High Throughput Kinomic Profiling of Human Clear Cell Renal Cell Carcinoma Identifies Kinase Activity Dependent Molecular Subtypes

• Published in: PloS one Vol. 10; no. 9; p. e0139267
• Main Authors: 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
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 25.09.2015; Public Library of Science (PLoS)
• Subjects: Analysis; Anderson, Christopher; Authorship; Brain cancer; Cancer therapies; Carcinoma, Renal Cell - genetics; Carcinoma, Renal Cell - pathology; Care and treatment; Classification; Clear cell-type renal cell carcinoma; Cluster Analysis; Clustering; Diagnosis; Disease Progression; Female; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Genetic aspects; Health aspects; Hematology; Human subjects; Humans; Identification methods; Immune response; Immune system; Kidney cancer; Kidney Neoplasms - genetics; Kidney Neoplasms - pathology; Kidneys; Kinases; Lysates; Male; Medical research; Middle Aged; Mutation; Oncology; Patient outcomes; Patients; Phosphotransferases; Powder injection molding; Privacy; Protein Kinases - genetics; Protein Kinases - metabolism; Renal cell carcinoma; Ribosomal protein S6 kinase; Substrates; Target recognition; Therapeutic applications; Translation initiation; Treatment Outcome; Tumors; Vascular endothelial growth factor; United States; United Kingdom > UK; United States > US; Maine; Egypt; England; Alabama; Alexandria Egypt
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0139267

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.