Abstract
BackgroundPrompted 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.MethodsA 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.ResultsWGS/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.ConclusionThese results present the first comprehensive comparison of technical and machine augmented analysis of targeted panel and WGS/RNA-seq to identify potential cancer treatments.
Highlights
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
84 additional clinically actionable calls were made using whole genome sequencing (WGS)/RNA sequencing (RNA-seq) that were not identified by panels, compared to four made by panels and missed by WGS/ RNA-seq
In creating drug databases, Watson Genomic Analysis (WGA) used an automated, comprehensive, and Discussion We undertook a comparative genomic-based study of GBM patients to investigate the utility of targeted panels versus WGS/RNA-seq and evaluated the feasibility and reliability of results obtained with manual versus automated curation by IBM’s WGA
Summary
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. Panel-based sequencing, using hybridization and capture of specific regions of key genes or of all genes (whole exomes; WES), versus whole genome sequencing (WGS) are different technologies with different costs that have not previously been directly compared. 10,000 cancer patients sequenced with the MSK-IMPACT panel identified potentially clinically actionable calls in 36.7% of individuals sequenced [5]. Deep sequencing coverage increases sensitivity for rare variants in heterogeneous tumors. WGS, does not rely on hybridization and capture, a source of potential bias, and is able to identify non-coding variants such as enhancer bindings sites [6] and increases sensitivity for small copy number variants (CNVs) and missense mutations, indels, [7] intronic variants, [8] and gene fusions [9]. The relative impact of of these technologies on making clinically actionable variant calls is unknown
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
