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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...

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Detalles Bibliográficos
Autores principales: Li, Yiting, Gu, Shinong, Li, Xuanwen, Huang, Qing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
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.
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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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