Whole Genome Sequencing of DCIS

Description

Ductal carcinoma in situ (DCIS) is a non-obligate precursor lesion of breast cancer (BC). Often detected by mammography, most cases are managed through surgical and/or radiotherapy approaches. Today, it is not possible to predict which patients will progress to invasive disease. We have evaluated high-depth whole-genome sequencing (WGS) of DCIS, in order to uncover biological insights into breast cancer progression as well as possible methods to stratify DCIS patients for individualised therapy or disease monitoring. Deposited here are the somatic mutation calls (SNVs, small insertions and deletions, structural variants and copy number changes) from WGS data for 113 breast DCIS samples.

Steps to reproduce

DNA extracted from fresh frozen DCIS tissue and matched normal, either from blood or adjacent normal breast, was subject to WGS on an Illumina HIseqX, or Illumina Novoseq to an average sequence depth of 104X for DCIS samples and 39x for matched-normals. The resultant reads were aligned to the reference human genome (GRCh38) using a Burrows–Wheeler Aligner, bwa mem (version 0.7.17-r1188 within dockstore-cgpmap v3.2.0). Paired tumor-normal bam files were interrogated for somatic mutations using the following algorithms, CaVEMan (Cancer Variants through Expectation Maximisation) (1.13.15) for single-nucleotide substitutions, Pindel version 3.2.0 for small insertions and deletions, BRASS 6.2.1 for structural rearrangements, and ASCAT 4.2.1 for copy number changes. Additional post-processing filters were applied prior to downstream analysis. For CaVEMan ASMD>=140, CLPM=0. For BRASS variants a successful local realignment step indicated by assembly score <0 was required. Pindel filters include QUAL≥250, REP<10, NP>0, PP>0; the calls were further filtered against SNPs with frequency > 0.01 to reduce the false positive rate. SNP databases used for filtering were gnomAD (version 4.0 whole genome data, build: hg38), and 1000 Genome Project (version 1000g2015aug, build: hg38). ASCAT was used to call copy number variants and to provide estimates of average tumour ploidy and aberrant cell fraction. The algorithms used are contained in the following dockstore (dockstore-cgpwgs v2.1.1 available at https://quay.io/repository/wtsicgp/dockstore-cgpwgs).

Institutions

• University of Cambridge

  England, Cambridge

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