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The Diagnostic and Prognostic Potential of microRNAs in Epithelial Ovarian Carcinoma

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Abstract

Ovarian cancer causes more than 100,000 deaths globally per year. Despite intensive research efforts, there has been little improvement in the overall survival of patients over the past three decades. Most patients are not diagnosed until the cancer is at an advanced stage, by which time their chances of still being alive after 5 years are appallingly low. Attempts to extend life in these patients have been, for the most part, unsuccessful. This owes partly to the lack of suitable biomarkers for stratifying patients at the molecular level, into responders and non-responders. This would lead to more drugs being shown to have a clinical benefit and being approved for use in subgroups of patients. There is also a desperate need for improved biomarkers for earlier detection of ovarian cancer; if the disease is detected sooner there is a significantly improved outlook. In this review, we outline the evidence that microRNAs are deregulated in ovarian cancer, what this can tell us about tumour progression and how it could be used to improve patient stratification in clinical trials. We also describe the potential for circulating microRNAs, both associated with proteins or carried in vesicles, to be used as diagnostics for earlier detection or as biomarkers for informing clinicians on the prognosis and best treatment of ovarian cancer.

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References

  1. Fitzmaurice C, Dicker D, Pain A, et al. The global burden of cancer 2013. JAMA Oncol. 2015;1(4):505–27.

    Article  PubMed  Google Scholar 

  2. Siegel RL, Miller KD, Jemal A. Cancer statistics. CA Cancer J Clin. 2016;66(1):7–30.

    Article  PubMed  Google Scholar 

  3. Smith RA, Andrews K, Brooks D, et al. Cancer screening in the United States, 2016: a review of current American Cancer Society guidelines and current issues in cancer screening. CA Cancer J Clin. 2016;66(2):96–114.

    Article  PubMed  Google Scholar 

  4. Galluzzi L, Senovilla L, Vitale I, et al. Molecular mechanisms of cisplatin resistance. Oncogene. 2012;31(15):1869–83.

    Article  CAS  PubMed  Google Scholar 

  5. Cannistra SA. Cancer of the ovary. N Engl J Med. 2004;351(24):2519–29.

    Article  CAS  PubMed  Google Scholar 

  6. Shih Ie M, Kurman RJ. Ovarian tumorigenesis: a proposed model based on morphological and molecular genetic analysis. Am J Pathol. 2004;64(5):1511–8.

    Article  Google Scholar 

  7. Bartel DP. MicroRNAs: target recognition and regulatory functions. Cell. 2009;136(2):215–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Ha M, Kim VN. Regulation of microRNA biogenesis. Nat Rev Mol Cell Biol. 2014;15(8):509–24.

    Article  CAS  PubMed  Google Scholar 

  9. Iorio MV, Croce CM. MicroRNAs in cancer: small molecules with a huge impact. J Clin Oncol. 2009;27(34):5848–56.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Jacobs LA, Bewicke-Copley F, Poolman MG, et al. Meta-analysis using a novel database, miRStress, reveals miRNAs that are frequently associated with the radiation and hypoxia stress-responses. PLoS One. 2013;8(11):e80844.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Mendell JT, Olson EN. MicroRNAs in stress signaling and human disease. Cell. 2012;148(6):1172–87.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Tüfekci KU, Meuwissen RL, Genç S. The role of microRNAs in biological processes. Methods Mol Biol. 2014;1107:15–31.

    Article  PubMed  CAS  Google Scholar 

  13. Katz B, Tropé CG, Reich R, Davidson B. MicroRNAs in ovarian cancer. Hum Pathol. 2015;46(9):1245–56.

    Article  CAS  PubMed  Google Scholar 

  14. Garofalo M, Croce CM. MicroRNAs as therapeutic targets in chemoresistance. Drug Resist Updat. 2013;6(3–5):47–59.

    Article  CAS  Google Scholar 

  15. Llauradó M, Majem B, Altadill T, et al. MicroRNAs as prognostic markers in ovarian cancer. Mol Cell Endocrinol. 2014;390(1–2):73–84.

    Article  PubMed  CAS  Google Scholar 

  16. Pink RC, Samuel P, Massa D, et al. The passenger strand, miR-21-3p, plays a role in mediating cisplatin resistance in ovarian cancer cells. Gynecol Oncol. 2015;137(1):143–51.

    Article  CAS  PubMed  Google Scholar 

  17. Samuel P, Pink RC, Caley DP, et al. Over-expression of miR-31 or loss of KCNMA1 leads to increased cisplatin resistance in ovarian cancer cells. Tumour Biol. 2016;37(2):2565–73.

    Article  CAS  PubMed  Google Scholar 

  18. Samuel P, Pink RC, Brooks SA, Carter DR. miRNAs and ovarian cancer: a miRiad of mechanisms to induce cisplatin drug resistance. Expert Rev Anticancer Ther. 2016;16(1):57–70.

    Article  CAS  PubMed  Google Scholar 

  19. Johnstone RM. Exosomes biological significance: a concise review. Blood Cells Mol Dis. 2006;36(2):315–21.

    Article  CAS  PubMed  Google Scholar 

  20. Bang C, Thum T. Exosomes: new players in cell-cell communication. Int J Biochem Cell Biol. 2012;44(11):2060–4.

    Article  CAS  PubMed  Google Scholar 

  21. Yáñez-Mó M, Siljander PR, Andreu Z, et al. Biological properties of extracellular vesicles and their physiological functions. J Extracell Vesicles. 2015;4:27066.

    Article  PubMed  Google Scholar 

  22. Mulcahy LA, Pink RC, Carter DR. Routes and mechanisms of extracellular vesicle uptake. J Extracell Vesicles. 2014;3:24641. doi:10.3402/jev.v3.24641.

    Google Scholar 

  23. Skog J, Wurdinger T, van Rijn S, et al. Glioblastoma microvesicles transport RNA and proteins that promote tumour growth and provide diagnostic biomarkers. Nat Cell Biol. 2008;10(12):1470–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Gercel-Taylor C, Atay S, Tullis RH, et al. Nanoparticle analysis of circulating cell-derived vesicles in ovarian cancer patients. Anal Biochem. 2012;428(1):44–53.

    Article  CAS  PubMed  Google Scholar 

  25. Prat J. Staging classification for cancer of the ovary, fallopian tube, and peritoneum. Int J Gynaecol Obstet. 2014;124(1):1–5.

    Article  PubMed  Google Scholar 

  26. Santillan A, Kim YW, Zahurak ML, et al. Differences of chemoresistance assay between invasive micropapillary/low-grade serous ovarian carcinoma and high-grade serous ovarian carcinoma. Int J Gynecol Cancer. 2007;17(3):601–6.

    Article  CAS  PubMed  Google Scholar 

  27. Pisano C, Greggi S, Tambaro R, et al. Activity of chemotherapy in mucinous epithelial ovarian cancer: a retrospective study. Anticancer Res. 2005;25(5):3501–5.

    CAS  PubMed  Google Scholar 

  28. Itamochi H, Kigawa J, Terakawa N. Mechanisms of chemoresistance and poor prognosis in ovarian clear cell carcinoma. Cancer Sci. 2008;99(4):653–8.

    Article  CAS  PubMed  Google Scholar 

  29. Cooke SL, Brenton JD. Evolution of platinum resistance in high-grade serous ovarian cancer. Lancet Oncol. 2011;12(12):1169–74.

    Article  CAS  PubMed  Google Scholar 

  30. Schorge JO, McCann C, Del Carmen MG. Surgical debulking of ovarian cancer: what difference does it make? Rev Obstet Gynecol. 2010;3(3):111–7.

    PubMed  PubMed Central  Google Scholar 

  31. Polterauer S, Vergote I, Concin N, et al. Prognostic value of residual tumor size in patients with epithelial ovarian cancer FIGO stages IIA-IV: analysis of the OVCAD data. Int J Gynecol Cancer. 2012;22(3):380–5.

    Article  PubMed  Google Scholar 

  32. Raja FA, Chopra N, Ledermann JA. Optimal first-line treatment in ovarian cancer. Ann Oncol. 2012;23(Suppl. 10):x118–27.

    Article  PubMed  Google Scholar 

  33. du Bois A, Luck HJ, Meier W, et al. A randomized clinical trial of cisplatin/paclitaxel versus carboplatin/paclitaxel as first-line treatment of ovarian cancer. J Natl Cancer Inst. 2003;95(17):1320–9.

    Article  PubMed  CAS  Google Scholar 

  34. McGuire WP, Hoskins WJ, Brady MF, et al. Cyclophosphamide and cisplatin compared with paclitaxel and cisplatin in patients with stage III and stage IV ovarian cancer. N Engl J Med. 1996;334(1):1–6.

    Article  CAS  PubMed  Google Scholar 

  35. Oza AM, Cook AD, Pfisterer J, et al. Standard chemotherapy with or without bevacizumab for women with newly diagnosed ovarian cancer (ICON7): overall survival results of a phase 3 randomised trial. Lancet Oncol. 2015;16(8):928–36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Meehan RS, Chen AP. New treatment option for ovarian cancer: PARP inhibitors. Gynecol Oncol Res Pract. 2016;3:3.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Moschetta M, George A, Kaye SB, Banerjee S. BRCA somatic mutations and epigenetic BRCA modifications in serous ovarian cancer. Ann Oncol. 2016;27(8):1449–55.

    Article  CAS  PubMed  Google Scholar 

  38. Narod SA. Have we given up on a cure for ovarian cancer? Curr Oncol. 2015;22(3):e139–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Kurman RJ, Shih Ie M. The dualistic model of ovarian carcinogenesis: revisited, revised, and expanded. Am J Pathol. 2016;186(4):733–47.

    Article  PubMed  Google Scholar 

  40. Bell DBA, Birrer M, Chien J, et al. Integrated genomic analyses of ovarian carcinoma. Nature. 2011;474(7353):609–15.

    Article  CAS  Google Scholar 

  41. Singer G, Oldt R 3rd, Cohen Y, et al. Mutations in BRAF and KRAS characterize the development of low-grade ovarian serous carcinoma. J Natl Cancer Inst. 2003;95(6):484–6.

    Article  CAS  PubMed  Google Scholar 

  42. Grisham RN, Iyer G, Garg K, et al. BRAF mutation is associated with early stage disease and improved outcome in patients with low-grade serous ovarian cancer. Cancer. 2013;119(3):548–54.

    Article  CAS  PubMed  Google Scholar 

  43. Sun C, Li N, Ding D, et al. The role of BRCA status on the prognosis of patients with epithelial ovarian cancer: a systematic review of the literature with a meta-analysis. PLoS One. 2014;9(5):e95285.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  44. Vencken PM, Kriege M, Hoogwerf D, et al. Chemosensitivity and outcome of BRCA1- and BRCA2-associated ovarian cancer patients after first-line chemotherapy compared with sporadic ovarian cancer patients. Ann Oncol. 2011;22(6):1346–52.

    Article  CAS  PubMed  Google Scholar 

  45. Li B, Jin H, Yu Y, et al. HOXA10 is overexpressed in human ovarian clear cell adenocarcinoma and correlates with poor survival. Int J Gynecol Cancer. 2009;19(8):1347–52.

    Article  PubMed  Google Scholar 

  46. Howitt BE, Hanamornroongruang S, Lin DI, et al. Evidence for a dualistic model of high-grade serous carcinoma: BRCA mutation status, histology, and tubal intraepithelial carcinoma. Am J Surg Pathol. 2015;39(3):287–93.

    Article  PubMed  Google Scholar 

  47. Soslow RA, Han G, Park KJ, et al. Morphologic patterns associated with BRCA1 and BRCA2 genotype in ovarian carcinoma. Mod Pathol. 2012;25(4):625–36.

    Article  CAS  PubMed  Google Scholar 

  48. Tothill RW, Tinker AV, George J, et al. Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome. Clin Cancer Res. 2008;14(16):5198–208.

    Article  CAS  PubMed  Google Scholar 

  49. Konecny GE, Wang C, Hamidi H, et al. Prognostic and therapeutic relevance of molecular subtypes in high-grade serous ovarian cancer. J Natl Cancer Inst. 2014;106(10). doi:10.1093/jnci/dju249.

  50. Winterhoff B, Hamidi H, Wang C, et al. Molecular classification of high grade endometrioid and clear cell ovarian cancer using TCGA gene expression signatures. Gynecol Oncol. 2016;41(1):95–100.

    Article  CAS  Google Scholar 

  51. Lu L, Katsaros D, Canuto EM, et al. LIN-28B/let-7a/IGF-II axis molecular subtypes are associated with epithelial ovarian cancer prognosis. Gynecol Oncol. 2016;141(1):121–7.

    Article  CAS  PubMed  Google Scholar 

  52. Lu L, Katsaros D, Risch HA, et al. MicroRNA let-7a modifies the effect of self-renewal gene HIWI on patient survival of epithelial ovarian cancer. Mol Carcinog. 2016;55(4):357–65.

    Article  CAS  PubMed  Google Scholar 

  53. Pennington KP, Walsh T, Harrell MI, 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. 2014;20(3):764–75.

    Article  CAS  PubMed  Google Scholar 

  54. Kim G, Ison G, McKee AE, et al. FDA approval summary: olaparib monotherapy in patients with deleterious germline BRCA-mutated advanced ovarian cancer treated with three or more lines of chemotherapy. Clin Cancer Res. 2015;21(19):4257–61.

    Article  CAS  PubMed  Google Scholar 

  55. Bitler BG, Aird KM, Garipov A, et al. Synthetic lethality by targeting EZH2 methyltransferase activity in ARID1A-mutated cancers. Nat Med. 2015;21(3):231–8.

    CAS  PubMed  Google Scholar 

  56. Bookman MA. Optimal primary therapy of ovarian cancer. Ann Oncol. 2016;27(Suppl 1):i58–62.

    Article  PubMed  Google Scholar 

  57. Ryland GL, Bearfoot JL, Doyle MA, et al. MicroRNA genes and their target 3′-untranslated regions are infrequently somatically mutated in ovarian cancers. PLoS One. 2012;7(4):e35805.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Zhang L, Volinia S, Bonome T, et al. Genomic and epigenetic alterations deregulate microRNA expression in human epithelial ovarian cancer. Proc Natl Acad Sci USA. 2008;105(19):7004–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Lu L, Katsaros D, Shaverdashvili K, et al. Pluripotent factor lin-28 and its homologue lin-28b in epithelial ovarian cancer and their associations with disease outcomes and expression of let-7a and IGF-II. Eur J Cancer. 2009;45(12):2212–8.

    Article  CAS  PubMed  Google Scholar 

  60. Kallen AN, Zhou XB, Xu J, et al. The imprinted H19 lncRNA antagonizes let-7 microRNAs. Mol Cell. 2013;52(1):101–12.

    Article  CAS  PubMed  Google Scholar 

  61. Poliseno L, Salmena L, Zhang J, et al. A coding-independent function of gene and pseudogene mRNAs regulates tumour biology. Nature. 2010;465(7301):1033–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Iorio MV, Visone R, Di Leva G, et al. MicroRNA signatures in human ovarian cancer. Cancer Res. 2007;67(18):8699–707.

    Article  CAS  PubMed  Google Scholar 

  63. Yang H, Kong W, He L, et al. MicroRNA expression profiling in human ovarian cancer: miR-214 induces cell survival and cisplatin resistance by targeting PTEN. Cancer Res. 2008;68(2):425–33.

    Article  CAS  PubMed  Google Scholar 

  64. Vilming Elgaaen B, Olstad OK, Haug KB, et al. Global miRNA expression analysis of serous and clear cell ovarian carcinomas identifies differentially expressed miRNAs including miR-200c-3p as a prognostic marker. BMC Cancer. 2014;14:80.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  65. Kim TH, Kim YK, Kwon Y, et al. Deregulation of miR-519a, 153, and 485-5p and its clinicopathological relevance in ovarian epithelial tumours. Histopathology. 2010;57(5):734–43.

    Article  PubMed  Google Scholar 

  66. Vecchione A, Belletti B, Lovat F, et al. A microRNA signature defines chemoresistance in ovarian cancer through modulation of angiogenesis. Proc Natl Acad Sci USA. 2013;110(24):9845–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Kim TH, Song JY, Park H, et al. miR-145, targeting high-mobility group A2, is a powerful predictor of patient outcome in ovarian carcinoma. Cancer Lett. 2015;356(2 Pt B):937–45.

    Article  CAS  PubMed  Google Scholar 

  68. Dong R, Liu X, Zhang Q, et al. miR-145 inhibits tumor growth and metastasis by targeting metadherin in high-grade serous ovarian carcinoma. Oncotarget. 2014;5(21):10816–29.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Liu G, Yang D, Rupaimoole R, et al. Augmentation of response to chemotherapy by microRNA-506 through regulation of RAD51 in serous ovarian cancers. J Natl Cancer Inst. 2015;107(7):djv108.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Sun Y, Hu L, Zheng H, et al. MiR-506 inhibits multiple targets in the epithelial-to-mesenchymal transition network and is associated with good prognosis in epithelial ovarian cancer. J Pathol. 2015;235(1):25–36.

    Article  CAS  PubMed  Google Scholar 

  71. Shell S, Park SM, Radjabi AR, et al. Let-7 expression defines two differentiation stages of cancer. Proc Natl Acad Sci USA. 2007;104(27):11400–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Yang N, Kaur S, Volinia S, et al. MicroRNA microarray identifies Let-7i as a novel biomarker and therapeutic target in human epithelial ovarian cancer. Cancer Res. 2008;68(24):10307–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Nam EJ, Yoon H, Kim SW, et al. MicroRNA expression profiles in serous ovarian carcinoma. Clin Cancer Res. 2008;14(9):2690–5.

    Article  CAS  PubMed  Google Scholar 

  74. Dahiya N, Sherman-Baust CA, Wang TL, et al. MicroRNA expression and identification of putative miRNA targets in ovarian cancer. PLoS One. 2008;3(6):e2436.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  75. Lu L, Schwartz P, Scarampi L, et al. MicroRNA let-7a: a potential marker for selection of paclitaxel in ovarian cancer management. Gynecol Oncol. 2011;122(2):366–71.

    Article  CAS  PubMed  Google Scholar 

  76. Lu L, Katsaros D, de la Longrais IA, Sochirca O, Yu H. Hypermethylation of let-7a-3 in epithelial ovarian cancer is associated with low insulin-like growth factor-II expression and favorable prognosis. Cancer Res. 2007;67(21):10117–22.

    Article  CAS  PubMed  Google Scholar 

  77. Marchini S, Cavalieri D, Fruscio R, et al. Association between miR-200c and the survival of patients with stage I epithelial ovarian cancer: a retrospective study of two independent tumour tissue collections. Lancet Oncol. 2011;12(3):273–85.

    Article  CAS  PubMed  Google Scholar 

  78. Hu X, Macdonald DM, Huettner PC, et al. A miR-200 microRNA cluster as prognostic marker in advanced ovarian cancer. Gynecol Oncol. 2009;114(3):457–64.

    Article  CAS  PubMed  Google Scholar 

  79. Leskela S, Leandro-Garcia LJ, Mendiola M, et al. The miR-200 family controls beta-tubulin III expression and is associated with paclitaxel-based treatment response and progression-free survival in ovarian cancer patients. Endocr Relat Cancer. 2011;18(1):85–95.

    Article  CAS  PubMed  Google Scholar 

  80. Chao A, Lin CY, Lee YS, et al. Regulation of ovarian cancer progression by microRNA-187 through targeting disabled homolog-2. Oncogene. 2012;31(6):764–75.

    Article  CAS  PubMed  Google Scholar 

  81. Cao Q, Lu K, Dai S, et al. Clinicopathological and prognostic implications of the miR-200 family in patients with epithelial ovarian cancer. Int J Clin Exp Pathol. 2014;7(5):2392–401.

    CAS  PubMed  PubMed Central  Google Scholar 

  82. Koutsaki M, Spandidos DA, Zaravinos A. Epithelial-mesenchymal transition-associated miRNAs in ovarian carcinoma, with highlight on the miR-200 family: prognostic value and prospective role in ovarian cancer therapeutics. Cancer Lett. 2014;351(2):173–81.

    Article  CAS  PubMed  Google Scholar 

  83. Prislei S, Martinelli E, Mariani M, et al. MiR-200c and HuR in ovarian cancer. BMC Cancer. 2013;13:72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Flavin R, Smyth P, Barrett C, et al. miR-29b expression is associated with disease-free survival in patients with ovarian serous carcinoma. Int J Gynecol Cancer. 2009;19(4):641–7.

    Article  PubMed  Google Scholar 

  85. Dai F, Zhang Y, Chen Y. Involvement of miR-29b signaling in the sensitivity to chemotherapy in patients with ovarian carcinoma. Hum Pathol. 2014;45(6):1285–93.

    Article  CAS  PubMed  Google Scholar 

  86. Li N, Kaur S, Greshock J, et al. A combined array-based comparative genomic hybridization and functional library screening approach identifies mir-30d as an oncomir in cancer. Cancer Res. 2012;72(1):154–64.

    Article  CAS  PubMed  Google Scholar 

  87. Lee H, Park CS, Deftereos G, et al. MicroRNA expression in ovarian carcinoma and its correlation with clinicopathological features. World J Surg Oncol. 2012;10:174.

    Article  PubMed  PubMed Central  Google Scholar 

  88. Blagden SP. Harnessing pandemonium: the clinical implications of tumor heterogeneity in ovarian cancer. Front Oncol. 2015;5:149.

    Article  PubMed  PubMed Central  Google Scholar 

  89. Kobel M, Kalloger SE, Boyd N, et al. Ovarian carcinoma subtypes are different diseases: implications for biomarker studies. PLoS Med. 2008;5(12):e232.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  90. Bolton KL, Chenevix-Trench G, Goh C, et al. Association between BRCA1 and BRCA2 mutations and survival in women with invasive epithelial ovarian cancer. JAMA. 2012;307(4):382–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Gu Y, Zhang M, Peng F, et al. The BRCA1/2-directed miRNA signature predicts a good prognosis in ovarian cancer patients with wild-type BRCA1/2. Oncotarget. 2015;6(4):2397–406.

    Article  PubMed  Google Scholar 

  92. Holschneider CH, Berek JS. Ovarian cancer: epidemiology, biology, and prognostic factors. Semin Surg Oncol. 2000;19(1):3–10.

    Article  CAS  PubMed  Google Scholar 

  93. Hogdall EV, Christensen L, Kjaer SK, et al. CA125 expression pattern, prognosis and correlation with serum CA125 in ovarian tumor patients: from The Danish “MALOVA” Ovarian Cancer Study. Gynecol Oncol. 2007;104(3):508–15.

    Article  CAS  PubMed  Google Scholar 

  94. Badgwell D, Bast RC Jr. Early detection of ovarian cancer. Dis Markers. 2017;23(5–6):397–410.

    Google Scholar 

  95. Meinhold-Heerlein I, Hauptmann S. The heterogeneity of ovarian cancer. Arch Gynecol Obstet. 2014;289(2):237–9.

    Article  CAS  PubMed  Google Scholar 

  96. Jacobs IJ, Menon U, Ryan A, et al. Ovarian cancer screening and mortality in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS): a randomised controlled trial. Lancet. 2016;387(10022):945–56.

    Article  PubMed  PubMed Central  Google Scholar 

  97. Buys SS, Partridge E, Black A, et al. Effect of screening on ovarian cancer mortality: the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer screening randomized controlled trial. JAMA. 2011;305(22):2295–303.

    Article  CAS  PubMed  Google Scholar 

  98. Forstner R, Meissnitzer M, Cunha TM. Update on imaging of ovarian cancer. Curr Radiol Rep. 2016;4:31.

    Article  PubMed  PubMed Central  Google Scholar 

  99. Ueland FR, Desimone CP, Seamon LG, et al. Effectiveness of a multivariate index assay in the preoperative assessment of ovarian tumors. Obstet Gynecol. 2011;117(6):1289–97.

    Article  PubMed  Google Scholar 

  100. Nolen BM, Lokshin AE. Biomarker testing for ovarian cancer: clinical utility of multiplex assays. Mol Diagn Ther. 2013;17(3):139–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Moore RG, McMeekin DS, Brown AK, et al. A novel multiple marker bioassay utilizing HE4 and CA125 for the prediction of ovarian cancer in patients with a pelvic mass. Gynecol Oncol. 2009;112(1):40–6.

    Article  CAS  PubMed  Google Scholar 

  102. Jacobs I, Oram D, Fairbanks J, et al. A risk of malignancy index incorporating CA 125, ultrasound and menopausal status for the accurate preoperative diagnosis of ovarian cancer. Br J Obstet Gynaecol. 1990;97(10):922–9.

    Article  CAS  PubMed  Google Scholar 

  103. Mitchell PS, Parkin RK, Kroh EM, et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA. 2008;105(30):10513–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Resnick KE, Alder H, Hagan JP, et al. The detection of differentially expressed microRNAs from the serum of ovarian cancer patients using a novel real-time PCR platform. Gynecol Oncol. 2009;112(1):55–9.

    Article  CAS  PubMed  Google Scholar 

  105. Liang H, Jiang Z, Xie G, Lu Y. Serum microRNA-145 as a novel biomarker in human ovarian cancer. Tumour Biol. 2015;36(7):5305–13.

    Article  CAS  PubMed  Google Scholar 

  106. Hong F, Li Y, Xu Y, Zhu L. Prognostic significance of serum microRNA-221 expression in human epithelial ovarian cancer. J Int Med Res. 2013;41(1):64–71.

    Article  CAS  PubMed  Google Scholar 

  107. Kan CW, Hahn MA, Gard GB, et al. Elevated levels of circulating microRNA-200 family members correlate with serous epithelial ovarian cancer. BMC Cancer. 2012;12:627.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Shapira I, Oswald M, Lovecchio J, et al. Circulating biomarkers for detection of ovarian cancer and predicting cancer outcomes. Br J Cancer. 2014;110(4):976–83.

    Article  CAS  PubMed  Google Scholar 

  109. Langhe R, Norris L, Saadeh FA, et al. A novel serum microRNA panel to discriminate benign from malignant ovarian disease. Cancer Lett. 2015;356(2 Pt B):628–36.

    Article  CAS  PubMed  Google Scholar 

  110. Wei LQ, Liang HT, Qin DC, et al. MiR-212 exerts suppressive effect on SKOV3 ovarian cancer cells through targeting HBEGF. Tumour Biol. 2014;35(12):12427–34.

    Article  CAS  PubMed  Google Scholar 

  111. Hausler SF, Keller A, Chandran PA, et al. Whole blood-derived miRNA profiles as potential new tools for ovarian cancer screening. Br J Cancer. 2010;103(5):693–700.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Zheng H, Zhang L, Zhao Y, et al. Plasma miRNAs as diagnostic and prognostic biomarkers for ovarian cancer. PLoS One. 2013;8(11):e77853.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Calura E, Fruscio R, Paracchini L, et al. MiRNA landscape in stage I epithelial ovarian cancer defines the histotype specificities. Clin Cancer Res. 2013;19(15):4114–23.

    Article  CAS  PubMed  Google Scholar 

  114. Chung YW, Bae HS, Song JY, et al. Detection of microRNA as novel biomarkers of epithelial ovarian cancer from the serum of ovarian cancer patients. Int J Gynecol Cancer. 2013;23(4):673–9.

    Article  PubMed  Google Scholar 

  115. Suryawanshi S, Vlad AM, Lin HM, et al. Plasma microRNAs as novel biomarkers for endometriosis and endometriosis-associated ovarian cancer. Clin Cancer Res. 2013;19(5):1213–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Xu YZ, Xi QH, Ge WL, Zhang XQ. Identification of serum microRNA-21 as a biomarker for early detection and prognosis in human epithelial ovarian cancer. Asian Pac J Cancer Prev. 2013;14(2):1057–60.

    Article  PubMed  Google Scholar 

  117. Zuberi M, Khan I, Mir R, et al. Utility of serum miR-125b as a diagnostic and prognostic indicator and its alliance with a panel of tumor suppressor genes in epithelial ovarian cancer. PLoS One. 2016;11(4):e0153902.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  118. Zavesky L, Jandakova E, Turyna R, et al. Evaluation of cell-free urine microRNAs expression for the use in diagnosis of ovarian and endometrial cancers: a pilot study. Pathol Oncol Res. 2015;21(4):1027–35.

    Article  CAS  PubMed  Google Scholar 

  119. Jensen SG, Lamy P, Rasmussen MH, et al. Evaluation of two commercial global miRNA expression profiling platforms for detection of less abundant miRNAs. BMC Genomics. 2011;2:435.

    Article  CAS  Google Scholar 

  120. MacLellan SA, MacAulay C, Lam S, Garnis C. Pre-profiling factors influencing serum microRNA levels. BMC Clin Pathol. 2014;14:27.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  121. Valadi H, Ekstrom K, Bossios A, et al. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol. 2007;9(6):654–9.

    Article  CAS  PubMed  Google Scholar 

  122. Meng X, Muller V, Milde-Langosch K, et al. Diagnostic and prognostic relevance of circulating exosomal miR-373, miR-200a, miR-200b and miR-200c in patients with epithelial ovarian cancer. Oncotarget. 2016;7(13):16923–35.

    PubMed  PubMed Central  Google Scholar 

  123. Taylor DD, Gercel-Taylor C. MicroRNA signatures of tumor-derived exosomes as diagnostic biomarkers of ovarian cancer. Gynecol Oncol. 2008;110(1):13–21.

    Article  CAS  PubMed  Google Scholar 

  124. Vaksman O, Trope C, Davidson B, Reich R. Exosome-derived miRNAs and ovarian carcinoma progression. Carcinogenesis. 2014;35(9):2113–20.

    Article  CAS  PubMed  Google Scholar 

  125. Laios A, O’Toole S, Flavin R, et al. Potential role of miR-9 and miR-223 in recurrent ovarian cancer. Mol Cancer. 2008;7:35.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  126. Jin M, Yang Z, Ye W, et al. MicroRNA-150 predicts a favorable prognosis in patients with epithelial ovarian cancer, and inhibits cell invasion and metastasis by suppressing transcriptional repressor ZEB1. PLoS One. 2014;9(8):e103965.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  127. Chen S, Chen X, Xiu YL, et al. Inhibition of ovarian epithelial carcinoma tumorigenesis and progression by microRNA 106b mediated through the RhoC pathway. PLoS One. 2015;10(5):e0125714.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  128. Corney DC, Hwang CI, Matoso A, et al. Frequent downregulation of miR-34 family in human ovarian cancers. Clin Cancer Res. 2010;16(4):1119–28.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Wan WN, Zhang YQ, Wang XM, et al. Down-regulated miR-22 as predictive biomarkers for prognosis of epithelial ovarian cancer. Diagn Pathol. 2014;9:178.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  130. Bagnoli M, De Cecco L, Granata A, et al. Identification of a chrXq27.3 microRNA cluster associated with early relapse in advanced stage ovarian cancer patients. Oncotarget. 2011;2(12):1265–78.

    Article  PubMed  PubMed Central  Google Scholar 

  131. Eitan R, Kushnir M, Lithwick-Yanai G, et al. Tumor microRNA expression patterns associated with resistance to platinum based chemotherapy and survival in ovarian cancer patients. Gynecol Oncol. 2009;114(2):253–9.

    Article  CAS  PubMed  Google Scholar 

  132. Wurz K, Garcia RL, Goff BA, et al. MiR-221 and MiR-222 alterations in sporadic ovarian carcinoma: relationship to CDKN1B, CDKNIC and overall survival. Genes Chromosomes Cancer. 2010;49(7):577–84.

    CAS  PubMed  PubMed Central  Google Scholar 

  133. Guo F, Tian J, Lin Y, et al. Serum microRNA-92 expression in patients with ovarian epithelial carcinoma. J Int Med Res. 2013;41(5):1456–61.

    Article  CAS  PubMed  Google Scholar 

  134. Ji T, Zheng ZG, Wang FM, et al. Differential microRNA expression by Solexa sequencing in the sera of ovarian cancer patients. Asian Pac J Cancer Prev. 2014;15(4):1739–43.

    Article  PubMed  Google Scholar 

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Correspondence to David Raul Francisco Carter.

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PS and DC have no conflicts of interest to declare.

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PS and DC thank The Cancer Polio Research Fund and Oxford Brookes University for their funding and support.

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Samuel, P., Carter, D.R.F. The Diagnostic and Prognostic Potential of microRNAs in Epithelial Ovarian Carcinoma. Mol Diagn Ther 21, 59–73 (2017). https://doi.org/10.1007/s40291-016-0242-z

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