Cargando…

Development of an Autophagy-Related Gene Prognostic Model and Nomogram for Estimating Renal Clear Cell Carcinoma Survival

BACKGROUND: Kidney renal clear cell carcinoma (KIRC) is a fatal malignancy of the urinary system. Autophagy is implicated in KIRC occurrence and development. Here, we evaluated the prognostic value of autophagy-related genes (ARGs) in kidney renal clear cell carcinoma. MATERIALS AND METHODS: We anal...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Ying, Yao, Yinhui, Zhao, Jingyi, Cai, Chunhua, Hu, Junhui, Zhao, Yanwu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910047/
https://www.ncbi.nlm.nih.gov/pubmed/33679977
http://dx.doi.org/10.1155/2021/8810849
_version_ 1783656047031877632
author Wang, Ying
Yao, Yinhui
Zhao, Jingyi
Cai, Chunhua
Hu, Junhui
Zhao, Yanwu
author_facet Wang, Ying
Yao, Yinhui
Zhao, Jingyi
Cai, Chunhua
Hu, Junhui
Zhao, Yanwu
author_sort Wang, Ying
collection PubMed
description BACKGROUND: Kidney renal clear cell carcinoma (KIRC) is a fatal malignancy of the urinary system. Autophagy is implicated in KIRC occurrence and development. Here, we evaluated the prognostic value of autophagy-related genes (ARGs) in kidney renal clear cell carcinoma. MATERIALS AND METHODS: We analyzed RNA sequencing and clinical KIRC patient data obtained from TCGA and ICGC to develop an ARG prognostic signature. Differentially expressed ARGs were further evaluated by functional assessment and bioinformatic analysis. Next, ARG score was determined in 215 KIRC patients using univariable Cox and LASSO regression analyses. An ARG nomogram was built based on multivariable Cox analysis. The prognosis nomogram model based on the ARG signatures and clinicopathological information was evaluated for discrimination, calibration, and clinical usefulness. RESULTS: A total of 47 differentially expressed ARGs were identified. Of these, 8 candidates that significantly correlated with KIRC overall survival were subjected to LASSO analysis and an ARG score built. Functional enrichment and bioinformatic analysis were used to reveal the differentially expressed ARGs in cancer-related biological processes and pathways. Multivariate Cox analysis was used to integrate the ARG nomogram with the ARG signature and clinicopathological information. The nomogram exhibited proper calibration and discrimination (C-index = 0.75, AUC = >0.7). Decision curve analysis also showed that the nomogram was clinically useful. CONCLUSIONS: KIRC patients and doctors could benefit from ARG nomogram use in clinical practice.
format Online
Article
Text
id pubmed-7910047
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-79100472021-03-04 Development of an Autophagy-Related Gene Prognostic Model and Nomogram for Estimating Renal Clear Cell Carcinoma Survival Wang, Ying Yao, Yinhui Zhao, Jingyi Cai, Chunhua Hu, Junhui Zhao, Yanwu J Oncol Research Article BACKGROUND: Kidney renal clear cell carcinoma (KIRC) is a fatal malignancy of the urinary system. Autophagy is implicated in KIRC occurrence and development. Here, we evaluated the prognostic value of autophagy-related genes (ARGs) in kidney renal clear cell carcinoma. MATERIALS AND METHODS: We analyzed RNA sequencing and clinical KIRC patient data obtained from TCGA and ICGC to develop an ARG prognostic signature. Differentially expressed ARGs were further evaluated by functional assessment and bioinformatic analysis. Next, ARG score was determined in 215 KIRC patients using univariable Cox and LASSO regression analyses. An ARG nomogram was built based on multivariable Cox analysis. The prognosis nomogram model based on the ARG signatures and clinicopathological information was evaluated for discrimination, calibration, and clinical usefulness. RESULTS: A total of 47 differentially expressed ARGs were identified. Of these, 8 candidates that significantly correlated with KIRC overall survival were subjected to LASSO analysis and an ARG score built. Functional enrichment and bioinformatic analysis were used to reveal the differentially expressed ARGs in cancer-related biological processes and pathways. Multivariate Cox analysis was used to integrate the ARG nomogram with the ARG signature and clinicopathological information. The nomogram exhibited proper calibration and discrimination (C-index = 0.75, AUC = >0.7). Decision curve analysis also showed that the nomogram was clinically useful. CONCLUSIONS: KIRC patients and doctors could benefit from ARG nomogram use in clinical practice. Hindawi 2021-02-18 /pmc/articles/PMC7910047/ /pubmed/33679977 http://dx.doi.org/10.1155/2021/8810849 Text en Copyright © 2021 Ying Wang et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wang, Ying
Yao, Yinhui
Zhao, Jingyi
Cai, Chunhua
Hu, Junhui
Zhao, Yanwu
Development of an Autophagy-Related Gene Prognostic Model and Nomogram for Estimating Renal Clear Cell Carcinoma Survival
title Development of an Autophagy-Related Gene Prognostic Model and Nomogram for Estimating Renal Clear Cell Carcinoma Survival
title_full Development of an Autophagy-Related Gene Prognostic Model and Nomogram for Estimating Renal Clear Cell Carcinoma Survival
title_fullStr Development of an Autophagy-Related Gene Prognostic Model and Nomogram for Estimating Renal Clear Cell Carcinoma Survival
title_full_unstemmed Development of an Autophagy-Related Gene Prognostic Model and Nomogram for Estimating Renal Clear Cell Carcinoma Survival
title_short Development of an Autophagy-Related Gene Prognostic Model and Nomogram for Estimating Renal Clear Cell Carcinoma Survival
title_sort development of an autophagy-related gene prognostic model and nomogram for estimating renal clear cell carcinoma survival
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910047/
https://www.ncbi.nlm.nih.gov/pubmed/33679977
http://dx.doi.org/10.1155/2021/8810849
work_keys_str_mv AT wangying developmentofanautophagyrelatedgeneprognosticmodelandnomogramforestimatingrenalclearcellcarcinomasurvival
AT yaoyinhui developmentofanautophagyrelatedgeneprognosticmodelandnomogramforestimatingrenalclearcellcarcinomasurvival
AT zhaojingyi developmentofanautophagyrelatedgeneprognosticmodelandnomogramforestimatingrenalclearcellcarcinomasurvival
AT caichunhua developmentofanautophagyrelatedgeneprognosticmodelandnomogramforestimatingrenalclearcellcarcinomasurvival
AT hujunhui developmentofanautophagyrelatedgeneprognosticmodelandnomogramforestimatingrenalclearcellcarcinomasurvival
AT zhaoyanwu developmentofanautophagyrelatedgeneprognosticmodelandnomogramforestimatingrenalclearcellcarcinomasurvival