Abstract
Somatic variant analysis of a tumour sample and its matched normal has been widely used in cancer research to distinguish germline polymorphisms from somatic mutations. However, due to the extensive intratumour heterogeneity of cancer, sequencing data from a single tumour sample may greatly underestimate the overall mutational landscape. In recent studies, multiple spatially or temporally separated tumour samples from the same patient were sequenced to identify the regional distribution of somatic mutations and study intratumour heterogeneity. There are a number of tools to perform somatic variant calling from matched tumour-normal next-generation sequencing (NGS) data; however none of these allow joint analysis of multiple same-patient samples. We discuss the benefits and challenges of multisample somatic variant calling and present multiSNV, a software package for calling single nucleotide variants (SNVs) using NGS data from multiple same-patient samples. Instead of performing multiple pairwise analyses of a single tumour sample and a matched normal, multiSNV jointly considers all available samples under a Bayesian framework to increase sensitivity of calling shared SNVs. By leveraging information from all available samples, multiSNV is able to detect rare mutations with variant allele frequencies down to 3% from whole-exome sequencing experiments.
Highlights
Somatic single nucleotide variants (SNVs) are point mutations found in the genomes of tumour cells, but not their matched normals
The probability of sampling a variant allele was set to the variant allele frequency, and sequencing noise was added at the base quality rate
Even in the case where we have primary and metastatic samples, we may not assume that a mutation present in the primary sample exists in the metastatic one, as the given mutation might have come from a clone present in the primary sample, and not ancestral to any of the clones in the metastasis
Summary
Somatic single nucleotide variants (SNVs) are point mutations found in the genomes of tumour cells, but not their matched normals. They often play important roles in tumour initiation, progression and metastasis by changing the amino acid sequence (missense mutation) or prematurely truncating encoded proteins (nonsense mutation). Discovering such cancer-related SNVs is confounded by the presence of millions of germline point mutations. To distinguish somatic from germline SNVs, it has become routine to sequence matched tumour-normal samples from the same individual. Multiregion sequencing studies, where multiple samples from the same individual are sequenced, are becoming increasingly popular
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