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Deciphering the scalene association among type‐2 diabetes mellitus, prostate cancer, and chronic myeloid leukemia via enrichment analysis of disease‐gene network

The potential biological relationship between type‐2 diabetes mellitus (T2DM) has been focused in numerous studies. To investigate the molecular associations among T2DM, prostate cancer (PCa), and chronic myeloid leukemia (CML), using a biomolecular network enrichment analysis. We obtained a list of...

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Autores principales: Liu, Qiong, Zhang, Yingying, Wang, Pengqian, Liu, Jun, Li, Bing, Yu, Yanan, Wu, Hongli, Kang, Ruixia, Zhang, Xiaoxu, Wang, Zhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6536925/
https://www.ncbi.nlm.nih.gov/pubmed/30938105
http://dx.doi.org/10.1002/cam4.1845
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author Liu, Qiong
Zhang, Yingying
Wang, Pengqian
Liu, Jun
Li, Bing
Yu, Yanan
Wu, Hongli
Kang, Ruixia
Zhang, Xiaoxu
Wang, Zhong
author_facet Liu, Qiong
Zhang, Yingying
Wang, Pengqian
Liu, Jun
Li, Bing
Yu, Yanan
Wu, Hongli
Kang, Ruixia
Zhang, Xiaoxu
Wang, Zhong
author_sort Liu, Qiong
collection PubMed
description The potential biological relationship between type‐2 diabetes mellitus (T2DM) has been focused in numerous studies. To investigate the molecular associations among T2DM, prostate cancer (PCa), and chronic myeloid leukemia (CML), using a biomolecular network enrichment analysis. We obtained a list of disease‐related genes and constructed disease networks. Then, GO enrichment analysis was performed to identify the significant functions and pathways of overlapping modules in the Database for Annotation, Visualization and Integrated Discovery (DAVID) database. More than 75% of these overlapping genes were found to be consistent with the findings of previous studies. In the three diseases, we found that Sarcoglycan delta (SGCD) and Rho family GTPase 3 (RND3) were the overlapping genes and identified negative regulation of apoptotic process and negative regulation of transcription from RNA polymerase II promoter RNA as the two overlapping biological functions. CML and PCa were the most closely related, with 34 overlapping genes, five overlapping modules, 27 overlapping biological functions, and nine overlapping pathways. There were 13 overlapping genes, one overlapping modules, four overlapping biological functions and one overlapping pathway (FoxO signaling pathway) were found in T2DM and CML.And T2DM and PCa were the least related pair in our study, with only six overlapping genes, five overlapping modules, and one overlapping biological function. SGCD and RND3 were the main gene‐to‐gene relationship among T2DM, CML, and PCa; apoptosis, development, and transcription from RNA polymerase II promote processes were the main functional connections among T2DM, CML, and PCa by network enrichment analysis. There is a “scalene” relationship among T2DM, CML, and PCa at gene, pathway, biological process, and module levels: CML and PCa were the most closely related, the second were T2DM and PCa, and T2DM and PCa were the least related pair in our study. Our study provides a new avenue for further studies on T2DM and cancers, which may promote the discovery and development of novel therapeutic and can be used to treat multiple diseases.
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spelling pubmed-65369252019-06-03 Deciphering the scalene association among type‐2 diabetes mellitus, prostate cancer, and chronic myeloid leukemia via enrichment analysis of disease‐gene network Liu, Qiong Zhang, Yingying Wang, Pengqian Liu, Jun Li, Bing Yu, Yanan Wu, Hongli Kang, Ruixia Zhang, Xiaoxu Wang, Zhong Cancer Med Cancer Biology The potential biological relationship between type‐2 diabetes mellitus (T2DM) has been focused in numerous studies. To investigate the molecular associations among T2DM, prostate cancer (PCa), and chronic myeloid leukemia (CML), using a biomolecular network enrichment analysis. We obtained a list of disease‐related genes and constructed disease networks. Then, GO enrichment analysis was performed to identify the significant functions and pathways of overlapping modules in the Database for Annotation, Visualization and Integrated Discovery (DAVID) database. More than 75% of these overlapping genes were found to be consistent with the findings of previous studies. In the three diseases, we found that Sarcoglycan delta (SGCD) and Rho family GTPase 3 (RND3) were the overlapping genes and identified negative regulation of apoptotic process and negative regulation of transcription from RNA polymerase II promoter RNA as the two overlapping biological functions. CML and PCa were the most closely related, with 34 overlapping genes, five overlapping modules, 27 overlapping biological functions, and nine overlapping pathways. There were 13 overlapping genes, one overlapping modules, four overlapping biological functions and one overlapping pathway (FoxO signaling pathway) were found in T2DM and CML.And T2DM and PCa were the least related pair in our study, with only six overlapping genes, five overlapping modules, and one overlapping biological function. SGCD and RND3 were the main gene‐to‐gene relationship among T2DM, CML, and PCa; apoptosis, development, and transcription from RNA polymerase II promote processes were the main functional connections among T2DM, CML, and PCa by network enrichment analysis. There is a “scalene” relationship among T2DM, CML, and PCa at gene, pathway, biological process, and module levels: CML and PCa were the most closely related, the second were T2DM and PCa, and T2DM and PCa were the least related pair in our study. Our study provides a new avenue for further studies on T2DM and cancers, which may promote the discovery and development of novel therapeutic and can be used to treat multiple diseases. John Wiley and Sons Inc. 2019-04-01 /pmc/articles/PMC6536925/ /pubmed/30938105 http://dx.doi.org/10.1002/cam4.1845 Text en © 2019 The Authors. Cancer Medicine published by 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 Cancer Biology
Liu, Qiong
Zhang, Yingying
Wang, Pengqian
Liu, Jun
Li, Bing
Yu, Yanan
Wu, Hongli
Kang, Ruixia
Zhang, Xiaoxu
Wang, Zhong
Deciphering the scalene association among type‐2 diabetes mellitus, prostate cancer, and chronic myeloid leukemia via enrichment analysis of disease‐gene network
title Deciphering the scalene association among type‐2 diabetes mellitus, prostate cancer, and chronic myeloid leukemia via enrichment analysis of disease‐gene network
title_full Deciphering the scalene association among type‐2 diabetes mellitus, prostate cancer, and chronic myeloid leukemia via enrichment analysis of disease‐gene network
title_fullStr Deciphering the scalene association among type‐2 diabetes mellitus, prostate cancer, and chronic myeloid leukemia via enrichment analysis of disease‐gene network
title_full_unstemmed Deciphering the scalene association among type‐2 diabetes mellitus, prostate cancer, and chronic myeloid leukemia via enrichment analysis of disease‐gene network
title_short Deciphering the scalene association among type‐2 diabetes mellitus, prostate cancer, and chronic myeloid leukemia via enrichment analysis of disease‐gene network
title_sort deciphering the scalene association among type‐2 diabetes mellitus, prostate cancer, and chronic myeloid leukemia via enrichment analysis of disease‐gene network
topic Cancer Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6536925/
https://www.ncbi.nlm.nih.gov/pubmed/30938105
http://dx.doi.org/10.1002/cam4.1845
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