Dataset Information

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 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.

SUBMITTER: Frank MO

PROVIDER: S-EPMC6485090 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Publications

Sequencing and curation strategies for identifying candidate glioblastoma treatments.

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

BMC medical genomics 20190425 1

<h4>Background</h4>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.<h4>Methods</h4>A consortium of seven institutions in New York City enrolled 30 patients with glioblastoma and performed tumor whole genome sequencing (WGS) a ...[more]

PMID: 31023376

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Project description:BackgroundForward genetic screens are a powerful approach for identifying the genes contributing to a trait of interest. However, mutants arising in genes already known can obscure the identification of new genes contributing to the trait. Here, we describe a strategy called Candidate gene-Sequencing (Can-Seq) for rapidly identifying and filtering out mutants carrying new alleles of known and candidate genes.ResultsWe carried out a forward genetic screen and identified 40 independent Arabidopsis mutants with defects in systemic spreading of RNA interference (RNAi), or more specifically in root-to-shoot transmission of post-transcriptional gene silencing (rtp). To classify the mutants as either representing a new allele of a known or candidate gene versus carrying a mutation in an undiscovered gene, bulk genomic DNA from up to 23 independent mutants was used as template to amplify a collection of 47 known or candidate genes. These amplified sequences were combined into Can-Seq libraries and deep sequenced. Subsequently, mutations in the known and candidate genes were identified using a custom Snakemake script (https://github.com/Carroll-Lab/can_seq), and PCR zygosity tests were then designed and used to identify the individual mutants carrying each mutation. Using this approach, we showed that 28 of the 40 rtp mutants carried homozygous nonsense, missense or splice site mutations in one or more of the 47 known or candidate genes. We conducted complementation tests to demonstrate that several of the candidate mutations were responsible for the rtp defect. Importantly, by exclusion, the Can-Seq pipeline also identified rtp mutants that did not carry a causative mutation in any of the 47 known and candidate genes, and these mutants represent an undiscovered gene(s) required for systemic RNAi.ConclusionsCan-Seq offers an accurate, cost-effective method for classifying new mutants into known versus unknown genes. It has several advantages over existing genetic and DNA sequencing approaches that are currently being used in forward genetic screens for gene discovery. Using Can-Seq in conjunction with map-based gene cloning is a cost-effective approach towards identifying the full complement of genes contributing to a trait of interest.

Dataset Information

Sequencing and curation strategies for identifying candidate glioblastoma treatments.

Background

Methods

Results

Conclusion

Publications

Sequencing and curation strategies for identifying candidate glioblastoma treatments.

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