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...

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Main Authors: Joshua C Anderson, Christopher D Willey, Amitkumar Mehta, Karim Welaya, Dongquan Chen, Christine W Duarte, Pooja Ghatalia, Waleed Arafat, Ankit Madan, Sunil Sudarshan, Gurudatta Naik, William E Grizzle, Toni K Choueiri, Guru Sonpavde
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4583516?pdf=render
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spelling doaj-808d0e821cff4e1e97f8403c1ebd8bd92020-11-25T02:32:14ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01109e013926710.1371/journal.pone.0139267High Throughput Kinomic Profiling of Human Clear Cell Renal Cell Carcinoma Identifies Kinase Activity Dependent Molecular Subtypes.Joshua C AndersonChristopher D WilleyAmitkumar MehtaKarim WelayaDongquan ChenChristine W DuartePooja GhataliaWaleed ArafatAnkit MadanSunil SudarshanGurudatta NaikWilliam E GrizzleToni K ChoueiriGuru SonpavdeDespite 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.http://europepmc.org/articles/PMC4583516?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Joshua C Anderson
Christopher D Willey
Amitkumar Mehta
Karim Welaya
Dongquan Chen
Christine W Duarte
Pooja Ghatalia
Waleed Arafat
Ankit Madan
Sunil Sudarshan
Gurudatta Naik
William E Grizzle
Toni K Choueiri
Guru Sonpavde
spellingShingle Joshua C Anderson
Christopher D Willey
Amitkumar Mehta
Karim Welaya
Dongquan Chen
Christine W Duarte
Pooja Ghatalia
Waleed Arafat
Ankit Madan
Sunil Sudarshan
Gurudatta Naik
William E Grizzle
Toni K Choueiri
Guru Sonpavde
High Throughput Kinomic Profiling of Human Clear Cell Renal Cell Carcinoma Identifies Kinase Activity Dependent Molecular Subtypes.
PLoS ONE
author_facet Joshua C Anderson
Christopher D Willey
Amitkumar Mehta
Karim Welaya
Dongquan Chen
Christine W Duarte
Pooja Ghatalia
Waleed Arafat
Ankit Madan
Sunil Sudarshan
Gurudatta Naik
William E Grizzle
Toni K Choueiri
Guru Sonpavde
author_sort Joshua C Anderson
title 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_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_sort high throughput kinomic profiling of human clear cell renal cell carcinoma identifies kinase activity dependent molecular subtypes.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2015-01-01
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.
url http://europepmc.org/articles/PMC4583516?pdf=render
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