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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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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 |
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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 |
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