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A Molecular Model for Predicting Overall Survival in Patients with Metastatic Clear Cell Renal Carcinoma: Results from CALGB 90206 (Alliance)
BACKGROUND: Prognosis associated with metastatic renal cell carcinoma (mRCC) can vary widely. METHODS: This study used pretreatment nephrectomy specimens from a randomized phase III trial. Expression levels of candidate genes were determined from archival tumors using the OpenArray® platform for Taq...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4740313/ https://www.ncbi.nlm.nih.gov/pubmed/26870806 http://dx.doi.org/10.1016/j.ebiom.2015.09.012 |
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author | Kim, Hyung L. Halabi, Susan Li, Ping Mayhew, Greg Simko, Jeff Nixon, Andrew B. Small, Eric J. Rini, Brian Morris, Michael J. Taplin, Mary-Ellen George, Daniel |
author_facet | Kim, Hyung L. Halabi, Susan Li, Ping Mayhew, Greg Simko, Jeff Nixon, Andrew B. Small, Eric J. Rini, Brian Morris, Michael J. Taplin, Mary-Ellen George, Daniel |
author_sort | Kim, Hyung L. |
collection | PubMed |
description | BACKGROUND: Prognosis associated with metastatic renal cell carcinoma (mRCC) can vary widely. METHODS: This study used pretreatment nephrectomy specimens from a randomized phase III trial. Expression levels of candidate genes were determined from archival tumors using the OpenArray® platform for TaqMan® RT-qPCR. The dataset was randomly divided at 2:1 ratio into training (n = 221) and testing (n = 103) sets to develop a multigene prognostic signature. FINDINGS: Gene expressions were measured in 324 patients. In the training set, multiple models testing 424 candidate genes identified a prognostic signature containing 8 genes plus MSKCC clinical risk factors. In the testing set, the time dependent (td) AUC for a prognostic model containing the 8 genes with and without MSKCC risk factors were 0.72 and 0.69, respectively. The tdAUC for the clinical risk factors alone was 0.61. Additional primary mRCCs from patients with mRCC (n = 12) were sampled in multiple sites and standard deviations of gene expressions within a tumor were used as a measure of heterogeneity. All 8 genes in the final prognostic model met our criteria for minimal heterogeneity. CONCLUSIONS: A molecular prognostic signature based on 8 genes was developed and is ready for external validation in this patient population and other related settings such as nonmetastatic RCC. |
format | Online Article Text |
id | pubmed-4740313 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-47403132016-02-11 A Molecular Model for Predicting Overall Survival in Patients with Metastatic Clear Cell Renal Carcinoma: Results from CALGB 90206 (Alliance) Kim, Hyung L. Halabi, Susan Li, Ping Mayhew, Greg Simko, Jeff Nixon, Andrew B. Small, Eric J. Rini, Brian Morris, Michael J. Taplin, Mary-Ellen George, Daniel EBioMedicine Research Article BACKGROUND: Prognosis associated with metastatic renal cell carcinoma (mRCC) can vary widely. METHODS: This study used pretreatment nephrectomy specimens from a randomized phase III trial. Expression levels of candidate genes were determined from archival tumors using the OpenArray® platform for TaqMan® RT-qPCR. The dataset was randomly divided at 2:1 ratio into training (n = 221) and testing (n = 103) sets to develop a multigene prognostic signature. FINDINGS: Gene expressions were measured in 324 patients. In the training set, multiple models testing 424 candidate genes identified a prognostic signature containing 8 genes plus MSKCC clinical risk factors. In the testing set, the time dependent (td) AUC for a prognostic model containing the 8 genes with and without MSKCC risk factors were 0.72 and 0.69, respectively. The tdAUC for the clinical risk factors alone was 0.61. Additional primary mRCCs from patients with mRCC (n = 12) were sampled in multiple sites and standard deviations of gene expressions within a tumor were used as a measure of heterogeneity. All 8 genes in the final prognostic model met our criteria for minimal heterogeneity. CONCLUSIONS: A molecular prognostic signature based on 8 genes was developed and is ready for external validation in this patient population and other related settings such as nonmetastatic RCC. Elsevier 2015-09-08 /pmc/articles/PMC4740313/ /pubmed/26870806 http://dx.doi.org/10.1016/j.ebiom.2015.09.012 Text en © 2015 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Kim, Hyung L. Halabi, Susan Li, Ping Mayhew, Greg Simko, Jeff Nixon, Andrew B. Small, Eric J. Rini, Brian Morris, Michael J. Taplin, Mary-Ellen George, Daniel A Molecular Model for Predicting Overall Survival in Patients with Metastatic Clear Cell Renal Carcinoma: Results from CALGB 90206 (Alliance) |
title | A Molecular Model for Predicting Overall Survival in Patients with Metastatic Clear Cell Renal Carcinoma: Results from CALGB 90206 (Alliance) |
title_full | A Molecular Model for Predicting Overall Survival in Patients with Metastatic Clear Cell Renal Carcinoma: Results from CALGB 90206 (Alliance) |
title_fullStr | A Molecular Model for Predicting Overall Survival in Patients with Metastatic Clear Cell Renal Carcinoma: Results from CALGB 90206 (Alliance) |
title_full_unstemmed | A Molecular Model for Predicting Overall Survival in Patients with Metastatic Clear Cell Renal Carcinoma: Results from CALGB 90206 (Alliance) |
title_short | A Molecular Model for Predicting Overall Survival in Patients with Metastatic Clear Cell Renal Carcinoma: Results from CALGB 90206 (Alliance) |
title_sort | molecular model for predicting overall survival in patients with metastatic clear cell renal carcinoma: results from calgb 90206 (alliance) |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4740313/ https://www.ncbi.nlm.nih.gov/pubmed/26870806 http://dx.doi.org/10.1016/j.ebiom.2015.09.012 |
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