A Novel Autophagy-Related Prognostic Risk Model and a Nomogram for Survival Prediction of Oral Cancer Patients
Background. This study is aimed at constructing a risk signature to predict survival outcomes of ORCA patients. Methods. We identified differentially expressed autophagy-related genes (DEARGs) based on the RNA sequencing data in the TCGA database; then, four independent survival-related ARGs were id...
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ftdoajarticles:oai:doaj.org/article:a4e9499b3ab24e0ab14b77e0880e3b7e 2023-05-15T17:53:10+02:00 A Novel Autophagy-Related Prognostic Risk Model and a Nomogram for Survival Prediction of Oral Cancer Patients Hongjun Fei Xiongming Chen 2022-01-01T00:00:00Z https://doi.org/10.1155/2022/2067540 https://doaj.org/article/a4e9499b3ab24e0ab14b77e0880e3b7e EN eng Hindawi Limited http://dx.doi.org/10.1155/2022/2067540 https://doaj.org/toc/2314-6141 2314-6141 doi:10.1155/2022/2067540 https://doaj.org/article/a4e9499b3ab24e0ab14b77e0880e3b7e BioMed Research International, Vol 2022 (2022) Medicine R article 2022 ftdoajarticles https://doi.org/10.1155/2022/2067540 2022-12-30T20:27:09Z Background. This study is aimed at constructing a risk signature to predict survival outcomes of ORCA patients. Methods. We identified differentially expressed autophagy-related genes (DEARGs) based on the RNA sequencing data in the TCGA database; then, four independent survival-related ARGs were identified to construct an autophagy-associated signature for survival prediction of ORCA patients. The validity and robustness of the prognostic model were validated by clinicopathological data and survival data. Subsequently, four independent prognostic DEARGs that composed the model were evaluated individually. Results. The expressions of 232 autophagy-related genes (ARGs) in 127 ORCA and 13 control tissues were compared, and 36 DEARGs were filtered out. We performed functional enrichment analysis and constructed protein–protein interaction network for 36 DEARGs. Univariate and multivariate Cox regression analyses were adopted for searching prognostic ARGs, and an autophagy-associated signature for ORCA patients was constructed. Eventually, 4 desirable independent survival-related ARGs (WDR45, MAPK9, VEGFA, and ATIC) were confirmed and comprised the prognostic model. We made use of multiple ways to verify the accuracy of the novel autophagy-related signature for survival evaluation, such as receiver-operator characteristic curve, Kaplan–Meier plotter, and clinicopathological correlational analyses. Four independent prognostic DEARGs that formed the model were also associated with the prognosis of ORCA patients. Conclusions. The autophagy-related risk model can evaluate OS for ORCA patients independently since it is accurate and stable. Four prognostic ARGs that composed the model can be studied deeply for target treatment. Article in Journal/Newspaper Orca Directory of Open Access Journals: DOAJ Articles Meier ENVELOPE(-45.900,-45.900,-60.633,-60.633) BioMed Research International 2022 1 13 |
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Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Medicine R |
spellingShingle |
Medicine R Hongjun Fei Xiongming Chen A Novel Autophagy-Related Prognostic Risk Model and a Nomogram for Survival Prediction of Oral Cancer Patients |
topic_facet |
Medicine R |
description |
Background. This study is aimed at constructing a risk signature to predict survival outcomes of ORCA patients. Methods. We identified differentially expressed autophagy-related genes (DEARGs) based on the RNA sequencing data in the TCGA database; then, four independent survival-related ARGs were identified to construct an autophagy-associated signature for survival prediction of ORCA patients. The validity and robustness of the prognostic model were validated by clinicopathological data and survival data. Subsequently, four independent prognostic DEARGs that composed the model were evaluated individually. Results. The expressions of 232 autophagy-related genes (ARGs) in 127 ORCA and 13 control tissues were compared, and 36 DEARGs were filtered out. We performed functional enrichment analysis and constructed protein–protein interaction network for 36 DEARGs. Univariate and multivariate Cox regression analyses were adopted for searching prognostic ARGs, and an autophagy-associated signature for ORCA patients was constructed. Eventually, 4 desirable independent survival-related ARGs (WDR45, MAPK9, VEGFA, and ATIC) were confirmed and comprised the prognostic model. We made use of multiple ways to verify the accuracy of the novel autophagy-related signature for survival evaluation, such as receiver-operator characteristic curve, Kaplan–Meier plotter, and clinicopathological correlational analyses. Four independent prognostic DEARGs that formed the model were also associated with the prognosis of ORCA patients. Conclusions. The autophagy-related risk model can evaluate OS for ORCA patients independently since it is accurate and stable. Four prognostic ARGs that composed the model can be studied deeply for target treatment. |
format |
Article in Journal/Newspaper |
author |
Hongjun Fei Xiongming Chen |
author_facet |
Hongjun Fei Xiongming Chen |
author_sort |
Hongjun Fei |
title |
A Novel Autophagy-Related Prognostic Risk Model and a Nomogram for Survival Prediction of Oral Cancer Patients |
title_short |
A Novel Autophagy-Related Prognostic Risk Model and a Nomogram for Survival Prediction of Oral Cancer Patients |
title_full |
A Novel Autophagy-Related Prognostic Risk Model and a Nomogram for Survival Prediction of Oral Cancer Patients |
title_fullStr |
A Novel Autophagy-Related Prognostic Risk Model and a Nomogram for Survival Prediction of Oral Cancer Patients |
title_full_unstemmed |
A Novel Autophagy-Related Prognostic Risk Model and a Nomogram for Survival Prediction of Oral Cancer Patients |
title_sort |
novel autophagy-related prognostic risk model and a nomogram for survival prediction of oral cancer patients |
publisher |
Hindawi Limited |
publishDate |
2022 |
url |
https://doi.org/10.1155/2022/2067540 https://doaj.org/article/a4e9499b3ab24e0ab14b77e0880e3b7e |
long_lat |
ENVELOPE(-45.900,-45.900,-60.633,-60.633) |
geographic |
Meier |
geographic_facet |
Meier |
genre |
Orca |
genre_facet |
Orca |
op_source |
BioMed Research International, Vol 2022 (2022) |
op_relation |
http://dx.doi.org/10.1155/2022/2067540 https://doaj.org/toc/2314-6141 2314-6141 doi:10.1155/2022/2067540 https://doaj.org/article/a4e9499b3ab24e0ab14b77e0880e3b7e |
op_doi |
https://doi.org/10.1155/2022/2067540 |
container_title |
BioMed Research International |
container_volume |
2022 |
container_start_page |
1 |
op_container_end_page |
13 |
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1766160892677849088 |