Real-Time Genomic Profiling of Pancreatic Ductal Adenocarcinoma: Potential Actionability and Correlation with Clinical Phenotype
Molecular profiling in cancer has identified potential actionable drug targets that have prompted attempts to discover clinically validated biomarkers to guide therapeutic decision-making and enrollment to clinical trials. We evaluated whether comprehensive genetic analysis of patients with pancreat...
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| Veröffentlicht in: | Clinical cancer research Jg. 23; H. 20; S. 6094 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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15.10.2017
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| ISSN: | 1078-0432, 1557-3265, 1557-3265 |
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| Abstract | Molecular profiling in cancer has identified potential actionable drug targets that have prompted attempts to discover clinically validated biomarkers to guide therapeutic decision-making and enrollment to clinical trials. We evaluated whether comprehensive genetic analysis of patients with pancreatic adenocarcinoma is feasible within a clinically relevant timeframe and whether such analyses provide predictive and/or prognostic information along with identification of potential targets for therapy.
Archival or prospectively acquired FFPE samples and matched normal DNA from
= 336 patients with pancreatic cancer were analyzed using a hybridization capture-based, next-generation sequencing assay designed to perform targeted deep sequencing of all exons and selected introns of 410 key cancer-associated genes. Demographic and treatment data were prospectively collected with the goal of correlating treatment outcomes and drug response with molecular profiles.
The median time from protocol consent to reporting of the genomic results was 45 days with a median time from tissue delivery of 20 days. All genetic alterations identified were stratified based upon prior evidence that the mutation is a predictive biomarker of drug response using the MSKCC OncoKB classification. Three of 225 patients (1%) received a matched therapy based upon the sequencing results.
The practical application of molecular results to guide individual patient treatment is currently limited in patients with pancreatic adenocarcinoma. Future prospective molecular profiling efforts should seek to incorporate routine germline genetic analysis and the identification of DNA profiles that predict for clinical benefit from agents that target DNA damage repair and or immunotherapy.
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| AbstractList | Purpose: Molecular profiling in cancer has identified potential actionable drug targets that have prompted attempts to discover clinically validated biomarkers to guide therapeutic decision-making and enrollment to clinical trials. We evaluated whether comprehensive genetic analysis of patients with pancreatic adenocarcinoma is feasible within a clinically relevant timeframe and whether such analyses provide predictive and/or prognostic information along with identification of potential targets for therapy.Experimental Design: Archival or prospectively acquired FFPE samples and matched normal DNA from N = 336 patients with pancreatic cancer were analyzed using a hybridization capture-based, next-generation sequencing assay designed to perform targeted deep sequencing of all exons and selected introns of 410 key cancer-associated genes. Demographic and treatment data were prospectively collected with the goal of correlating treatment outcomes and drug response with molecular profiles.Results: The median time from protocol consent to reporting of the genomic results was 45 days with a median time from tissue delivery of 20 days. All genetic alterations identified were stratified based upon prior evidence that the mutation is a predictive biomarker of drug response using the MSKCC OncoKB classification. Three of 225 patients (1%) received a matched therapy based upon the sequencing results.Conclusions: The practical application of molecular results to guide individual patient treatment is currently limited in patients with pancreatic adenocarcinoma. Future prospective molecular profiling efforts should seek to incorporate routine germline genetic analysis and the identification of DNA profiles that predict for clinical benefit from agents that target DNA damage repair and or immunotherapy. Clin Cancer Res; 23(20); 6094-100. ©2017 AACR.Purpose: Molecular profiling in cancer has identified potential actionable drug targets that have prompted attempts to discover clinically validated biomarkers to guide therapeutic decision-making and enrollment to clinical trials. We evaluated whether comprehensive genetic analysis of patients with pancreatic adenocarcinoma is feasible within a clinically relevant timeframe and whether such analyses provide predictive and/or prognostic information along with identification of potential targets for therapy.Experimental Design: Archival or prospectively acquired FFPE samples and matched normal DNA from N = 336 patients with pancreatic cancer were analyzed using a hybridization capture-based, next-generation sequencing assay designed to perform targeted deep sequencing of all exons and selected introns of 410 key cancer-associated genes. Demographic and treatment data were prospectively collected with the goal of correlating treatment outcomes and drug response with molecular profiles.Results: The median time from protocol consent to reporting of the genomic results was 45 days with a median time from tissue delivery of 20 days. All genetic alterations identified were stratified based upon prior evidence that the mutation is a predictive biomarker of drug response using the MSKCC OncoKB classification. Three of 225 patients (1%) received a matched therapy based upon the sequencing results.Conclusions: The practical application of molecular results to guide individual patient treatment is currently limited in patients with pancreatic adenocarcinoma. Future prospective molecular profiling efforts should seek to incorporate routine germline genetic analysis and the identification of DNA profiles that predict for clinical benefit from agents that target DNA damage repair and or immunotherapy. Clin Cancer Res; 23(20); 6094-100. ©2017 AACR. Molecular profiling in cancer has identified potential actionable drug targets that have prompted attempts to discover clinically validated biomarkers to guide therapeutic decision-making and enrollment to clinical trials. We evaluated whether comprehensive genetic analysis of patients with pancreatic adenocarcinoma is feasible within a clinically relevant timeframe and whether such analyses provide predictive and/or prognostic information along with identification of potential targets for therapy. Archival or prospectively acquired FFPE samples and matched normal DNA from = 336 patients with pancreatic cancer were analyzed using a hybridization capture-based, next-generation sequencing assay designed to perform targeted deep sequencing of all exons and selected introns of 410 key cancer-associated genes. Demographic and treatment data were prospectively collected with the goal of correlating treatment outcomes and drug response with molecular profiles. The median time from protocol consent to reporting of the genomic results was 45 days with a median time from tissue delivery of 20 days. All genetic alterations identified were stratified based upon prior evidence that the mutation is a predictive biomarker of drug response using the MSKCC OncoKB classification. Three of 225 patients (1%) received a matched therapy based upon the sequencing results. The practical application of molecular results to guide individual patient treatment is currently limited in patients with pancreatic adenocarcinoma. Future prospective molecular profiling efforts should seek to incorporate routine germline genetic analysis and the identification of DNA profiles that predict for clinical benefit from agents that target DNA damage repair and or immunotherapy. . |
| Author | Schultz, Nikolaus Solit, David B Jarnagin, William R Saltz, Leonard B Hechtman, Jaclyn F Askan, Gokce Abou-Alfa, Ghassan K Hyman, David M O'Reilly, Eileen M Yu, Kenneth H Zehir, Ahmet Lowery, Maeve A Leach, Tanisha Varghese, Anna M Ptashkin, Ryan N Maynard, Hannah Basturk, Olca Berger, Michael F Allen, Peter J Herbst, Brian Covington, Christina Leach, Steven D Glassman, Danielle Harding, James J Jordan, Emmet J Balachandran, Vinod P Klimstra, David S Schattner, Mark A Iacobuzio-Donahue, Christine A |
| Author_xml | – sequence: 1 givenname: Maeve A surname: Lowery fullname: Lowery, Maeve A email: maevelowery@gmail.com, oreillye@mskcc.org organization: Department of Medicine, Weill Cornell Medical College, New York, New York – sequence: 2 givenname: Emmet J surname: Jordan fullname: Jordan, Emmet J organization: Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 3 givenname: Olca surname: Basturk fullname: Basturk, Olca organization: Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 4 givenname: Ryan N surname: Ptashkin fullname: Ptashkin, Ryan N organization: Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 5 givenname: Ahmet surname: Zehir fullname: Zehir, Ahmet organization: Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 6 givenname: Michael F surname: Berger fullname: Berger, Michael F organization: Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 7 givenname: Tanisha surname: Leach fullname: Leach, Tanisha organization: David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 8 givenname: Brian surname: Herbst fullname: Herbst, Brian organization: David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 9 givenname: Gokce surname: Askan fullname: Askan, Gokce organization: David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 10 givenname: Hannah surname: Maynard fullname: Maynard, Hannah organization: Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 11 givenname: Danielle surname: Glassman fullname: Glassman, Danielle organization: Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 12 givenname: Christina surname: Covington fullname: Covington, Christina organization: Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 13 givenname: Nikolaus surname: Schultz fullname: Schultz, Nikolaus organization: Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 14 givenname: Ghassan K surname: Abou-Alfa fullname: Abou-Alfa, Ghassan K organization: Department of Medicine, Weill Cornell Medical College, New York, New York – sequence: 15 givenname: James J surname: Harding fullname: Harding, James J organization: Department of Medicine, Weill Cornell Medical College, New York, New York – sequence: 16 givenname: David S surname: Klimstra fullname: Klimstra, David S organization: Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 17 givenname: Jaclyn F surname: Hechtman fullname: Hechtman, Jaclyn F organization: Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 18 givenname: David M surname: Hyman fullname: Hyman, David M organization: Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 19 givenname: Peter J surname: Allen fullname: Allen, Peter J organization: Department of Medicine, Weill Cornell Medical College, New York, New York – sequence: 20 givenname: William R surname: Jarnagin fullname: Jarnagin, William R organization: Department of Medicine, Weill Cornell Medical College, New York, New York – sequence: 21 givenname: Vinod P surname: Balachandran fullname: Balachandran, Vinod P organization: Department of Medicine, Weill Cornell Medical College, New York, New York – sequence: 22 givenname: Anna M surname: Varghese fullname: Varghese, Anna M organization: Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 23 givenname: Mark A surname: Schattner fullname: Schattner, Mark A organization: David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 24 givenname: Kenneth H surname: Yu fullname: Yu, Kenneth H organization: Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 25 givenname: Leonard B surname: Saltz fullname: Saltz, Leonard B organization: Department of Medicine, Weill Cornell Medical College, New York, New York – sequence: 26 givenname: David B surname: Solit fullname: Solit, David B organization: Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 27 givenname: Christine A surname: Iacobuzio-Donahue fullname: Iacobuzio-Donahue, Christine A organization: Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 28 givenname: Steven D surname: Leach fullname: Leach, Steven D organization: Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York – sequence: 29 givenname: Eileen M surname: O'Reilly fullname: O'Reilly, Eileen M email: maevelowery@gmail.com, oreillye@mskcc.org organization: Department of Medicine, Weill Cornell Medical College, New York, New York |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28754816$$D View this record in MEDLINE/PubMed |
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| SubjectTerms | Carcinoma, Pancreatic Ductal - diagnosis Carcinoma, Pancreatic Ductal - genetics DNA Damage Female Gene Frequency Genetic Association Studies Genetic Testing Genetic Variation Genome-Wide Association Study Genomics High-Throughput Nucleotide Sequencing Humans Male Neoplasm Staging Oncogenes Pancreatic Neoplasms - diagnosis Pancreatic Neoplasms - genetics Phenotype |
| Title | Real-Time Genomic Profiling of Pancreatic Ductal Adenocarcinoma: Potential Actionability and Correlation with Clinical Phenotype |
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