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To identify biomarkers associated with the transfer of diabetes combined with cancer in human genes using bioinformatics analysis
Currently, the incidence of diabetes mellitus is increasing rapidly, particularly in China, and its pathogenesis is still unclear. The goal of this study was to find meaningful biomarkers of metastasis in patients with diabetes and cancer using bioinformatic analysis in order to predict gene express...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10508432/ https://www.ncbi.nlm.nih.gov/pubmed/37713834 http://dx.doi.org/10.1097/MD.0000000000035080 |
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author | Li, Yiting Gu, Shinong Li, Xuanwen Huang, Qing |
author_facet | Li, Yiting Gu, Shinong Li, Xuanwen Huang, Qing |
author_sort | Li, Yiting |
collection | PubMed |
description | Currently, the incidence of diabetes mellitus is increasing rapidly, particularly in China, and its pathogenesis is still unclear. The goal of this study was to find meaningful biomarkers of metastasis in patients with diabetes and cancer using bioinformatic analysis in order to predict gene expression and prognostic importance for survival. We used the Differentially Expressed Gene, Database for Annotation Visualization and Integrated Discovery, and Gene Set Enrichment Analyses databases, as well as several bioinformatics tools, to explore the key genes in diabetes. Based on the above database, we ended up with 10 hub genes (FOS, ATF3, JUN, EGR1, FOSB, JUNB, BTG2, EGR2, ZFP36, and NR4A2). A discussion of the 10 critical genes, with extensive literature mentioned to validate the association between the 10 key genes and patients with diabetes and cancer, to demonstrate the importance of gene expression and survival prognosis. This study identifies several biomarkers associated with diabetes and cancer development and metastasis that may provide novel therapeutic targets for diabetes combined with cancer patients. |
format | Online Article Text |
id | pubmed-10508432 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-105084322023-09-20 To identify biomarkers associated with the transfer of diabetes combined with cancer in human genes using bioinformatics analysis Li, Yiting Gu, Shinong Li, Xuanwen Huang, Qing Medicine (Baltimore) Research Article: Observational Study Currently, the incidence of diabetes mellitus is increasing rapidly, particularly in China, and its pathogenesis is still unclear. The goal of this study was to find meaningful biomarkers of metastasis in patients with diabetes and cancer using bioinformatic analysis in order to predict gene expression and prognostic importance for survival. We used the Differentially Expressed Gene, Database for Annotation Visualization and Integrated Discovery, and Gene Set Enrichment Analyses databases, as well as several bioinformatics tools, to explore the key genes in diabetes. Based on the above database, we ended up with 10 hub genes (FOS, ATF3, JUN, EGR1, FOSB, JUNB, BTG2, EGR2, ZFP36, and NR4A2). A discussion of the 10 critical genes, with extensive literature mentioned to validate the association between the 10 key genes and patients with diabetes and cancer, to demonstrate the importance of gene expression and survival prognosis. This study identifies several biomarkers associated with diabetes and cancer development and metastasis that may provide novel therapeutic targets for diabetes combined with cancer patients. Lippincott Williams & Wilkins 2023-09-15 /pmc/articles/PMC10508432/ /pubmed/37713834 http://dx.doi.org/10.1097/MD.0000000000035080 Text en Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC) (https://creativecommons.org/licenses/by-nc/4.0/) , where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. |
spellingShingle | Research Article: Observational Study Li, Yiting Gu, Shinong Li, Xuanwen Huang, Qing To identify biomarkers associated with the transfer of diabetes combined with cancer in human genes using bioinformatics analysis |
title | To identify biomarkers associated with the transfer of diabetes combined with cancer in human genes using bioinformatics analysis |
title_full | To identify biomarkers associated with the transfer of diabetes combined with cancer in human genes using bioinformatics analysis |
title_fullStr | To identify biomarkers associated with the transfer of diabetes combined with cancer in human genes using bioinformatics analysis |
title_full_unstemmed | To identify biomarkers associated with the transfer of diabetes combined with cancer in human genes using bioinformatics analysis |
title_short | To identify biomarkers associated with the transfer of diabetes combined with cancer in human genes using bioinformatics analysis |
title_sort | to identify biomarkers associated with the transfer of diabetes combined with cancer in human genes using bioinformatics analysis |
topic | Research Article: Observational Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10508432/ https://www.ncbi.nlm.nih.gov/pubmed/37713834 http://dx.doi.org/10.1097/MD.0000000000035080 |
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