Sequencing and curation strategies for identifying candidate glioblastoma treatments
Abstract Background Prompted by the revolution in high-throughput sequencing and its potential impact for treating cancer patients, we initiated a clinical research study to compare the ability of different sequencing assays and analysis methods to analyze glioblastoma tumors and generate real-time...
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BMC
2019-04-01
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Series: | BMC Medical Genomics |
Online Access: | http://link.springer.com/article/10.1186/s12920-019-0500-0 |
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language |
English |
format |
Article |
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DOAJ |
author |
Mayu O. Frank Takahiko Koyama Kahn Rhrissorrakrai Nicolas Robine Filippo Utro Anne-Katrin Emde Bo-Juen Chen Kanika Arora Minita Shah Heather Geiger Vanessa Felice Esra Dikoglu Sadia Rahman Alice Fang Vladimir Vacic Ewa A. Bergmann Julia L. Moore Vogel Catherine Reeves Depinder Khaira Anthony Calabro Duyang Kim Michelle F. Lamendola-Essel Cecilia Esteves Phaedra Agius Christian Stolte John Boockvar Alexis Demopoulos Dimitris G. Placantonakis John G. Golfinos Cameron Brennan Jeffrey Bruce Andrew B. Lassman Peter Canoll Christian Grommes Mariza Daras Eli Diamond Antonio Omuro Elena Pentsova Dana E. Orange Stephen J. Harvey Jerome B. Posner Vanessa V. Michelini Vaidehi Jobanputra Michael C. Zody John Kelly Laxmi Parida Kazimierz O. Wrzeszczynski Ajay K. Royyuru Robert B. Darnell |
spellingShingle |
Mayu O. Frank Takahiko Koyama Kahn Rhrissorrakrai Nicolas Robine Filippo Utro Anne-Katrin Emde Bo-Juen Chen Kanika Arora Minita Shah Heather Geiger Vanessa Felice Esra Dikoglu Sadia Rahman Alice Fang Vladimir Vacic Ewa A. Bergmann Julia L. Moore Vogel Catherine Reeves Depinder Khaira Anthony Calabro Duyang Kim Michelle F. Lamendola-Essel Cecilia Esteves Phaedra Agius Christian Stolte John Boockvar Alexis Demopoulos Dimitris G. Placantonakis John G. Golfinos Cameron Brennan Jeffrey Bruce Andrew B. Lassman Peter Canoll Christian Grommes Mariza Daras Eli Diamond Antonio Omuro Elena Pentsova Dana E. Orange Stephen J. Harvey Jerome B. Posner Vanessa V. Michelini Vaidehi Jobanputra Michael C. Zody John Kelly Laxmi Parida Kazimierz O. Wrzeszczynski Ajay K. Royyuru Robert B. Darnell Sequencing and curation strategies for identifying candidate glioblastoma treatments BMC Medical Genomics |
author_facet |
Mayu O. Frank Takahiko Koyama Kahn Rhrissorrakrai Nicolas Robine Filippo Utro Anne-Katrin Emde Bo-Juen Chen Kanika Arora Minita Shah Heather Geiger Vanessa Felice Esra Dikoglu Sadia Rahman Alice Fang Vladimir Vacic Ewa A. Bergmann Julia L. Moore Vogel Catherine Reeves Depinder Khaira Anthony Calabro Duyang Kim Michelle F. Lamendola-Essel Cecilia Esteves Phaedra Agius Christian Stolte John Boockvar Alexis Demopoulos Dimitris G. Placantonakis John G. Golfinos Cameron Brennan Jeffrey Bruce Andrew B. Lassman Peter Canoll Christian Grommes Mariza Daras Eli Diamond Antonio Omuro Elena Pentsova Dana E. Orange Stephen J. Harvey Jerome B. Posner Vanessa V. Michelini Vaidehi Jobanputra Michael C. Zody John Kelly Laxmi Parida Kazimierz O. Wrzeszczynski Ajay K. Royyuru Robert B. Darnell |
author_sort |
Mayu O. Frank |
title |
Sequencing and curation strategies for identifying candidate glioblastoma treatments |
title_short |
Sequencing and curation strategies for identifying candidate glioblastoma treatments |
title_full |
Sequencing and curation strategies for identifying candidate glioblastoma treatments |
title_fullStr |
Sequencing and curation strategies for identifying candidate glioblastoma treatments |
title_full_unstemmed |
Sequencing and curation strategies for identifying candidate glioblastoma treatments |
title_sort |
sequencing and curation strategies for identifying candidate glioblastoma treatments |
publisher |
BMC |
series |
BMC Medical Genomics |
issn |
1755-8794 |
publishDate |
2019-04-01 |
description |
Abstract Background Prompted by the revolution in high-throughput sequencing and its potential impact for treating cancer patients, we initiated a clinical research study to compare the ability of different sequencing assays and analysis methods to analyze glioblastoma tumors and generate real-time potential treatment options for physicians. Methods A consortium of seven institutions in New York City enrolled 30 patients with glioblastoma and performed tumor whole genome sequencing (WGS) and RNA sequencing (RNA-seq; collectively WGS/RNA-seq); 20 of these patients were also analyzed with independent targeted panel sequencing. We also compared results of expert manual annotations with those from an automated annotation system, Watson Genomic Analysis (WGA), to assess the reliability and time required to identify potentially relevant pharmacologic interventions. Results WGS/RNAseq identified more potentially actionable clinical results than targeted panels in 90% of cases, with an average of 16-fold more unique potentially actionable variants identified per individual; 84 clinically actionable calls were made using WGS/RNA-seq that were not identified by panels. Expert annotation and WGA had good agreement on identifying variants [mean sensitivity = 0.71, SD = 0.18 and positive predictive value (PPV) = 0.80, SD = 0.20] and drug targets when the same variants were called (mean sensitivity = 0.74, SD = 0.34 and PPV = 0.79, SD = 0.23) across patients. Clinicians used the information to modify their treatment plan 10% of the time. Conclusion These results present the first comprehensive comparison of technical and machine augmented analysis of targeted panel and WGS/RNA-seq to identify potential cancer treatments. |
url |
http://link.springer.com/article/10.1186/s12920-019-0500-0 |
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doaj-11a5273709844f08a3cc53b25ce397172021-04-02T15:18:37ZengBMCBMC Medical Genomics1755-87942019-04-0112111610.1186/s12920-019-0500-0Sequencing and curation strategies for identifying candidate glioblastoma treatmentsMayu O. Frank0Takahiko Koyama1Kahn Rhrissorrakrai2Nicolas Robine3Filippo Utro4Anne-Katrin Emde5Bo-Juen Chen6Kanika Arora7Minita Shah8Heather Geiger9Vanessa Felice10Esra Dikoglu11Sadia Rahman12Alice Fang13Vladimir Vacic14Ewa A. Bergmann15Julia L. Moore Vogel16Catherine Reeves17Depinder Khaira18Anthony Calabro19Duyang Kim20Michelle F. Lamendola-Essel21Cecilia Esteves22Phaedra Agius23Christian Stolte24John Boockvar25Alexis Demopoulos26Dimitris G. Placantonakis27John G. Golfinos28Cameron Brennan29Jeffrey Bruce30Andrew B. Lassman31Peter Canoll32Christian Grommes33Mariza Daras34Eli Diamond35Antonio Omuro36Elena Pentsova37Dana E. Orange38Stephen J. Harvey39Jerome B. Posner40Vanessa V. Michelini41Vaidehi Jobanputra42Michael C. Zody43John Kelly44Laxmi Parida45Kazimierz O. Wrzeszczynski46Ajay K. Royyuru47Robert B. Darnell48New York Genome CenterIBM Thomas J. Watson Research CenterIBM Thomas J. Watson Research CenterNew York Genome CenterIBM Thomas J. Watson Research CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNew York Genome CenterNorthwell Health, Lenox Hill HospitalNorthwell Health, The Brain Tumor CenterNew York University, School of MedicineNew York University, School of MedicineMemorial Sloan-Kettering Cancer CenterColumbia University Medical CenterColumbia University Medical CenterColumbia University Medical CenterMemorial Sloan-Kettering Cancer CenterMemorial Sloan-Kettering Cancer CenterMemorial Sloan-Kettering Cancer CenterMemorial Sloan-Kettering Cancer CenterMemorial Sloan-Kettering Cancer CenterLaboratory of Molecular Neuro-Oncology, The Rockefeller UniversityIBM Watson HealthMemorial Sloan-Kettering Cancer CenterIBM Watson HealthNew York Genome CenterNew York Genome CenterIBM Thomas J. Watson Research CenterIBM Thomas J. Watson Research CenterNew York Genome CenterIBM Thomas J. Watson Research CenterNew York Genome CenterAbstract Background Prompted by the revolution in high-throughput sequencing and its potential impact for treating cancer patients, we initiated a clinical research study to compare the ability of different sequencing assays and analysis methods to analyze glioblastoma tumors and generate real-time potential treatment options for physicians. Methods A consortium of seven institutions in New York City enrolled 30 patients with glioblastoma and performed tumor whole genome sequencing (WGS) and RNA sequencing (RNA-seq; collectively WGS/RNA-seq); 20 of these patients were also analyzed with independent targeted panel sequencing. We also compared results of expert manual annotations with those from an automated annotation system, Watson Genomic Analysis (WGA), to assess the reliability and time required to identify potentially relevant pharmacologic interventions. Results WGS/RNAseq identified more potentially actionable clinical results than targeted panels in 90% of cases, with an average of 16-fold more unique potentially actionable variants identified per individual; 84 clinically actionable calls were made using WGS/RNA-seq that were not identified by panels. Expert annotation and WGA had good agreement on identifying variants [mean sensitivity = 0.71, SD = 0.18 and positive predictive value (PPV) = 0.80, SD = 0.20] and drug targets when the same variants were called (mean sensitivity = 0.74, SD = 0.34 and PPV = 0.79, SD = 0.23) across patients. Clinicians used the information to modify their treatment plan 10% of the time. Conclusion These results present the first comprehensive comparison of technical and machine augmented analysis of targeted panel and WGS/RNA-seq to identify potential cancer treatments.http://link.springer.com/article/10.1186/s12920-019-0500-0 |