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New biomarkers in peripheral blood of patients with ovarian cancer: high expression levels of miR-16-5p, miR-17-5p, and miR-638

  • Gynecologic Oncology
  • Published:
Archives of Gynecology and Obstetrics Aims and scope Submit manuscript

Abstract

Objectives

Ovarian cancer is one of the most fatal gynecologic malignities. miR-16-5p, miR-17-5p, and miR-638 genes were found to have been associated with ovarian cancer in accordance with the data obtained from the previous microarray research performed by Tuncer et al. (J Ovarian Res 13(1):99, 2020). The expression levels of these miRNAs in the peripheral blood samples of 142 ovarian cancer patients, and 97 healthy controls were investigated for performing the validation, and to identify whether these genes were the possible biomarkers to be used in the early diagnosis of high-risk ovarian cancer patients, and in the prognosis of patients.

Methods

The miRNA expression analysis was performed using the miRNA-specific cDNA synthesis, and real-time PCR methods following the RNA isolation from the peripheral blood lymphocytes.

Results

miR-16-5p, miR-17-5p, and miR-638 miRNA gene expression levels were found to have twofold higher expression levels in patient groups compared with the gene expression levels in healthy controls, and were statistically significant (p < 0.05). In addition, the comparison of the miRNA expression levels with the clinical data of patients showed that there was a significant difference with smoking history and the increased expression level of miR-17-5 (p: 0.007). There was a significant difference between the increased expression level of miR-638 with the locally advanced stage, and abdominal/pelvic metastatic patients (p: 0.03).

Conclusions

The obtained data suggest that miR-16-5p, miR-17-5p, and miR-638 molecules might be the noninvasive biomarkers in identifying the ovarian cancer. However, the investigation and monitoring of the changeability of these biomarkers in benign ovarian diseases, and during the treatment must be performed in future studies for identifying the accurate diagnostic, and prognostic features of miRNAs.

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Availability of the data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. All data generated or analysed during this study are included in this published article.

References

  1. Bray F et al (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 68(6):394–424

    Article  PubMed  Google Scholar 

  2. Dong X et al (2014) Advances in tumor markers of ovarian cancer for early diagnosis. Indian J Cancer 51(Suppl 3):e72–e76

    PubMed  Google Scholar 

  3. Bottoni P, Scatena R (2015) The role of CA 125 as tumor marker: biochemical and clinical aspects. Adv Exp Med Biol 867:229–244

    Article  CAS  PubMed  Google Scholar 

  4. Moore LE et al (2012) Proteomic biomarkers in combination with CA 125 for detection of epithelial ovarian cancer using prediagnostic serum samples from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Cancer 118(1):91–100

    Article  CAS  PubMed  Google Scholar 

  5. Elias KM, Guo J, Bast RC Jr (2018) Early detection of ovarian cancer. Hematol Oncol Clin N Am 32(6):903–914

    Article  Google Scholar 

  6. Mahdian-Shakib A et al (2016) Differential role of microRNAs in prognosis, diagnosis, and therapy of ovarian cancer. Biomed Pharmacother 84:592–600

    Article  CAS  PubMed  Google Scholar 

  7. Boyd J, Rubin SC (1997) Hereditary ovarian cancer: molecular genetics and clinical implications. Gynecol Oncol 64(2):196–206

    Article  CAS  PubMed  Google Scholar 

  8. Webb PM, Jordan SJ (2017) Epidemiology of epithelial ovarian cancer. Best Pract Res Clin Obstet Gynaecol 41:3–14

    Article  PubMed  Google Scholar 

  9. Salehi F et al (2008) Risk factors for ovarian cancer: an overview with emphasis on hormonal factors. J Toxicol Environ Health B Crit Rev 11(3–4):301–321

    Article  CAS  PubMed  Google Scholar 

  10. Kurman RJ, Shih-Ie M (2010) The origin and pathogenesis of epithelial ovarian cancer: a proposed unifying theory. Am J Surg Pathol 34(3):433–443

    Article  PubMed  PubMed Central  Google Scholar 

  11. Kim J et al (2018) Cell origins of high-grade serous ovarian cancer. Cancers (Basel) 10(11):433

    Article  CAS  Google Scholar 

  12. Kurman RJ, Shih-Ie M (2016) The dualistic model of ovarian carcinogenesis: revisited, revised, and expanded. Am J Pathol 186(4):733–747

    Article  PubMed  PubMed Central  Google Scholar 

  13. Katz B et al (2015) MicroRNAs in ovarian cancer. Hum Pathol 46(9):1245–1256

    Article  CAS  PubMed  Google Scholar 

  14. Peng Y, Croce CM (2016) The role of MicroRNAs in human cancer. Signal Transduct Target Ther 1:15004

    Article  PubMed  PubMed Central  Google Scholar 

  15. Tsuchiya S, Okuno Y, Tsujimoto G (2006) MicroRNA: biogenetic and functional mechanisms and involvements in cell differentiation and cancer. J Pharmacol Sci 101(4):267–270

    Article  CAS  PubMed  Google Scholar 

  16. Ahmed FE (2007) Role of miRNA in carcinogenesis and biomarker selection: a methodological view. Expert Rev Mol Diagn 7(5):569–603

    Article  CAS  PubMed  Google Scholar 

  17. Zheng D (2017) Non-coding RNAs and ovarian diseases. Mol Med Rep 1435–1440 (Review)

  18. Lei L et al (2010) The regulatory role of Dicer in folliculogenesis in mice. Mol Cell Endocrinol 315(1–2):63–73

    Article  CAS  PubMed  Google Scholar 

  19. Tuncer SB et al (2019) The expression levels of miRNA-15a and miRNA-16-1 in circulating tumor cells of patients with diffuse large B cell lymphoma. Mol Biol Rep 46(1):975–980

    Article  CAS  PubMed  Google Scholar 

  20. Erdogan OS et al (2020) Genome-wide methylation profiles in monozygotic twins with discordance for ovarian carcinoma. Oncol Lett 20(6):357

    Article  PubMed  PubMed Central  Google Scholar 

  21. Shenouda SK, Alahari SK (2009) MicroRNA function in cancer: oncogene or a tumor suppressor? Cancer Metastasis Rev 28(3–4):369–378

    Article  CAS  PubMed  Google Scholar 

  22. Costa PM, Pedroso-de-Lima MC (2013) MicroRNAs as molecular targets for cancer therapy: on the modulation of microRNA expression. Pharmaceuticals (Basel) 6(10):1195–1220

    Article  Google Scholar 

  23. Erson AE, Petty EM (2009) miRNAs and cancer: new research developments and potential clinical applications. Cancer Biol Ther 8(24):2317–2322

    Article  CAS  PubMed  Google Scholar 

  24. Cowland JB, Hother C, Gronbaek K (2007) MicroRNAs and cancer. APMIS 115(10):1090–1106

    Article  CAS  PubMed  Google Scholar 

  25. Lu J et al (2005) MicroRNA expression profiles classify human cancers. Nature 435(7043):834–838

    Article  CAS  PubMed  Google Scholar 

  26. Zhang J et al (2015) Circulating MiR-16-5p and MiR-19b-3p as two novel potential biomarkers to indicate progression of gastric cancer. Theranostics 5(7):733–745

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Xing Z et al (2014) MicroRNAs and anticancer drugs. Acta Biochim Biophys Sin (Shanghai) 46(3):233–239

    Article  CAS  Google Scholar 

  28. Tuncer SB et al (2020) miRNA expression profile changes in the peripheral blood of monozygotic discordant twins for epithelial ovarian carcinoma: potential new biomarkers for early diagnosis and prognosis of ovarian carcinoma. J Ovarian Res 13(1):99

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Chen SN et al (2019) MicroRNA in ovarian cancer: biology, pathogenesis, and therapeutic opportunities. Int J Environ Res Public Health 16(9):1510

    Article  CAS  PubMed Central  Google Scholar 

  30. Wang X et al (2019) Circulating microRNAs as novel potential diagnostic biomarkers for ovarian cancer: a systematic review and updated meta-analysis. J Ovarian Res 12(1):24

    Article  PubMed  PubMed Central  Google Scholar 

  31. Pal MK et al (2015) MicroRNA: a new and promising potential biomarker for diagnosis and prognosis of ovarian cancer. Cancer Biol Med 12(4):328–341

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Lengyel E (2010) Ovarian cancer development and metastasis. Am J Pathol 177(3):1053–1064

    Article  PubMed  PubMed Central  Google Scholar 

  33. Calin GA et al (2004) Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers. Proc Natl Acad Sci U S A 101(9):2999–3004

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Jay C et al (2007) miRNA profiling for diagnosis and prognosis of human cancer. DNA Cell Biol 26(5):293–300

    Article  CAS  PubMed  Google Scholar 

  35. Zhang B, Cai FF, Zhong XY (2011) An overview of biomarkers for the ovarian cancer diagnosis. Eur J Obstet Gynecol Reprod Biol 158(2):119–123

    Article  CAS  PubMed  Google Scholar 

  36. McGinnis LK, Luense LJ, Christenson LK (2015) MicroRNA in ovarian biology and disease. Cold Spring Harb Perspect Med 5(9):a022962

    Article  PubMed  PubMed Central  Google Scholar 

  37. Montazerian M, Yasari F, Aghaalikhani N (2018) Ovarian extracellular MicroRNAs as the potential non-invasive biomarkers: an update. Biomed Pharmacother 106:1633–1640

    Article  CAS  PubMed  Google Scholar 

  38. Donadeu FX, Schauer SN (2013) Differential miRNA expression between equine ovulatory and anovulatory follicles. Domest Anim Endocrinol 45(3):122–125

    Article  CAS  PubMed  Google Scholar 

  39. Imbar T, Eisenberg I (2014) Regulatory role of microRNAs in ovarian function. Fertil Steril 101(6):1524–1530

    Article  CAS  PubMed  Google Scholar 

  40. Yerushalmi GM et al (2018) Characterization of the miRNA regulators of the human ovulatory cascade. Sci Rep 8(1):15605

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Machtinger R et al (2017) Extracellular microRNAs in follicular fluid and their potential association with oocyte fertilization and embryo quality: an exploratory study. J Assist Reprod Genet 34(4):525–533

    Article  PubMed  PubMed Central  Google Scholar 

  42. Wang F et al (2009) Down-regulation of the cyclin E1 oncogene expression by microRNA-16-1 induces cell cycle arrest in human cancer cells. BMB Rep 42(11):725–730

    Article  CAS  PubMed  Google Scholar 

  43. Zhang X et al (2018) Biology of MiR-17-92 cluster and its progress in lung cancer. Int J Med Sci 15(13):1443–1448

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Volinia S et al (2006) A microRNA expression signature of human solid tumors defines cancer gene targets. Proc Natl Acad Sci U S A 103(7):2257–2261

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Chen Q et al (2013) Prognostic significance of serum miR-17-5p in lung cancer. Med Oncol 30(1):353

    Article  PubMed  Google Scholar 

  46. Qu Y et al (2016) MiR-17-5p regulates cell proliferation and migration by targeting transforming growth factor-beta receptor 2 in gastric cancer. Oncotarget 7(22):33286–33296

    Article  PubMed  PubMed Central  Google Scholar 

  47. Zhu Y et al (2018) MiR-17-5p enhances pancreatic cancer proliferation by altering cell cycle profiles via disruption of RBL2/E2F4-repressing complexes. Cancer Lett 412:59–68

    Article  CAS  PubMed  Google Scholar 

  48. Bhattacharya A et al (2015) miR-638 promotes melanoma metastasis and protects melanoma cells from apoptosis and autophagy. Oncotarget 6(5):2966–2980

    Article  PubMed  Google Scholar 

Download references

Funding

The present work was supported by the Research Fund of Istanbul University. Project No: TDK-2018-29694.

Author information

Authors and Affiliations

  1. Division of Cancer Genetics, Department of Basic Oncology, Oncology Institute, Istanbul University, Fatih , 34093, Istanbul, Turkey

    Mukaddes Avsar Saral, Seref Bugra Tuncer, Demet Akdeniz Odemis, Ozge Sukruoglu Erdogan, Seda Kilic Erciyas & Hulya Yazici

  2. Department of Medical Oncology in Oncology Institute, Istanbul University, Fatih, 34093, Istanbul, Turkey

    Pınar Saip

  3. Department of Biostatistics, Istanbul Faculty of Medicine, Istanbul University, Fatih, 34093, Istanbul, Turkey

    Sevda Ozel

  4. Health Sciences Institute, Istanbul University, Beyazıt/Fatih, 34452, Istanbul, Turkey

    Mukaddes Avsar Saral

  5. Health Services Vocational School of Higher Education, T.C. Istanbul Aydin University, Sefakoy Kucukcekmece, 34295, Istanbul, Turkey

    Mukaddes Avsar Saral

Authors
  1. Mukaddes Avsar Saral
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  2. Seref Bugra Tuncer
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  3. Demet Akdeniz Odemis
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  6. Pınar Saip
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  7. Sevda Ozel
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  8. Hulya Yazici
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Contributions

ASM project development, data collection, manuscript writing. TSB study concept, and design, data collection. AOD, SEO, KES, SP data collection. OS statistical analysis. YH project development, data collection, check of manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Hulya Yazici.

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Conflict of interest

There are no conflicts of interest to declare (Mukaddes Avsar Saral, Seref Bugra Tuncer, Demet Akdeniz Odemis, Ozge Sukruoglu Erdogan, Seda Kilic Erciyas, Pınar Saip, Sevda Ozel, Hulya Yazici).

Ethics approval

All the performed human participant involving procedures were in accordance with the ethical standards of the institutional and/or national research committee, and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Ethics Committee of Istanbul Faculty of Medicine in Istanbul University (Ethics Approval No: 2018/190).

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Informed consent was obtained from all individual participants included in the study.

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Patients signed informed consent regarding the publishing of their data.

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Saral, M.A., Tuncer, S.B., Odemis, D.A. et al. New biomarkers in peripheral blood of patients with ovarian cancer: high expression levels of miR-16-5p, miR-17-5p, and miR-638. Arch Gynecol Obstet 305, 193–201 (2022). https://doi.org/10.1007/s00404-021-06138-z

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  • DOI: https://doi.org/10.1007/s00404-021-06138-z

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