Dataset Information

Clinical targeted exome-based sequencing in combination with genome-wide copy number profiling: precision medicine analysis of 203 pediatric brain tumors.

ABSTRACT: Clinical genomics platforms are needed to identify targetable alterations, but implementation of these technologies and best practices in routine clinical pediatric oncology practice are not yet well established.Profile is an institution-wide prospective clinical research initiative that uses targeted sequencing to identify targetable alterations in tumors. OncoPanel, a multiplexed targeted exome-sequencing platform that includes 300 cancer-causing genes, was used to assess single nucleotide variants and rearrangements/indels. Alterations were annotated (Tiers 1-4) based on clinical significance, with Tier 1 alterations having well-established clinical utility. OncoCopy, a clinical genome-wide array comparative genomic hybridization (aCGH) assay, was also performed to evaluate copy number alterations and better define rearrangement breakpoints.Cancer genomes of 203 pediatric brain tumors were profiled across histological subtypes, including 117 samples analyzed by OncoPanel, 146 by OncoCopy, and 60 tumors subjected to both methodologies. OncoPanel revealed clinically relevant alterations in 56% of patients (44 cancer mutations and 20 rearrangements), including BRAF alterations that directed the use of targeted inhibitors. Rearrangements in MYB-QKI, MYBL1, BRAF, and FGFR1 were also detected. Furthermore, while copy number profiles differed across histologies, the combined use of OncoPanel and OncoCopy identified subgroup-specific alterations in 89% (17/19) of medulloblastomas.The combination of OncoPanel and OncoCopy multiplex genomic assays can identify critical diagnostic, prognostic, and treatment-relevant alterations and represents an effective precision medicine approach for clinical evaluation of pediatric brain tumors.

SUBMITTER: Ramkissoon SH

PROVIDER: S-EPMC5570190 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Clinical targeted exome-based sequencing in combination with genome-wide copy number profiling: precision medicine analysis of 203 pediatric brain tumors.

Ramkissoon Shakti H SH Bandopadhayay Pratiti P Hwang Jaeho J Ramkissoon Lori A LA Greenwald Noah F NF Schumacher Steven E SE O'Rourke Ryan R Pinches Nathan N Ho Patricia P Malkin Hayley H Sinai Claire C Filbin Mariella M Plant Ashley A Bi Wenya Linda WL Chang Michael S MS Yang Edward E Wright Karen D KD Manley Peter E PE Ducar Matthew M Alexandrescu Sanda S Lidov Hart H Delalle Ivana I Goumnerova Liliana C LC Church Alanna J AJ Janeway Katherine A KA Harris Marian H MH MacConaill Laura E LE Folkerth Rebecca D RD Lindeman Neal I NI Stiles Charles D CD Kieran Mark W MW Ligon Azra H AH Santagata Sandro S Dubuc Adrian M AM Chi Susan N SN Beroukhim Rameen R Ligon Keith L KL

Neuro-oncology 20170701 7

<h4>Background</h4>Clinical genomics platforms are needed to identify targetable alterations, but implementation of these technologies and best practices in routine clinical pediatric oncology practice are not yet well established.<h4>Methods</h4>Profile is an institution-wide prospective clinical research initiative that uses targeted sequencing to identify targetable alterations in tumors. OncoPanel, a multiplexed targeted exome-sequencing platform that includes 300 cancer-causing genes, was u ...[more]

PMID: 28104717

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Project description:Somatic copy number variations (CNVs) play a crucial role in development of many human cancers. The broad availability of next-generation sequencing data has enabled the development of algorithms to computationally infer CNV profiles from a variety of data types including exome and targeted sequence data; currently the most prevalent types of cancer genomics data. However, systemic evaluation and comparison of these tools remains challenging due to a lack of ground truth reference sets. To address this need, we have developed Bamgineer, a tool written in Python to introduce user-defined haplotype-phased allele-specific copy number events into an existing Binary Alignment Mapping (BAM) file, with a focus on targeted and exome sequencing experiments. As input, this tool requires a read alignment file (BAM format), lists of non-overlapping genome coordinates for introduction of gains and losses (bed file), and an optional file defining known haplotypes (vcf format). To improve runtime performance, Bamgineer introduces the desired CNVs in parallel using queuing and parallel processing on a local machine or on a high-performance computing cluster. As proof-of-principle, we applied Bamgineer to a single high-coverage (mean: 220X) exome sequence file from a blood sample to simulate copy number profiles of 3 exemplar tumors from each of 10 tumor types at 5 tumor cellularity levels (20-100%, 150 BAM files in total). To demonstrate feasibility beyond exome data, we introduced read alignments to a targeted 5-gene cell-free DNA sequencing library to simulate EGFR amplifications at frequencies consistent with circulating tumor DNA (10, 1, 0.1 and 0.01%) while retaining the multimodal insert size distribution of the original data. We expect Bamgineer to be of use for development and systematic benchmarking of CNV calling algorithms by users using locally-generated data for a variety of applications. The source code is freely available at http://github.com/pughlab/bamgineer.

Dataset Information

Clinical targeted exome-based sequencing in combination with genome-wide copy number profiling: precision medicine analysis of 203 pediatric brain tumors.

Publications

Clinical targeted exome-based sequencing in combination with genome-wide copy number profiling: precision medicine analysis of 203 pediatric brain tumors.

Similar Datasets

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