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Computational analysis for identification of the extracellular matrix molecules involved in endometrial cancer progression

Recurrence and poorly differentiated (grade 3 and above) and atypical cell type endometrial cancer (EC) have poor prognosis outcome. The mechanisms and characteristics of recurrence and distal metastasis of EC remain unclear. The extracellular matrix (ECM) of the reproductive tract in women undergoe...

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Autores principales: Yadav, Vijesh Kumar, Lee, Tzong-Yi, Hsu, Justin Bo-Kai, Huang, Hsien-Da, Yang, Wei-Chung Vivian, Chang, Tzu-Hao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7173926/
https://www.ncbi.nlm.nih.gov/pubmed/32315343
http://dx.doi.org/10.1371/journal.pone.0231594
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author Yadav, Vijesh Kumar
Lee, Tzong-Yi
Hsu, Justin Bo-Kai
Huang, Hsien-Da
Yang, Wei-Chung Vivian
Chang, Tzu-Hao
author_facet Yadav, Vijesh Kumar
Lee, Tzong-Yi
Hsu, Justin Bo-Kai
Huang, Hsien-Da
Yang, Wei-Chung Vivian
Chang, Tzu-Hao
author_sort Yadav, Vijesh Kumar
collection PubMed
description Recurrence and poorly differentiated (grade 3 and above) and atypical cell type endometrial cancer (EC) have poor prognosis outcome. The mechanisms and characteristics of recurrence and distal metastasis of EC remain unclear. The extracellular matrix (ECM) of the reproductive tract in women undergoes extensive structural remodelling changes every month. Altered ECMs surrounding cells were believed to play crucial roles in a cancer progression. To decipher the associations between ECM and EC development, we generated a PAN-ECM Data list of 1516 genes including ECM molecules (ECMs), synthetic and degradation enzymes for ECMs, ECM receptors, and soluble molecules that regulate ECM and used RNA-Seq data from The Cancer Genome Atlas (TCGA) for the studies. The alterations of PAN-ECM genes by comparing the RNA-Seq expressions profiles of EC samples which have been grouped as tumorigenesis and metastasis group based on their pathological grading were identified. Differential analyses including functional enrichment, co-expression network, and molecular network analysis were carried out to identify the specific PAN-ECM genes that may involve in the progression of EC. Eight hundred and thirty-one and 241 PAN-ECM genes were significantly involved in tumorigenesis (p-value <1.571e-15) and metastasis (p-value <2.2e-16), respectively, whereas 140 genes were in the intersection of tumorigenesis and metastasis. Interestingly, 92 of the 140 intersecting PAN-ECM genes showed contrasting fold changes between the tumorigenesis and metastasis datasets. Enrichment analysis for the contrast PAN-ECM genes indicated pathways such as GP6 signaling, ILK signaling, and interleukin (IL)-8 signaling pathways were activated in metastasis but inhibited in tumorigenesis. The significantly activated ECM and ECM associated genes in GP6 signaling, ILK signaling, and interleukin (IL)-8 signaling pathways may play crucial roles in metastasis of EC. Our study provides a better understanding of the etiology and the progression of EC.
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spelling pubmed-71739262020-04-27 Computational analysis for identification of the extracellular matrix molecules involved in endometrial cancer progression Yadav, Vijesh Kumar Lee, Tzong-Yi Hsu, Justin Bo-Kai Huang, Hsien-Da Yang, Wei-Chung Vivian Chang, Tzu-Hao PLoS One Research Article Recurrence and poorly differentiated (grade 3 and above) and atypical cell type endometrial cancer (EC) have poor prognosis outcome. The mechanisms and characteristics of recurrence and distal metastasis of EC remain unclear. The extracellular matrix (ECM) of the reproductive tract in women undergoes extensive structural remodelling changes every month. Altered ECMs surrounding cells were believed to play crucial roles in a cancer progression. To decipher the associations between ECM and EC development, we generated a PAN-ECM Data list of 1516 genes including ECM molecules (ECMs), synthetic and degradation enzymes for ECMs, ECM receptors, and soluble molecules that regulate ECM and used RNA-Seq data from The Cancer Genome Atlas (TCGA) for the studies. The alterations of PAN-ECM genes by comparing the RNA-Seq expressions profiles of EC samples which have been grouped as tumorigenesis and metastasis group based on their pathological grading were identified. Differential analyses including functional enrichment, co-expression network, and molecular network analysis were carried out to identify the specific PAN-ECM genes that may involve in the progression of EC. Eight hundred and thirty-one and 241 PAN-ECM genes were significantly involved in tumorigenesis (p-value <1.571e-15) and metastasis (p-value <2.2e-16), respectively, whereas 140 genes were in the intersection of tumorigenesis and metastasis. Interestingly, 92 of the 140 intersecting PAN-ECM genes showed contrasting fold changes between the tumorigenesis and metastasis datasets. Enrichment analysis for the contrast PAN-ECM genes indicated pathways such as GP6 signaling, ILK signaling, and interleukin (IL)-8 signaling pathways were activated in metastasis but inhibited in tumorigenesis. The significantly activated ECM and ECM associated genes in GP6 signaling, ILK signaling, and interleukin (IL)-8 signaling pathways may play crucial roles in metastasis of EC. Our study provides a better understanding of the etiology and the progression of EC. Public Library of Science 2020-04-21 /pmc/articles/PMC7173926/ /pubmed/32315343 http://dx.doi.org/10.1371/journal.pone.0231594 Text en © 2020 Yadav et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Yadav, Vijesh Kumar
Lee, Tzong-Yi
Hsu, Justin Bo-Kai
Huang, Hsien-Da
Yang, Wei-Chung Vivian
Chang, Tzu-Hao
Computational analysis for identification of the extracellular matrix molecules involved in endometrial cancer progression
title Computational analysis for identification of the extracellular matrix molecules involved in endometrial cancer progression
title_full Computational analysis for identification of the extracellular matrix molecules involved in endometrial cancer progression
title_fullStr Computational analysis for identification of the extracellular matrix molecules involved in endometrial cancer progression
title_full_unstemmed Computational analysis for identification of the extracellular matrix molecules involved in endometrial cancer progression
title_short Computational analysis for identification of the extracellular matrix molecules involved in endometrial cancer progression
title_sort computational analysis for identification of the extracellular matrix molecules involved in endometrial cancer progression
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7173926/
https://www.ncbi.nlm.nih.gov/pubmed/32315343
http://dx.doi.org/10.1371/journal.pone.0231594
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