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Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer
Hoadley K.A.11; Yau C.9; Hinoue T.4; Wolf D.M.1; Lazar A.J.14; Drill E.2; Shen R.2; Taylor A.M.8; Cherniack A.D.8; Thorsson V.7; Akbani R.14; Bowlby R.15; Wong C.K.16; Wiznerowicz M.12; Sanchez-Vega F.2; Robertson A.G.15; Schneider B.G.18; Lawrence M.S.8; Noushmehr H.17; Malta T.M.17; Caesar-Johnson S.J.; Demchok J.A.; Felau I.; Kasapi M.; Ferguson M.L.; Hutter C.M.; Sofia H.J.; Tarnuzzer R.; Wang Z.; Yang L.; Zenklusen J.C.; Zhang J.J.; Chudamani S.; Liu J.; Lolla L.; Naresh R.; Pihl T.; Sun Q.; Wan Y.; Wu Y.; Cho J.; DeFreitas T.; Frazer S.; Gehlenborg N.; Getz G.; Heiman D.I.; Kim J.; Lawrence M.S.; Lin P.; Meier S.; Noble M.S.; Saksena G.; Voet D.; Zhang H.; Bernard B.; Chambwe N.; Dhankani V.; Knijnenburg T.; Kramer R.; Leinonen K.; Liu Y.; Miller M.; Reynolds S.; Shmulevich I.; Thorsson V.; Zhang W.; Akbani R.; Broom B.M.; Hegde A.M.; Ju Z.; Kanchi R.S.; Korkut A.; Li J.; Liang H.; Ling S.; Liu W.; Lu Y.; Mills G.B.; Ng K.-S.; Rao A.; Ryan M.; Wang J.; Weinstein J.N.; Zhang J.; Abeshouse A.; Armenia J.; Chakravarty D.; Chatila W.K.; de Bruijn I.; Gao J.; Gross B.E.; Heins Z.J.; Kundra R.; La K.; Ladanyi M.; Luna A.; Nissan M.G.; Ochoa A.; Phillips S.M.; Reznik E.; Sanchez-Vega F.2; Sander C.; Schultz N.; Sheridan R.; Sumer S.O.; Sun Y.; Taylor B.S.; Wang J.; Zhang H.; Anur P.; Peto M.; Spellman P.; Benz C.9; Stuart J.M.; Wong C.K.; Yau C.; Hayes D.N.; Parker J.S.; Wilkerson M.D.; Ally A.; Balasundaram M.; Bowlby R.; Brooks D.; Carlsen R.; Chuah E.; Dhalla N.; Holt R.; Jones S.J.M.; Kasaian K.; Lee D.; Ma Y.; Marra M.A.; Mayo M.; Moore R.A.; Mungall A.J.; Mungall K.; Robertson A.G.; Sadeghi S.; Schein J.E.; Sipahimalani P.; Tam A.; Thiessen N.; Tse K.; Wong T.; Berger A.C.; Beroukhim R.; Cherniack A.D.; Cibulskis C.; Gabriel S.B.; Gao G.F.; Ha G.; Meyerson M.; Schumacher S.E.; Shih J.; Kucherlapati M.H.; Kucherlapati R.S.; Baylin S.; Cope L.; Danilova L.; Bootwalla M.S.; Lai P.H.; Maglinte D.T.; Van Den Berg D.J.; Weisenberger D.J.; Auman J.T.; Balu S.; Bodenheimer T.; Fan C.; Hoadley K.A.; Hoyle A.P.; Jefferys S.R.; Jones C.D.; Meng S.; Mieczkowski P.A.; Mose L.E.; Perou A.H.; Perou C.M.; Roach J.; Shi Y.; Simons J.V.; Skelly T.; Soloway M.G.; Tan D.; Veluvolu U.; Fan H.; Hinoue T.; Laird P.W.; Shen H.; Zhou W.; Bellair M.; Chang K.; Covington K.; Creighton C.J.; Dinh H.; Doddapaneni H.; Donehower L.A.; Drummond J.; Gibbs R.A.; Glenn R.; Hale W.; Han Y.; Hu J.; Korchina V.; Lee S.; Lewis L.; Li W.; Liu X.; Morgan M.; Morton D.; Muzny D.; Santibanez J.; Sheth M.; Shinbrot E.; Wang L.; Wang M.; Wheeler D.A.; Xi L.; Zhao F.; Hess J.; Appelbaum E.L.; Bailey M.; Cordes M.G.; Ding L.; Fronick C.C.; Fulton L.A.; Fulton R.S.; Kandoth C.; Mardis E.R.; McLellan M.D.; Miller C.A.; Schmidt H.K.; Wilson R.K.; Crain D.; Curley E.; Gardner J.; Lau K.; Mallery D.; Morris S.; Paulauskis J.; Penny R.; Shelton C.; Shelton T.; Sherman M.; Thompson E.; Yena P.; Bowen J.; Gastier-Foster J.M.; Gerken M.; Leraas K.M.; Lichtenberg T.M.; Ramirez N.C.; Wise L.; Zmuda E.; Corcoran N.; 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Dottino P.R.; Martignetti J.A.; Gabra H.; Juhl H.; Akeredolu T.; Stepa S.; Hoon D.; Ahn K.; Kang K.J.; Beuschlein F.; Breggia A.; Birrer M.; Bell D.; Borad M.; Bryce A.H.; Castle E.; Chandan V.; Cheville J.; Copland J.A.; Farnell M.; Flotte T.; Giama N.; Ho T.; Kendrick M.; Kocher J.-P.; Kopp K.; Moser C.; Nagorney D.; O'Brien D.; O'Neill B.P.; Patel T.; Petersen G.; Que F.; Rivera M.; Roberts L.; Smallridge R.; Smyrk T.; Stanton M.; Thompson R.H.; Torbenson M.; Yang J.D.; Zhang L.; Brimo F.; Ajani J.A.; Gonzalez A.M.A.; Behrens C.; Bondaruk O.; Broaddus R.; Czerniak B.; Esmaeli B.; Fujimoto J.; Gershenwald J.; Guo C.; Lazar A.J.; Logothetis C.; Meric-Bernstam F.; Moran C.; Ramondetta L.; Rice D.; Sood A.; Tamboli P.; Thompson T.; Troncoso P.; Tsao A.; Wistuba I.; Carter C.; Haydu L.; Hersey P.; Jakrot V.; Kakavand H.; Kefford R.; Lee K.; Long G.; Mann G.; Quinn M.; Saw R.; Scolyer R.; Shannon K.; Spillane A.; Stretch J.; Synott M.; Thompson J.; Wilmott J.; Al-Ahmadie H.; Chan T.A.; Ghossein R.; Gopalan A.; Levine D.A.; Reuter V.; Singer S.; Singh B.; Tien N.V.; Broudy T.; Mirsaidi C.; Nair P.; Drwiega P.; Miller J.; Smith J.; Zaren H.; Park J.-W.; Hung N.P.; Kebebew E.; Linehan W.M.; Metwalli A.R.; Pacak K.; Pinto P.A.; Schiffman M.; Schmidt L.S.; Vocke C.D.; Wentzensen N.; Worrell R.; Yang H.; Moncrieff M.; Goparaju C.; Melamed J.; Pass H.; Botnariuc N.; Caraman I.; Cernat M.; Chemencedji I.; Clipca A.; Doruc S.; Gorincioi G.; Mura S.; Pirtac M.; Stancul I.; Tcaciuc D.; Albert M.; Alexopoulou I.; Arnaout A.; Bartlett J.; Engel J.; Gilbert S.; Parfitt J.; Sekhon H.; Thomas G.; Rassl D.M.; Rintoul R.C.; Bifulco C.; Tamakawa R.; Urba W.; Hayward N.; Timmers H.; Antenucci A.; Facciolo F.; Grazi G.; Marino M.; Merola R.; de Krijger R.; Gimenez-Roqueplo A.-P.; Piche A.; Chevalier S.; McKercher G.; Birsoy K.; Barnett G.; Brewer C.; Farver C.; Naska T.; Pennell N.A.; Raymond D.; Schilero C.; Smolenski K.; Williams F.; Morrison C.; Borgia J.A.; Liptay M.J.; Pool M.; Seder C.W.; Junker K.; Omberg L.; Dinkin M.; Manikhas G.; Alvaro D.; Bragazzi M.C.; Cardinale V.; Carpino G.; Gaudio E.; Chesla D.; Cottingham S.; Dubina M.; Moiseenko F.; Dhanasekaran R.; Becker K.-F.; Janssen K.-P.; Slotta-Huspenina J.; Abdel-Rahman M.H.; Aziz D.; Bell S.; Cebulla C.M.; Davis A.; Duell R.; Elder J.B.; Hilty J.; Kumar B.; Lang J.; Lehman N.L.; Mandt R.; Nguyen P.; Pilarski R.; Rai K.; Schoenfield L.; Senecal K.; Wakely P.; Hansen P.; Lechan R.; Powers J.; Tischler A.; Grizzle W.E.; Sexton K.C.; Kastl A.; Henderson J.; Porten S.; Waldmann J.; Fassnacht M.; Asa S.L.; Schadendorf D.; Couce M.; Graefen M.; Huland H.; Sauter G.; Schlomm T.; Simon R.; Tennstedt P.; Olabode O.; Nelson M.; Bathe O.; Carroll P.R.; Chan J.M.; Disaia P.; Glenn P.; Kelley R.K.; Landen C.N.; Phillips J.; Prados M.; Simko J.; Smith-McCune K.; VandenBerg S.; Roggin K.; Fehrenbach A.; Kendler A.; Sifri S.; Steele R.; Jimeno A.; Carey F.; Forgie I.; Mannelli M.; Carney M.; Hernandez B.; Campos B.; Herold-Mende C.; Jungk C.; Unterberg A.; von Deimling A.; Bossler A.; Galbraith J.; Jacobus L.; Knudson M.; Knutson T.; Ma D.; Milhem M.; Sigmund R.; Godwin A.K.; Madan R.; Rosenthal H.G.; Adebamowo C.; Adebamowo S.N.; Boussioutas A.; Beer D.; Giordano T.; Mes-Masson A.-M.; Saad F.; Bocklage T.; Landrum L.; Mannel R.; Moore K.; Moxley K.; Postier R.; Walker J.; Zuna R.; Feldman M.; Valdivieso F.; Dhir R.; Luketich J.; Pinero E.M.M.; Quintero-Aguilo M.; Carlotti C.G.; Dos Santos J.S.; Kemp R.; Sankarankuty A.; Tirapelli D.; Catto J.; Agnew K.; Swisher E.; Creaney J.; Robinson B.; Shelley C.S.; Godwin E.M.; Kendall S.; Shipman C.; Bradford C.; Carey T.; Haddad A.; Moyer J.; Peterson L.; Prince M.; Rozek L.; Wolf G.; Bowman R.; Fong K.M.; Yang I.; Korst R.; Rathmell W.K.; Fantacone-Campbell J.L.; Hooke J.A.; Kovatich A.J.; Shriver C.D.; DiPersio J.; Drake B.; Govindan R.; Heath S.; Ley T.; Van Tine B.; Westervelt P.; Rubin M.A.; Lee J.I.; Aredes N.D.; Mariamidze A.; Stuart J.M.16; Benz C.9; Laird P.W.4
2018-04-05
Source PublicationCell
ISSN10974172 00928674
Volume173Issue:2Pages:291-304.e6
AbstractWe conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development. Comprehensive, integrated molecular analysis identifies molecular relationships across a large diverse set of human cancers, suggesting future directions for exploring clinical actionability in cancer treatment.
Keywordcancer cell-of-origin genome methylome organs proteome subtypes TCGA tissues transcriptome
DOI10.1016/j.cell.2018.03.022
URLView the original
Language英語
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Cited Times [WOS]:106   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.University of California, San Francisco
2.Memorial Sloan-Kettering Cancer Center
3.International Institute for Molecular Oncology
4.Van Andel Research Institute
5.Greater Poland Cancer Centre
6.Massachusetts General Hospital Cancer Center
7.Institute for Systems Biology
8.Broad Institute
9.Buck Institute for Age Research
10.Universidade de Sao Paulo - USP
11.The University of North Carolina at Chapel Hill
12.Poznan University of Medical Sciences
13.Dana-Farber Cancer Institute
14.University of Texas MD Anderson Cancer Center
15.British Columbia Cancer Agency
16.University of California, Santa Cruz
17.Henry Ford Health System
18.Vanderbilt University Medical Center
Recommended Citation
GB/T 7714
Hoadley K.A.,Yau C.,Hinoue T.,et al. Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer[J]. Cell,2018,173(2):291-304.e6.
APA Hoadley K.A..,Yau C..,Hinoue T..,Wolf D.M..,Lazar A.J..,...&Laird P.W..(2018).Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer.Cell,173(2),291-304.e6.
MLA Hoadley K.A.,et al."Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer".Cell 173.2(2018):291-304.e6.
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