Abstract
Advanced cancer genomics technologies are now being employed in clinical sequencing, where next-generation sequencers are used to simultaneously identify multiple types of DNA alterations for prescription of molecularly targeted drugs. However, no computational tool is available to accurately detect DNA alterations in formalin-fixed paraffin-embedded (FFPE) samples commonly used in hospitals. Here, we developed a computational tool tailored to the detection of single nucleotide variations, indels, fusions, and copy number alterations in FFPE samples. Elaborated multilayer noise filters reduced the inherent noise while maintaining high sensitivity, as evaluated in tumor-unmatched normal samples using orthogonal technologies. This tool, cisCall, should facilitate clinical sequencing in everyday diagnostics. It is available at https://www.ciscall.org.
Highlights
In recent years, large-scale cancer genome projects such as the International Cancer Genome Consortium [1,2,3] (ICGC) and The Cancer Genome Atlas (TCGA) have greatly expanded the available knowledge on genomic alterations in cancer
70 formalin-fixed paraffin-embedded (FFPE) clinical samples were used as foreground datasets for Single nucleotide variation (SNV)/indel analysis, and 75 FFPE clinical samples were used as foreground datasets for Copy number alteration (CNA) analysis
All exons of 90 genes and reportedly translocated introns of 35 fusion genes (12 kinases and 23 partners) were captured by our original gene panel (NCC oncopanel v2; Additional file 2: Table S2). These exons and introns were sequenced for the detection of SNVs/ indels, CNAs, and DNA gene fusions
Summary
Large-scale cancer genome projects such as the International Cancer Genome Consortium [1,2,3] (ICGC) and The Cancer Genome Atlas (TCGA) have greatly expanded the available knowledge on genomic alterations in cancer. Along with this increasing knowledge, the number of investigational and approved drugs that target aberrant gene products continues to grow [4]. The advantage of NGS technologies is that they allow the simultaneous detection of various types of aberrations, i.e., single nucleotide variations (SNVs), indels,
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