Abstract
Background
Extracellular vesicle (EV)-associated microRNAs (miRNAs) have been suggested as promising biomarkers for blood-based cancer diagnosis. However, one of the major limitations for the use of EVs with diagnostic purpose is the lack of standardized EV-profiling techniques. In this regard, the objective of our study was to design an integrated next-generation sequencing (NGS)-based workflow for analyzing the signature of EV-associated miRNA in the plasma of platinum-resistant ovarian cancer patients.
Methods
For EV-extraction, different enrichment methods were compared (ExoQuick vs. exoRNeasy). NGS was performed with the Illumina platform.
Results
We established an integrated NGS-based workflow, including EV-enrichment with the ExoQuick system, which resulted in an optimal RNA-yield and consistent small RNA libraries. We applied this workflow in a pilot cohort of clinically documented platinum-sensitive (n=15) vs. platinum-resistant (n=15) ovarian cancer patients, resulting in a panel of mature EV-associated miRNAs (including ovarian cancer associated miR-181a, miR-1908, miR-21, miR-486 and miR-223), which were differentially abundant in the plasma of platinum-resistant patients.
Conclusions
This is the first study, analyzing the profile of EV-associated miRNAs in platinum-resistant ovarian cancer patients. We provide rationale to further validate these miRNA candidates in an independent set of patients, in order to characterize their biomarker potential as predictors for platinum-resistance.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: This study was funded by “VFK Krebsforschung gGmbH”.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
References
1. Goodman MT, Howe HL, Tung KH, Hotes J, Miller BA, Coughlin SS, et al. Incidence of ovarian cancer by race and ethnicity in the United States, 1992–1997. Cancer 2003;97:2676–85.10.1002/cncr.11349Search in Google Scholar PubMed
2. du Bois A, Quinn M, Thigpen T, Vermorken J, Avall-Lundqvist E, Bookman M, et al. 2004 consensus statements on the management of ovarian cancer: final document of the 3rd International Gynecologic Cancer Intergroup Ovarian Cancer Consensus Conference (GCIG OCCC 2004). Ann Oncol 2005;16(Suppl. 8): viii7–12.10.1093/annonc/mdi961Search in Google Scholar PubMed
3. du Bois A, Reuss A, Pujade-Lauraine E, Harter P, Ray-Coquard I, Pfisterer J. 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 2009;115:1234–44.10.1002/cncr.24149Search in Google Scholar PubMed
4. Wimberger P, Lehmann N, Kimmig R, Burges A, Meier W, Du Bois A, et al. Prognostic factors for complete debulking in advanced ovarian cancer and its impact on survival. An exploratory analysis of a prospectively randomized phase III study of the Arbeitsgemeinschaft Gynaekologische Onkologie Ovarian Cancer Study Group (AGO-OVAR). Gynecol Oncol 2007;106:69–74.10.1016/j.ygyno.2007.02.026Search in Google Scholar PubMed
5. Wimberger P, Wehling M, Lehmann N, Kimmig R, Schmalfeldt B, Burges A, et al. Influence of residual tumor on outcome in ovarian cancer patients with FIGO stage IV disease: an exploratory analysis of the AGO-OVAR (Arbeitsgemeinschaft Gynaekologische Onkologie Ovarian Cancer Study Group). Ann Surg Oncol 2010;17:1642–8.10.1245/s10434-010-0964-9Search in Google Scholar PubMed
6. Martin LP, Schilder RJ. Management of recurrent ovarian carcinoma: current status and future directions. Semin Oncol 2009;36:112–25.10.1053/j.seminoncol.2008.12.003Search in Google Scholar PubMed
7. Burger RA, Brady MF, Bookman MA, Fleming GF, Monk BJ, Huang H, et al. Incorporation of bevacizumab in the primary treatment of ovarian cancer. N Engl J Med 2011;365:2473–83.10.1056/NEJMoa1104390Search in Google Scholar PubMed
8. Ledermann J, Harter P, Gourley C, Friedlander M, Vergote I, Rustin G, 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 2014;15:852–61.10.1097/OGX.0000000000000107Search in Google Scholar
9. Bookman MA. Extending the platinum-free interval in recurrent ovarian cancer: the role of topotecan in second-line chemotherapy. Oncologist 1999;4:87–94.10.1634/theoncologist.4-2-87Search in Google Scholar
10. 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 USA 2008;105:10513–8.10.1073/pnas.0804549105Search in Google Scholar PubMed PubMed Central
11. Kuhlmann JD, Baraniskin A, Hahn SA, Mosel F, Bredemeier M, Wimberger P, et al. Circulating U2 small nuclear RNA fragments as a novel diagnostic tool for patients with epithelial ovarian cancer. Clin Chem 2014;60:206–13.10.1373/clinchem.2013.213066Search in Google Scholar PubMed
12. Ma R, Jiang T, Kang X. Circulating microRNAs in cancer: origin, function and application. J Exp Clin Cancer Res 2012;31:38.10.1186/1756-9966-31-38Search in Google Scholar PubMed PubMed Central
13. Wang J, Chen J, Chang P, LeBlanc A, Li D, Abbruzzesse JL, et al. MicroRNAs in plasma of pancreatic ductal adenocarcinoma patients as novel blood-based biomarkers of disease. Cancer Prev Res (Phila) 2009;2:807–13.10.1158/1940-6207.CAPR-09-0094Search in Google Scholar PubMed PubMed Central
14. 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 USA 2011;108:5003–8.10.1073/pnas.1019055108Search in Google Scholar PubMed PubMed Central
15. Schwarzenbach H, Nishida N, Calin GA, Pantel K. Clinical relevance of circulating cell-free microRNAs in cancer. Nat Rev Clin Oncol 2014;11:145–56.10.1038/nrclinonc.2014.5Search in Google Scholar PubMed
16. Chen X, Liang H, Zhang J, Zen K, Zhang CY. Secreted microRNAs: a new form of intercellular communication. Trends Cell Biol 2012;22:125–32.10.1016/j.tcb.2011.12.001Search in Google Scholar PubMed
17. Singh R, Pochampally R, Watabe K, Lu Z, Mo YY. Exosome-mediated transfer of miR-10b promotes cell invasion in breast cancer. Mol Cancer 2014;13:256.10.1186/1476-4598-13-256Search in Google Scholar PubMed PubMed Central
18. Cheng L, Wu S, Zhang K, Qing Y, Xu T. A comprehensive overview of exosomes in ovarian cancer: emerging biomarkers and therapeutic strategies. J Ovarian Res 2017;10:73.10.1186/s13048-017-0368-6Search in Google Scholar PubMed PubMed Central
19. Crow J, Atay S, Banskota S, Artale B, Schmitt S, Godwin AK. Exosomes as mediators of platinum resistance in ovarian cancer. Oncotarget 2017;8:11917–36.10.18632/oncotarget.14440Search in Google Scholar PubMed PubMed Central
20. 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;15:48.10.1186/s12943-016-0536-0Search in Google Scholar PubMed PubMed Central
21. Momen-Heravi F. Isolation of extracellular vesicles by ultracentrifugation. Methods Mol Biol 2017;1660:25–32.10.1007/978-1-4939-7253-1_3Search in Google Scholar PubMed
22. Silverberg SG. Histopathologic grading of ovarian carcinoma: a review and proposal. Int J Gynecol Pathol 2000;19:7–15.10.1097/00004347-200001000-00003Search in Google Scholar PubMed
23. FIGO Committee on Gynecologic Oncology. Current FIGO staging for cancer of the vagina, fallopian tube, ovary, and gestational trophoblastic neoplasia. Int J Gynaecol Obstet 2009;105:3–4.10.1016/j.ijgo.2008.12.015Search in Google Scholar PubMed
24. Huang X, Yuan T, Tschannen M, Sun Z, Jacob H, Du M, et al. Characterization of human plasma-derived exosomal RNAs by deep sequencing. BMC Genomics 2013;14:319.10.1186/1471-2164-14-319Search in Google Scholar PubMed PubMed Central
25. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods 2012;9:357–9.10.1038/nmeth.1923Search in Google Scholar PubMed PubMed Central
26. Shi J, Dong M, Li L, Liu L, Luz-Madrigal A, Tsonis PA, et al. mirPRo-a novel standalone program for differential expression and variation analysis of miRNAs. Sci Rep 2015;5:14617.10.1038/srep14617Search in Google Scholar PubMed PubMed Central
27. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014;15:550.10.1186/s13059-014-0550-8Search in Google Scholar PubMed PubMed Central
28. Yuan T, Huang X, Woodcock M, Du M, Dittmar R, Wang Y, et al. Plasma extracellular RNA profiles in healthy and cancer patients. Sci Rep 2016;6:19413.10.1038/srep19413Search in Google Scholar PubMed PubMed Central
29. Thijssen MA, Swinkels DW, Ruers TJ, de Kok JB. Difference between free circulating plasma and serum DNA in patients with colorectal liver metastases. Anticancer Res 2002;22: 421–5.Search in Google Scholar
30. Jung M, Klotzek S, Lewandowski M, Fleischhacker M, Jung K. Changes in concentration of DNA in serum and plasma during storage of blood samples. Clin Chem 2003;49:1028–9.10.1373/49.6.1028Search in Google Scholar PubMed
31. Wang K, Yuan Y, Cho JH, McClarty S, Baxter D, Galas DJ. Comparing the microRNA spectrum between serum and plasma. PLoS One 2012;7:e41561.10.1371/journal.pone.0041561Search in Google Scholar PubMed PubMed Central
32. Shivapurkar N, Vietsch EE, Carney E, Isaacs C, Wellstein A. Circulating microRNAs in patients with hormone receptor-positive, metastatic breast cancer treated with dovitinib. Clin Transl Med 2017;6:37.10.1186/s40169-017-0169-ySearch in Google Scholar PubMed PubMed Central
33. Meng X, Muller V, Milde-Langosch K, Trillsch F, Pantel K, Schwarzenbach H. Diagnostic and prognostic relevance of circulating exosomal miR-373, miR-200a, miR-200b and miR-200c in patients with epithelial ovarian cancer. Oncotarget 2016;7:16923–35.10.18632/oncotarget.7850Search in Google Scholar PubMed PubMed Central
34. Melo SA, Luecke LB, Kahlert C, Fernandez AF, Gammon ST, Kaye J, et al. Glypican-1 identifies cancer exosomes and detects early pancreatic cancer. Nature 2015;523:177–82.10.1038/nature14581Search in Google Scholar PubMed PubMed Central
35. Uratani R, Toiyama Y, Kitajima T, Kawamura M, Hiro J, Kobayashi M, et al. Diagnostic potential of cell-free and exosomal microRNAs in the identification of patients with high-risk colorectal adenomas. PLoS One 2016;11:e0160722.10.1371/journal.pone.0160722Search in Google Scholar PubMed PubMed Central
36. Schwarzenbach H. Clinical relevance of circulating, cell-free and exosomal microRNAs in plasma and serum of breast cancer patients. Oncol Res Treat 2017;40:423–9.10.1159/000478019Search in Google Scholar PubMed
37. Sodar BW, Kittel A, Paloczi K, Vukman KV, Osteikoetxea X, Szabo-Taylor K, et al. Low-density lipoprotein mimics blood plasma-derived exosomes and microvesicles during isolation and detection. Sci Rep 2016;6:24316.10.1038/srep24316Search in Google Scholar PubMed PubMed Central
38. Vickers KC, Palmisano BT, Shoucri BM, Shamburek RD, Remaley AT. MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins. Nat Cell Biol 2011;13:423–33.10.1038/ncb2210Search in Google Scholar PubMed PubMed Central
39. Li L, Xu QH, Dong YH, Li GX, Yang L, Wang LW, et al. MiR-181a upregulation is associated with epithelial-to-mesenchymal transition (EMT) and multidrug resistance (MDR) of ovarian cancer cells. Eur Rev Med Pharmacol Sci 2016;20:2004–10.Search in Google Scholar
40. Teng C, Zheng H. Low expression of microRNA-1908 predicts a poor prognosis for patients with ovarian cancer. Oncol Lett 2017;14:4277–81.10.3892/ol.2017.6714Search in Google Scholar PubMed PubMed Central
41. Ma H, Tian T, Liang S, Liu X, Shen H, Xia M, et al. Estrogen receptor-mediated miR-486-5p regulation of OLFM4 expression in ovarian cancer. Oncotarget 2016;7:10594–605.10.18632/oncotarget.7236Search in Google Scholar PubMed PubMed Central
42. Fang G, Liu J, Wang Q, Huang X, Yang R, Pang Y, et al. MicroRNA-223-3p regulates ovarian cancer cell proliferation and invasion by targeting SOX11 expression. Int J Mol Sci 2017;18.10.3390/ijms18061208Search in Google Scholar PubMed PubMed Central
43. Pink RC, Samuel P, Massa D, Caley DP, Brooks SA, Carter DR. The passenger strand, miR-21-3p, plays a role in mediating cisplatin resistance in ovarian cancer cells. Gynecol Oncol 2015;137:143–51.10.1016/j.ygyno.2014.12.042Search in Google Scholar PubMed
Supplementary Material
The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2018-1048).
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