Nature. 2011 Jun 29;474(7353):609-15. doi: 10.1038/nature10166.
Integrated genomic analyses of ovarian carcinoma.
Bell D, Berchuck A, Birrer M, Chien J, Cramer D, Dao F, Dhir R, DiSaia P, Gabra H, Glenn P, Godwin A, Gross J, Hartmann L, Huang M, Huntsman D, Iacocca M, Imielinski M, Kalloger S, Karlan B, Levine D, Mills G, Morrison C, Mutch D, Olvera N, Orsulic S, Park K, Petrelli N, Rabeno B, Rader J, Sikic B, Smith-McCune K, Sood A, Bowtell D, Penny R, Testa J, Chang K, Dinh H, Drummond J, Fowler G, Gunaratne P, Hawes A, Kovar C, Lewis L, Morgan M, Newsham I, Santibanez J, Reid J, Trevino L, Wu Y-, Wang M, Muzny D, Wheeler D, Gibbs R, Getz G, Lawrence M, Cibulskis K, Sivachenko A, Sougnez C, Voet D, Wilkinson J, Bloom T, Ardlie K, Fennell T, Baldwin J, Gabriel S, Lander E, Ding LL, Fulton R, Koboldt D, McLellan M, Wylie T, Walker J, O'Laughlin M, Dooling D, Fulton L, Abbott R, Dees N, Zhang Q, Kandoth C, Wendl M, Schierding W, Shen D, Harris C, Schmidt H, Kalicki J, Delehaunty K, Fronick C, Demeter R, Cook L, Wallis J, Lin L, Magrini V, Hodges J, Eldred J, Smith S, Pohl C, Vandin F, Raphael B, Weinstock G, Mardis E, Wilson R, Meyerson M, Winckler W, Getz G, Verhaak R, Carter S, Mermel C, Saksena G, Nguyen H, Onofrio R, Lawrence M, Hubbard D, Gupta S, Crenshaw A, Ramos A, Ardlie K, Chin L, Protopopov A, Zhang J, Kim T, Perna I, Xiao Y, Zhang H, Ren G, Sathiamoorthy N, Park R, Lee E, Park P, Kucherlapati R, Absher M, Waite L, Sherlock G, Brooks J, Li J, Xu J, Myers R, Laird PW, Cope L, Herman J, Shen H, Weisenberger D, Noushmehr H, Pan F, Triche T Jr, Berman B, Van Den Berg D, Buckley J, Baylin S, Spellman P, Purdom E, Neuvial P, Bengtsson H, Jakkula L, Durinck S, Han J, Dorton S, Marr H, Choi Y, Wang V, Wang N, Ngai J, Conboy J, Parvin B, Feiler H, Speed T, Gray J, Levine A, Socci N, Liang Y, Taylor B, Schultz N, Borsu L, Lash A, Brennan C, Viale A, Sander C, Ladanyi M, Hoadley K, Meng S, Du Y, Shi Y, Li L, Turman Y, Zang D, Helms E, Balu S, Zhou X, Wu J, Topal M, Hayes D, Perou C, Getz G, Voet D, Saksena G, Zhang J, Zhang H, Wu C, Shukla S, Cibulskis K, Lawrence M, Sivachenko A, Jing R, Park R, Liu Y, Park P, Noble M, Chin L, Carter H, Kim D, Karchin R, Spellman P, Purdom E, Neuvial P, Bengtsson H, Durinck S, Han J, Korkola J, Heiser L, Cho R, Hu Z, Parvin B, Speed T, Gray J, Schultz N, Cerami E, Taylor B, Olshen A, Reva B, Antipin Y, Shen R, Mankoo P, Sheridan R, Ciriello G, Chang W, Bernanke J, Borsu L, Levine D, Ladanyi M, Sander C, Haussler D, Benz C, Stuart J, Benz S, Sanborn J, Vaske C, Zhu J, Szeto C, Scott G, Yau C, Hoadley K, Du Y, Balu S, Hayes D, Perou C, Wilkerson M, Zhang N, Akbani R, Baggerly K, Yung W, Mills G, Weinstein J, Penny R, Shelton T, Grimm D, Hatfield M, Morris S, Yena P, Rhodes P, Sherman M, Paulauskis J, Millis S, Kahn A, Greene J, Sfeir R, Jensen M, Chen J, Whitmore J, Alonso S, Jordan J, Chu A, Zhang J, Barker A, Compton C, Eley G, Ferguson M, Fielding P, Gerhard D, Myles R, Schaefer C, Mills Shaw K, Vaught J, Vockley J, Good P, Guyer M, Ozenberger B, Peterson J, Thomson E.
Erratum in
- Nature. 2012 Oct 11;490(7419):298.
Abstract
A catalogue of molecular aberrations that cause ovarian cancer is critical for developing and deploying therapies that will improve patients' lives. The Cancer Genome Atlas project has analysed messenger RNA expression, microRNA expression, promoter methylation and DNA copy number in 489 high-grade serous ovarian adenocarcinomas and the DNA sequences of exons from coding genes in 316 of these tumours. Here we report that high-grade serous ovarian cancer is characterized by TP53 mutations in almost all tumours (96%); low prevalence but statistically recurrent somatic mutations in nine further genes including NF1, BRCA1, BRCA2, RB1 and CDK12; 113 significant focal DNA copy number aberrations; and promoter methylation events involving 168 genes. Analyses delineated four ovarian cancer transcriptional subtypes, three microRNA subtypes, four promoter methylation subtypes and a transcriptional signature associated with survival duration, and shed new light on the impact that tumours with BRCA1/2 (BRCA1 or BRCA2) and CCNE1 aberrations have on survival. Pathway analyses suggested that homologous recombination is defective in about half of the tumours analysed, and that NOTCH and FOXM1 signalling are involved in serous ovarian cancer pathophysiology.
- PMID:
- 21720365
- [PubMed - indexed for MEDLINE]
- PMCID:
- PMC3163504
Free PMC ArticleFigure 1Genome copy number abnormalities
(a) Copy-number profiles of 489 HGS-OvCa, compared to profiles of 197 glioblastoma multiforme (GBM) tumors46. Copy number increases (red) and decreases (blue) are plotted as a function of distance along the normal genome. (b) Significant, focally amplified (red) and deleted (blue) regions are plotted along the gnome. Annotations include the 20 most significant amplified and deleted regions, well-localized regions with 8 or fewer genes, and regions with known cancer genes or genes identified by genome-wide loss-of-function screens. The number of genes included in each region is given in brackets. (c) Significantly amplified (red) and deleted (blue) chromosome arms.
Nature. 2011 June 29;474(7353):609-615.
Figure 3Altered Pathways in HGS-OvCa
(a) The RB and PI3K/RAS pathways, identified by curated analysis and (b) NOTCH pathway, identified by HotNet analysis, are commonly altered. Alterations are defined by somatic mutations, DNA copy-number changes, or in some cases by significant up- or down-regulation compared to expression in diploid tumors. Alteration frequencies are in percentage of all cases; activated genes are red, inactivated genes are blue. (c) Genes in the HR pathway are altered in up to 49% of cases. Survival analysis of BRCA status shows divergent outcome for BRCA mutated cases (exhibiting better overall survival) than BRCA wild-type, and BRCA1 epigenetically silenced cases exhibiting worse survival. (d) The FOXM1 transcription factor network is activated in 87% of cases. Each gene is depicted as a multi-ring circle in which its copy number (outer ring) and gene expression (inner ring) are plotted such that each “spoke” in the ring represents a single patient sample, with samples sorted in increasing order of FOXM1 expression. Excitatory (red arrows) and inhibitory interactions (blue lines) were taken from the NCI Pathway Interaction Database. Dashed lines indicate transcriptional regulation.
Nature. 2011 June 29;474(7353):609-615.
Figure 2Gene and miRNA expression patterns of molecular subtype and outcome prediction in HGS-OvCa
(a) Tumors from TCGA and Tothill et al. separated into four clusters, based on gene expression. (b) Using a training dataset, a prognostic gene signature was defined and applied to a test dataset. (c) Kaplan-Meier analysis of four independent expression profile datasets, comparing survival for predicted higher risk versus lower risk patients. Univariate Cox p-value for risk index included. (d) Tumors separated into three clusters, based on miRNA expression, overlapping with gene-based clusters as indicated. (e) Differences in patient survival among the three miRNA-based clusters.
Nature. 2011 June 29;474(7353):609-615.
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