decomposition, etc In the biological process, it is mainly involved in signalling pathways such as PPAR, PI3K‐Akt and ECM receptor interaction. Prognostic analysis showed the expression levels of four genes were significantly correlated with the overall survival time of patients with pancreatic cancer, namely SCG5, CRYBA2, CPE and CHGB. qPCR experiments showed the expression of these four genes was decreased in both the primary pancreatic cancer group and the metastatic pancreatic cancer group, and the latter was more significantly reduced. Pancreatic cancer metastasis is closely related to the activation of PPAR pathway, PI3K‐Akt pathway and ECM receptor interaction. SCG5, CRYBA2, CPE and CHGB genes are associated with the prognosis of pancreatic cancer, and their low expression suggests a poor prognosis. John Wiley and Sons Inc. 2020-11-09 2020-12 /pmc/articles/PMC7754005/ /pubmed/33164330 http://dx.doi.org/10.1111/jcmm.16023 Text en © 2020 The Authors. Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Xu, Jia‐Sheng Liao, Kai‐li Wang, Xinlu He, Jiarui Wang, Xiao‐Zhong Combining bioinformatics techniques to explore the molecular mechanisms involved in pancreatic cancer metastasis and prognosis |
title | Combining bioinformatics techniques to explore the molecular mechanisms involved in pancreatic cancer metastasis and prognosis |
title_full | Combining bioinformatics techniques to explore the molecular mechanisms involved in pancreatic cancer metastasis and prognosis |
title_fullStr | Combining bioinformatics techniques to explore the molecular mechanisms involved in pancreatic cancer metastasis and prognosis |
title_full_unstemmed | Combining bioinformatics techniques to explore the molecular mechanisms involved in pancreatic cancer metastasis and prognosis |
title_short | Combining bioinformatics techniques to explore the molecular mechanisms involved in pancreatic cancer metastasis and prognosis |
title_sort | combining bioinformatics techniques to explore the molecular mechanisms involved in pancreatic cancer metastasis and prognosis |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7754005/ https://www.ncbi.nlm.nih.gov/pubmed/33164330 http://dx.doi.org/10.1111/jcmm.16023 |
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