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Screening and identification of autophagy‐related biomarkers for oral squamous cell carcinoma (OSCC) via integrated bioinformatics analysis
Increasing evidences have showed that autophagy played a significant role in oral squamous cell carcinoma (OSCC). Purpose of our study was to explore the prognostic value of autophagy‐related genes (ATGs) and screen autophagy‐related biomarkers for OSCC. RNA‐seq and clinical data were downloaded fro...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093968/ https://www.ncbi.nlm.nih.gov/pubmed/33837652 http://dx.doi.org/10.1111/jcmm.16512 |
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author | Huang, Guang‐zhao Lu, Zhi‐yun Rao, Yu Gao, Hai Lv, Xiao‐zhi |
author_facet | Huang, Guang‐zhao Lu, Zhi‐yun Rao, Yu Gao, Hai Lv, Xiao‐zhi |
author_sort | Huang, Guang‐zhao |
collection | PubMed |
description | Increasing evidences have showed that autophagy played a significant role in oral squamous cell carcinoma (OSCC). Purpose of our study was to explore the prognostic value of autophagy‐related genes (ATGs) and screen autophagy‐related biomarkers for OSCC. RNA‐seq and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database following extracting ATG expression profiles. Then, differentially expressed analysis was performed in R software and a risk score model according to ATGs was established. Moreover, comprehensive bioinformatics analyses were used to screen autophagy‐related biomarkers which were later verified in OSCC tissues and cell lines. A total of 232 ATGs were extracted, and 37 genes were differentially expressed in OSCC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that these genes were mainly located in autophagosome membrane and associated with autophagy. Furthermore, the risk score on basis of ATGs was identified as potential independent prognostic biomarker. Moreover, ATG12 and BID were identified as potential autophagy‐related biomarkers of OSCC. This study successfully constructed a risk model, and the risk score could predict the prognosis of OSCC patients accurately. Moreover, ATG12 and BID were identified as two potential independent prognostic autophagy‐related biomarkers and might provide new OSCC therapeutic targets. |
format | Online Article Text |
id | pubmed-8093968 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80939682021-05-10 Screening and identification of autophagy‐related biomarkers for oral squamous cell carcinoma (OSCC) via integrated bioinformatics analysis Huang, Guang‐zhao Lu, Zhi‐yun Rao, Yu Gao, Hai Lv, Xiao‐zhi J Cell Mol Med Original Articles Increasing evidences have showed that autophagy played a significant role in oral squamous cell carcinoma (OSCC). Purpose of our study was to explore the prognostic value of autophagy‐related genes (ATGs) and screen autophagy‐related biomarkers for OSCC. RNA‐seq and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database following extracting ATG expression profiles. Then, differentially expressed analysis was performed in R software and a risk score model according to ATGs was established. Moreover, comprehensive bioinformatics analyses were used to screen autophagy‐related biomarkers which were later verified in OSCC tissues and cell lines. A total of 232 ATGs were extracted, and 37 genes were differentially expressed in OSCC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that these genes were mainly located in autophagosome membrane and associated with autophagy. Furthermore, the risk score on basis of ATGs was identified as potential independent prognostic biomarker. Moreover, ATG12 and BID were identified as potential autophagy‐related biomarkers of OSCC. This study successfully constructed a risk model, and the risk score could predict the prognosis of OSCC patients accurately. Moreover, ATG12 and BID were identified as two potential independent prognostic autophagy‐related biomarkers and might provide new OSCC therapeutic targets. John Wiley and Sons Inc. 2021-04-09 2021-05 /pmc/articles/PMC8093968/ /pubmed/33837652 http://dx.doi.org/10.1111/jcmm.16512 Text en © 2021 The Authors. Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Huang, Guang‐zhao Lu, Zhi‐yun Rao, Yu Gao, Hai Lv, Xiao‐zhi Screening and identification of autophagy‐related biomarkers for oral squamous cell carcinoma (OSCC) via integrated bioinformatics analysis |
title | Screening and identification of autophagy‐related biomarkers for oral squamous cell carcinoma (OSCC) via integrated bioinformatics analysis |
title_full | Screening and identification of autophagy‐related biomarkers for oral squamous cell carcinoma (OSCC) via integrated bioinformatics analysis |
title_fullStr | Screening and identification of autophagy‐related biomarkers for oral squamous cell carcinoma (OSCC) via integrated bioinformatics analysis |
title_full_unstemmed | Screening and identification of autophagy‐related biomarkers for oral squamous cell carcinoma (OSCC) via integrated bioinformatics analysis |
title_short | Screening and identification of autophagy‐related biomarkers for oral squamous cell carcinoma (OSCC) via integrated bioinformatics analysis |
title_sort | screening and identification of autophagy‐related biomarkers for oral squamous cell carcinoma (oscc) via integrated bioinformatics analysis |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093968/ https://www.ncbi.nlm.nih.gov/pubmed/33837652 http://dx.doi.org/10.1111/jcmm.16512 |
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