Diagnostic plasma miRNA-profiles for ovarian cancer in patients with pelvic mass


Autoři: Douglas Nogueira Perez Oliveira aff001;  Anting Liu Carlsen aff002;  Niels H. H. Heegaard aff002;  Kira Philipsen Prahm aff001;  Ib Jarle Christensen aff001;  Claus K. Høgdall aff004;  Estrid V. Høgdall aff001
Působiště autorů: Department of Pathology, Herlev Hospital, University of Copenhagen, Herlev, Denmark aff001;  Department of Autoimmunology and Biomarkers, Statens Serum Institut, Copenhagen, Denmark aff002;  Department of Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark aff003;  Department of Gynaecology, Juliane Marie Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark aff004
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: 10.1371/journal.pone.0225249

Souhrn

Background

Ovarian cancer is the fifth most common cancer in women worldwide. Moreover, there are no reliable minimal invasive tests to secure the diagnosis of malignant pelvic masses. Cell-free, circulating microRNAs have the potential as diagnostic biomarkers in cancer. Here, we performed and validated a miRNA panel with the potential to distinguish OC from benign pelvic masses.

Methods

The profile of plasma microRNA was determined with a panel of 46 candidates in a discovery group and a validation group, each consisting of 190 pre-surgery plasma samples from age-matched patients with malignant (n = 95) and benign pelvic mass (n = 95), by real time RT-qPCR.

Results

Four up-regulated (miR-200c-3p, miR-221-3p, miR-21-5p, and miR-484) and two down-regulated (miR-195-5p and miR-451a) microRNAs were discovered. From those, miR-200c-3p and miR-221-3p were further confirmed in a validation cohort. A combination of these 2 microRNAs together with CA-125 yielded an overall diagnostic accuracy of AUC = 0.96.

Conclusions

We showed consistent plasma microRNA profiles that provide independent diagnostic information of late stage OC.

Klíčová slova:

Adenocarcinomas – Biomarkers – Cancer detection and diagnosis – Diagnostic medicine – MicroRNAs – Ovarian cancer – Surgical and invasive medical procedures – Surgical oncology


Zdroje

1. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2013. CA Cancer J Clin. 2013;63(1):11–30. Epub 2013/01/22. doi: 10.3322/caac.21166 23335087.

2. Sørensen SM, Bjørn SF, Jochumsen KM, Jensen PT, Thranov IR, Hare-Bruun H, et al. Danish gynecological cancer database. Clinical Epidemiology. 2016;8:485–90. doi: 10.2147/CLEP.S99479 27822089

3. Gottschau M, Mellemkjaer L, Hannibal CG, Kjaer SK. Ovarian and tubal cancer in Denmark: an update on incidence and survival. Acta Obstetricia et Gynecologica Scandinavica. 2016;95(10):1181–9. doi: 10.1111/aogs.12948 27454324

4. Moore RG, McMeekin DS, Brown AK, DiSilvestro P, Miller MC, Allard WJ, et al. A novel multiple marker bioassay utilizing HE4 and CA125 for the prediction of ovarian cancer in patients with a pelvic mass. Gynecologic Oncology. 2009;112(1):40–6. doi: 10.1016/j.ygyno.2008.08.031 18851871

5. Håkansson F, Høgdall EVS, Nedergaard L, Lundvall L, Engelholm SA, Pedersen AT, et al. Risk of malignancy index used as a diagnostic tool in a tertiary centre for patients with a pelvic mass. Acta Obstetricia et Gynecologica Scandinavica. 2012;91(4):496–502. doi: 10.1111/j.1600-0412.2012.01359.x 22229703

6. Moore RG, Jabre-Raughley M, Brown AK, Robison KM, Miller MC, Allard WJ, et al. Comparison of a novel multiple marker assay vs the Risk of Malignancy Index for the prediction of epithelial ovarian cancer in patients with a pelvic mass. American Journal of Obstetrics and Gynecology. 2010;203(3):228.e1–.e6. doi: 10.1016/j.ajog.2010.03.043 20471625

7. Shapira I, Oswald M, Lovecchio J, Khalili H, Menzin A, Whyte J, et al. Circulating biomarkers for detection of ovarian cancer and predicting cancer outcomes. Br J Cancer. 2014;110(4):976–83. Epub 2013/12/25. doi: 10.1038/bjc.2013.795 24366298; PubMed Central PMCID: PMC3929876.

8. Bartel DP. MicroRNAs: target recognition and regulatory functions. Cell. 2009;136(2):215–33. Epub 2009/01/27. doi: 10.1016/j.cell.2009.01.002 19167326; PubMed Central PMCID: PMC3794896.

9. Ha M, Kim VN. Regulation of microRNA biogenesis. Nat Rev Mol Cell Biol. 2014;15(8):509–24. Epub 2014/07/17. doi: 10.1038/nrm3838 25027649.

10. Iorio MV, Visone R, Di Leva G, Donati V, Petrocca F, Casalini P, et al. MicroRNA signatures in human ovarian cancer. Cancer Res. 2007;67(18):8699–707. Epub 2007/09/19. doi: 10.1158/0008-5472.CAN-07-1936 17875710.

11. Creighton CJ, Hernandez-Herrera A, Jacobsen A, Levine DA, Mankoo P, Schultz N, et al. Integrated analyses of microRNAs demonstrate their widespread influence on gene expression in high-grade serous ovarian carcinoma. PLoS One. 2012;7(3):e34546. Epub 2012/04/06. doi: 10.1371/journal.pone.0034546 22479643; PubMed Central PMCID: PMC3315571.

12. Flores CP, Garcia-Vázquez R, Rincón DG, Ruiz-Garcia E, De La Vega HA, Marchat LA, et al. MicroRNAs driving invasion and metastasis in ovarian cancer: Opportunities for translational medicine (Review). International Journal of Oncology. 2017;50(5):1461–76. doi: 10.3892/ijo.2017.3948 28393213

13. Prahm KP, Novotny GW, Hogdall C, Hogdall E. Current status on microRNAs as biomarkers for ovarian cancer. APMIS. 2016;124(5):337–55. Epub 2016/01/27. doi: 10.1111/apm.12514 26809719.

14. Resnick KE, Alder H, Hagan JP, Richardson DL, Croce CM, Cohn DE. 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. Epub 2008/10/29. doi: 10.1016/j.ygyno.2008.08.036 18954897.

15. Cortez MA, Bueso-Ramos C, Ferdin J, Lopez-Berestein G, Sood AK, Calin GA. MicroRNAs in body fluids—the mix of hormones and biomarkers. Nat Rev Clin Oncol. 2011;8(8):467–77. Epub 2011/06/08. doi: 10.1038/nrclinonc.2011.76 21647195; PubMed Central PMCID: PMC3423224.

16. Kim YK. Extracellular microRNAs as Biomarkers in Human Disease. Chonnam Med J. 2015;51(2):51–7. Epub 2015/08/26. doi: 10.4068/cmj.2015.51.2.51 26306299; PubMed Central PMCID: PMC4543150.

17. Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci U S A. 2008;105(30):10513–8. Epub 2008/07/30. doi: 10.1073/pnas.0804549105 18663219; PubMed Central PMCID: PMC2492472.

18. Reid G, Kirschner MB, van Zandwijk N. Circulating microRNAs: Association with disease and potential use as biomarkers. Crit Rev Oncol Hematol. 2011;80(2):193–208. Epub 2010/12/15. doi: 10.1016/j.critrevonc.2010.11.004 21145252.

19. Nakamura K, Sawada K, Yoshimura A, Kinose Y, Nakatsuka E, Kimura T. Clinical relevance of circulating cell-free microRNAs in ovarian cancer. Mol Cancer. 2016;15(1):48. Epub 2016/06/28. doi: 10.1186/s12943-016-0536-0 27343009; PubMed Central PMCID: PMC4921011.

20. West-Nielsen M, Hogdall EV, Marchiori E, Hogdall CK, Schou C, Heegaard NH. Sample handling for mass spectrometric proteomic investigations of human sera. Anal Chem. 2005;77(16):5114–23. Epub 2005/08/16. doi: 10.1021/ac050253g 16097747.

21. Rubin DB. Inference and Missing Data. Biometrika. 1976;63(3):12. doi: 10.2307/2335739

22. Hosmer DW, Lemeshow S. Goodness of fit tests for the multiple logistic regression model. Communications in Statistics—Theory and Methods. 1980;9(10):27.

23. Team RC. R: A Language and Environment for Statistical Computing. 3.4.1 (Single Candle) ed2017.

24. Arroyo JD, Chevillet JR, Kroh EM, Ruf IK, Pritchard CC, Gibson DF, et al. Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma. Proc Natl Acad Sci U S A. 2011;108(12):5003–8. Epub 2011/03/09. doi: 10.1073/pnas.1019055108 21383194; PubMed Central PMCID: PMC3064324.

25. Schwarzenbach H, Nishida N, Calin GA, Pantel K. Clinical relevance of circulating cell-free microRNAs in cancer. Nature Reviews Clinical Oncology. 2014;11(3):145–56. doi: 10.1038/nrclinonc.2014.5 24492836

26. Wu K, Li L, Li S. Circulating microRNA-21 as a biomarker for the detection of various carcinomas: an updated meta-analysis based on 36 studies. Tumour Biol. 2015;36(3):1973–81. Epub 2014/12/21. doi: 10.1007/s13277-014-2803-2 25527152.

27. Suryawanshi S, Vlad AM, Lin HM, Mantia-Smaldone G, Laskey R, Lee M, et al. Plasma microRNAs as novel biomarkers for endometriosis and endometriosis-associated ovarian cancer. Clin Cancer Res. 2013;19(5):1213–24. Epub 2013/01/31. doi: 10.1158/1078-0432.CCR-12-2726 23362326; PubMed Central PMCID: PMC3596045.

28. Taylor DD, Gercel-Taylor C. MicroRNA signatures of tumor-derived exosomes as diagnostic biomarkers of ovarian cancer. Gynecol Oncol. 2008;110(1):13–21. Epub 2008/07/01. doi: 10.1016/j.ygyno.2008.04.033 18589210.

29. Zearo S, Kim E, Zhu Y, Zhao JT, Sidhu SB, Robinson BG, et al. MicroRNA-484 is more highly expressed in serum of early breast cancer patients compared to healthy volunteers. BMC Cancer. 2014;14:200. Epub 2014/03/20. doi: 10.1186/1471-2407-14-200 24641801; PubMed Central PMCID: PMC3995145.

30. Luo Q, Wei C, Li X, Li J, Chen L, Huang Y, et al. MicroRNA-195-5p is a potential diagnostic and therapeutic target for breast cancer. Oncology Reports. 2014;31(3):1096–102. doi: 10.3892/or.2014.2971 24402230

31. Ouyang M, Li Y, Ye S, Ma J, Lu L, Lv W, et al. MicroRNA profiling implies new markers of chemoresistance of triple-negative breast cancer. PLoS ONE. 2014;9(5):1–8. doi: 10.1371/journal.pone.0096228 24788655

32. Langhe R, Norris L, Saadeh FA, Blackshields G, Varley R, Harrison A, et al. A novel serum microRNA panel to discriminate benign from malignant ovarian disease. Cancer Letters. 2015;356(2):628–36. doi: 10.1016/j.canlet.2014.10.010 25451316

33. Humphries B, Yang C. The microRNA-200 family: small molecules with novel roles in cancer development, progression and therapy. Oncotarget. 2015;6(9). doi: 10.18632/oncotarget.3052 25762624

34. Bendoraite A, Knouf EC, Garg KS, Parkin RK, Kroh EM, O'Briant KC, et al. Regulation of miR-200 family microRNAs and ZEB transcription factors in ovarian cancer: evidence supporting a mesothelial-to-epithelial transition. Gynecol Oncol. 2010;116(1):117–25. Epub 2009/10/27. doi: 10.1016/j.ygyno.2009.08.009 19854497; PubMed Central PMCID: PMC2867670.

35. Koutsaki M, Libra M, Spandidos DA, Zaravinos A. The miR-200 family in ovarian cancer. Oncotarget. 2017;8(39):66629–40. Epub 2017/10/17. doi: 10.18632/oncotarget.18343 29029543; PubMed Central PMCID: PMC5630443.

36. Muralidhar GG, Barbolina MV. The miR-200 Family: Versatile Players in Epithelial Ovarian Cancer. Int J Mol Sci. 2015;16(8):16833–47. Epub 2015/07/28. doi: 10.3390/ijms160816833 26213923; PubMed Central PMCID: PMC4581173.

37. Cochrane DR, Spoelstra NS, Howe EN, Nordeen SK, Richer JK. MicroRNA-200c mitigates invasiveness and restores sensitivity to microtubule-targeting chemotherapeutic agents. Mol Cancer Ther. 2009;8(5):1055–66. Epub 2009/05/14. doi: 10.1158/1535-7163.MCT-08-1046 19435871; PubMed Central PMCID: PMC4573391.

38. Brabletz S, Brabletz T. The ZEB/miR-200 feedback loop—a motor of cellular plasticity in development and cancer? EMBO Rep. 2010;11(9):670–7. Epub 2010/08/14. doi: 10.1038/embor.2010.117 20706219; PubMed Central PMCID: PMC2933868.

39. Garofalo M, Quintavalle C, Romano G, Croce CM, Condorelli G. miR221/222 in cancer: their role in tumor progression and response to therapy. Current molecular medicine. 2012;12(1):27–33. doi: 10.2174/156652412798376170 22082479

40. Hong F, Li Y, Xu Y, Zhu L. Prognostic significance of serum microRNA-221 expression in human epithelial ovarian cancer. Journal of International Medical Research. 2013;41(1):64–71. doi: 10.1177/0300060513475759 23569131

41. Zhang CZ, Zhang JX, Zhang AL, Shi ZD, Han L, Jia ZF, et al. MiR-221 and miR-222 target PUMA to induce cell survival in glioblastoma. Mol Cancer. 2010;9:229. Epub 2010/09/04. doi: 10.1186/1476-4598-9-229 20813046; PubMed Central PMCID: PMC2939570.

42. Chen Y, Zaman MS, Deng G, Majid S, Saini S, Liu J, et al. MicroRNAs 221/222 and genistein-mediated regulation of ARHI tumor suppressor gene in prostate cancer. Cancer Prev Res (Phila). 2011;4(1):76–86. Epub 2010/11/13. doi: 10.1158/1940-6207.CAPR-10-0167 21071579; PubMed Central PMCID: PMC3894108.

43. McDonald JS, Milosevic D, Reddi HV, Grebe SK, Algeciras-Schimnich A. Analysis of circulating microRNA: preanalytical and analytical challenges. Clin Chem. 2011;57(6):833–40. Epub 2011/04/14. doi: 10.1373/clinchem.2010.157198 21487102.

44. Witwer KW. Circulating microRNA biomarker studies: pitfalls and potential solutions. Clin Chem. 2015;61(1):56–63. Epub 2014/11/14. doi: 10.1373/clinchem.2014.221341 25391989.

45. Jemal A, Siegel R, Xu J, Ward E. Cancer statistics, 2010. CA Cancer J Clin. 2010;60(5):277–300. Epub 2010/07/09. doi: 10.3322/caac.20073 20610543.

46. Romagnolo C, Leon AE, Fabricio ASC, Taborelli M, Polesel J, Del Pup L, et al. HE4, CA125 and risk of ovarian malignancy algorithm (ROMA) as diagnostic tools for ovarian cancer in patients with a pelvic mass: An Italian multicenter study. Gynecol Oncol. 2016;141(2):303–11. Epub 2016/01/24. doi: 10.1016/j.ygyno.2016.01.016 26801941.


Článek vyšel v časopise

PLOS One


2019 Číslo 11