Tumor exome sequencing and copy number alterations reveal potential predictors of intrinsic resistance to multi-targeted tyrosine kinase inhibitors
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...
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| Published in | Oncotarget Vol. 8; no. 70; pp. 115114 - 115127 |
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| Main Authors | , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Impact Journals LLC
29.12.2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1949-2553 1949-2553 |
| DOI | 10.18632/oncotarget.22914 |
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| Abstract | 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
,
,
, and
and CNA in
,
, and
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
and
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. |
|---|---|
| AbstractList | 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.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. 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. 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 , , , and and CNA in , , and 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 and 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. |
| Author | McLeod, Howard L. Carulli, Michael A. Yao, Jiqiang Rotroff, Daniel M. Mesa, Tania E. Chen, Zhihua Yoder, Sean J. Walko, Christine M. Gillis, Nancy K. Teer, Jamie K. |
| AuthorAffiliation | 6 Cancer Informatics Core, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA 5 Molecular Genomics Core, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA 7 College of Pharmacy, University of South Florida, Tampa, FL, USA 3 Center for Pharmacogenomics and Individualized Therapy Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA 8 Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA 1 DeBartolo Family Personalized Medicine Institute, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA 2 Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA 4 Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA |
| AuthorAffiliation_xml | – name: 6 Cancer Informatics Core, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA – name: 5 Molecular Genomics Core, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA – name: 2 Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA – name: 1 DeBartolo Family Personalized Medicine Institute, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA – name: 3 Center for Pharmacogenomics and Individualized Therapy Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA – name: 7 College of Pharmacy, University of South Florida, Tampa, FL, USA – name: 8 Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA – name: 4 Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA |
| Author_xml | – sequence: 1 givenname: Nancy K. surname: Gillis fullname: Gillis, Nancy K. organization: DeBartolo Family Personalized Medicine Institute, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA, Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA, Center for Pharmacogenomics and Individualized Therapy Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA – sequence: 2 givenname: Daniel M. surname: Rotroff fullname: Rotroff, Daniel M. organization: Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA – sequence: 3 givenname: Tania E. surname: Mesa fullname: Mesa, Tania E. organization: Molecular Genomics Core, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA – sequence: 4 givenname: Jiqiang surname: Yao fullname: Yao, Jiqiang organization: Cancer Informatics Core, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA – sequence: 5 givenname: Zhihua surname: Chen fullname: Chen, Zhihua organization: Cancer Informatics Core, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA – sequence: 6 givenname: Michael A. surname: Carulli fullname: Carulli, Michael A. organization: College of Pharmacy, University of South Florida, Tampa, FL, USA – sequence: 7 givenname: Sean J. surname: Yoder fullname: Yoder, Sean J. organization: Molecular Genomics Core, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA – sequence: 8 givenname: Christine M. surname: Walko fullname: Walko, Christine M. organization: DeBartolo Family Personalized Medicine Institute, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA, Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA – sequence: 9 givenname: Jamie K. surname: Teer fullname: Teer, Jamie K. organization: Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA – sequence: 10 givenname: Howard L. surname: McLeod fullname: McLeod, Howard L. organization: DeBartolo Family Personalized Medicine Institute, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA, Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29383146$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1007_s00204_021_03063_7 crossref_primary_10_1016_j_drup_2025_101229 crossref_primary_10_3390_ijms25136815 crossref_primary_10_1016_j_cpt_2024_07_002 |
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| Keywords | tyrosine kinase inhibitors somatic genetics copy number intrinsic resistance |
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| Title | Tumor exome sequencing and copy number alterations reveal potential predictors of intrinsic resistance to multi-targeted tyrosine kinase inhibitors |
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