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Published on: January 22, 2013
High Throughput Kinomic Profiling of Human Clear Cell Renal Cell Carcinoma Identifies Kinase Activity Dependent
Joshua C Anderson1, Christopher D Willey1, Amitkumar Mehta2
1Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
Abstract:
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.
Insights
Comprehensive kinomic profiling of clear cell renal cell carcinoma (CC-RCC) reveals distinct tumor groups linked to inflammation, translation, and immune response. This approach may classify CC-RCC and identify new therapeutic targets.
Area of Science:
- Oncology
- Molecular Biology
- Biochemistry
Background:
- Clear cell renal cell carcinoma (CC-RCC) treatment often involves kinase-targeted agents.
- A comprehensive understanding of kinase activity (kinomic profiling) in CC-RCC is currently lacking.
- Kinomic profiling could enable a classification system for CC-RCC based on clinical outcomes and identify novel therapeutic targets.
Purpose of the Study:
- To perform kinomic profiling on localized CC-RCC tumors.
- To correlate kinomic profiles with clinical outcomes, including tumor recurrence.
- To identify potential therapeutic targets and functional classification strategies for CC-RCC.
Main Methods:
- Kinomic profiling of 41 CC-RCC tumor lysates and 12 matched normal kidney samples using the PamStation®12 microarray system.
- Unsupervised hierarchical clustering to identify kinomic groups.
- Supervised comparisons, network modeling, and upstream kinase prediction to analyze tumor vs. normal tissue and clinical outcomes.
Main Results:
- Unsupervised clustering identified three CC-RCC kinomic groups associated with inflammation (A), translation initiation (B), and immune response/cell adhesion (C).
- Potential driver kinases PFTAIRE (PFTK1), PKG1, and SRC were implicated in groups A, B, and C, respectively.
- Tumor recurrence was predominantly observed outside of Group B. Decreased CDK1 and RSK1-4 substrate activity correlated with progression. Tumors showed increased PIM's and MAPKAPK's compared to normal kidney tissue.
Conclusions:
- Comprehensive kinomic profiling offers a functional classification strategy for localized CC-RCC patients.
- This approach can identify distinct CC-RCC subtypes and potential therapeutic targets.
- Kinomic data provides insights into CC-RCC biology, potentially guiding personalized treatment strategies.
