Journal Article

Sequencing and curation strategies for identifying candidate glioblastoma treatments

Agius, Phaedra, Zody, Michael C., Arora, Kanika, Stolte, Christian, Michelini, Vanessa V., Shah, Minita, Bruce, Jeffrey, Lassman, Andrew B., Robine, Nicolas, Emde, Anne-Katrin, Esteves, Cecilia, Parida, Laxmi, Chen, Bo-Juen, Posner, Jerome B., Lamendola-Essel, Michelle F., Darnell, Robert B., Omuro, Antonio, Pentsova, Elena, Harvey, Stephen J., Vacic, Vladimir, Dikoglu, Esra, Golfinos, John G., Boockvar, John, Frank, Mayu O., Kelly, John, Reeves, Catherine, Canoll, Peter, Grommes, Christian, Utro, Filippo, Vogel, Julia L. Moore, Bergmann, Ewa A., Calabro, Anthony, Rhrissorrakrai, Kahn, Fang, Alice, Koyama, Takahiko, Khaira, Depinder, Orange, Dana E., Royyuru, Ajay K., Daras, Mariza, Felice, Vanessa, Kim, Duyang, Rahman, Sadia, Brennan, Cameron, Placantonakis, Dimitris G., Geiger, Heather, Wrzeszczynski, Kazimierz O., Demopoulos, Alexis, Diamond, Eli, Jobanputra, Vaidehi

2019

Overview

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.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Adult / Aged / Aged, 80 and over / Automation / Biomedical and Life Sciences / Biomedicine / Brain cancer / Cancer patients / Cancer research / Cancer therapies / Cancer treatment / Care and treatment / Clinical trials / Comparative analysis / Consortia / DNA sequencing / Feasibility studies / Female / Functional and structural genomics / Gene Expression / Genetic aspects / Genomes / Genomic analysis / Genomics / Glioblastoma / Glioblastoma - drug therapy / Glioblastoma - genetics / Glioblastomas / Gliomas / Health aspects / High-Throughput Nucleotide Sequencing / Human Genetics / Humans / Male / Medical research / Medical schools / Microarrays / Middle Aged / Molecular Targeted Therapy / Mutation / Natural language processing / Next-generation sequencing / Patients / Physicians / Ploidies / Reproducibility of Results / Research Article / Ribonucleic acid / RNA / RNA sequencing / Therapeutic applications / Tumors / Whole Genome Sequencing