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Gerstung M, Jolly C, Leshchiner I, Dentro SC, Gonzalez S, Rosebrock D, Mitchell TJ, Rubanova Y, Anur P, Yu K, Tarabichi M, Deshwar A, Wintersinger J, Kleinheinz K, Vázquez-García I, Haase K, Jerman L, Sengupta S, Macintyre G, Malikic S, Donmez N, Livitz DG, Cmero M, Demeulemeester J, Schumacher S, Fan Y, Yao X, Lee J, Schlesner M, Boutros PC, Bowtell DD, Zhu H, Getz G, Imielinski M, Beroukhim R, Sahinalp SC, Ji Y, Peifer M, Markowetz F, Mustonen V, Yuan K, Wang W, Morris QD, Spellman PT, Wedge DC, Van Loo P, Tarabichi M, Wintersinger J, Deshwar AG, Yu K, Gonzalez S, Rubanova Y, Macintyre G, Adams DJ, Anur P, Beroukhim R, Boutros PC, Bowtell DD, Campbell PJ, Cao S, Christie EL, Cmero M, Cun Y, Dawson KJ, Demeulemeester J, Donmez N, Drews RM, Eils R, Fan Y, Fittall M, Garsed DW, Getz G, Ha G, Imielinski M, Jerman L, Ji Y, Kleinheinz K, Lee J, Lee-Six H, Livitz DG, Malikic S, Markowetz F, Martincorena I, Mitchell TJ, Mustonen V, Oesper L, Peifer M, Peto M, Raphael BJ, Rosebrock D, Sahinalp SC, Salcedo A, Schlesner M, Schumacher S, Sengupta S, Shi R, Shin SJ, Spiro O, Pitkänen E, Pivot X, Piñeiro-Yáñez E, Planko L, Plass C, Polak P, Pons T, Popescu I, Potapova O, Prasad A, Stein LD, Preston SR, Prinz M, Pritchard AL, Prokopec SD, Provenzano E, Puente XS, Puig S, Puiggròs M, Pulido-Tamayo S, Pupo GM, Vázquez-García I, Purdie CA, Quinn MC, Rabionet R, Rader JS, Radlwimmer B, Radovic P, Raeder B, Raine KM, Ramakrishna M, Ramakrishnan K, Vembu S, Ramalingam S, Raphael BJ, Rathmell WK, Rausch T, Reifenberger G, Reimand J, Reis-Filho J, Reuter V, Reyes-Salazar I, Reyna MA, Wheeler DA, Reynolds SM, Rheinbay E, Riazalhosseini Y, Richardson AL, Richter J, Ringel M, Ringnér M, Rino Y, Rippe K, Roach J, Yang TP, Roberts LR, Roberts ND, Roberts SA, Robertson AG, Robertson AJ, Rodriguez JB, Rodriguez-Martin B, Rodríguez-González FG, Roehrl MHA, Rohde M, Yao X, Rokutan H, Romieu G, Rooman I, Roques T, Rosebrock D, Rosenberg M, Rosenstiel PC, Rosenwald A, Rowe EW, Royo R, Yuan K, Rozen SG, Rubanova Y, Rubin MA, Rubio-Perez C, Rudneva VA, Rusev BC, Ruzzenente A, Rätsch G, Sabarinathan R, Sabelnykova VY, Zhu H, Sadeghi S, Sahinalp SC, Saini N, Saito-Adachi M, Saksena G, Salcedo A, Salgado R, Salichos L, Sallari R, Saller C, Wang W, Salvia R, Sam M, Samra JS, Sanchez-Vega F, Sander C, Sanders G, Sarin R, Sarrafi I, Sasaki-Oku A, Sauer T, Morris QD, Sauter G, Saw RPM, Scardoni M, Scarlett CJ, Scarpa A, Scelo G, Schadendorf D, Schein JE, Schilhabel MB, Schlesner M, Spellman PT, Schlomm T, Schmidt HK, Schramm SJ, Schreiber S, Schultz N, Schumacher SE, Schwarz RF, Scolyer RA, Scott D, Scully R, Wedge DC, Seethala R, Segre AV, Selander I, Semple CA, Senbabaoglu Y, Sengupta S, Sereni E, Serra S, Sgroi DC, Shackleton M, Van Loo P, Shah NC, Shahabi S, Shang CA, Shang P, Shapira O, Shelton T, Shen C, Shen H, Shepherd R, Shi R, Spellman PT, Shi Y, Shiah YJ, Shibata T, Shih J, Shimizu E, Shimizu K, Shin SJ, Shiraishi Y, Shmaya T, Shmulevich I, Wedge DC, Shorser SI, Short C, Shrestha R, Shringarpure SS, Shriver C, Shuai S, Sidiropoulos N, Siebert R, Sieuwerts AM, Sieverling L, Van Loo P, Signoretti S, Sikora KO, Simbolo M, Simon R, Simons JV, Simpson JT, Simpson PT, Singer S, Sinnott-Armstrong N, Sipahimalani P, Aaltonen LA, Skelly TJ, Smid M, Smith J, Smith-McCune K, Socci ND, Sofia HJ, Soloway MG, Song L, Sood AK, Sothi S, Abascal F, Sotiriou C, Soulette CM, Span PN, Spellman PT, Sperandio N, Spillane AJ, Spiro O, Spring J, Staaf J, Stadler PF, Abeshouse A, Staib P, Stark SG, Stebbings L, Stefánsson ÓA, Stegle O, Stein LD, Stenhouse A, Stewart C, Stilgenbauer S, Stobbe MD, Aburatani H, Stratton MR, Stretch JR, Struck AJ, Stuart JM, Stunnenberg HG, Su H, Su X, Sun RX, Sungalee S, Susak H, Adams DJ, Suzuki A, Sweep F, Szczepanowski M, Sültmann H, Yugawa T, Tam A, Tamborero D, Tan BKT, Tan D, Tan P, Agrawal N, Tanaka H, Taniguchi H, Tanskanen TJ, Tarabichi M, Tarnuzzer R, Tarpey P, Taschuk ML, Tatsuno K, Tavaré S, Taylor DF, Ahn KS, Taylor-Weiner A, Teague JW, Teh BT, Tembe V, Temes J, Thai K, Thayer SP, Thiessen N, Thomas G, Thomas S, Ahn SM, Thompson A, Thompson AM, Thompson JFF, Thompson RH, Thorne H, Thorne LB, Thorogood A, Tiao G, Tijanic N, Timms LE, Aikata H, Tirabosco R, Tojo M, Tommasi S, Toon CW, Toprak UH, Torrents D, Tortora G, Tost J, Totoki Y, Townend D, Akbani R, Traficante N, Treilleux I, Trotta JR, Trümper LHP, Tsao M, Tsunoda T, Tubio JMC, Tucker O, Turkington R, Turner DJ, Akdemir KC, Tutt A, Ueno M, Ueno NT, Umbricht C, Umer HM, Underwood TJ, Urban L, Urushidate T, Ushiku T, Uusküla-Reimand L, Al-Ahmadie H, Valencia A, Van Den Berg DJ, Van Laere S, Van Loo P, Van Meir EG, Van den Eynden GG, Van der Kwast T, Vasudev N, Vazquez M, Vedururu R, Al-Sedairy ST, Veluvolu U, Vembu S, Verbeke LPC, Vermeulen P, Verrill C, Viari A, Vicente D, Vicentini C, VijayRaghavan K, Viksna J, Al-Shahrour F, Vilain RE, Villasante I, Vincent-Salomon A, Visakorpi T, Voet D, Vyas P, Vázquez-García I, Waddell NM, Waddell N, Wadelius C, Alawi M, Wadi L, Wagener R, Wala JA, Wang J, Wang J, Wang L, Wang Q, Wang W, Wang Y, Wang Z, Albert M, Waring PM, Warnatz HJ, Warrell J, Warren AY, Waszak SM, Wedge DC, Weichenhan D, Weinberger P, Weinstein JN, Weischenfeldt J, Aldape K, Weisenberger DJ, Welch I, Wendl MC, Werner J, Whalley JP, Wheeler DA, Whitaker HC, Wigle D, Wilkerson MD, Williams A, Alexandrov LB, Wilmott JS, Wilson GW, Wilson JM, Wilson RK, Winterhoff B, Wintersinger JA, Wiznerowicz M, Wolf S, Wong BH, Wong T, Ally A, Wong W, Woo Y, Wood S, Wouters BG, Wright AJ, Wright DW, Wright MH, Wu CL, Wu DY, Wu G, Alsop K, Wu J, Wu K, Wu Y, Wu Z, Xi L, Xia T, Xiang Q, Xiao X, Xing R, Xiong H, Alvarez EG, Xu Q, Xu Y, Xue H, Yachida S, Yakneen S, Yamaguchi R, Yamaguchi TN, Yamamoto M, Yamamoto S, Yamaue H, Amary F, Yang F, Yang H, Yang JY, Yang L, Yang L, Yang S, Yang TP, Yang Y, Yao X, Yaspo ML, Amin SB, Yates L, Yau C, Ye C, Ye K, Yellapantula VD, Yoon CJ, Yoon SS, Yousif F, Yu J, Yu K, Aminou B, Yu W, Yu Y, Yuan K, Yuan Y, Yuen D, Yung CK, Zaikova O, Zamora J, Zapatka M, Zenklusen JC, Ammerpohl O, Zenz T, Zeps N, Zhang CZ, Zhang F, Zhang H, Zhang H, Zhang H, Zhang J, Zhang J, Zhang J, Anderson MJ, Zhang X, Zhang X, Zhang Y, Zhang Z, Zhao Z, Zheng L, Zheng X, Zhou W, Zhou Y, Zhu B, Ang Y, Zhu H, Zhu J, Zhu S, Zou L, Zou X, deFazio A, van As N, van Deurzen CHM, van de Vijver MJ, van’t Veer L, Antonello D, von Mering C, Anur P, Aparicio S, Appelbaum EL, Arai Y, Aretz A, Arihiro K, Ariizumi SI, Armenia J, Arnould L, Asa S, Assenov Y, Atwal G, Aukema S, Auman JT, Aure MRR, Awadalla P, Aymerich M, Bader GD, Baez-Ortega A, Bailey MH, Bailey PJ, Balasundaram M, Balu S, Bandopadhayay P, Banks RE, Barbi S, Barbour AP, Barenboim J, Barnholtz-Sloan J, Barr H, Barrera E, Bartlett J, Bartolome J, Bassi C, Bathe OF, Baumhoer D, Bavi P, Baylin SB, Bazant W, Beardsmore D, Beck TA, Behjati S, Behren A, Niu B, Bell C, Beltran S, Benz C, Berchuck A, Bergmann AK, Bergstrom EN, Berman BP, Berney DM, Bernhart SH, Beroukhim R, 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Chan-Seng-Yue M, Chandan VS, Chang DK, Chanock SJ, Chantrill LA, Chateigner A, Chatterjee N, Chayama K, Chen HW, Chen J, Chen K, Chen Y, Chen Z, Cherniack AD, Chien J, Chiew YE, Chin SF, Cho J, Cho S, Choi JK, Choi W, Chomienne C, Chong Z, Choo SP, Chou A, Christ AN, Christie EL, Chuah E, Cibulskis C, Cibulskis K, Cingarlini S, Clapham P, Claviez A, Cleary S, Cloonan N, Cmero M, Collins CC, Connor AA, Cooke SL, Cooper CS, Cope L, Corbo V, Cordes MG, Cordner SM, Cortés-Ciriano I, Covington K, Cowin PA, Craft B, Craft D, Creighton CJ, Cun Y, Curley E, Cutcutache I, Czajka K, Czerniak B, Dagg RA, Danilova L, Davi MV, Davidson NR, Davies H, Davis IJ, Davis-Dusenbery BN, Dawson KJ, De La Vega FM, De Paoli-Iseppi R, Defreitas T, Tos APD, Delaneau O, Demchok JA, Demeulemeester J, Demidov GM, Demircioğlu D, Dennis NM, Denroche RE, Dentro SC, Desai N, Deshpande V, Deshwar AG, Desmedt C, Deu-Pons J, Dhalla N, Dhani NC, Dhingra P, Dhir R, DiBiase A, Diamanti K, Ding L, Ding S, Dinh HQ, Dirix L, 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George J, Gerhard DS, Gerhauser C, Gershenwald JE, Gerstein M, Gerstung M, Getz G, Ghori M, Ghossein R, Giama NH, Gibbs RA, Gibson B, Gill AJ, Gill P, Giri DD, Glodzik D, Gnanapragasam VJ, Goebler ME, Goldman MJ, Gomez C, Gonzalez S, Gonzalez-Perez A, Gordenin DA, Gossage J, Gotoh K, Govindan R, Grabau D, Graham JS, Grant RC, Green AR, Green E, Greger L, Grehan N, Grimaldi S, Grimmond SM, Grossman RL, Grundhoff A, Gundem G, Guo Q, Gupta M, Gupta S, Gut IG, Gut M, Göke J, Ha G, Haake A, Haan D, Haas S, Haase K, Haber JE, Habermann N, Hach F, Haider S, Hama N, Hamdy FC, Hamilton A, Hamilton MP, Han L, Hanna GB, Hansmann M, Haradhvala NJ, Harismendy O, Harliwong I, Harmanci AO, Harrington E, Hasegawa T, Haussler D, Hawkins S, Hayami S, Hayashi S, Hayes DN, Hayes SJ, Hayward NK, Hazell S, He Y, Heath AP, Heath SC, Hedley D, Hegde AM, Heiman DI, Heinold MC, Heins Z, Heisler LE, Hellstrom-Lindberg E, Helmy M, Heo SG, Hepperla AJ, Heredia-Genestar JM, Herrmann C, Hersey P, Hess JM, Hilmarsdottir H, Hinton J, Hirano S, Hiraoka N, Hoadley KA, Hobolth A, Hodzic E, Hoell JI, Hoffmann S, Hofmann O, Holbrook A, Holik AZ, Hollingsworth MA, Holmes O, Holt RA, Hong C, Hong EP, Hong JH, Hooijer GK, Hornshøj H, Hosoda F, Hou Y, Hovestadt V, Howat W, Hoyle AP, Hruban RH, Hu J, Hu T, Hua X, Huang KL, Huang M, Huang MN, Huang V, Huang Y, Huber W, Hudson TJ, Hummel M, Hung JA, Huntsman D, Hupp TR, Huse J, Huska MR, Hutter B, Hutter CM, Hübschmann D, Iacobuzio-Donahue CA, Imbusch CD, Imielinski M, Imoto S, Isaacs WB, Isaev K, Ishikawa S, Iskar M, Islam SMA, Ittmann M, Ivkovic S, Izarzugaza JMG, Jacquemier J, Jakrot V, Jamieson NB, Jang GH, Jang SJ, Jayaseelan JC, Jayasinghe R, Jefferys SR, Jegalian K, Jennings JL, Jeon SH, Jerman L, Ji Y, Jiao W, Johansson PA, Johns AL, Johns J, Johnson R, Johnson TA, Jolly C, Joly Y, Jonasson JG, Jones CD, Jones DR, Jones DTW, Jones N, Jones SJM, Jonkers J, Ju YS, Juhl H, Jung J, Juul M, Juul RI, Juul S, Jäger N, Kabbe R, Kahles A, Kahraman A, Kaiser VB, Kakavand H, Kalimuthu S, von Kalle C, Kang KJ, Karaszi K, Karlan B, Karlić R, Karsch D, Kasaian K, Kassahn KS, Katai H, Kato M, Katoh H, Kawakami Y, Kay JD, Kazakoff SH, Kazanov MD, Keays M, Kebebew E, Kefford RF, Kellis M, Kench JG, Kennedy CJ, Kerssemakers JNA, Khoo D, Khoo V, Khuntikeo N, Khurana E, Kilpinen H, Kim HK, Kim HL, Kim HY, Kim H, Kim J, Kim J, Kim JK, Kim Y, King TA, Klapper W, Kleinheinz K, Klimczak LJ, Knappskog S, Kneba M, Knoppers BM, Koh Y, Komorowski J, Komura D, Komura M, Kong G, Kool M, Korbel JO, Korchina V, Korshunov A, Koscher M, Koster R, Kote-Jarai Z, Koures A, Kovacevic M, Kremeyer B, Kretzmer H, Kreuz M, Krishnamurthy S, Kube D, Kumar K, Kumar P, Kumar S, Kumar Y, Kundra R, Kübler K, Küppers R, Lagergren J, Lai PH, Laird PW, Lakhani SR, Lalansingh CM, Lalonde E, Lamaze FC, Lambert A, Lander E, Landgraf P, Landoni L, Langerød A, Lanzós A, Larsimont D, Larsson E, Lathrop M, Lau LMS, Lawerenz C, Lawlor RT, Lawrence MS, Lazar AJ, Lazic AM, Le X, Lee D, Lee D, Lee EA, Lee HJ, Lee JJK, Lee JY, Lee J, Lee MTM, Lee-Six H, Lehmann KV, Lehrach H, Lenze D, Leonard CR, Leongamornlert DA, Leshchiner I, Letourneau L, Letunic I, Levine DA, Lewis L, Ley T, Li C, Li CH, Li HI, Li J, Li L, Li S, Li S, Li X, Li X, Li X, Li Y, Liang H, Liang SB, Lichter P, Lin P, Lin Z, Linehan WM, Lingjærde OC, Liu D, Liu EM, Liu FFF, Liu F, Liu J, Liu X, Livingstone J, Livitz D, Livni N, Lochovsky L, Loeffler M, Long GV, Lopez-Guillermo A, Lou S, Louis DN, Lovat LB, Lu Y, Lu YJ, Lu Y, Luchini C, Lungu I, Luo X, Luxton HJ, Lynch AG, Lype L, López C, López-Otín C, Ma EZ, Ma Y, MacGrogan G, MacRae S, Macintyre G, Madsen T, Maejima K, Mafficini A, Maglinte DT, Maitra A, Majumder PP, Malcovati L, Malikic S, Malleo G, Mann GJ, Mantovani-Löffler L, Marchal K, Marchegiani G, Mardis ER, Margolin AA, Marin MG, Markowetz F, Markowski J, Marks J, Marques-Bonet T, Marra MA, Marsden L, Martens JWM, Martin S, Martin-Subero JI, Martincorena I, Martinez-Fundichely A, Maruvka YE, Mashl RJ, Massie CE, Matthew TJ, Matthews L, Mayer E, Mayes S, Mayo M, Mbabaali F, McCune K, McDermott U, McGillivray PD, McLellan MD, McPherson JD, McPherson JR, McPherson TA, Meier SR, Meng A, Meng S, Menzies A, Merrett ND, Merson S, Meyerson M, Meyerson W, Mieczkowski PA, Mihaiescu GL, Mijalkovic S, Mikkelsen T, Milella M, Mileshkin L, Miller CA, Miller DK, Miller JK, Mills GB, Milovanovic A, Minner S, Miotto M, Arnau GM, Mirabello L, Mitchell C, Mitchell TJ, Miyano S, Miyoshi N, Mizuno S, Molnár-Gábor F, Moore MJ, Moore RA, Morganella S, Morris QD, Morrison C, Mose LE, Moser CD, Muiños F, Mularoni L, Mungall AJ, Mungall K, Musgrove EA, Mustonen V, Mutch D, Muyas F, Muzny DM, Muñoz A, Myers J, Myklebost O, Möller P, Nagae G, Nagrial AM, Nahal-Bose HK, Nakagama H, Nakagawa H, Nakamura H, Nakamura T, Nakano K, Nandi T, Nangalia J, Nastic M, Navarro A, Navarro FCP, Neal DE, Nettekoven G, Newell F, Newhouse SJ, Newton Y, Ng AWT, Ng A, Nicholson J, Nicol D, Nie Y, Nielsen GP, Nielsen MM, Nik-Zainal S, Noble MS, Nones K, Northcott PA, Notta F, O’Connor BD, O’Donnell P, O’Donovan M, O’Meara S, O’Neill BP, O’Neill JR, Ocana D, Ochoa A, Oesper L, Ogden C, Ohdan H, Ohi K, Ohno-Machado L, Oien KA, Ojesina AI, Ojima H, Okusaka T, Omberg L, Ong CK, Ossowski S, Ott G, Ouellette BFF, P’ng C, Paczkowska M, Paiella S, Pairojkul C, Pajic M, Pan-Hammarström Q, Papaemmanuil E, Papatheodorou I, Paramasivam N, Park JW, Park JW, Park K, Park K, Park PJ, Parker JS, Parsons SL, Pass H, Pasternack D, Pastore A, Patch AM, Pauporté I, Pea A, Pearson JV, Pedamallu CS, Pedersen JS, Pederzoli P, Peifer M, Pennell NA, Perou CM, Perry MD, Petersen GM, Peto M, Petrelli N, Petryszak R, Pfister SM, Phillips M, Pich O, Pickett HA, Pihl TD, Pillay N, Pinder S, Pinese M, Pinho AV. Author Correction: The evolutionary history of 2,658 cancers. Nature 2023; 614:E42. [PMID: 36697833 PMCID: PMC9931577 DOI: 10.1038/s41586-022-05601-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
- Moritz Gerstung
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK. .,European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany. .,Wellcome Sanger Institute, Cambridge, UK.
| | - Clemency Jolly
- grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK
| | - Ignaty Leshchiner
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Stefan C. Dentro
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK ,grid.4991.50000 0004 1936 8948Big Data Institute, University of Oxford, Oxford, UK
| | - Santiago Gonzalez
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK
| | - Daniel Rosebrock
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Thomas J. Mitchell
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934University of Cambridge, Cambridge, UK
| | - Yulia Rubanova
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | - Pavana Anur
- grid.5288.70000 0000 9758 5690Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR USA
| | - Kaixian Yu
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Maxime Tarabichi
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK
| | - Amit Deshwar
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | - Jeff Wintersinger
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | - Kortine Kleinheinz
- grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany ,grid.7700.00000 0001 2190 4373Heidelberg University, Heidelberg, Germany
| | - Ignacio Vázquez-García
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934University of Cambridge, Cambridge, UK
| | - Kerstin Haase
- grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK
| | - Lara Jerman
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK ,grid.8954.00000 0001 0721 6013University of Ljubljana, Ljubljana, Slovenia
| | - Subhajit Sengupta
- grid.240372.00000 0004 0400 4439NorthShore University HealthSystem, Evanston, IL USA
| | - Geoff Macintyre
- grid.5335.00000000121885934Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Salem Malikic
- grid.61971.380000 0004 1936 7494Simon Fraser University, Burnaby, British Columbia Canada ,grid.412541.70000 0001 0684 7796Vancouver Prostate Centre, Vancouver, British Columbia Canada
| | - Nilgun Donmez
- grid.61971.380000 0004 1936 7494Simon Fraser University, Burnaby, British Columbia Canada ,grid.412541.70000 0001 0684 7796Vancouver Prostate Centre, Vancouver, British Columbia Canada
| | - Dimitri G. Livitz
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Marek Cmero
- grid.1008.90000 0001 2179 088XUniversity of Melbourne, Melbourne, Victoria Australia ,grid.1042.70000 0004 0432 4889Walter and Eliza Hall Institute, Melbourne, Victoria Australia
| | - Jonas Demeulemeester
- grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK ,grid.5596.f0000 0001 0668 7884University of Leuven, Leuven, Belgium
| | - Steven Schumacher
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Yu Fan
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Xiaotong Yao
- grid.5386.8000000041936877XWeill Cornell Medicine, New York, NY USA ,grid.429884.b0000 0004 1791 0895New York Genome Center, New York, NY USA
| | - Juhee Lee
- grid.205975.c0000 0001 0740 6917University of California Santa Cruz, Santa Cruz, CA USA
| | - Matthias Schlesner
- grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Paul C. Boutros
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.419890.d0000 0004 0626 690XOntario Institute for Cancer Research, Toronto, Ontario Canada ,grid.19006.3e0000 0000 9632 6718University of California, Los Angeles, CA USA
| | - David D. Bowtell
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, Melbourne, Victoria Australia
| | - Hongtu Zhu
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Gad Getz
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.32224.350000 0004 0386 9924Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA USA ,grid.32224.350000 0004 0386 9924Department of Pathology, Massachusetts General Hospital, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | - Marcin Imielinski
- grid.5386.8000000041936877XWeill Cornell Medicine, New York, NY USA ,grid.429884.b0000 0004 1791 0895New York Genome Center, New York, NY USA
| | - Rameen Beroukhim
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA
| | - S. Cenk Sahinalp
- grid.412541.70000 0001 0684 7796Vancouver Prostate Centre, Vancouver, British Columbia Canada ,grid.411377.70000 0001 0790 959XIndiana University, Bloomington, IN USA
| | - Yuan Ji
- grid.240372.00000 0004 0400 4439NorthShore University HealthSystem, Evanston, IL USA ,grid.170205.10000 0004 1936 7822The University of Chicago, Chicago, IL USA
| | - Martin Peifer
- grid.6190.e0000 0000 8580 3777University of Cologne, Cologne, Germany
| | - Florian Markowetz
- grid.5335.00000000121885934Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Ville Mustonen
- grid.7737.40000 0004 0410 2071University of Helsinki, Helsinki, Finland
| | - Ke Yuan
- grid.5335.00000000121885934Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK ,grid.8756.c0000 0001 2193 314XUniversity of Glasgow, Glasgow, UK
| | - Wenyi Wang
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Quaid D. Morris
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | | | - Paul T. Spellman
- grid.5288.70000 0000 9758 5690Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR USA
| | - David C. Wedge
- grid.4991.50000 0004 1936 8948Big Data Institute, University of Oxford, Oxford, UK ,grid.454382.c0000 0004 7871 7212Oxford NIHR Biomedical Research Centre, Oxford, UK
| | - Peter Van Loo
- The Francis Crick Institute, London, UK. .,University of Leuven, Leuven, Belgium.
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Calabrese C, Davidson NR, Demircioğlu D, Fonseca NA, He Y, Kahles A, Lehmann KV, Liu F, Shiraishi Y, Soulette CM, Urban L, Greger L, Li S, Liu D, Perry MD, Xiang Q, Zhang F, Zhang J, Bailey P, Erkek S, Hoadley KA, Hou Y, Huska MR, Kilpinen H, Korbel JO, Marin MG, Markowski J, Nandi T, Pan-Hammarström Q, Pedamallu CS, Siebert R, Stark SG, Su H, Tan P, Waszak SM, Yung C, Zhu S, Awadalla P, Creighton CJ, Meyerson M, Ouellette BFF, Wu K, Yang H, Brazma A, Brooks AN, Göke J, Rätsch G, Schwarz RF, Stegle O, Zhang Z, Wu K, Yang H, Fonseca NA, Kahles A, Lehmann KV, Urban L, Soulette CM, Shiraishi Y, Liu F, He Y, Demircioğlu D, Davidson NR, Calabrese C, Zhang J, Perry MD, Xiang Q, Greger L, Li S, Liu D, Stark SG, Zhang F, Amin SB, Bailey P, Chateigner A, Cortés-Ciriano I, Craft B, Erkek S, Frenkel-Morgenstern M, Goldman M, Hoadley KA, Hou Y, Huska MR, Khurana E, Kilpinen H, Korbel JO, Lamaze FC, Li C, Li X, Li X, Liu X, Marin MG, Markowski J, Nandi T, Nielsen MM, Ojesina AI, Pan-Hammarström Q, 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KH, Busanovich J, Bustamante CD, Butler AP, Butte AJ, Byrne NJ, Børresen-Dale AL, Caesar-Johnson SJ, Cafferkey A, Cahill D, Calabrese C, Caldas C, Calvo F, Camacho N, Campbell PJ, Campo E, Cantù C, Cao S, Carey TE, Carlevaro-Fita J, Carlsen R, Cataldo I, Cazzola M, Cebon J, Cerfolio R, Chadwick DE, Chakravarty D, Chalmers D, Chan CWY, Chan K, Chan-Seng-Yue M, Chandan VS, Chang DK, Chanock SJ, Chantrill LA, Chateigner A, Chatterjee N, Chayama K, Chen HW, Chen J, Chen K, Chen Y, Chen Z, Cherniack AD, Chien J, Chiew YE, Chin SF, Cho J, Cho S, Choi JK, Choi W, Chomienne C, Chong Z, Choo SP, Chou A, Christ AN, Christie EL, Chuah E, Cibulskis C, Cibulskis K, Cingarlini S, Clapham P, Claviez A, Cleary S, Cloonan N, Cmero M, Collins CC, Connor AA, Cooke SL, Cooper CS, Cope L, Corbo V, Cordes MG, Cordner SM, Cortés-Ciriano I, Covington K, Cowin PA, Craft B, Craft D, Creighton CJ, Cun Y, Curley E, Cutcutache I, Czajka K, Czerniak B, Dagg RA, Danilova L, Davi MV, Davidson NR, Davies H, Davis IJ, 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Author Correction: Genomic basis for RNA alterations in cancer. Nature 2023; 614:E37. [PMID: 36697831 PMCID: PMC9931574 DOI: 10.1038/s41586-022-05596-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
| | - Claudia Calabrese
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Natalie R. Davidson
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.5386.8000000041936877XWeill Cornell Medical College, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Deniz Demircioğlu
- grid.4280.e0000 0001 2180 6431National University of Singapore, Singapore, Singapore ,grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore
| | - Nuno A. Fonseca
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Yao He
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
| | - André Kahles
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Kjong-Van Lehmann
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Fenglin Liu
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
| | - Yuichi Shiraishi
- grid.26999.3d0000 0001 2151 536XThe University of Tokyo, Minato-ku, Japan
| | - Cameron M. Soulette
- grid.205975.c0000 0001 0740 6917University of California, Santa Cruz, Santa Cruz, CA USA
| | - Lara Urban
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Liliana Greger
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Siliang Li
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Dongbing Liu
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Marc D. Perry
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada ,grid.266102.10000 0001 2297 6811University of California, San Francisco, San Francisco, CA USA
| | - Qian Xiang
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Fan Zhang
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
| | - Junjun Zhang
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Peter Bailey
- grid.8756.c0000 0001 2193 314XUniversity of Glasgow, Glasgow, UK
| | - Serap Erkek
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Katherine A. Hoadley
- grid.10698.360000000122483208The University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Yong Hou
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Matthew R. Huska
- grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany
| | - Helena Kilpinen
- grid.83440.3b0000000121901201University College London, London, UK
| | - Jan O. Korbel
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Maximillian G. Marin
- grid.205975.c0000 0001 0740 6917University of California, Santa Cruz, Santa Cruz, CA USA
| | - Julia Markowski
- grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany
| | - Tannistha Nandi
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore
| | - Qiang Pan-Hammarström
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.4714.60000 0004 1937 0626Karolinska Institutet, Stockholm, Sweden
| | - Chandra Sekhar Pedamallu
- grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | - Reiner Siebert
- grid.410712.10000 0004 0473 882XUlm University and Ulm University Medical Center, Ulm, Germany
| | - Stefan G. Stark
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Hong Su
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Patrick Tan
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore ,grid.428397.30000 0004 0385 0924Duke-NUS Medical School, Singapore, Singapore
| | - Sebastian M. Waszak
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Christina Yung
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Shida Zhu
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Philip Awadalla
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada ,grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada
| | - Chad J. Creighton
- grid.39382.330000 0001 2160 926XBaylor College of Medicine, Houston, TX USA
| | - Matthew Meyerson
- grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | | | - Kui Wu
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Huanming Yang
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China
| | | | - Alvis Brazma
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK.
| | - Angela N. Brooks
- grid.205975.c0000 0001 0740 6917University of California, Santa Cruz, Santa Cruz, CA USA ,grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA
| | - Jonathan Göke
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore ,grid.410724.40000 0004 0620 9745National Cancer Centre Singapore, Singapore, Singapore
| | - Gunnar Rätsch
- ETH Zurich, Zurich, Switzerland. .,Memorial Sloan Kettering Cancer Center, New York, NY, USA. .,Weill Cornell Medical College, New York, NY, USA. .,SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland. .,University Hospital Zurich, Zurich, Switzerland.
| | - Roland F. Schwarz
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK ,grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), partner site Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Oliver Stegle
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK ,grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Zemin Zhang
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
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Aaltonen LA, Abascal F, Abeshouse A, Aburatani H, Adams DJ, Agrawal N, Ahn KS, Ahn SM, Aikata H, Akbani R, Akdemir KC, Al-Ahmadie H, Al-Sedairy ST, Al-Shahrour F, Alawi M, Albert M, Aldape K, Alexandrov LB, Ally A, Alsop K, Alvarez EG, Amary F, Amin SB, Aminou B, Ammerpohl O, Anderson MJ, Ang Y, Antonello D, Anur P, Aparicio S, Appelbaum EL, Arai Y, Aretz A, Arihiro K, Ariizumi SI, Armenia J, Arnould L, Asa S, Assenov Y, Atwal G, Aukema S, Auman JT, Aure MRR, Awadalla P, Aymerich M, Bader GD, Baez-Ortega A, Bailey MH, Bailey PJ, Balasundaram M, Balu S, Bandopadhayay P, Banks RE, Barbi S, Barbour AP, Barenboim J, Barnholtz-Sloan J, Barr H, Barrera E, Bartlett J, Bartolome J, Bassi C, Bathe OF, Baumhoer D, Bavi P, Baylin SB, Bazant W, Beardsmore D, Beck TA, Behjati S, Behren A, Niu B, Bell C, Beltran S, Benz C, Berchuck A, Bergmann AK, Bergstrom EN, Berman BP, Berney DM, Bernhart SH, Beroukhim R, Berrios M, Bersani S, Bertl J, Betancourt M, Bhandari V, Bhosle SG, Biankin AV, Bieg M, 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Pan-cancer analysis of whole genomes. Nature 2020; 578:82-93. [PMID: 32025007 PMCID: PMC7025898 DOI: 10.1038/s41586-020-1969-6] [Citation(s) in RCA: 1435] [Impact Index Per Article: 358.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2018] [Accepted: 12/11/2019] [Indexed: 02/07/2023]
Abstract
Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.
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4
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Rheinbay E, Nielsen MM, Abascal F, Wala JA, Shapira O, Tiao G, Hornshøj H, Hess JM, Juul RI, Lin Z, Feuerbach L, Sabarinathan R, Madsen T, Kim J, Mularoni L, Shuai S, Lanzós A, Herrmann C, Maruvka YE, Shen C, Amin SB, Bandopadhayay P, Bertl J, Boroevich KA, Busanovich J, Carlevaro-Fita J, Chakravarty D, Chan CWY, Craft D, Dhingra P, Diamanti K, Fonseca NA, Gonzalez-Perez A, Guo Q, Hamilton MP, Haradhvala NJ, Hong C, Isaev K, Johnson TA, Juul M, Kahles A, Kahraman A, Kim Y, Komorowski J, Kumar K, Kumar S, Lee D, Lehmann KV, Li Y, Liu EM, Lochovsky L, Park K, Pich O, Roberts ND, Saksena G, Schumacher SE, Sidiropoulos N, Sieverling L, Sinnott-Armstrong N, Stewart C, Tamborero D, Tubio JMC, Umer HM, Uusküla-Reimand L, Wadelius C, Wadi L, Yao X, Zhang CZ, Zhang J, Haber JE, Hobolth A, Imielinski M, Kellis M, Lawrence MS, von Mering C, Nakagawa H, Raphael BJ, Rubin MA, Sander C, Stein LD, Stuart JM, Tsunoda T, Wheeler DA, Johnson R, Reimand J, Gerstein M, Khurana E, Campbell PJ, López-Bigas N, Weischenfeldt J, Beroukhim R, Martincorena I, Pedersen JS, Getz G. Analyses of non-coding somatic drivers in 2,658 cancer whole genomes. Nature 2020; 578:102-111. [PMID: 32025015 PMCID: PMC7054214 DOI: 10.1038/s41586-020-1965-x] [Citation(s) in RCA: 332] [Impact Index Per Article: 83.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Accepted: 12/02/2019] [Indexed: 01/28/2023]
Abstract
The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.
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Affiliation(s)
- Esther Rheinbay
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Morten Muhlig Nielsen
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | | | - Jeremiah A Wala
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA, USA
| | - Ofer Shapira
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Grace Tiao
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Henrik Hornshøj
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | - Julian M Hess
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Randi Istrup Juul
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | - Ziao Lin
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard University, Cambridge, MA, USA
| | - Lars Feuerbach
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Radhakrishnan Sabarinathan
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Research Program on Biomedical Informatics, Universitat Pompeu Fabra, Barcelona, Spain
| | - Tobias Madsen
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | - Jaegil Kim
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Loris Mularoni
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Research Program on Biomedical Informatics, Universitat Pompeu Fabra, Barcelona, Spain
| | - Shimin Shuai
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Andrés Lanzós
- Department for BioMedical Research, University of Bern, Bern, Switzerland
- Graduate School of Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
- Department of Medical Oncology, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Carl Herrmann
- Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Bioquant Center, Institute of Pharmacy and Molecular Biotechnology, University of Heidelberg, Heidelberg, Germany
| | - Yosef E Maruvka
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA
| | - Ciyue Shen
- Department of Cell Biology, Harvard Medical School, Boston, MA, USA
- cBio Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Samirkumar B Amin
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Graduate Program in Structural and Computational Biology and Molecular Biophysics, Baylor College of Medicine, Houston, TX, USA
| | - Pratiti Bandopadhayay
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Johanna Bertl
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | - Keith A Boroevich
- Laboratory for Medical Science Mathematics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - John Busanovich
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Joana Carlevaro-Fita
- Department for BioMedical Research, University of Bern, Bern, Switzerland
- Graduate School of Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
- Department of Medical Oncology, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Dimple Chakravarty
- Department of Genitourinary Medical Oncology - Research, Division of Cancer Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Urology, Icahn school of Medicine at Mount Sinai, New York, NY, USA
| | - Calvin Wing Yiu Chan
- Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - David Craft
- Department of Radiation Oncology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Priyanka Dhingra
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | - Klev Diamanti
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Nuno A Fonseca
- European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK
| | - Abel Gonzalez-Perez
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Research Program on Biomedical Informatics, Universitat Pompeu Fabra, Barcelona, Spain
| | - Qianyun Guo
- Bioinformatics Research Centre (BiRC), Aarhus University, Aarhus, Denmark
| | - Mark P Hamilton
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA
| | - Nicholas J Haradhvala
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA
| | - Chen Hong
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Keren Isaev
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Todd A Johnson
- Laboratory for Medical Science Mathematics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Malene Juul
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | - Andre Kahles
- Division of Computational Biology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Abdullah Kahraman
- Institute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland
| | - Youngwook Kim
- Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Jan Komorowski
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
- Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland
| | - Kiran Kumar
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Sushant Kumar
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Donghoon Lee
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Kjong-Van Lehmann
- Division of Computational Biology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Yilong Li
- SBGD Inc, Cambridge, MA, USA
- Department of Haematology, University of Cambridge, Cambridge, UK
| | - Eric Minwei Liu
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | - Lucas Lochovsky
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Keunchil Park
- Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Oriol Pich
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Research Program on Biomedical Informatics, Universitat Pompeu Fabra, Barcelona, Spain
| | - Nicola D Roberts
- Department of Haematology, University of Cambridge, Cambridge, UK
| | - Gordon Saksena
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Steven E Schumacher
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Nikos Sidiropoulos
- Biotech Research & Innovation Centre (BRIC), The Finsen Laboratory, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Lina Sieverling
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | | | - Chip Stewart
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - David Tamborero
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Research Program on Biomedical Informatics, Universitat Pompeu Fabra, Barcelona, Spain
| | - Jose M C Tubio
- Department of Zoology, Genetics and Physical Anthropology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- The Biomedical Research Centre (CINBIO), Universidade de Vigo, Vigo, Spain
| | - Husen M Umer
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
- Department of Oncology-Pathology, Science for Life Laboratory, Karolinska Institute, Stockholm, Sweden
| | - Liis Uusküla-Reimand
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, Ontario, Canada
- Department of Gene Technology, Tallinn University of Technology, Tallinn, Estonia
| | - Claes Wadelius
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Lina Wadi
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | | | - Cheng-Zhong Zhang
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Jing Zhang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - James E Haber
- Department of Biology and Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, MA, USA
| | - Asger Hobolth
- Bioinformatics Research Centre (BiRC), Aarhus University, Aarhus, Denmark
| | - Marcin Imielinski
- New York Genome Center, New York, NY, USA
- Department of Pathology and Laboratory Medicine, and Englander Institute for Precision Medicine, and Institute for Computational Biomedicine, and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Manolis Kellis
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA
| | - Michael S Lawrence
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA
| | - Christian von Mering
- Institute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland
| | - Hidewaki Nakagawa
- Laboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Tokyo, Japan
| | - Benjamin J Raphael
- Department of Computer Science, Princeton University, Princeton, NJ, USA
| | - Mark A Rubin
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
- Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Chris Sander
- Department of Cell Biology, Harvard Medical School, Boston, MA, USA
- cBio Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Lincoln D Stein
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Joshua M Stuart
- Center for Biomolecular Science and Engineering, University of California at Santa Cruz, Santa Cruz, CA, USA
| | - Tatsuhiko Tsunoda
- Laboratory for Medical Science Mathematics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan
- Laboratory for Medical Science Mathematics, Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo, Japan
| | - David A Wheeler
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Rory Johnson
- Department for BioMedical Research, University of Bern, Bern, Switzerland
- Department of Medical Oncology, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Jüri Reimand
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
- Department of Computer Science, Yale University, New Haven, CT, USA
| | - Ekta Khurana
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Peter J Campbell
- Wellcome Trust Sanger Institute, Hinxton, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
| | - Núria López-Bigas
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Research Program on Biomedical Informatics, Universitat Pompeu Fabra, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Joachim Weischenfeldt
- Biotech Research & Innovation Centre (BRIC), The Finsen Laboratory, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
| | - Rameen Beroukhim
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA, USA.
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
| | | | - Jakob Skou Pedersen
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark.
- Bioinformatics Research Centre (BiRC), Aarhus University, Aarhus, Denmark.
| | - Gad Getz
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Department of Pathology, Massachusetts General Hospital, Boston, MA, USA.
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5
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Madsen T, Świtnicki M, Juul M, Pedersen JS. EBADIMEX: an empirical Bayes approach to detect joint differential expression and methylation and to classify samples. Stat Appl Genet Mol Biol 2019; 18:/j/sagmb.ahead-of-print/sagmb-2018-0050/sagmb-2018-0050.xml. [PMID: 31734658 DOI: 10.1515/sagmb-2018-0050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
DNA methylation and gene expression are interdependent and both implicated in cancer development and progression, with many individual biomarkers discovered. A joint analysis of the two data types can potentially lead to biological insights that are not discoverable with separate analyses. To optimally leverage the joint data for identifying perturbed genes and classifying clinical cancer samples, it is important to accurately model the interactions between the two data types. Here, we present EBADIMEX for jointly identifying differential expression and methylation and classifying samples. The moderated t-test widely used with empirical Bayes priors in current differential expression methods is generalised to a multivariate setting by developing: (1) a moderated Welch t-test for equality of means with unequal variances; (2) a moderated F-test for equality of variances; and (3) a multivariate test for equality of means with equal variances. This leads to parametric models with prior distributions for the parameters, which allow fast evaluation and robust analysis of small data sets. EBADIMEX is demonstrated on simulated data as well as a large breast cancer (BRCA) cohort from TCGA. We show that the use of empirical Bayes priors and moderated tests works particularly well on small data sets.
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Affiliation(s)
- Tobias Madsen
- Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, DK-8200 Aarhus N, Denmark.,Bioinformatics Research Centre, Aarhus University, C.F. Møllers Alle 8 DK-8000 Aarhus C, Denmark
| | - Michał Świtnicki
- Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, DK-8200 Aarhus N, Denmark
| | - Malene Juul
- Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, DK-8200 Aarhus N, Denmark.,Bioinformatics Research Centre, Aarhus University, C.F. Møllers Alle 8 DK-8000 Aarhus C, Denmark
| | - Jakob Skou Pedersen
- Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, DK-8200 Aarhus N, Denmark.,Bioinformatics Research Centre, Aarhus University, C.F. Møllers Alle 8 DK-8000 Aarhus C, Denmark
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6
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Juul M, Madsen T, Guo Q, Bertl J, Hobolth A, Kellis M, Pedersen JS. ncdDetect2: improved models of the site-specific mutation rate in cancer and driver detection with robust significance evaluation. Bioinformatics 2019; 35:189-199. [PMID: 29945188 PMCID: PMC6330011 DOI: 10.1093/bioinformatics/bty511] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Accepted: 06/24/2018] [Indexed: 01/22/2023] Open
Abstract
Motivation Understanding the mutational processes that act during cancer development is a key topic of cancer biology. Nevertheless, much remains to be learned, as a complex interplay of processes with dependencies on a range of genomic features creates highly heterogeneous cancer genomes. Accurate driver detection relies on unbiased models of the mutation rate that also capture rate variation from uncharacterized sources. Results Here, we analyse patterns of observed-to-expected mutation counts across 505 whole cancer genomes, and find that genomic features missing from our mutation-rate model likely operate on a megabase length scale. We extend our site-specific model of the mutation rate to include the additional variance from these sources, which leads to robust significance evaluation of candidate cancer drivers. We thus present ncdDetect v.2, with greatly improved cancer driver detection specificity. Finally, we show that ranking candidates by their posterior mean value of their effect sizes offers an equivalent and more computationally efficient alternative to ranking by their P-values. Availability and implementation ncdDetect v.2 is implemented as an R-package and is freely available at http://github.com/TobiasMadsen/ncdDetect2 Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Malene Juul
- Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, DK-8200 Aarhus N, Denmark.,Bioinformatics Research Centre, Aarhus University, C.F. Mollers Alle 8, DK-8000 Aarhus C, Denmark
| | - Tobias Madsen
- Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, DK-8200 Aarhus N, Denmark.,Bioinformatics Research Centre, Aarhus University, C.F. Mollers Alle 8, DK-8000 Aarhus C, Denmark
| | - Qianyun Guo
- Bioinformatics Research Centre, Aarhus University, C.F. Mollers Alle 8, DK-8000 Aarhus C, Denmark
| | - Johanna Bertl
- Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, DK-8200 Aarhus N, Denmark
| | - Asger Hobolth
- Bioinformatics Research Centre, Aarhus University, C.F. Mollers Alle 8, DK-8000 Aarhus C, Denmark
| | - Manolis Kellis
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
| | - Jakob Skou Pedersen
- Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, DK-8200 Aarhus N, Denmark.,Bioinformatics Research Centre, Aarhus University, C.F. Mollers Alle 8, DK-8000 Aarhus C, Denmark
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7
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Bertl J, Guo Q, Juul M, Besenbacher S, Nielsen MM, Hornshøj H, Pedersen JS, Hobolth A. A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data. BMC Bioinformatics 2018; 19:147. [PMID: 29673314 PMCID: PMC5909259 DOI: 10.1186/s12859-018-2141-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Accepted: 03/27/2018] [Indexed: 01/02/2023] Open
Abstract
Background Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration. Results To take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures. Conclusion We find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model for the mutational process; regions that deviate from the null model are candidates for elements that drive cancer development. Electronic supplementary material The online version of this article (10.1186/s12859-018-2141-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Johanna Bertl
- Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, Aarhus N, DK-8200, Denmark.
| | - Qianyun Guo
- Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, Aarhus N, DK-8200, Denmark
| | - Malene Juul
- Bioinformatics Research Centre, Aarhus University, C.F. Mollers Alle 8, Aarhus C, DK-8000, Denmark
| | - Søren Besenbacher
- Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, Aarhus N, DK-8200, Denmark
| | - Morten Muhlig Nielsen
- Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, Aarhus N, DK-8200, Denmark
| | - Henrik Hornshøj
- Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, Aarhus N, DK-8200, Denmark
| | - Jakob Skou Pedersen
- Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, Aarhus N, DK-8200, Denmark
| | - Asger Hobolth
- Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, Aarhus N, DK-8200, Denmark
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Juul M, Bertl J, Guo Q, Nielsen MM, Świtnicki M, Hornshøj H, Madsen T, Hobolth A, Pedersen JS. Non-coding cancer driver candidates identified with a sample- and position-specific model of the somatic mutation rate. eLife 2017; 6. [PMID: 28362259 PMCID: PMC5440169 DOI: 10.7554/elife.21778] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2016] [Accepted: 03/14/2017] [Indexed: 02/06/2023] Open
Abstract
Non-coding mutations may drive cancer development. Statistical detection of non-coding driver regions is challenged by a varying mutation rate and uncertainty of functional impact. Here, we develop a statistically founded non-coding driver-detection method, ncdDetect, which includes sample-specific mutational signatures, long-range mutation rate variation, and position-specific impact measures. Using ncdDetect, we screened non-coding regulatory regions of protein-coding genes across a pan-cancer set of whole-genomes (n = 505), which top-ranked known drivers and identified new candidates. For individual candidates, presence of non-coding mutations associates with altered expression or decreased patient survival across an independent pan-cancer sample set (n = 5454). This includes an antigen-presenting gene (CD1A), where 5'UTR mutations correlate significantly with decreased survival in melanoma. Additionally, mutations in a base-excision-repair gene (SMUG1) correlate with a C-to-T mutational-signature. Overall, we find that a rich model of mutational heterogeneity facilitates non-coding driver identification and integrative analysis points to candidates of potential clinical relevance.
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Affiliation(s)
- Malene Juul
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | - Johanna Bertl
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | - Qianyun Guo
- Bioinformatics Research Centre (BiRC), Aarhus University, Aarhus, Denmark
| | - Morten Muhlig Nielsen
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | - Michał Świtnicki
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | - Henrik Hornshøj
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | - Tobias Madsen
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark
| | - Asger Hobolth
- Bioinformatics Research Centre (BiRC), Aarhus University, Aarhus, Denmark
| | - Jakob Skou Pedersen
- Department of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark.,Bioinformatics Research Centre (BiRC), Aarhus University, Aarhus, Denmark
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Świtnicki MP, Juul M, Madsen T, Sørensen KD, Pedersen JS. PINCAGE: probabilistic integration of cancer genomics data for perturbed gene identification and sample classification. Bioinformatics 2016; 32:1353-65. [PMID: 26740525 DOI: 10.1093/bioinformatics/btv758] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2015] [Accepted: 12/17/2015] [Indexed: 02/02/2023] Open
Abstract
MOTIVATION Cancer development and progression is driven by a complex pattern of genomic and epigenomic perturbations. Both types of perturbations can affect gene expression levels and disease outcome. Integrative analysis of cancer genomics data may therefore improve detection of perturbed genes and prediction of disease state. As different data types are usually dependent, analysis based on independence assumptions will make inefficient use of the data and potentially lead to false conclusions. MODEL Here, we present PINCAGE (Probabilistic INtegration of CAncer GEnomics data), a method that uses probabilistic integration of cancer genomics data for combined evaluation of RNA-seq gene expression and 450k array DNA methylation measurements of promoters as well as gene bodies. It models the dependence between expression and methylation using modular graphical models, which also allows future inclusion of additional data types. RESULTS We apply our approach to a Breast Invasive Carcinoma dataset from The Cancer Genome Atlas consortium, which includes 82 adjacent normal and 730 cancer samples. We identify new biomarker candidates of breast cancer development (PTF1A, RABIF, RAG1AP1, TIMM17A, LOC148145) and progression (SERPINE3, ZNF706). PINCAGE discriminates better between normal and tumour tissue and between progressing and non-progressing tumours in comparison with established methods that assume independence between tested data types, especially when using evidence from multiple genes. Our method can be applied to any type of cancer or, more generally, to any genomic disease for which sufficient amount of molecular data is available. AVAILABILITY AND IMPLEMENTATION R scripts available at http://moma.ki.au.dk/prj/pincage/ CONTACT : michal.switnicki@clin.au.dk or jakob.skou@clin.au.dk SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | | | | | | | - Jakob S Pedersen
- Department of Molecular Medicine (MOMA) Bioinformatics Research Centre (BiRC), Aarhus University, Aarhus, 8000, Denmark
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Nordentoft I, Lamy P, Birkenkamp-Demtröder K, Shumansky K, Vang S, Hornshøj H, Juul M, Villesen P, Hedegaard J, Roth A, Thorsen K, Høyer S, Borre M, Reinert T, Fristrup N, Dyrskjøt L, Shah S, Pedersen JS, Ørntoft TF. Mutational context and diverse clonal development in early and late bladder cancer. Cell Rep 2014; 7:1649-1663. [PMID: 24835989 DOI: 10.1016/j.celrep.2014.04.038] [Citation(s) in RCA: 105] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2013] [Revised: 04/02/2014] [Accepted: 04/21/2014] [Indexed: 11/16/2022] Open
Abstract
Bladder cancer (or urothelial cell carcinoma [UCC]) is characterized by field disease (malignant alterations in surrounding mucosa) and frequent recurrences. Whole-genome, exome, and transcriptome sequencing of 38 tumors, including four metachronous tumor pairs and 20 superficial tumors, identified an APOBEC mutational signature in one-third. This was biased toward the sense strand, correlated with mean expression level, and clustered near breakpoints. A>G mutations were up to eight times more frequent on the sense strand (p<0.002) in [ACG]AT contexts. The patient-specific APOBEC signature was negatively correlated to repair-gene expression and was not related to clinicopathological parameters. Mutations in gene families and single genes were related to tumor stage, and expression of chromatin modifiers correlated with survival. Evolutionary and subclonal analyses of early/late tumor pairs showed a unitary origin, and discrete tumor clones contained mutated cancer genes. The ancestral clones contained Pik3ca/Kdm6a mutations and may reflect the field-disease mutations shared among later tumors.
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Affiliation(s)
- Iver Nordentoft
- Department of Molecular Medicine, Aarhus University Hospital, Brendstrupgaardsvej 100, 8200 Aarhus, Denmark
| | - Philippe Lamy
- Department of Molecular Medicine, Aarhus University Hospital, Brendstrupgaardsvej 100, 8200 Aarhus, Denmark
| | - Karin Birkenkamp-Demtröder
- Department of Molecular Medicine, Aarhus University Hospital, Brendstrupgaardsvej 100, 8200 Aarhus, Denmark
| | - Karey Shumansky
- BC Cancer Research Centre, 675 West 10(th) Avenue, Vancouver, BC V5T4E6, Canada
| | - Søren Vang
- Department of Molecular Medicine, Aarhus University Hospital, Brendstrupgaardsvej 100, 8200 Aarhus, Denmark
| | - Henrik Hornshøj
- Department of Molecular Medicine, Aarhus University Hospital, Brendstrupgaardsvej 100, 8200 Aarhus, Denmark
| | - Malene Juul
- Department of Molecular Medicine, Aarhus University Hospital, Brendstrupgaardsvej 100, 8200 Aarhus, Denmark
| | - Palle Villesen
- Department of Bioinformatic Research, Aarhus University, Universitetsparken, 8000 Aarhus, Denmark
| | - Jakob Hedegaard
- Department of Molecular Medicine, Aarhus University Hospital, Brendstrupgaardsvej 100, 8200 Aarhus, Denmark
| | - Andrew Roth
- BC Cancer Research Centre, 675 West 10(th) Avenue, Vancouver, BC V5T4E6, Canada
| | - Kasper Thorsen
- Department of Molecular Medicine, Aarhus University Hospital, Brendstrupgaardsvej 100, 8200 Aarhus, Denmark
| | - Søren Høyer
- Department of Pathology, Aarhus University Hospital, North Road Ringgade 8000 Aarhus, Denmark
| | - Michael Borre
- Department of Urology, Aarhus University Hospital, Brendstrupgaardsvej 100, 8200 Aarhus, Denmark
| | - Thomas Reinert
- Department of Molecular Medicine, Aarhus University Hospital, Brendstrupgaardsvej 100, 8200 Aarhus, Denmark
| | - Niels Fristrup
- Department of Urology, Aarhus University Hospital, Brendstrupgaardsvej 100, 8200 Aarhus, Denmark
| | - Lars Dyrskjøt
- Department of Molecular Medicine, Aarhus University Hospital, Brendstrupgaardsvej 100, 8200 Aarhus, Denmark
| | - Sohrab Shah
- BC Cancer Research Centre, 675 West 10(th) Avenue, Vancouver, BC V5T4E6, Canada
| | - Jakob Skou Pedersen
- Department of Molecular Medicine, Aarhus University Hospital, Brendstrupgaardsvej 100, 8200 Aarhus, Denmark
| | - Torben F Ørntoft
- Department of Molecular Medicine, Aarhus University Hospital, Brendstrupgaardsvej 100, 8200 Aarhus, Denmark.
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Prichard R, Juul M, Gazibarich G, Walker R, Salamonsen R, Kotlyar E, Keogh A, Macdonald P, Hayward C, Woodard J, Ayre P. Six-Minute Walk Distance Predicts VO2max in Patients Supported with Continuous Flow Left Ventricular Assist Devices. Heart Lung Circ 2009. [DOI: 10.1016/j.hlc.2009.05.428] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Waehre H, Amellem O, Stenwig AE, Tverå K, Juul M, Pettersen EO, Fosså SD. Deoxyribonucleic acid cytometry and histological findings before and after 125iodine implantation of primary prostate cancer. J Urol 1992; 148:838-41; discussion 841-2. [PMID: 1512835 DOI: 10.1016/s0022-5347(17)36737-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Deoxyribonucleic acid (DNA) flow cytometry and light microscopy were performed in pre-radiotherapy and post-radiotherapy biopsies obtained from the primary tumor in 31 patients with prostate cancer. Radiotherapy was applied by means of transperineal 125iodine (125I) implantation. Of the patients 21 had pretreatment biopsies and in 19 of these biopsies also were performed 1 and/or 1 1/2 years after the 125I implantation. Posttreatment biopsies were available for DNA flow cytometry in 12 additional patients without pretreatment DNA flow cytometry assessment. Of the 21 pretreatment biopsies 7 were diploid, 6 tetraploid and 8 aneuploid. All 31 posttreatment biopsies were either tetraploid (21) or aneuploid (10). All 6 pretreatment diploid tumors became tetraploid after radiotherapy. At 1 and/or 1 1/2 years after 125I implantation residual tumors were found in 28 of 31 prostatic glands. The high frequency of nondiploid DNA stemlines 1 or more years after 125I implantation and the high rate of residual tumor leave some doubt about the radiocurability of prostate cancer by the chosen radiotherapy technique.
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Affiliation(s)
- H Waehre
- Department of Surgical Oncology, Norwegian Radium Hospital, Oslo
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Jacobsen AB, Berner A, Juul M, Ous S, Pettersen EO, Fosså SD. DNA flow cytometry and neo-adjuvant chemotherapy/radiotherapy in operable muscle-invasive bladder carcinoma. A preliminary report. Eur Urol 1992; 22:316-22. [PMID: 1490510 DOI: 10.1159/000474779] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Fifty-five patients with muscle-invasive transitional cell carcinoma of the bladder were treated with preoperative cisplatin-based chemotherapy followed by radiotherapy (20 Gy within 1 week) and cystectomy. DNA flow cytometry (FCM) was performed in paraffin-embedded tissue obtained by transurethral resection immediately before therapy. Together with the T-category and histological grade, DNA ploidy and S-phase fraction (SPF) were evaluated for the ability to predict the response to chemotherapy/radiotherapy and survival: a low T-category, but neither DNA ploidy nor SPF, was predictive for the response to neo-adjuvant treatment. The T-category was not related to the patients' survival. In the Cox regression analysis, SPF was an independent prognostic parameter together with response to the precystectomy therapy. We concluded that, in spite of remaining technical problems, paraffin-embedded tissue from bladder carcinoma is suitable for DNA FCM. Contrary to the situation in superficial bladder cancer, DNA ploidy is not related to the clinical outcome in muscle-invasive bladder carcinoma treated by neo-adjuvant chemo-/radiotherapy and cystectomy. SPF seems to be a clinically worthwhile parameter with significance that has to be further studied in larger series.
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Affiliation(s)
- A B Jacobsen
- Department of Tissue Culture, Norwegian Radium Hospital, Oslo
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