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Unique protein expression signatures of survival time in kidney renal clear cell carcinoma through a pan-cancer screening
BACKGROUND: In 2016, it is estimated that there will be 62,700 new cases of kidney cancer in the United States, and 14,240 patients will die from the disease. Because the incidence of kidney renal clear cell carcinoma (KIRC), the most common type of kidney cancer, is expected to continue to increase...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5629613/ https://www.ncbi.nlm.nih.gov/pubmed/28984208 http://dx.doi.org/10.1186/s12864-017-4026-6 |
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author | Han, Guangchun Zhao, Wei Song, Xiaofeng Kwok-Shing Ng, Patrick Karam, Jose A. Jonasch, Eric Mills, Gordon B. Zhao, Zhongming Ding, Zhiyong Jia, Peilin |
author_facet | Han, Guangchun Zhao, Wei Song, Xiaofeng Kwok-Shing Ng, Patrick Karam, Jose A. Jonasch, Eric Mills, Gordon B. Zhao, Zhongming Ding, Zhiyong Jia, Peilin |
author_sort | Han, Guangchun |
collection | PubMed |
description | BACKGROUND: In 2016, it is estimated that there will be 62,700 new cases of kidney cancer in the United States, and 14,240 patients will die from the disease. Because the incidence of kidney renal clear cell carcinoma (KIRC), the most common type of kidney cancer, is expected to continue to increase in the US, there is an urgent need to find effective diagnostic biomarkers for KIRC that could help earlier detection of and customized treatment strategies for the disease. Accordingly, in this study we systematically investigated KIRC’s prognostic biomarkers for survival using the reverse phase protein array (RPPA) data and the high throughput sequencing data from The Cancer Genome Atlas (TCGA). RESULTS: With comprehensive data available in TCGA, we systematically screened protein expression based survival biomarkers in 10 major cancer types, among which KIRC presented many protein prognostic biomarkers of survival time. This is in agreement with a previous report that expression level changes (mRNAs, microRNA and protein) may have a better performance for prognosis of KIRC. In this study, we also identified 52 prognostic genes for KIRC, many of which are involved in cell-cycle and cancer signaling, as well as 15 tumor-stage-specific prognostic biomarkers. Notably, we found fewer prognostic biomarkers for early-stage than for late-stage KIRC. Four biomarkers (the RPPA protein IDs: FASN, ACC1, Cyclin_B1 and Rad51) were found to be prognostic for survival based on both protein and mRNA expression data. CONCLUSIONS: Through pan-cancer screening, we found that many protein biomarkers were prognostic for patients’ survival in KIRC. Stage-specific survival biomarkers in KIRC were also identified. Our study indicated that these protein biomarkers might have potential clinical value in terms of predicting survival in KIRC patients and developing individualized treatment strategies. Importantly, we found many biomarkers in KIRC at both the mRNA expression level and the protein expression level. These biomarkers shared a significant overlap, indicating that they were technically replicable. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-4026-6) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5629613 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-56296132017-10-13 Unique protein expression signatures of survival time in kidney renal clear cell carcinoma through a pan-cancer screening Han, Guangchun Zhao, Wei Song, Xiaofeng Kwok-Shing Ng, Patrick Karam, Jose A. Jonasch, Eric Mills, Gordon B. Zhao, Zhongming Ding, Zhiyong Jia, Peilin BMC Genomics Research BACKGROUND: In 2016, it is estimated that there will be 62,700 new cases of kidney cancer in the United States, and 14,240 patients will die from the disease. Because the incidence of kidney renal clear cell carcinoma (KIRC), the most common type of kidney cancer, is expected to continue to increase in the US, there is an urgent need to find effective diagnostic biomarkers for KIRC that could help earlier detection of and customized treatment strategies for the disease. Accordingly, in this study we systematically investigated KIRC’s prognostic biomarkers for survival using the reverse phase protein array (RPPA) data and the high throughput sequencing data from The Cancer Genome Atlas (TCGA). RESULTS: With comprehensive data available in TCGA, we systematically screened protein expression based survival biomarkers in 10 major cancer types, among which KIRC presented many protein prognostic biomarkers of survival time. This is in agreement with a previous report that expression level changes (mRNAs, microRNA and protein) may have a better performance for prognosis of KIRC. In this study, we also identified 52 prognostic genes for KIRC, many of which are involved in cell-cycle and cancer signaling, as well as 15 tumor-stage-specific prognostic biomarkers. Notably, we found fewer prognostic biomarkers for early-stage than for late-stage KIRC. Four biomarkers (the RPPA protein IDs: FASN, ACC1, Cyclin_B1 and Rad51) were found to be prognostic for survival based on both protein and mRNA expression data. CONCLUSIONS: Through pan-cancer screening, we found that many protein biomarkers were prognostic for patients’ survival in KIRC. Stage-specific survival biomarkers in KIRC were also identified. Our study indicated that these protein biomarkers might have potential clinical value in terms of predicting survival in KIRC patients and developing individualized treatment strategies. Importantly, we found many biomarkers in KIRC at both the mRNA expression level and the protein expression level. These biomarkers shared a significant overlap, indicating that they were technically replicable. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-4026-6) contains supplementary material, which is available to authorized users. BioMed Central 2017-10-03 /pmc/articles/PMC5629613/ /pubmed/28984208 http://dx.doi.org/10.1186/s12864-017-4026-6 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Han, Guangchun Zhao, Wei Song, Xiaofeng Kwok-Shing Ng, Patrick Karam, Jose A. Jonasch, Eric Mills, Gordon B. Zhao, Zhongming Ding, Zhiyong Jia, Peilin Unique protein expression signatures of survival time in kidney renal clear cell carcinoma through a pan-cancer screening |
title | Unique protein expression signatures of survival time in kidney renal clear cell carcinoma through a pan-cancer screening |
title_full | Unique protein expression signatures of survival time in kidney renal clear cell carcinoma through a pan-cancer screening |
title_fullStr | Unique protein expression signatures of survival time in kidney renal clear cell carcinoma through a pan-cancer screening |
title_full_unstemmed | Unique protein expression signatures of survival time in kidney renal clear cell carcinoma through a pan-cancer screening |
title_short | Unique protein expression signatures of survival time in kidney renal clear cell carcinoma through a pan-cancer screening |
title_sort | unique protein expression signatures of survival time in kidney renal clear cell carcinoma through a pan-cancer screening |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5629613/ https://www.ncbi.nlm.nih.gov/pubmed/28984208 http://dx.doi.org/10.1186/s12864-017-4026-6 |
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