title: Studying cancer genomics through next-generation DNA sequencing and bioinformatics.
abstract: Cancer is a complex disease driven by multiple mutations acquired over the lifetime of the cancer cells. These alterations, termed somatic mutations to distinguish them from inherited germline mutations, can include single-nucleotide substitutions, insertions, deletions, copy number alterations, and structural rearrangements. A patient's cancer can contain a combination of these aberrations, and the ability to generate a comprehensive genetic profile should greatly improve patient diagnosis and treatment. Next-generation sequencing has become the tool of choice to uncover multiple cancer mutations from a single tumor source, and the falling costs of this rapid high-throughput technology are encouraging its transition from basic research into a clinical setting. However, the detection of mutations in sequencing data is still an evolving area and cancer genomic data requires some special considerations. This chapter discusses these aspects and gives an overview of current bioinformatics methods for the detection of somatic mutations in cancer sequencing data.
authors.affiliation: Peter MacCallum Cancer Centre, St Andrews Place, East Melbourne, VIC, 3002, Australia, Maria.Doyle@petermac.org.
authors.forename: Maria A
authors.initials: MA
authors.lastname: Doyle
authors.forename: Jason
authors.initials: J
authors.lastname: Li
authors.forename: Ken
authors.initials: K
authors.lastname: Doig
authors.forename: Andrew
authors.initials: A
authors.lastname: Fellowes
authors.forename: Stephen Q
authors.initials: SQ
authors.lastname: Wong
mesh_terms: D019295:Computational Biology / Q000379:methods*; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D009369:Neoplasms / Q000235:genetics*