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High Throughput Kinomic Profiling of Human Clear Cell Renal Cell Carcinoma Identifies Kinase Activity Dependent Molecular Subtypes
Despite the widespread use of kinase-targeted agents in clear cell renal cell carcinoma (CC-RCC), comprehensive kinase activity evaluation (kinomic profiling) of these tumors is lacking. Thus, kinomic profiling of CC-RCC may assist in devising a classification system associated with clinical outcome...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4583516/ https://www.ncbi.nlm.nih.gov/pubmed/26406598 http://dx.doi.org/10.1371/journal.pone.0139267 |
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author | Anderson, Joshua C. Willey, Christopher D. Mehta, Amitkumar Welaya, Karim Chen, Dongquan Duarte, Christine W. Ghatalia, Pooja Arafat, Waleed Madan, Ankit Sudarshan, Sunil Naik, Gurudatta Grizzle, William E. Choueiri, Toni K. Sonpavde, Guru |
author_facet | Anderson, Joshua C. Willey, Christopher D. Mehta, Amitkumar Welaya, Karim Chen, Dongquan Duarte, Christine W. Ghatalia, Pooja Arafat, Waleed Madan, Ankit Sudarshan, Sunil Naik, Gurudatta Grizzle, William E. Choueiri, Toni K. Sonpavde, Guru |
author_sort | Anderson, Joshua C. |
collection | PubMed |
description | Despite the widespread use of kinase-targeted agents in clear cell renal cell carcinoma (CC-RCC), comprehensive kinase activity evaluation (kinomic profiling) of these tumors is lacking. Thus, kinomic profiling of CC-RCC may assist in devising a classification system associated with clinical outcomes, and help identify potential therapeutic targets. Fresh frozen CC-RCC tumor lysates from 41 clinically annotated patients who had localized disease at diagnosis were kinomically profiled using the PamStation®12 high-content phospho-peptide substrate microarray system (PamGene International). Twelve of these patients also had matched normal kidneys available that were also profiled. Unsupervised hierarchical clustering and supervised comparisons based on tumor vs. normal kidney and clinical outcome (tumor recurrence) were performed and coupled with advanced network modeling and upstream kinase prediction methods. Unsupervised clustering analysis of localized CC-RCC tumors identified 3 major kinomic groups associated with inflammation (A), translation initiation (B), and immune response and cell adhesions (C) processes. Potential driver kinases implicated include PFTAIRE (PFTK1), PKG1, and SRC, which were identified in groups A, B, and C, respectively. Of the 9 patients who had tumor recurrence, only one was found in Group B. Supervised analysis showed decreased kinase activity of CDK1 and RSK1-4 substrates in those which progressed compared to others. Twelve tumors with matching normal renal tissue implicated increased PIM’s and MAPKAPK’s in tumors compared to adjacent normal renal tissue. As such, comprehensive kinase profiling of CC-RCC tumors could provide a functional classification strategy for patients with localized disease and identify potential therapeutic targets. |
format | Online Article Text |
id | pubmed-4583516 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-45835162015-10-02 High Throughput Kinomic Profiling of Human Clear Cell Renal Cell Carcinoma Identifies Kinase Activity Dependent Molecular Subtypes Anderson, Joshua C. Willey, Christopher D. Mehta, Amitkumar Welaya, Karim Chen, Dongquan Duarte, Christine W. Ghatalia, Pooja Arafat, Waleed Madan, Ankit Sudarshan, Sunil Naik, Gurudatta Grizzle, William E. Choueiri, Toni K. Sonpavde, Guru PLoS One Research Article Despite the widespread use of kinase-targeted agents in clear cell renal cell carcinoma (CC-RCC), comprehensive kinase activity evaluation (kinomic profiling) of these tumors is lacking. Thus, kinomic profiling of CC-RCC may assist in devising a classification system associated with clinical outcomes, and help identify potential therapeutic targets. Fresh frozen CC-RCC tumor lysates from 41 clinically annotated patients who had localized disease at diagnosis were kinomically profiled using the PamStation®12 high-content phospho-peptide substrate microarray system (PamGene International). Twelve of these patients also had matched normal kidneys available that were also profiled. Unsupervised hierarchical clustering and supervised comparisons based on tumor vs. normal kidney and clinical outcome (tumor recurrence) were performed and coupled with advanced network modeling and upstream kinase prediction methods. Unsupervised clustering analysis of localized CC-RCC tumors identified 3 major kinomic groups associated with inflammation (A), translation initiation (B), and immune response and cell adhesions (C) processes. Potential driver kinases implicated include PFTAIRE (PFTK1), PKG1, and SRC, which were identified in groups A, B, and C, respectively. Of the 9 patients who had tumor recurrence, only one was found in Group B. Supervised analysis showed decreased kinase activity of CDK1 and RSK1-4 substrates in those which progressed compared to others. Twelve tumors with matching normal renal tissue implicated increased PIM’s and MAPKAPK’s in tumors compared to adjacent normal renal tissue. As such, comprehensive kinase profiling of CC-RCC tumors could provide a functional classification strategy for patients with localized disease and identify potential therapeutic targets. Public Library of Science 2015-09-25 /pmc/articles/PMC4583516/ /pubmed/26406598 http://dx.doi.org/10.1371/journal.pone.0139267 Text en © 2015 Anderson et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Anderson, Joshua C. Willey, Christopher D. Mehta, Amitkumar Welaya, Karim Chen, Dongquan Duarte, Christine W. Ghatalia, Pooja Arafat, Waleed Madan, Ankit Sudarshan, Sunil Naik, Gurudatta Grizzle, William E. Choueiri, Toni K. Sonpavde, Guru High Throughput Kinomic Profiling of Human Clear Cell Renal Cell Carcinoma Identifies Kinase Activity Dependent Molecular Subtypes |
title | High Throughput Kinomic Profiling of Human Clear Cell Renal Cell Carcinoma Identifies Kinase Activity Dependent Molecular Subtypes |
title_full | High Throughput Kinomic Profiling of Human Clear Cell Renal Cell Carcinoma Identifies Kinase Activity Dependent Molecular Subtypes |
title_fullStr | High Throughput Kinomic Profiling of Human Clear Cell Renal Cell Carcinoma Identifies Kinase Activity Dependent Molecular Subtypes |
title_full_unstemmed | High Throughput Kinomic Profiling of Human Clear Cell Renal Cell Carcinoma Identifies Kinase Activity Dependent Molecular Subtypes |
title_short | High Throughput Kinomic Profiling of Human Clear Cell Renal Cell Carcinoma Identifies Kinase Activity Dependent Molecular Subtypes |
title_sort | high throughput kinomic profiling of human clear cell renal cell carcinoma identifies kinase activity dependent molecular subtypes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4583516/ https://www.ncbi.nlm.nih.gov/pubmed/26406598 http://dx.doi.org/10.1371/journal.pone.0139267 |
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