Computational protocol: Glioblastoma adaptation traced through decline of an IDH1 clonal driver and macro-evolution of a double-minute chromosome

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Protocol publication

[…] WGS was carried out by Illumina, UK. Mutation calling and filtering was carried out using VarScan2 as described [], annotation of coding mutations were carried out using ANNOVAR []. Structural variant (SV) breakpoint mechanism classification was carried out according to the criteria defined in Yang et al. []. Reconstruction of the putative double-minute chromosomes was carried out as described in Sanborn et al. [] and breakpoints mapping to the focal amplifications were validated by PCR and Sanger Sequencing. Copy-number variation (CNV) analysis was carried out on the WGS data. Purity, ploidy and allele-specific copy-number estimates were obtained with Sequenza []. Clonal analysis was carried out as described in Bolli et al. [], estimating the cancer cell fraction (CCF) by integrating variant allele frequency estimates with copy number, purity and ploidy estimates. Single-sample and multi-sample Dirichlet process clustering was carried out using the DPpackage R package []. In this work, mutations are referred to as ‘sub-clonal’ if their CCF indicates they are present in only a subset of cancer cells within a given sample (CCF <1). Mutations present in all cancer cells of a given sample (CCF ∼ 1) are referred to as ‘clonal’. Genome doubling (GD) was determined from the comparison of the sequencing of the grade II and the grade IV regions and by considering the mutations located in the portion of the genome where a clear doubling of the number of alleles was detected, see supplementary Information, available at Annals of Oncology online, for details. All data analysis was carried out in R version 3.0.2, all P values are two sided. […]

Pipeline specifications

Software tools VarScan, ANNOVAR, Sequenza
Application WGS analysis
Organisms Homo sapiens
Diseases Brain Neoplasms, Glioblastoma, Neoplasms