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Identifying driver mutations in sequenced cancer genomes: computational approaches to enable precision medicine

Benjamin J Raphael, Jason R Dobson, Layla Oesper and 1 more

Genome Medicine · 2014 · Review

doi:10.1186/gm524

Abstract

High-throughput DNA sequencing is revolutionizing the study of cancer and enabling the measurement of the somatic mutations that drive cancer development. However, the resulting sequencing datasets are large and complex, obscuring the clinically important mutations in a background of errors, noise, and random mutations. Here, we review computational approaches to identify somatic mutations in cancer genome sequences and to distinguish the driver mutations that are responsible for cancer from random, passenger mutations. First, we describe approaches to detect somatic mutations from high-throughput DNA sequencing data, particularly for tumor samples that comprise heterogeneous populations of cells. Next, we review computational approaches that aim to predict driver mutations according to their frequency of occurrence in a cohort of samples, or according to their predicted functional impact on protein sequence or structure. Finally, we review techniques to identify recurrent combinations of somatic mutations, including approaches that examine mutations in known pathways or protein-interaction networks, as well as de novo approaches that identify combinations of mutations according to statistical patterns of mutual exclusivity. These techniques, coupled with advances in high-throughput DNA sequencing, are enabling precision medicine approaches to the diagnosis and treatment of cancer.

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    Dias-Santagata D Akhavanfard S David SS Vernovsky K Kuhlmann G Boisvert SL Stubbs H McDermott U Settleman J Kwak EL Clark JW Isakoff SJ Sequist LV Engelman JA Lynch TJ Haber DA Louis DN Ellisen LW Borger DR Iafrate AJ Rapid targeted mutational analysis of human tumours: a clinical platform to guide personalized cancer medicineEMBO Mol Med2010 2146158

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    Wagle N Berger MF Davis MJ Blumenstiel B Defelice M Pochanard P Ducar M Van Hummelen P Macconaill LE Hahn WC Meyerson M Gabriel SB Garraway LA High-throughput detection of actionable genomic alterations in clinical tumor samples by targeted, massively parallel sequencingCancer Discov2012 28293

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    Thomas RK Baker AC Debiasi RM Winckler W Laframboise T Lin WM Wang M Feng W Zander T MacConaill L MacConnaill LE Lee JC Nicoletti R Hatton C Goyette M Girard L Majmudar K Ziaugra L Wong KK Gabriel S Beroukhim R Peyton M Barretina J Dutt A Emery C Greulich H Shah K Sasaki H Gazdar A Minna J High-throughput oncogene mutation profiling in human cancerNature Genetics2007 39347351

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    Kim ES Herbst RS Wistuba II Lee JJ Blumenschein GR Tsao A Stewart DJ Hicks ME Erasmus J Gupta S Alden CM Liu S Tang X Khuri FR Tran HT Johnson BE Heymach JV Mao L Fossella F Kies MS Papadimitrakopoulou V Davis SE Lippman SM Hong WK The BATTLE trial: personalizing therapy for lung cancerCancer Discov2011 14453

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    Huang FW Hodis E Xu MJ Kryukov GV Chin L Garraway LA Highly recurrent TERT promoter mutations in human melanomaScience2013 339957959

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    Dunham I Kundaje A Aldred SF Collins PJ Davis CA Doyle F Epstein CB Frietze S Harrow J Kaul R Khatun J Lajoie BR Landt SG Lee BK Pauli F Rosenbloom KR Sabo P Safi A Sanyal A Shoresh N Simon JM Song L Trinklein ND Altshuler RC Birney E Brown JB Cheng C Djebali S Dong X Ernst J An integrated encyclopedia of DNA elements in the human genomeNature2012 4895774

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    Hofree M Shen JP Carter H Gross A Ideker T Network-based stratification of tumor mutationsNat Methods2013 1011081115

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    Weinstein JN Collisson EA Mills GB Shaw KRM Ozenberger BA Ellrott K Shmulevich I Sander C Stuart JM Cancer Genome Atlas Research NetworkThe Cancer Genome Atlas Pan-Cancer analysis projectNat Genet2013 4511131120

    Not in our library10.1038/ng.2764

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    Kandoth C McLellan MD Vandin F Ye K Niu B Lu C Xie M Zhang Q McMichael JF Wyczalkowski MA Leiserson MDM Miller CA Welch JS Walter MJ Wendl MC Ley TJ Wilson RK Raphael BJ Ding L Mutational landscape and significance across 12 major cancer typesNature2013 502333339

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    Not in our library10.1038/ng.2762

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    Zack TI Schumacher SE Carter SL Cherniack AD Saksena G Tabak B Lawrence MS Zhang CZ Wala J Mermel CH Sougnez C Gabriel SB Hernandez B Shen H Laird PW Getz G Meyerson M Beroukhim R Pan-cancer patterns of somatic copy number alterationNat Genet2013 4511341140

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    Roth A Ding J Morin R Crisan A Ha G Giuliany R Bashashati A Hirst M Turashvili G Oloumi A Marra MA Aparicio S Shah SP JointSNVMix: a probabilistic model for accurate detection of somatic mutations in normal/tumour paired next-generation sequencing dataBioinformatics2012 28907913

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    Xi R Luquette J Hadjipanayis A Kim TM Park PJ BIC-seq: a fast algorithm for detection of copy number alterations based on high-throughput sequencing dataGenome Biol2010 11O10

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    Krumm N Sudmant PH Ko A O’Roak BJ Malig M Coe BP Quinlan AR Nickerson DA Eichler EE NHLBI Exome Sequencing ProjectCopy number variation detection and genotyping from exome sequence dataGenome Res2012 2215251532

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    Chen K Wallis JW McLellan MD Larson DE Kalicki JM Pohl CS McGrath SD Wendl MC Zhang Q Locke DP Shi X Fulton RS Ley TJ Wilson RK Ding L Mardis ER BreakDancer: an algorithm for high-resolution mapping of genomic structural variationNat Methods2009 6677681

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    Sindi SS Onal S Peng LC Wu HT Raphael BJ An integrative probabilistic model for identification of structural variation in sequencing dataGenome Biol2012 13R22

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    Escaramís G Tornador C Bassaganyas L Rabionet R Tubio JMC Martínez-Fundichely A Cáceres M Gut M Ossowski S Estivill X PeSV-Fisher: identification of somatic and non-somatic structural variants using next generation sequencing dataPLoS One2013 8e63377

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    Drier Y Lawrence MS Carter SL Stewart C Gabriel SB Lander ES Meyerson M Beroukhim R Getz G Somatic rearrangements across cancer reveal classes of samples with distinct patterns of DNA breakage and rearrangement-induced hypermutabilityGenome Res2013 23228235

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    Hua X Xu H Yang Y Zhu J Liu P Lu Y DrGaP: a powerful tool for identifying driver genes and pathways in cancer sequencing studiesAm J Hum Genet2013 93439451

    Not in our library10.1016/j.ajhg.2013.07.003

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