title: Mining the coding and non-coding genome for cancer drivers.
abstract: Progress in next-generation sequencing provides unprecedented opportunities to fully characterize the spectrum of somatic mutations of cancer genomes. Given the large number of somatic mutations identified by such technologies, the prioritization of cancer-driving events is a consistent bottleneck. Most bioinformatics tools concentrate on driver mutations in the coding fraction of the genome, those causing changes in protein products. As more non-coding pathogenic variants are identified and characterized, the development of computational approaches to effectively prioritize cancer-driving variants within the non-coding fraction of human genome is becoming critical. After a short summary of methods for coding variant prioritization, we here review the highly diverse non-coding elements that may act as cancer drivers and describe recent methods that attempt to evaluate the deleteriousness of sequence variation in these elements. With such tools, the prioritization and identification of cancer-implicated regulatory elements and non-coding RNAs is becoming a reality.
authors.affiliation: Institute for Integrative Biology of the Cell (I2BC), CNRS, CEA, Université Paris-Sud, Université Paris-Saclay, 91198 Gif sur Yvette, France.
authors.forename: Jia
authors.initials: J
authors.lastname: Li
authors.affiliation: Service de Biostatistique et d'Epidemiologie, Gustave Roussy, Villejuif, France; INSERM U1018, CESP, Université Paris-Sud, Université Paris-Saclay, Villejuif, France.
authors.forename: Damien
authors.initials: D
authors.lastname: Drubay
authors.affiliation: Service de Biostatistique et d'Epidemiologie, Gustave Roussy, Villejuif, France; INSERM U1018, CESP, Université Paris-Sud, Université Paris-Saclay, Villejuif, France.
authors.forename: Stefan
authors.initials: S
authors.lastname: Michiels
authors.affiliation: Institute for Integrative Biology of the Cell (I2BC), CNRS, CEA, Université Paris-Sud, Université Paris-Saclay, 91198 Gif sur Yvette, France. Electronic address: daniel.gautheret@u-psud.fr.
authors.forename: Daniel
authors.initials: D
authors.lastname: Gautheret
mesh_terms: D019295:Computational Biology / Q000379:methods*; D015894:Genome, Human; D006801:Humans; D009154:Mutation; D009369:Neoplasms / Q000235:genetics* / Q000378:metabolism
keywords: Bioinformatics; Cancer drivers; Non-coding drivers; Somatic mutation scoring