Cargando…
Identification of Key Candidate Genes and Pathways for Relationship between Ovarian Cancer and Diabetes Mellitus Using Bioinformatical Analysis
Ovarian cancer is one of the three major gynecologic cancers in the world. The aim of this study is to find the relationship between ovarian cancer and diabetes mellitus by using the genetic screening technique. By GEO database query and related online tools of analysis, we analyzed 185 cases of ova...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
West Asia Organization for Cancer Prevention
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6485580/ https://www.ncbi.nlm.nih.gov/pubmed/30678426 http://dx.doi.org/10.31557/APJCP.2019.20.1.145 |
_version_ | 1783414280040742912 |
---|---|
author | Sun, Yi Xiaoyan, Huang Yun, Liu Chaoqun, Liu Jialing, Wen Liu, Yang Yingqi, Zhao Peipei, Yi Junjun, Peng Yuanming, Lu |
author_facet | Sun, Yi Xiaoyan, Huang Yun, Liu Chaoqun, Liu Jialing, Wen Liu, Yang Yingqi, Zhao Peipei, Yi Junjun, Peng Yuanming, Lu |
author_sort | Sun, Yi |
collection | PubMed |
description | Ovarian cancer is one of the three major gynecologic cancers in the world. The aim of this study is to find the relationship between ovarian cancer and diabetes mellitus by using the genetic screening technique. By GEO database query and related online tools of analysis, we analyzed 185 cases of ovarian cancer and 10 control samples from GSE26712, and a total of 379 different genes were identified, including 104 up-regulated genes and 275 down-regulated genes. The up-regulated genes were mainly enriched in biological processes, including cell adhesion, transcription of nucleic acid and biosynthesis, and negative regulation of cell metabolism. The down-regulated genes were enriched in cell proliferation, migration, angiogenesis and macromolecular metabolism. Protein-protein interaction was analyzed by network diagram and module synthesis analysis. The top ten hub genes (CDC20, H2AFX, ENO1, ACTB, ISG15, KAT2B, HNRNPD, YWHAE, GJA1 and CAV1) were identified, which play important roles in critical signaling pathways that regulate the process of oxidation-reduction reaction and carboxylic acid metabolism. CTD analysis showed that the hub genes were involved in 1,128 distinct diseases (bonferroni-corrected P<0.05). Further analysis by drawing the Kaplan-Meier survival curve indicated that CDC20 and ISG15 were statistically significant (P<0.05). In conclusion, glycometabolism was related to ovarian cancer and genes and proteins in glycometabolism could serve as potential targets in ovarian cancer treatment. |
format | Online Article Text |
id | pubmed-6485580 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | West Asia Organization for Cancer Prevention |
record_format | MEDLINE/PubMed |
spelling | pubmed-64855802019-05-13 Identification of Key Candidate Genes and Pathways for Relationship between Ovarian Cancer and Diabetes Mellitus Using Bioinformatical Analysis Sun, Yi Xiaoyan, Huang Yun, Liu Chaoqun, Liu Jialing, Wen Liu, Yang Yingqi, Zhao Peipei, Yi Junjun, Peng Yuanming, Lu Asian Pac J Cancer Prev Research Article Ovarian cancer is one of the three major gynecologic cancers in the world. The aim of this study is to find the relationship between ovarian cancer and diabetes mellitus by using the genetic screening technique. By GEO database query and related online tools of analysis, we analyzed 185 cases of ovarian cancer and 10 control samples from GSE26712, and a total of 379 different genes were identified, including 104 up-regulated genes and 275 down-regulated genes. The up-regulated genes were mainly enriched in biological processes, including cell adhesion, transcription of nucleic acid and biosynthesis, and negative regulation of cell metabolism. The down-regulated genes were enriched in cell proliferation, migration, angiogenesis and macromolecular metabolism. Protein-protein interaction was analyzed by network diagram and module synthesis analysis. The top ten hub genes (CDC20, H2AFX, ENO1, ACTB, ISG15, KAT2B, HNRNPD, YWHAE, GJA1 and CAV1) were identified, which play important roles in critical signaling pathways that regulate the process of oxidation-reduction reaction and carboxylic acid metabolism. CTD analysis showed that the hub genes were involved in 1,128 distinct diseases (bonferroni-corrected P<0.05). Further analysis by drawing the Kaplan-Meier survival curve indicated that CDC20 and ISG15 were statistically significant (P<0.05). In conclusion, glycometabolism was related to ovarian cancer and genes and proteins in glycometabolism could serve as potential targets in ovarian cancer treatment. West Asia Organization for Cancer Prevention 2019 /pmc/articles/PMC6485580/ /pubmed/30678426 http://dx.doi.org/10.31557/APJCP.2019.20.1.145 Text en Copyright: © Asian Pacific Journal of Cancer Prevention http://creativecommons.org/licenses/BY-SA/4.0 This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License |
spellingShingle | Research Article Sun, Yi Xiaoyan, Huang Yun, Liu Chaoqun, Liu Jialing, Wen Liu, Yang Yingqi, Zhao Peipei, Yi Junjun, Peng Yuanming, Lu Identification of Key Candidate Genes and Pathways for Relationship between Ovarian Cancer and Diabetes Mellitus Using Bioinformatical Analysis |
title | Identification of Key Candidate Genes and Pathways for Relationship between Ovarian Cancer and Diabetes Mellitus Using Bioinformatical Analysis |
title_full | Identification of Key Candidate Genes and Pathways for Relationship between Ovarian Cancer and Diabetes Mellitus Using Bioinformatical Analysis |
title_fullStr | Identification of Key Candidate Genes and Pathways for Relationship between Ovarian Cancer and Diabetes Mellitus Using Bioinformatical Analysis |
title_full_unstemmed | Identification of Key Candidate Genes and Pathways for Relationship between Ovarian Cancer and Diabetes Mellitus Using Bioinformatical Analysis |
title_short | Identification of Key Candidate Genes and Pathways for Relationship between Ovarian Cancer and Diabetes Mellitus Using Bioinformatical Analysis |
title_sort | identification of key candidate genes and pathways for relationship between ovarian cancer and diabetes mellitus using bioinformatical analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6485580/ https://www.ncbi.nlm.nih.gov/pubmed/30678426 http://dx.doi.org/10.31557/APJCP.2019.20.1.145 |
work_keys_str_mv | AT sunyi identificationofkeycandidategenesandpathwaysforrelationshipbetweenovariancanceranddiabetesmellitususingbioinformaticalanalysis AT xiaoyanhuang identificationofkeycandidategenesandpathwaysforrelationshipbetweenovariancanceranddiabetesmellitususingbioinformaticalanalysis AT yunliu identificationofkeycandidategenesandpathwaysforrelationshipbetweenovariancanceranddiabetesmellitususingbioinformaticalanalysis AT chaoqunliu identificationofkeycandidategenesandpathwaysforrelationshipbetweenovariancanceranddiabetesmellitususingbioinformaticalanalysis AT jialingwen identificationofkeycandidategenesandpathwaysforrelationshipbetweenovariancanceranddiabetesmellitususingbioinformaticalanalysis AT liuyang identificationofkeycandidategenesandpathwaysforrelationshipbetweenovariancanceranddiabetesmellitususingbioinformaticalanalysis AT yingqizhao identificationofkeycandidategenesandpathwaysforrelationshipbetweenovariancanceranddiabetesmellitususingbioinformaticalanalysis AT peipeiyi identificationofkeycandidategenesandpathwaysforrelationshipbetweenovariancanceranddiabetesmellitususingbioinformaticalanalysis AT junjunpeng identificationofkeycandidategenesandpathwaysforrelationshipbetweenovariancanceranddiabetesmellitususingbioinformaticalanalysis AT yuanminglu identificationofkeycandidategenesandpathwaysforrelationshipbetweenovariancanceranddiabetesmellitususingbioinformaticalanalysis |