Tumor exome sequencing and copy number alterations reveal potential predictors of intrinsic resistance to multi-targeted tyrosine kinase inhibitors
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Nancy K. Gillis1,2,3, Daniel M. Rotroff4, Tania E. Mesa5, Jiqiang Yao6, Zhihua Chen6, Michael A. Carulli7, Sean J. Yoder5, Christine M. Walko1,2, Jamie K. Teer8 and Howard L. McLeod1,2
1DeBartolo Family Personalized Medicine Institute, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
2Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
3Center for Pharmacogenomics and Individualized Therapy Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA
4Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
5Molecular Genomics Core, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
6Cancer Informatics Core, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
7College of Pharmacy, University of South Florida, Tampa, FL, USA
8Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
Howard L. McLeod, email: [email protected]
Keywords: tyrosine kinase inhibitors; resistance; somatic genetics; intrinsic; copy number
Received: September 06, 2017 Accepted: November 05, 2017 Published: December 04, 2017
Multi-targeted tyrosine kinase inhibitors (TKIs) have broad efficacy and similar FDA-approved indications, suggesting shared molecular drug targets across cancer types. Irrespective of tumor type, 20-30% of patients treated with multi-targeted TKIs demonstrate intrinsic resistance, with progressive disease as a best response. We conducted a retrospective cohort study to identify tumor (somatic) point mutations, insertion/deletions, and copy number alterations (CNA) associated with intrinsic resistance to multi-targeted TKIs. Using a candidate gene approach (n=243), tumor next-generation sequencing and CNA data was associated with resistant and non-resistant outcomes. Resistant individuals (n=11) more commonly harbored somatic point mutations in NTRK1, KDR, TGFBR2, and PTPN11 and CNA in CDK4, CDKN2B, and ERBB2 compared to non-resistant (n=26, p<0.01). Using a random forest classification model for variable reduction and a decision tree classification model, we were able to differentiate intrinsically resistant from non-resistant patients. CNA in CDK4 and CDKN2B were the most important analytical features, implicating the cyclin D pathway as a potentially important factor in resistance to multi-targeted TKIs. Replication of these results in a larger, independent patient cohort has potential to inform personalized prescribing of these widely utilized agents.
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