Integrated genomic analyses of ovarian carcinoma

Cancer Genome Atlas Research Network, D Bell, A Berchuck, M Birrer, J Chien, D W Cramer, F Dao, R Dhir, P DiSaia, H Gabra, P Glenn, A K Godwin, J Gross, L Hartmann, M Huang, D G Huntsman, M Iacocca, M Imielinski, S Kalloger, B Y Karlan, D A Levine, G B Mills, C Morrison, D Mutch, N Olvera, S Orsulic, K Park, N Petrelli, B Rabeno, J S Rader, B I Sikic, K Smith-McCune, A K Sood, D Bowtell, R Penny, J R Testa, K Chang, H H Dinh, J A Drummond, G Fowler, P Gunaratne, A C Hawes, C L Kovar, L R Lewis, M B Morgan, I F Newsham, J Santibanez, J G Reid, L R Trevino, Y -Q Wu, M Wang, D M Muzny, D A Wheeler, R A Gibbs, G Getz, M S Lawrence, K Cibulskis, A Y Sivachenko, C Sougnez, D Voet, J Wilkinson, T Bloom, K Ardlie, T Fennell, J Baldwin, S Gabriel, E S Lander, Louis L Ding, R S Fulton, D C Koboldt, M D McLellan, T Wylie, J Walker, M O'Laughlin, D J Dooling, L Fulton, R Abbott, N D Dees, Q Zhang, C Kandoth, M Wendl, W Schierding, D Shen, C C Harris, H Schmidt, J Kalicki, K D Delehaunty, C C Fronick, R Demeter, L Cook, J W Wallis, L Lin, V J Magrini, J S Hodges, J M Eldred, S M Smith, C S Pohl, F Vandin, B J Raphael, G M Weinstock, E R Mardis, R K Wilson, M Meyerson, W Winckler, G Getz, R G W Verhaak, S L Carter, C H Mermel, G Saksena, H Nguyen, R C Onofrio, M S Lawrence, D Hubbard, S Gupta, A Crenshaw, A H Ramos, K Ardlie, L Chin, A Protopopov, Juinhua Zhang, T M Kim, I Perna, Y Xiao, H Zhang, G Ren, N Sathiamoorthy, R W Park, E Lee, P J Park, R Kucherlapati, M Absher, L Waite, G Sherlock, J D Brooks, J Z Li, J Xu, R M Myers, P W Laird, L Cope, J G Herman, H Shen, D J Weisenberger, H Noushmehr, F Pan, T Triche Jr, B P Berman, D J Van Den Berg, J Buckley, S B Baylin, P T Spellman, E Purdom, P Neuvial, H Bengtsson, L R Jakkula, S Durinck, J Han, S Dorton, H Marr, Y G Choi, V Wang, N J Wang, J Ngai, J G Conboy, B Parvin, H S Feiler, T P Speed, J W Gray, A Levine, N D Socci, Y Liang, B S Taylor, N Schultz, L Borsu, A E Lash, C Brennan, A Viale, C Sander, M Ladanyi, K A Hoadley, S Meng, Y Du, Y Shi, L Li, Y J Turman, D Zang, E B Helms, S Balu, X Zhou, J Wu, M D Topal, D N Hayes, C M Perou, G Getz, D Voet, G Saksena, Junihua Zhang, H Zhang, C J Wu, S Shukla, K Cibulskis, M S Lawrence, A Sivachenko, R Jing, R W Park, Y Liu, P J Park, M Noble, L Chin, H Carter, D Kim, R Karchin, P T Spellman, E Purdom, P Neuvial, H Bengtsson, S Durinck, J Han, J E Korkola, L M Heiser, R J Cho, Z Hu, B Parvin, T P Speed, J W Gray, N Schultz, E Cerami, B S Taylor, A Olshen, B Reva, Y Antipin, R Shen, P Mankoo, R Sheridan, G Ciriello, W K Chang, J A Bernanke, L Borsu, D A Levine, M Ladanyi, C Sander, D Haussler, C C Benz, J M Stuart, S C Benz, J Z Sanborn, C J Vaske, J Zhu, C Szeto, G K Scott, C Yau, K A Hoadley, Y Du, S Balu, D N Hayes, C M Perou, M D Wilkerson, N Zhang, R Akbani, K A Baggerly, W K Yung, G B Mills, J N Weinstein, R Penny, T Shelton, D Grimm, M Hatfield, S Morris, P Yena, P Rhodes, M Sherman, J Paulauskis, S Millis, A Kahn, J M Greene, R Sfeir, M A Jensen, J Chen, J Whitmore, S Alonso, J Jordan, A Chu, Jinghui Zhang, A Barker, C Compton, G Eley, M Ferguson, P Fielding, D S Gerhard, R Myles, C Schaefer, K R Mills Shaw, J Vaught, J B Vockley, P J Good, M S Guyer, B Ozenberger, J Peterson, E Thomson, Cancer Genome Atlas Research Network, D Bell, A Berchuck, M Birrer, J Chien, D W Cramer, F Dao, R Dhir, P DiSaia, H Gabra, P Glenn, A K Godwin, J Gross, L Hartmann, M Huang, D G Huntsman, M Iacocca, M Imielinski, S Kalloger, B Y Karlan, D A Levine, G B Mills, C Morrison, D Mutch, N Olvera, S Orsulic, K Park, N Petrelli, B Rabeno, J S Rader, B I Sikic, K Smith-McCune, A K Sood, D Bowtell, R Penny, J R Testa, K Chang, H H Dinh, J A Drummond, G Fowler, P Gunaratne, A C Hawes, C L Kovar, L R Lewis, M B Morgan, I F Newsham, J Santibanez, J G Reid, L R Trevino, Y -Q Wu, M Wang, D M Muzny, D A Wheeler, R A Gibbs, G Getz, M S Lawrence, K Cibulskis, A Y Sivachenko, C Sougnez, D Voet, J Wilkinson, T Bloom, K Ardlie, T Fennell, J Baldwin, S Gabriel, E S Lander, Louis L Ding, R S Fulton, D C Koboldt, M D McLellan, T Wylie, J Walker, M O'Laughlin, D J Dooling, L Fulton, R Abbott, N D Dees, Q Zhang, C Kandoth, M Wendl, W Schierding, D Shen, C C Harris, H Schmidt, J Kalicki, K D Delehaunty, C C Fronick, R Demeter, L Cook, J W Wallis, L Lin, V J Magrini, J S Hodges, J M Eldred, S M Smith, C S Pohl, F Vandin, B J Raphael, G M Weinstock, E R Mardis, R K Wilson, M Meyerson, W Winckler, G Getz, R G W Verhaak, S L Carter, C H Mermel, G Saksena, H Nguyen, R C Onofrio, M S Lawrence, D Hubbard, S Gupta, A Crenshaw, A H Ramos, K Ardlie, L Chin, A Protopopov, Juinhua Zhang, T M Kim, I Perna, Y Xiao, H Zhang, G Ren, N Sathiamoorthy, R W Park, E Lee, P J Park, R Kucherlapati, M Absher, L Waite, G Sherlock, J D Brooks, J Z Li, J Xu, R M Myers, P W Laird, L Cope, J G Herman, H Shen, D J Weisenberger, H Noushmehr, F Pan, T Triche Jr, B P Berman, D J Van Den Berg, J Buckley, S B Baylin, P T Spellman, E Purdom, P Neuvial, H Bengtsson, L R Jakkula, S Durinck, J Han, S Dorton, H Marr, Y G Choi, V Wang, N J Wang, J Ngai, J G Conboy, B Parvin, H S Feiler, T P Speed, J W Gray, A Levine, N D Socci, Y Liang, B S Taylor, N Schultz, L Borsu, A E Lash, C Brennan, A Viale, C Sander, M Ladanyi, K A Hoadley, S Meng, Y Du, Y Shi, L Li, Y J Turman, D Zang, E B Helms, S Balu, X Zhou, J Wu, M D Topal, D N Hayes, C M Perou, G Getz, D Voet, G Saksena, Junihua Zhang, H Zhang, C J Wu, S Shukla, K Cibulskis, M S Lawrence, A Sivachenko, R Jing, R W Park, Y Liu, P J Park, M Noble, L Chin, H Carter, D Kim, R Karchin, P T Spellman, E Purdom, P Neuvial, H Bengtsson, S Durinck, J Han, J E Korkola, L M Heiser, R J Cho, Z Hu, B Parvin, T P Speed, J W Gray, N Schultz, E Cerami, B S Taylor, A Olshen, B Reva, Y Antipin, R Shen, P Mankoo, R Sheridan, G Ciriello, W K Chang, J A Bernanke, L Borsu, D A Levine, M Ladanyi, C Sander, D Haussler, C C Benz, J M Stuart, S C Benz, J Z Sanborn, C J Vaske, J Zhu, C Szeto, G K Scott, C Yau, K A Hoadley, Y Du, S Balu, D N Hayes, C M Perou, M D Wilkerson, N Zhang, R Akbani, K A Baggerly, W K Yung, G B Mills, J N Weinstein, R Penny, T Shelton, D Grimm, M Hatfield, S Morris, P Yena, P Rhodes, M Sherman, J Paulauskis, S Millis, A Kahn, J M Greene, R Sfeir, M A Jensen, J Chen, J Whitmore, S Alonso, J Jordan, A Chu, Jinghui Zhang, A Barker, C Compton, G Eley, M Ferguson, P Fielding, D S Gerhard, R Myles, C Schaefer, K R Mills Shaw, J Vaught, J B Vockley, P J Good, M S Guyer, B Ozenberger, J Peterson, E Thomson

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.

Figures

Figure 1. Genome copy number abnormalities
Figure 1. Genome copy number abnormalities
(a) Copy-number profiles of 489 HGS-OvCa, compared to profiles of 197 glioblastoma multiforme (GBM) tumors. 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.
Figure 2. Gene and miRNA expression patterns…
Figure 2. Gene 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.
Figure 3. Altered Pathways in HGS-OvCa
Figure 3. Altered 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.

References

    1. Jemal A, Siegel R, Xu J, Ward E. Cancer Statistics, 2010. CA Cancer J Clin
    1. Koonings PP, Campbell K, Mishell DR, Jr., Grimes DA. Relative frequency of primary ovarian neoplasms: a 10-year review. Obstet Gynecol. 1989;74:921–926.
    1. Seidman JD, et al. The histologic type and stage distribution of ovarian carcinomas of surface epithelial origin. Int J Gynecol Pathol. 2004;23:41–44.
    1. Miller DS, et al. Phase II evaluation of pemetrexed in the treatment of recurrent or persistent platinum-resistant ovarian or primary peritoneal carcinoma: a study of the Gynecologic Oncology Group. J Clin Oncol. 2009;27:2686–2691.
    1. Jemal A, et al. Cancer statistics, 2009. CA Cancer J Clin. 2009;59:225–249.
    1. Pal T, et al. BRCA1 and BRCA2 mutations account for a large proportion of ovarian carcinoma cases. Cancer. 2005;104:2807–2816.
    1. Risch HA, et al. Population BRCA1 and BRCA2 mutation frequencies and cancer penetrances: a kin-cohort study in Ontario, Canada. J Natl Cancer Inst. 2006;98:1694–1706.
    1. Bast RC, Jr., Hennessy B, Mills GB. The biology of ovarian cancer: new opportunities for translation. Nat Rev Cancer. 2009;9:415–428.
    1. Gnirke A, et al. Solution hybrid selection with ultra-long oligonucleotides for massively parallel targeted sequencing. Nature biotechnology. 2009;27:182–189.
    1. Hodges E, et al. Hybrid selection of discrete genomic intervals on custom-designed microarrays for massively parallel sequencing. Nature protocols. 2009;4:960–974.
    1. Bookman MA, et al. Evaluation of new platinum-based treatment regimens in advanced-stage ovarian cancer: a Phase III Trial of the Gynecologic Cancer Intergroup. J Clin Oncol. 2009;27:1419–1425.
    1. Muggia FM, et al. Phase III randomized study of cisplatin versus paclitaxel versus cisplatin and paclitaxel in patients with suboptimal stage III or IV ovarian cancer: a gynecologic oncology group study. J Clin Oncol. 2000;18:106–115.
    1. Ahmed AA, et al. Driver mutations in TP53 are ubiquitous in high grade serous carcinoma of the ovary. J Pathol. 221:49–56.
    1. Chen HH, Wang YC, Fann MJ. Identification and characterization of the CDK12/cyclin L1 complex involved in alternative splicing regulation. Molecular and cellular biology. 2006;26:2736–2745.
    1. Ding L, et al. Somatic mutations affect key pathways in lung adenocarcinoma. Nature. 2008;455:1069–1075.
    1. Aldred MA, Trembath RC. Activating and inactivating mutations in the human GNAS1 gene. Human mutation. 2000;16:183–189.
    1. Forbes SA, et al. Current protocols in human genetics / editorial board, Jonathan L. Haines … [et al. 2008. The Catalogue of Somatic Mutations in Cancer (COSMIC) p. 11. Chapter 10, Unit 10.
    1. McKusick VA. Mendelian Inheritance in Man and its online version, OMIM. American journal of human genetics. 2007;80:588–604.
    1. Carter H, et al. Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations. Cancer Res. 2009;69:6660–6667.
    1. Carter H, Samayoa J, Hruban RH, Karchin R. Prioritization of driver mutations in pancreatic cancer using cancer-specific high-throughput annotation of somatic mutations (CHASM) Cancer biology & therapy. 10
    1. Beroukhim R, et al. The landscape of somatic copy-number alteration across human cancers. Nature. 463:899–905.
    1. Etemadmoghadam D, et al. Integrated genome-wide DNA copy number and expression analysis identifies distinct mechanisms of primary chemoresistance in ovarian carcinomas. Clin Cancer Res. 2009;15:1417–1427.
    1. Beroukhim R, et al. Assessing the significance of chromosomal aberrations in cancer: methodology and application to glioma. Proc Natl Acad Sci U S A. 2007;104:20007–20012.
    1. Verhaak RG, et al. Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer Cell. 17:98–110.
    1. Tothill RW, et al. Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome. Clin Cancer Res. 2008;14:5198–5208.
    1. Dubeau L. The cell of origin of ovarian epithelial tumours. Lancet Oncol. 2008;9:1191–1197.
    1. Cheng KW, et al. The RAB25 small GTPase determines aggressiveness of ovarian and breast cancers. Nat Med. 2004;10:1251–1256.
    1. Esteller M, et al. Promoter hypermethylation and BRCA1 inactivation in sporadic breast and ovarian tumors. J Natl Cancer Inst. 2000;92:564–569.
    1. Bonome T, et al. A gene signature predicting for survival in suboptimally debulked patients with ovarian cancer. Cancer Res. 2008;68:5478–5486.
    1. Dressman HK, et al. An integrated genomic-based approach to individualized treatment of patients with advanced-stage ovarian cancer. J Clin Oncol. 2007;25:517–525.
    1. Creighton CJ, et al. Insulin-like growth factor-I activates gene transcription programs strongly associated with poor breast cancer prognosis. J Clin Oncol. 2008;26:4078–4085.
    1. Keshava Prasad TS, et al. Human Protein Reference Database--2009 update. Nucleic Acids Res. 2009;37:D767–772.
    1. Vandin F, Upfal E, Raphael BJ. Algorithms for Detecting Significantly Mutated Pathways in Cancer; 14th International Conference on Research in Computational Molecular Biology; 2010. Springer pp. 506–521.
    1. Choi JH, et al. Jagged-1 and Notch3 juxtacrine loop regulates ovarian tumor growth and adhesion. Cancer Res. 2008;68:5716–5723.
    1. Farmer H, et al. Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy. Nature. 2005;434:917–921.
    1. Fong PC, et al. Inhibition of poly(ADP-ribose) polymerase in tumors from BRCA mutation carriers. N Engl J Med. 2009;361:123–134.
    1. Veeck J, et al. BRCA1 CpG island hypermethylation predicts sensitivity to poly(adenosine diphosphate)-ribose polymerase inhibitors. J Clin Oncol. 28:e563–564. author reply e565-566.
    1. Mendes-Pereira AM, et al. Synthetic lethal targeting of PTEN mutant cells with PARP inhibitors. EMBO Mol Med. 2009;1:315–322.
    1. Nakayama N, et al. Gene amplification CCNE1 is related to poor survival and potential therapeutic target in ovarian cancer. Cancer. 116:2621–2634.
    1. Vaske CJ, et al. Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM. Bioinformatics. 26:i237–245.
    1. Schaefer CF, et al. PID: the Pathway Interaction Database. Nucleic Acids Res. 2009;37:D674–679.
    1. Barsotti AM, Prives C. Pro-proliferative FoxM1 is a target of p53-mediated repression. Oncogene. 2009;28:4295–4305.
    1. Tone AA, et al. Gene expression profiles of luteal phase fallopian tube epithelium from BRCA mutation carriers resemble high-grade serous carcinoma. Clin Cancer Res. 2008;14:4067–4078.
    1. Myatt SS, Lam EW. The emerging roles of forkhead box (Fox) proteins in cancer. Nat Rev Cancer. 2007;7:847–859.
    1. Wang IC, et al. Deletion of Forkhead Box M1 transcription factor from respiratory epithelial cells inhibits pulmonary tumorigenesis. PLoS One. 2009;4:e6609.
    1. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature. 2008;455:1061–1068.
    1. Ho ES, et al. p53 mutation is infrequent in clear cell carcinoma of the ovary. Gynecol Oncol. 2001;80:189–193.
    1. Wiegand KC, et al. ARID1A mutations in endometriosis-associated ovarian carcinomas. N Engl J Med. 2010;363:1532–1543.
    1. Kuo KT, et al. Frequent activating mutations of PIK3CA in ovarian clear cell carcinoma. Am J Pathol. 2009;174:1597–1601.
    1. Cuatrecasas M, Villanueva A, Matias-Guiu X, Prat J. K-ras mutations in mucinous ovarian tumors: a clinicopathologic and molecular study of 95 cases. Cancer. 1997;79:1581–1586.

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