Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Rethinking ovarian cancer II: reducing mortality from high-grade serous ovarian cancer

Abstract

High-grade serous ovarian cancer (HGSOC) accounts for 70–80% of ovarian cancer deaths, and overall survival has not changed significantly for several decades. In this Opinion article, we outline a set of research priorities that we believe will reduce incidence and improve outcomes for women with this disease. This 'roadmap' for HGSOC was determined after extensive discussions at an Ovarian Cancer Action meeting in January 2015.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Clinical and molecular features of HGSOC at a glance.
Figure 2: Fallopian tube origins of HGSOC.
Figure 3: The complex tumour microenvironment of HGSOC.

References

  1. 1

    Vaughan, S. et al. Rethinking ovarian cancer: recommendations for improving outcomes. Nat. Rev. Cancer 11, 719–725 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. 2

    The Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature 490, 61–70 (2012).

  3. 3

    Mehra, K. et al. STICS, SCOUTs and p53 signatures; a new language for pelvic serous carcinogenesis. Front. Biosci. (Elite Ed) 3, 625–634 (2011).

    Google Scholar 

  4. 4

    Lee, Y. et al. A candidate precursor to serous carcinoma that originates in the distal fallopian tube. J. Pathol. 211, 26–35 (2007).

    Article  CAS  PubMed  Google Scholar 

  5. 5

    Piek, J. M. et al. Dysplastic changes in prophylactically removed Fallopian tubes of women predisposed to developing ovarian cancer. J. Pathol. 195, 451–456 (2001).

    Article  CAS  PubMed  Google Scholar 

  6. 6

    Falconer, H., Yin, L., Gronberg, H. & Altman, D. Ovarian cancer risk after salpingectomy: a nationwide population-based study. J. Natl. Cancer Inst. 107 (2015).

  7. 7

    Kuhn, E. et al. TP53 mutations in serous tubal intraepithelial carcinoma and concurrent pelvic high-grade serous carcinoma—evidence supporting the clonal relationship of the two lesions. J. Pathol. 226, 421–426 (2012).

    Article  CAS  PubMed  Google Scholar 

  8. 8

    Kindelberger, D. W. et al. Intraepithelial carcinoma of the fimbria and pelvic serous carcinoma: Evidence for a causal relationship. Am. J. Surg. Pathol. 31, 161–169 (2007).

    Article  PubMed  Google Scholar 

  9. 9

    Perets, R. et al. Transformation of the fallopian tube secretory epithelium leads to high-grade serous ovarian cancer in Brca;Tp53;Pten models. Cancer Cell 24, 751–765 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. 10

    Kim, J., Coffey, D. M., Ma, L. & Matzuk, M. M. The ovary is an alternative site of origin for high-grade serous ovarian cancer in mice. Endocrinology 156, 1975–1981 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. 11

    Howitt, B. E. et al. Evidence for a dualistic model of high-grade serous carcinoma: BRCA mutation status, histology, and tubal intraepithelial carcinoma. Am. J. Surg. Pathol. 39, 287–293 (2015).

    Article  PubMed  Google Scholar 

  12. 12

    Yemelyanova, A. et al. Immunohistochemical staining patterns of p53 can serve as a surrogate marker for TP53 mutations in ovarian carcinoma: an immunohistochemical and nucleotide sequencing analysis. Mod. Pathol. 24, 1248–1253 (2011).

    Article  CAS  PubMed  Google Scholar 

  13. 13

    Ahmed, A. A. et al. Driver mutations in TP53 are ubiquitous in high grade serous carcinoma of the ovary. J. Pathol. 221, 49–56 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. 14

    The Cancer Genome Atlas Research Network. Integrated genomic analysis of ovarian cancer. Nature 474, 609–615 (2011).

  15. 15

    Ciriello, G. et al. Emerging landscape of oncogenic signatures across human cancers. Nat. Genet. 45, 1127–1133 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. 16

    Martins, F. C. et al. Combined image and genomic analysis of high-grade serous ovarian cancer reveals PTEN loss as a common driver event and prognostic classifier. Genome Biol. 15, 526 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. 17

    Patch, A. M. et al. Whole-genome characterization of chemoresistant ovarian cancer. Nature 521, 489–494 (2015).

    Article  CAS  PubMed  Google Scholar 

  18. 18

    Mukhopadhyay, A. et al. Development of a functional assay for homologous recombination status in primary cultures of epithelial ovarian tumor and correlation with sensitivity to poly(ADP-ribose) polymerase inhibitors. Clin. Cancer Res. 16, 2344–2351 (2010).

    Article  CAS  PubMed  Google Scholar 

  19. 19

    Mukhopadhyay, A. et al. Clinicopathological features of homologous recombination-deficient epithelial ovarian cancers: sensitivity to PARP inhibitors, platinum, and survival. Cancer Res. 72, 5675–5682 (2012).

    Article  CAS  PubMed  Google Scholar 

  20. 20

    Alsop, K. et al. BRCA mutation frequency and patterns of treatment response in BRCA mutation-positive women with ovarian cancer: A report from the Australian Ovarian Cancer Study Group. J. Clin. Oncol. 30, 2654–2663 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. 21

    Walsh, T. et al. Detection of inherited mutations for breast and ovarian cancer using genomic capture and massively parallel sequencing. Proc. Natl Acad. Sci. USA 107, 12629–12633 (2010).

    Article  PubMed  Google Scholar 

  22. 22

    Fong, P. C. et al. Inhibition of poly(ADP-ribose) polymerase in tumors from BRCA mutation carriers. N. Engl. J. Med. 361, 123–134 (2009).

    Article  CAS  PubMed  Google Scholar 

  23. 23

    Ledermann, J. et al. Olaparib maintenance therapy in platinum-sensitive relapsed ovarian cancer. N. Engl. J. Med. 366, 1382–1392 (2012).

    Article  CAS  PubMed  Google Scholar 

  24. 24

    Scott, C. L., Swisher, E. M. & Kaufmann, S. H. Poly (adp-ribose) polymerase inhibitors: recent advances and future development. J. Clin. Oncol. 33, 1397–1406 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. 25

    Karst, A. M. et al. Cyclin E1 deregulation occurs early in secretory cell transformation to promote formation of fallopian tube-derived high-grade serous ovarian cancers. Cancer Res. 74, 1141–1152 (2014).

    Article  CAS  PubMed  Google Scholar 

  26. 26

    Etemadmoghadam, D. et al. Amplicon-dependent CCNE1 expression is critical for clonogenic survival after cisplatin treatment and is correlated with 20q11 gain in ovarian cancer. PLoS ONE 5, e15498 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. 27

    Tothill, R. W. et al. Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome. Clin. Cancer Res. 14, 5198–5208 (2008).

    Article  CAS  PubMed  Google Scholar 

  28. 28

    Konecny, G. E. et al. Prognostic and therapeutic relevance of molecular subtypes in high-grade serous ovarian cancer. J. Natl. Cancer Inst. 106, dju249 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. 29

    Nieman, K. M. et al. Adipocytes promote ovarian cancer metastasis and provide energy for rapid tumor growth. Nat. Med. 17, 1498–1503 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. 30

    Pradeep, S. et al. Hematogenous metastasis of ovarian cancer: rethinking mode of spread. Cancer Cell 26, 77–91 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. 31

    Yang, D. et al. Integrated analyses identify a master microRNA regulatory network for the mesenchymal subtype in serous ovarian cancer. Cancer Cell 23, 186–199 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. 32

    Vecchione, A. et al. A microRNA signature defines chemoresistance in ovarian cancer through modulation of angiogenesis. Proc. Natl Acad. Sci. USA 110, 9845–9850 (2013).

    Article  PubMed  Google Scholar 

  33. 33

    Parikh, A. et al. microRNA-181a has a critical role in ovarian cancer progression through the regulation of the epithelial-mesenchymal transition. Nat. Commun. 5, 2977 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. 34

    Zhang, L. et al. Intratumoral T cells, recurrence, and survival in epithelial ovarian cancer. N. Engl. J. Med. 348, 203–213 (2003).

    Article  CAS  PubMed  Google Scholar 

  35. 35

    Anglesio, M. S. et al. Type-specific cell line models for type-specific ovarian cancer research. PLoS ONE 8, e72162 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. 36

    Domcke, S., Sinha, R., Levine, D. A., Sander, C. & Schultz, N. Evaluating cell lines as tumour models by comparison of genomic profiles. Nat. Commun. 4, 2126 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. 37

    Beaufort, C. M. et al. Ovarian cancer cell line panel (OCCP): clinical importance of in vitro morphological subtypes. PLoS ONE 9, e103988 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. 38

    O'Donnell, R. et al. The use of ovarian cancer cells from patients undergoing surgery to generate primary cultures capable of undergoing functional analysis. PLoS ONE 9, e90604 (2014).

    Article  PubMed Central  Google Scholar 

  39. 39

    Ince, T. A. et al. Characterization of twenty-five ovarian tumour cell lines that phenocopy primary tumours. Nat. Commun. 6, 7419 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. 40

    Kenny, H. A. et al. Quantitative high throughput screening using a primary human three-dimensional organotypic culture predicts in vivo efficacy. Nat. Commun. 6, 6220 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. 41

    Kenny, H. A. et al. Mesothelial cells promote early ovarian cancer metastasis through fibronectin secretion. J. Clin. Invest. 124, 4614–4628 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. 42

    Karst, A. M. & Drapkin, R. Primary culture and immortalization of human fallopian tube secretory epithelial cells. Nat. Protoc. 7, 1755–1764 (2012).

    Article  CAS  PubMed  Google Scholar 

  43. 43

    Karst, A. M., Levanon, K. & Drapkin, R. Modeling high-grade serous ovarian carcinogenesis from the fallopian tube. Proc. Natl Acad. Sci. USA 108, 7547–7552 (2011).

    Article  PubMed  Google Scholar 

  44. 44

    Jazaeri, A. A. et al. Molecular requirements for transformation of fallopian tube epithelial cells into serous carcinoma. Neoplasia 13, 899–911 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. 45

    Sherman-Baust, C. A. et al. A genetically engineered ovarian cancer mouse model based on fallopian tube transformation mimics human high-grade serous carcinoma development. J. Pathol. 233, 228–237 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. 46

    Platt, R. J. et al. CRISPR-Cas9 knockin mice for genome editing and cancer modeling. Cell 159, 440–455 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. 47

    Topp, M. D. et al. Molecular correlates of platinum response in human high-grade serous ovarian cancer patient-derived xenografts. Mol. Oncol. 8, 656–668 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  48. 48

    Weroha, S. J. et al. Tumorgrafts as in vivo surrogates for women with ovarian cancer. Clin. Cancer Res. 20, 1288–1297 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. 49

    Dobbin, Z. C. et al. Using heterogeneity of the patient-derived xenograft model to identify the chemoresistant population in ovarian cancer. Oncotarget 5, 8750–8764 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  50. 50

    Ricci, F. et al. Patient-derived ovarian tumor xenografts recapitulate human clinicopathology and genetic alterations. Cancer Res. 74, 6980–6990 (2014).

    Article  CAS  PubMed  Google Scholar 

  51. 51

    Malaney, P., Nicosia, S. V. & Dave, V. One mouse, one patient paradigm: New avatars of personalized cancer therapy. Cancer Lett. 344, 1–12 (2014).

    Article  CAS  PubMed  Google Scholar 

  52. 52

    Cai, S. et al. Humanized bone marrow mouse model as a preclinical tool to assess therapy-mediated hematotoxicity. Clin. Cancer Res. 17, 2195–2206 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. 53

    Bashashati, A. et al. Distinct evolutionary trajectories of primary high-grade serous ovarian cancers revealed through spatial mutational profiling. J. Pathol. 231, 21–34 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. 54

    Cowin, P. A. et al. LRP1B deletion in high-grade serous ovarian cancers is associated with acquired chemotherapy resistance to liposomal doxorubicin. Cancer Res. 72, 4060–4073 (2012).

    Article  CAS  PubMed  Google Scholar 

  55. 55

    Cooke, S. L. et al. Genomic analysis of genetic heterogeneity and evolution in high-grade serous ovarian carcinoma. Oncogene 29, 4905–4913 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. 56

    Schwarz, R. F. et al. Spatial and temporal heterogeneity in high-grade serous ovarian cancer: a phylogenetic analysis. PLoS Med. 12, e1001789 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. 57

    Roth, A. et al. PyClone: statistical inference of clonal population structure in cancer. Nat. Methods 11, 396–398 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. 58

    Stronach, E. A. et al. DNA-PK mediates AKT activation and apoptosis inhibition in clinically acquired platinum resistance. Neoplasia 13, 1069–1080 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. 59

    Norquist, B. et al. Secondary somatic mutations restoring BRCA1/2 predict chemotherapy resistance in hereditary ovarian carcinomas. J. Clin. Oncol. 29, 3008–3015 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. 60

    Sakai, W. et al. Secondary mutations as a mechanism of cisplatin resistance in BRCA2-mutated cancers. Nature 451, 1116–1120 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. 61

    Blagden, S. et al. Afuresertib (GSK2110183), an oral AKT kinase inhibitor, in combination with carboplatin and paclitaxel in recurrent ovarian cancer. Eur. J. Cancer 50, 7 (2014).

    Article  Google Scholar 

  62. 62

    Lu, Z. et al. DIRAS3 regulates the autophagosome initiation complex in dormant ovarian cancer cells. Autophagy 10, 1071–1092 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. 63

    Murtaza, M. et al. Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature 497, 108–112 (2013).

    Article  CAS  PubMed  Google Scholar 

  64. 64

    Marx, V. Cancer: A most exceptional response. Nature 520, 389–393 (2015).

    Article  CAS  PubMed  Google Scholar 

  65. 65

    Ye, Q. et al. CD137 accurately identifies and enriches for naturally occurring tumor-reactive T cells in tumor. Clin. Cancer Res. 20, 44–55 (2014).

    Article  CAS  PubMed  Google Scholar 

  66. 66

    Kandalaft, L. E., Powell, D. J. Jr, Singh, N. & Coukos, G. Immunotherapy for ovarian cancer: what's next? J. Clin. Oncol. 29, 925–933 (2011).

    Article  CAS  PubMed  Google Scholar 

  67. 67

    Wick, D. A. et al. Surveillance of the tumor mutanome by T cells during progression from primary to recurrent ovarian cancer. Clin. Cancer Res. 20, 1125–1134 (2014).

    Article  CAS  PubMed  Google Scholar 

  68. 68

    Chao, M. P., Weissman, I. L. & Majeti, R. The CD47-SIRPα pathway in cancer immune evasion and potential therapeutic implications. Curr. Opin. Immunol. 24, 225–232 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. 69

    Inaba, T. et al. Role of the immunosuppressive enzyme indoleamine 2,3-dioxygenase in the progression of ovarian carcinoma. Gynecol. Oncol. 115, 185–192 (2009).

    Article  CAS  PubMed  Google Scholar 

  70. 70

    Duraiswamy, J., Freeman, G. J. & Coukos, G. Therapeutic PD-1 pathway blockade augments with other modalities of immunotherapy T-cell function to prevent immune decline in ovarian cancer. Cancer Res. 73, 6900–6912 (2013).

    Article  CAS  PubMed  Google Scholar 

  71. 71

    Motz, G. T. & Coukos, G. Deciphering and reversing tumor immune suppression. Immunity 39, 61–73 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. 72

    Kryczek, I. et al. Relationship between B7-H4, regulatory T cells, and patient outcome in human ovarian carcinoma. Cancer Res. 67, 8900–8905 (2007).

    Article  CAS  PubMed  Google Scholar 

  73. 73

    Chen, D. S. & Mellman, I. Oncology meets immunology: the cancer-immunity cycle. Immunity 39, 1–10 (2013).

    Article  CAS  PubMed  Google Scholar 

  74. 74

    Rizvi, N. A. et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science 348, 124–128 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. 75

    Snyder, A. et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N. Engl. J. Med. 371, 2189–2199 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. 76

    Rooney, M. S., Shukla, S. A., Wu, C. J., Getz, G. & Hacohen, N. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell 160, 48–61 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. 77

    George, J. et al. Nonequivalent gene expression and copy number alterations in high-grade serous ovarian cancers with BRCA1 and BRCA2 mutations. Clin. Cancer Res. 19, 3474–3484 (2013).

    Article  CAS  PubMed  Google Scholar 

  78. 78

    Soslow, R. A. et al. Morphologic patterns associated with BRCA1 and BRCA2 genotype in ovarian carcinoma. Mod. Pathol. 25, 625–636 (2012).

    Article  CAS  PubMed  Google Scholar 

  79. 79

    Fujiwara, M. et al. Prediction of BRCA1 germline mutation status in women with ovarian cancer using morphology-based criteria: identification of a BRCA1 ovarian cancer phenotype. Am. J. Surg. Pathol. 36, 1170–1177 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  80. 80

    Clarke, B. et al. Intraepithelial T cells and prognosis in ovarian carcinoma: novel associations with stage, tumor type, and BRCA1 loss. Mod. Pathol. 22, 393–402 (2009).

    Article  CAS  PubMed  Google Scholar 

  81. 81

    Yang, D. et al. Association of BRCA1 and BRCA2 mutations with survival, chemotherapy sensitivity, and gene mutator phenotype in patients with ovarian cancer. JAMA 306, 1557–1565 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. 82

    Bjorkman, A. et al. Aberrant recombination and repair during immunoglobulin class switching in BRCA1-deficient human B cells. Proc. Natl Acad. Sci. USA 112, 2157–2162 (2015).

    Article  CAS  PubMed  Google Scholar 

  83. 83

    Galon, J. et al. Towards the introduction of the 'Immunoscore' in the classification of malignant tumours. J. Pathol. 232, 199–209 (2014).

    Article  CAS  PubMed  Google Scholar 

  84. 84

    Galon, J., Angell, H. K., Bedognetti, D. & Marincola, F. M. The continuum of cancer immunosurveillance: prognostic, predictive, and mechanistic signatures. Immunity 39, 11–26 (2013).

    Article  CAS  PubMed  Google Scholar 

  85. 85

    Wrangle, J. et al. Alterations of immune response of non-small cell lung cancer with azacytidine. Oncotarget 4, 2067–2079 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  86. 86

    Li, H. et al. Immune regulation by low doses of the DNA methyltransferase inhibitor 5-azacitidine in common human epithelial cancers. Oncotarget 5, 587–598 (2014).

    PubMed  PubMed Central  Google Scholar 

  87. 87

    Fang, F. et al. The novel, small-molecule DNA methylation inhibitor SGI-110 as an ovarian cancer chemosensitizer. Clin. Cancer Res. 20, 6504–6516 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. 88

    Fang, F. et al. Decitabine reactivated pathways in platinum resistant ovarian cancer. Oncotarget 5, 3579–3589 (2014).

    PubMed  PubMed Central  Google Scholar 

  89. 89

    Matei, D. et al. Epigenetic resensitization to platinum in ovarian cancer. Cancer Res. 72, 2197–2205 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. 90

    Nielsen, J. S. et al. CD20+ tumor-infiltrating lymphocytes have an atypical CD27- memory phenotype and together with CD8+ T cells promote favorable prognosis in ovarian cancer. Clin. Cancer Res. 18, 3281–3292 (2012).

    Article  CAS  PubMed  Google Scholar 

  91. 91

    Coward, J. et al. Interleukin-6 as a therapeutic target in human ovarian cancer. Clin. Cancer Res. 17, 6083–6096 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. 92

    Bindea, G. et al. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity 39, 782–795 (2013).

    Article  CAS  PubMed  Google Scholar 

  93. 93

    Galon, J. et al. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science 313, 1960–1964 (2006).

    Article  CAS  PubMed  Google Scholar 

  94. 94

    Davidowitz, R. A. et al. Mesenchymal gene program-expressing ovarian cancer spheroids exhibit enhanced mesothelial clearance. J. Clin. Invest. 124, 2611–2625 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. 95

    Iwanicki, M. P. et al. Ovarian cancer spheroids use myosin-generated force to clear the mesothelium. Cancer Discov. 1, 144–157 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. 96

    Yeung, T. L. et al. TGF-β modulates ovarian cancer invasion by upregulating CAF-derived versican in the tumor microenvironment. Cancer Res. 73, 5016–5028 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. 97

    Cheon, D. J. et al. A collagen-remodeling gene signature regulated by TGF-β signaling is associated with metastasis and poor survival in serous ovarian cancer. Clin. Cancer Res. 20, 711–723 (2014).

    Article  CAS  PubMed  Google Scholar 

  98. 98

    Olive, K. P. et al. Inhibition of Hedgehog signaling enhances delivery of chemotherapy in a mouse model of pancreatic cancer. Science 324, 1457–1461 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. 99

    Ahmed, A. A. et al. The extracellular matrix protein TGFBI induces microtubule stabilization and sensitizes ovarian cancers to paclitaxel. Cancer Cell 12, 514–527 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. 100

    Ozdemir, B. C. et al. Depletion of carcinoma-associated fibroblasts and fibrosis induces immunosuppression and accelerates pancreas cancer with reduced survival. Cancer Cell 25, 719–734 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. 101

    Rhim, A. D. et al. Stromal elements act to restrain, rather than support, pancreatic ductal adenocarcinoma. Cancer Cell 25, 735–747 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. 102

    Farmer, H. et al. Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy. Nature 434, 917–921 (2005).

    Article  CAS  PubMed  Google Scholar 

  103. 103

    Ledermann, J. et al. Olaparib maintenance therapy in patients with platinum-sensitive relapsed serous ovarian cancer: a preplanned retrospective analysis of outcomes by BRCA status in a randomised phase 2 trial. Lancet Oncol. 15, 852–861 (2014).

    Article  CAS  PubMed  Google Scholar 

  104. 104

    Abkevich, V. et al. Patterns of genomic loss of heterozygosity predict homologous recombination repair defects in epithelial ovarian cancer. Br. J. Cancer 107, 1776–1782 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. 105

    McNeish, I. A. et al. Results of ARIEL2: A phase 2 trial to prospectively identify ovarian cancer patients likely to respond to rucaparib using tumor genetic analysis. J. Clin. Oncol. 33, 5508 (2015).

    Article  Google Scholar 

  106. 106

    Edwards, S. L. et al. Resistance to therapy caused by intragenic deletion in BRCA2. Nature 451, 1111–1115 (2008).

    Article  CAS  PubMed  Google Scholar 

  107. 107

    Perren, T. J. et al. A phase 3 trial of bevacizumab in ovarian cancer. N. Engl. J. Med. 365, 2484–2496 (2011).

    Article  CAS  PubMed  Google Scholar 

  108. 108

    Burger, R. A. et al. Incorporation of bevacizumab in the primary treatment of ovarian cancer. N. Engl. J. Med. 365, 2473–2483 (2011).

    Article  CAS  PubMed  Google Scholar 

  109. 109

    Pujade-Lauraine, E. et al. Bevacizumab combined with chemotherapy for platinum-resistant recurrent ovarian cancer: The AURELIA open-label randomized phase III trial. J. Clin. Oncol. 32, 1302–1308 (2014).

    Article  CAS  PubMed  Google Scholar 

  110. 110

    Oliver, K. E. & McGuire, W. P. Ovarian cancer and antiangiogenic therapy: caveat emptor. J. Clin. Oncol. 32, 3353–3356 (2014).

    Article  CAS  PubMed  Google Scholar 

  111. 111

    Hall, M. et al. Targeted anti-vascular therapies for ovarian cancer: current evidence. Br. J. Cancer 108, 250–258 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. 112

    Gourley, G. et al. Molecular subgroup of high-grade serous ovarian cancer (HGSOC) as a predictor of outcome following bevacizumab. J. Clin. Oncol. 32, 5502 (2014).

    Article  Google Scholar 

  113. 113

    Choi, H. J. et al. Anti-vascular therapies in ovarian cancer: moving beyond anti-VEGF approaches. Cancer Metastasis Rev. 34, 19–40 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. 114

    Zaid, T. M. et al. Identification of FGFR4 as a potential therapeutic target for advanced-stage, high-grade serous ovarian cancer. Clin. Cancer Res. 19, 809–820 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. 115

    Liu, J. F. et al. Combination cediranib and olaparib versus olaparib alone for women with recurrent platinum-sensitive ovarian cancer: a randomised phase 2 study. Lancet Oncol. 15, 1207–1214 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. 116

    Rubin, E. H., Anderson, K. M. & Gause, C. K. The BATTLE trial: a bold step toward improving the efficiency of biomarker-based drug development. Cancer Discov. 1, 17–20 (2011).

    Article  CAS  PubMed  Google Scholar 

  117. 117

    Cheung, H. W. et al. Systematic investigation of genetic vulnerabilities across cancer cell lines reveals lineage-specific dependencies in ovarian cancer. Proc. Natl Acad. Sci. USA 108, 12372–12377 (2011).

    Article  PubMed  Google Scholar 

  118. 118

    Baratta, M. G. et al. An in-tumor genetic screen reveals that the BET bromodomain protein, BRD4, is a potential therapeutic target in ovarian carcinoma. Proc. Natl Acad. Sci. USA 112, 232–237 (2015).

    Article  CAS  PubMed  Google Scholar 

  119. 119

    Barretina, J. et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 483, 603–607 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. 120

    Angelo, M. et al. Multiplexed ion beam imaging of human breast tumors. Nat. Med. 20, 436–442 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  121. 121

    Bookman, M. A., Darcy, K. M., Clarke-Pearson, D., Boothby, R. A. & Horowitz, I. R. Evaluation of monoclonal humanized anti-HER2 antibody, trastuzumab, in patients with recurrent or refractory ovarian or primary peritoneal carcinoma with overexpression of HER2: a phase II trial of the Gynecologic Oncology Group. J. Clin. Oncol. 21, 283–290 (2003).

    Article  CAS  PubMed  Google Scholar 

  122. 122

    McKie, A. B. et al. The OPCML tumor suppressor functions as a cell surface repressor-adaptor, negatively regulating receptor tyrosine kinases in epithelial ovarian cancer. Cancer Discov. 2, 156–171 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. 123

    Gao, J. et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci. Signal 6, pl1 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. 124

    Cerami, E. et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2, 401–404 (2012).

    Article  PubMed  Google Scholar 

  125. 125

    Ramos, P. et al. Small cell carcinoma of the ovary, hypercalcemic type, displays frequent inactivating germline and somatic mutations in SMARCA4. Nat. Genet. 46, 427–429 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. 126

    Silva, I. A. et al. Aldehyde dehydrogenase in combination with CD133 defines angiogenic ovarian cancer stem cells that portend poor patient survival. Cancer Res. 71, 3991–4001 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. 127

    Condello, S. et al. β-catenin-regulated ALDH1A1 is a target in ovarian cancer spheroids. Oncogene 34, 2297–2308 (2015).

    Article  CAS  PubMed  Google Scholar 

  128. 128

    Wang, Y. et al. Epigenetic targeting of ovarian cancer stem cells. Cancer Res. 74, 4922–4936 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. 129

    Zhang, S. et al. Ovarian cancer stem cells express ROR1, which can be targeted for anti-cancer-stem-cell therapy. Proc. Natl Acad. Sci. USA 111, 17266–17271 (2014).

    Article  CAS  PubMed  Google Scholar 

  130. 130

    Kalinsky, K. & Hershman, D. L. Cracking open window of opportunity trials. J. Clin. Oncol. 30, 2573–2575 (2012).

    Article  CAS  PubMed  Google Scholar 

  131. 131

    Rustin, G., van der Burg, M., Griffin, C., Qian, W. & Swart, A. M. Early versus delayed treatment of relapsed ovarian cancer. Lancet 377, 380–381 (2011).

    Article  PubMed  Google Scholar 

  132. 132

    Kotsopoulos, J. et al. Factors influencing ovulation and the risk of ovarian cancer in BRCA1 and BRCA2 mutation carriers. Int. J. Cancer 137, 1136–1146 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. 133

    Trabert, B. et al. Aspirin, nonaspirin nonsteroidal anti-inflammatory drug, and acetaminophen use and risk of invasive epithelial ovarian cancer: a pooled analysis in the Ovarian Cancer Association Consortium. J. Natl. Cancer Inst. 106, djt431 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  134. 134

    Baandrup, L., Kjaer, S. K., Olsen, J. H., Dehlendorff, C. & Friis, S. Low-dose aspirin use and the risk of ovarian cancer in Denmark. Ann. Oncol. 4, 787–792 (2014).

    Google Scholar 

  135. 135

    Kumar, S. et al. Metformin intake is associated with better survival in ovarian cancer: a case-control study. Cancer 119, 555–562 (2013).

    Article  CAS  PubMed  Google Scholar 

  136. 136

    Lengyel, E. et al. Metformin inhibits ovarian cancer growth and increases sensitivity to paclitaxel in mouse models. Am. J. Obstet. Gynecol. 212, e1–479.e10 (2014).

    Google Scholar 

  137. 137

    Collaborative Group on Epidemiological Studies of Ovarian Cancer. Menopausal hormone use and ovarian cancer risk: individual participant meta-analysis of 52 epidemiological studies. Lancet 385, 1835–1842 (2015).

  138. 138

    Collaborative Group on Epidemiological Studies of Ovarian Cancer. Ovarian cancer and body size: individual participant meta-analysis including 25,157 women with ovarian cancer from 47 epidemiological studies. PLoS Med. 9, e1001200 (2012).

  139. 139

    Bristow, R. E. et al. Disparities in ovarian cancer care quality and survival according to race and socioeconomic status. J. Natl Cancer Inst. 105, 823–832 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  140. 140

    Norquist, B. M. et al. Characteristics of women with ovarian carcinoma who have BRCA1 and BRCA2 mutations not identified by clinical testing. Gynecol. Oncol. 128, 483–487 (2013).

    Article  CAS  PubMed  Google Scholar 

  141. 141

    Daniels, M. S. et al. Underestimation of risk of a BRCA1 or BRCA2 mutation in women with high-grade serous ovarian cancer by BRCAPRO: a multi-institution study. J. Clin. Oncol. 32, 1249–1255 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  142. 142

    Schrader, K. A. et al. Germline BRCA1 and BRCA2 mutations in ovarian cancer: utility of a histology-based referral strategy. Obstet. Gynecol. 120, 235–240 (2012).

    Article  CAS  PubMed  Google Scholar 

  143. 143

    Song, H. et al. The contribution of deleterious germline mutations in BRCA1, BRCA2 and the mismatch repair genes to ovarian cancer in the population. Hum. Mol. Genet. 23, 4703–4709 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. 144

    Pennington, K. P. et al. Germline and somatic mutations in homologous recombination genes predict platinum response and survival in ovarian, fallopian tube, and peritoneal carcinomas. Clin. Cancer Res. 20, 764–775 (2014).

    Article  CAS  PubMed  Google Scholar 

  145. 145

    Manchanda, R. et al. Cost-effectiveness of population screening for BRCA mutations in Ashkenazi jewish women compared with family history-based testing. J. Natl Cancer Inst. 107, 380 (2015).

    PubMed  Google Scholar 

  146. 146

    Manchanda, R. et al. Population testing for cancer predisposing BRCA1/BRCA2 mutations in the Ashkenazi-Jewish community: a randomized controlled trial. J. Natl Cancer Inst. 107, 379 (2015).

    PubMed  Google Scholar 

  147. 147

    Meyer, L. A. et al. Evaluating women with ovarian cancer for BRCA1 and BRCA2 mutations: missed opportunities. Obstet. Gynecol. 115, 945–952 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  148. 148

    Loveday, C. et al. Germline RAD51C mutations confer susceptibility to ovarian cancer. Nat. Genet. 44, 475–476 (2012).

    Article  CAS  PubMed  Google Scholar 

  149. 149

    Loveday, C. et al. Germline mutations in RAD51D confer susceptibility to ovarian cancer. Nat. Genet. 43, 879–882 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  150. 150

    Meindl, A. et al. Germline mutations in breast and ovarian cancer pedigrees establish RAD51C as a human cancer susceptibility gene. Nat. Genet. 42, 410–414 (2010).

    Article  CAS  PubMed  Google Scholar 

  151. 151

    Rafnar, T. et al. Mutations in BRIP1 confer high risk of ovarian cancer. Nat. Genet. 43, 1104–1107 (2011).

    Article  CAS  PubMed  Google Scholar 

  152. 152

    Kuchenbaecker, K. B. et al. Identification of six new susceptibility loci for invasive epithelial ovarian cancer. Nat. Genet. 47, 164–171 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  153. 153

    Wenzel, L. et al. Biopsychological stress factors in BRCA mutation carriers. Psychosomatics 53, 582–590 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  154. 154

    Bell, K. Biomarkers, the molecular gaze and the transformation of cancer survivorship. Biosocieties 8, 124–143 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  155. 155

    Kwon, J. S. et al. Prophylactic salpingectomy and delayed oophorectomy as an alternative for BRCA mutation carriers. Obstet. Gynecol. 121, 14–24 (2013).

    Article  PubMed  Google Scholar 

  156. 156

    McAlpine, J. N. et al. Opportunistic salpingectomy: uptake, risks, and complications of a regional initiative for ovarian cancer prevention. Am. J. Obstet. Gynecol. 210, 471e1-11 (2014).

    Article  Google Scholar 

  157. 157

    Pearce, C. L. et al. Population distribution of lifetime risk of ovarian cancer in the United States. Cancer Epidemiol. Biomarkers Prev. 24, 671–676 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  158. 158

    Buys, S. S. et al. Effect of screening on ovarian cancer mortality: the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Randomized Controlled Trial. JAMA 305, 2295–2303 (2011).

    Article  CAS  PubMed  Google Scholar 

  159. 159

    Menon, U. et al. Risk algorithm using serial biomarker measurements doubles the number of screen-detected cancers compared with a single-threshold rule in the United Kingdom collaborative trial of ovarian cancer screening. J. Clin. Oncol. 33, 2062–2071 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  160. 160

    Horowitz, N. S. et al. Does aggressive surgery improve outcomes? interaction between preoperative disease burden and complex surgery in patients with advanced-stage ovarian cancer: an analysis of GOG 182. J. Clin. Oncol. 33, 937–943 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  161. 161

    Menon, U., Griffin, M. & Gentry-Maharaj, A. Ovarian cancer screening—current status, future directions. Gynecol. Oncol. 132, 490–495 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  162. 162

    Drescher, C. W. et al. Longitudinal screening algorithm that incorporates change over time in CA125 levels identifies ovarian cancer earlier than a single-threshold rule. J. Clin. Oncol. 31, 387–392 (2013).

    Article  PubMed  Google Scholar 

  163. 163

    Forshew, T. et al. Noninvasive identification and monitoring of cancer mutations by targeted deep sequencing of plasma DNA. Sci. Transl Med. 4, 136ra68 (2012).

    Article  CAS  PubMed  Google Scholar 

  164. 164

    Kinde, I. et al. Evaluation of DNA from the Papanicolaou test to detect ovarian and endometrial cancers. Sci. Transl Med. 5, 167ra4 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  165. 165

    McAlpine, J. N. et al. Autofluorescence imaging can identify preinvasive or clinically occult lesions in fallopian tube epithelium: a promising step towards screening and early detection. Gynecol. Oncol. 120, 385–392 (2011).

    Article  CAS  PubMed  Google Scholar 

  166. 166

    Lutz, A. M. et al. Ultrasound molecular imaging in a human CD276 expression-modulated murine ovarian cancer model. Clin. Cancer Res. 20, 1313–1322 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  167. 167

    Bristow, R. E., Montz, F. J., Lagasse, L. D., Leuchter, R. S. & Karlan, B. Y. Survival impact of surgical cytoreduction in stage IV epithelial ovarian cancer. Gynecol. Oncol. 72, 278–287 (1999).

    Article  CAS  PubMed  Google Scholar 

  168. 168

    du Bois, A. et al. Role of surgical outcome as prognostic factor in advanced epithelial ovarian cancer: a combined exploratory analysis of 3 prospectively randomized phase 3 multicenter trials: by the Arbeitsgemeinschaft Gynaekologische Onkologie Studiengruppe Ovarialkarzinom (AGO-OVAR) and the Groupe d'Investigateurs Nationaux Pour les Etudes des Cancers de l'Ovaire (GINECO). Cancer 115, 1234–1244 (2009).

    Article  CAS  PubMed  Google Scholar 

  169. 169

    Vergote, I. et al. Neoadjuvant chemotherapy or primary surgery in stage IIIC or IV ovarian cancer. N. Engl. J. Med. 363, 943–953 (2010).

    Article  CAS  PubMed  Google Scholar 

  170. 170

    Naik, R., Edmondson, R. J., Galaal, K., Hatem, M. H. & Godfrey, K. A. A statement for extensive primary cytoreductive surgery in advanced ovarian cancer. BJOG 115, 1713–1714 (2008).

    CAS  PubMed  Google Scholar 

  171. 171

    Enshaei, A., Robson, C. N. & Edmondson, R. J. Artificial intelligence systems as prognostic and predictive tools in ovarian cancer. Ann. Surg. Oncol. 22, 3970–3975 (2015).

    Article  CAS  PubMed  Google Scholar 

  172. 172

    van Meurs, H. S. et al. Which patients benefit most from primary surgery or neoadjuvant chemotherapy in stage IIIC or IV ovarian cancer? An exploratory analysis of the European Organisation for Research and Treatment of Cancer 55971 randomised trial. Eur. J. Cancer 49, 3191–3201 (2013).

    Article  PubMed  Google Scholar 

  173. 173

    Riester, M. et al. Risk prediction for late-stage ovarian cancer by meta-analysis of 1525 patient samples. J. Natl Cancer Inst. 106, dju048 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  174. 174

    Nick, A. M., Coleman, R. L., Ramirez, P. T. & Sood, A. K. A framework for a personalized surgical approach to ovarian cancer. Nat. Rev. Clin. Oncol. 12, 239–245 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  175. 175

    Harter, P. et al. Prospective validation study of a predictive score for operability of recurrent ovarian cancer: the Multicenter Intergroup Study DESKTOP II. A project of the AGO Kommission OVAR, AGO Study Group, NOGGO, AGO-Austria, and MITO. Int. J. Gynecol. Cancer 21, 289–295 (2011).

    Article  PubMed  Google Scholar 

  176. 176

    Harter, P. et al. Surgery in recurrent ovarian cancer: the Arbeitsgemeinschaft Gynaekologische Onkologie (AGO) DESKTOP OVAR trial. Ann. Surg. Oncol. 13, 1702–1710 (2006).

    Article  PubMed  Google Scholar 

  177. 177

    Fotopoulou, C. et al. Value of tertiary cytoreductive surgery in epithelial ovarian cancer: an international multicenter evaluation. Ann. Surg. Oncol. 20, 1348–1354 (2013).

    Article  PubMed  Google Scholar 

  178. 178

    Hanahan, D. & Weinberg, R. A. Hallmarks of cancer: the next generation. Cell 144, 646–674 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  179. 179

    Mittag, J., Winterhager, E., Bauer, K. & Grummer, R. Congenital hypothyroid female pax8-deficient mice are infertile despite thyroid hormone replacement therapy. Endocrinology 148, 719–725 (2007).

    Article  CAS  PubMed  Google Scholar 

  180. 180

    Tacha, D., Zhou, D. & Cheng, L. Expression of PAX8 in normal and neoplastic tissues: a comprehensive immunohistochemical study. Appl. Immunohistochem Mol. Morphol. 19, 293–299 (2011).

    Article  CAS  PubMed  Google Scholar 

  181. 181

    Laury, A. R. et al. PAX8 reliably distinguishes ovarian serous tumors from malignant mesothelioma. Am. J. Surg. Pathol. 34, 627–635 (2010).

    PubMed  Google Scholar 

  182. 182

    Whiteaker, J. R. et al. CPTAC Assay Portal: a repository of targeted proteomic assays. Nat. Methods 11, 703–704 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  183. 183

    Aspuria, P. J. et al. Succinate dehydrogenase inhibition leads to epithelial-mesenchymal transition and reprogrammed carbon metabolism. Cancer Metab. 2, 21 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  184. 184

    Karst, A. M. et al. Stathmin 1, a marker of PI3K pathway activation and regulator of microtubule dynamics, is expressed in early pelvic serous carcinomas. Gynecol. Oncol. 123, 5–12 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding authors

Correspondence to David D. Bowtell or Frances R. Balkwill.

Ethics declarations

Competing interests

The following authors declare competing interests: D.D.B. has received research grant funding from Astra Zeneca, Pfizer and Roche. M.A.B. declares participation in ad-hoc advisory boards regarding investigational (non-marketed) agents for development of clinical trials in ovarian cancer, including AbbVie, AstraZeneca, Novartis, Sanofi-Aventis, Clovis, Daiichi-Sankyo, Cerulean, Emdocyte, Immunogen, Oxigene, Genentech-Roche and Boehringer Ingelheim. He declares financial compensation and travel support for these meetings. He has participated in Independent Data Monitoring Committees (IDMC) for Phase III trials in ovarian cancer for Genentech-Roche and Boehringer Ingelheim, with financial compensation for time and travel. J.D.B. is cofounder and own shares in Inivata Ltd. R.C.B. has royalties from Fujirebio Diagnostics. G.C. has undertaken consultancies for Roche, Sanofi and Pierre-Fabre, and has grants or support for research from Boehringer Ingelheim. R.D. is on the scientific advisory board of Siamab Therapeutics. C.G's employer (Edinburgh University) has received payments for his attendance at advisory boards from Roche, AstraZeneca and Nucana, for his lectures from Roche and AstraZeneca, and for clinical research from AstraZeneca, Aprea and GlaxoSmithKline. He is named as an inventor on issued patents and patent applications regarding the Almac AADX assay. J.G. is cofounder and shareholder of HalioDx Biotech company. D.G.H. is founder, shareholder and Chief Medical Officer of Contextual Genomics. B.Y.K. has grants or support for research from AstraZeneca, Tesaro, Dana-Farber Cancer Center/NCI, Amgen and Cancer International Research Group, and is co-inventor of 'Molecular Signatures of Ovarian Cancer', patent pending. D.A.L. declares speaking honoraria from Roche Products, has a patent application on Detection of Ovarian Cancer and stock options in Critical Outcomes Technologies I.A.M. is on advisory boards for Clovis Oncology, Astra Zeneca and Roche. U.M. owns stock in Abcodia that has an interest in early detection of ovarian cancer. D.J.P. has obtained consulting fees from Lion Biotherapeutics, research funding through an alliance between The University of Pennsylvania and Novartis, and patents on the application of chimeric antigen receptors in oncology. C.L.S. has had honoraria, travel and accommodation expenses from Roche, Astra Zeneca, Clovis Oncology and given expert testimony for Astra Zeneca and Speakers' Bureau Prime Oncology. All other authors declare no competing interests.

Related links

PowerPoint slides

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Bowtell, D., Böhm, S., Ahmed, A. et al. Rethinking ovarian cancer II: reducing mortality from high-grade serous ovarian cancer. Nat Rev Cancer 15, 668–679 (2015). https://doi.org/10.1038/nrc4019

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing