Skip to main content
Egyptian Journal of Medical Human Genetics
Download PDF

Evaluation of miRNA-21 and CA-125 as a promising diagnostic biomarker in patients with ovarian cancer

Egyptian Journal of Medical Human Genetics volume 23, Article number: 123 (2022) Cite this article

Abstract

Introduction/objective

Ovarian cancer is the 6th leading cause of mortality in women, killing more women than any other reproductive system cancer. We studied the expression of serum micro-ribonucleic acid-21 (miRNA-21) in ovarian cancer patients and explored associations with diagnosis, clinicopathological parameters, and prognosis.

Methods

Real-time fluorescence-quantitative polymerase chain reaction was used to examine the relative expression of miRNA-21 in serum. Cancer antigen 125 (CA-125) levels were measured using an enzyme immunoassay test kit (ELISA).

Results

Serum miR-21 expression was significantly elevated in ovarian cancer patients compared to controls (p < 0.001). The same was true for CA-125 serum levels, which were also significantly in cancer patients (p < 0.001). The sensitivity and specificity of miR-21 detection in the diagnosis of ovarian cancer were 96%, 88% versus 74%, and 80% for CA-125.

Conclusions

miR-21 is highly expressed in the serum of ovarian cancer patients and may be important in the development and progression of ovarian cancer, with more sensitivity and specificity than CA-125. Our results suggest that circulating serum miRNA-21 is a promising tumor marker for use in the diagnosis and prognosis of ovarian cancer.

Introduction

Ovarian cancer is the sixth most prevalent cause of cancer-related death in women in the USA, accounting for 3% of all cancers in women [1]. In women, it is the fourth most frequent cancer. According to the Egyptian National Population-Based Registry Program 2008–2011, ovarian cancer accounts for 4.12% of the population, with a crude rate of 4.6. The incidence of ovarian cancer is expected to rise steadily from 2288 in 2013 to 5957 in 2050, representing a 260% increase. Upper Egypt (6.1%) had the highest incidence, 6.1%. Lower rates were found in middle and lower Egypt (3.8% and 3.9%, respectively) [2].

Ovarian cancer is currently diagnosed using pelvic examination, ultrasound (US), and tumor biomarkers; however, the inability to detect symptoms, weak invasiveness, and treatment resistance are linked to poor prognosis [3]. Various serum and plasma biomarkers, such as CA-125, human epididymis protein 4 (HE4), mesothelin, kallikreins, and aldehyde dehydrogenase 1 (ALDH1), show higher sensitivity and specificity at the malignant stage, but lower sensitivity and specificity in early stages [4]. CA-125 levels play a significant role in monitoring patients with ovarian cancer, but its significance at first diagnosis is still debated [5]. As a result, signature biomarkers with improved specificity and sensitivity are needed to improve ovarian cancer patient survival. Micro-RNAs (miRNAs) are currently being investigated as hallmark biomarkers for early diagnosis [4].

miRNAs are short non-coding RNA molecules (18–25 nucleotides) that regulate the translation of specific genes by binding to the 3′ untranslated region of target mRNAs in a sequence-specific manner. miRNAs participate in cell growth, differentiation, invasion, angiogenesis, and epithelial-mesenchymal transition, all of which are common in cancer [6, 7]. Specific miRNAs play a role in carcinogenesis because of their oncogenic or tumor-suppressive characteristics [8, 9]. Plasma, serum, saliva, urine, and feces all contain miRNAs [10]. miRNAs are fundamentally stable, and their use as indicators of human disease and therapeutic targets is increasing [11, 12]. Circulating miRNAs can resist harsh physiological conditions, such as pH changes, temperature changes, and freeze/thaw cycles [13]. Further, expression levels of circulating miRNAs are consistent across physically healthy individuals [14].

miR-21 is a widely expressed miRNA in mammalian cells, and its overexpression has been linked to a variety of cancers [15]. miR-21 functions as an oncogene, with overexpression leading to malignant B-cell lymphoma, as evidenced using conditional miR-21 knock-in mice [16]. In a study of 540 clinical samples from cancer patients, miR-21 was the only consistently elevated miRNA [17].

Insufficient work on the expression of serum miR-21 in ovarian cancer patients has been accomplished. Thus, its diagnostic value and relationships with pathological characteristics and prognosis are not completely understood. In this study, we explored the expression of miR-21 in serum from ovarian cancer patients and assessed its value for ovarian cancer diagnosis, clinicopathology, and prognosis. Our findings may assist the development of a theoretical foundation for early clinical diagnosis and treatment of ovarian cancer.

Methodology

The study was conducted at the Medical Biochemistry Department, Faculty of Medicine, Zagazig University, and the Gynecology and Obstetrics Department, Zagazig University Hospitals. Approval for the study was obtained from the Institutional Review Board (IRB), Faculty of Medicine, Zagazig University (reference number is 9066/27-1-2021). A case–control study was conducted with 100 adult subjects: 50 healthy adult women served as controls, and 50 were diagnosed with ovarian cancer. Informed written consent was obtained from all subjects to allow the use of samples and clinical data. Consent was provided with a dedicated form consistent with the Declaration of Helsinki. Fifty patients with histopathological confirmation of ovarian cancer, and with adequate hepatic, renal, cardiac, and respiratory function, were included. Individuals with a personal history of other malignant tumors and patients refusing to participate in the study were excluded.

Blood sampling

Participant blood samples were collected into RNase-free tubes, and serum was separated. miRNAs were extracted from serum using miRNeasy (Cat Number: Q217004; Qiagen, Germany), and serum CA-125 levels were measured using an enzyme immunoassay test kit (Catalog No. MBS454004).

RT-qPCR

TaqMan miRNA assays were used to assess levels of miRNA-21 (miR-21) in the blood (Applied Biosystems, Catalog Number 4427975). In a total volume of (15 μL), a fixed volume (2 μL) of total RNA was reverse transcribed using TaqMan miRNA Reverse Transcription Kits (Applied Biosystems, Catalog No. 4366596) under the following conditions: 16 °C for 30 min, 42 °C for 30 min, and 85 °C for 5 min, 4 °C maintained. miRNA Assay Kits and a TaqMan Universal Master Mix II, no UNG (Applied Biosystems, Catalog No. 4440040) were used in real-time PCR, which was carried out in duplicate on the StepOne Plus system (Applied Biosystems) under the following cycle conditions: 10 min at 95 °C, followed by 40 cycles of 95 °C for 15 s and 60 °C for 1 min. Step One Software v2.3 (Applied Biosystems) was used to calculate cycle threshold (Ct) values. The 2−ΔΔCt method was used to determine expression levels of miRNA, normalized to RNU6 [18].

ΔCt was calculated as:

ΔCt = Ct (miRNA of interest) − Ct (RNU6). Then, ΔΔCt was calculated with a sample from a healthy volunteer as a calibrator: ΔΔCt = ΔCt (tested sample) − ΔCt (calibrator).

Statistical analysis

Data were analyzed using SPSS version 22, and data are expressed as means ± SD for quantitative parametric variables, as medians for nonparametric variables, and as frequency and percentage for categorical variables. Student’s t tests, Mann–Whitney, Chi-squared tests, and Pearson correlation were used as appropriate. p < 0.05 was considered statistically significant. The analysis was based on the accuracy of miRNAs for diagnosis of ovarian cancer as determined using receiver operator characteristic (ROC) curves as the area under the curve (AUC) values and sensitivity and specificity.

Results

Baseline characteristics of 50 ovarian cancer patients and 50 control subjects indicated no significant differences in age, residence, family history, and menstrual status (p > 0.05; Table1). Thirty patients were diagnosed with early-stage (FIGO I and II) and 20 with advanced-stage (FIGO III and IV) epithelial ovarian cancer. Twenty cases were confirmed as serous ovarian carcinoma, 14 mucinous, and 16 endometrioid. Twenty-two had bilateral, 16 multilocular, and 12 solid tumors. Thirty-four patients were negative for metastases and 16 positive (Table 2).

Table 1 Risk factors and demographic data of controls and ovarian cancer patients
Full size table
Table 2 Clinical characteristics of cancer patients
Full size table

Serum miR-21 expression and CA-125 serum level were significantly higher in cancer patients than in controls (p < 0.001) (Table 3). Significant associations were observed between high miR-21 and family history, FIGO stage, and histological type. Correlations with age, residence, and US type were not statistically significant (Table 4). Serum CA-125 levels were significantly correlated with clinicopathological variables—FIGO stage, histological type, and US type—but not with age, residence, and family history (Table 5).

Table 3 Comparison of serum miR-21 expression and CA-125 serum levels among patients and controls
Full size table
Table 4 Associations among serum miR-21 expression and clinicopathological parameters in ovarian cancer patients
Full size table
Table 5 Relationships among serum CA-125 level and clinicopathological parameters in ovarian cancer patients
Full size table

Serum miR-21 was a reliable diagnostic marker for the detection of ovarian cancer (Table 6), with a sensitivity of 96%, specificity of 88%, and accuracy of 92%. Serum CA-125 was less dependable—sensitivity 74%, specificity 80%, and accuracy 77% (Fig. 1). Correlation coefficients for AUC were 0.99 for miR-21 and 0 0.84 for CA125. There was a statistically significant positive correlation between CA-125 and miRNA-21 among the studied groups as shown in Table 7 and Fig. 2).

Table 6 Validity of miRNA 21 expression and CA-125 serum level as diagnostic markers of ovarian cancer
Full size table
Fig. 1
figure 1

ROC curve for miR-21 as a diagnostic marker of ovarian cancer

Full size image
Table 7 Correlation between CA-125 and miRNA-21 among studied groups
Full size table
Fig. 2
figure 2

Correlation between CA-125 and miRN-21 among the studied groups

Full size image

Discussion

Ovarian cancer is the sixth leading cause of mortality in women, killing more women than any other cancer of the reproductive system. A woman’s lifetime risk of developing ovarian cancer is about 1 in 78 [1]. A family history of breast or ovarian cancer is the most significant risk factor for ovarian cancer, and heritable susceptibility accounts for about 25% of all malignancies [19]. Currently, miRNAs are being investigated as serum biomarkers. These tiny non-coding RNA molecules are likely non-invasive blood biomarkers [20]. Zhang et al. reported miRNAs as diagnostic or prognostic indicators [21]. A panel of miRNAs was apparently better than traditional methods for distinguishing between malignant and reactive lesions, and among cancers with various histogenetic origins and histological subtypes of the same type of tumor. Ashrafizadeh et al. indicated that miRNAs can also function as major regulators of carcinogenesis and that targeting these molecules, or their functions, might be an effective treatment strategy [22]. Thus, our study evaluated the involvement of miR-21 in ovarian cancer progression.

We found that the expression of miR-21 was considerably elevated in sera of ovarian cancer patients compared with age-matched controls. The fold change value in serum miR-21 expression in patients with advanced stage cancer was 7.16 ± 1.57, substantially higher than for early stages, 4.46 ± 1.13. Similarly, XU et al. reported higher blood miR-21 levels in EOC patients, which correlated with FIGO stage and tumor grade [23]. Further, higher plasma miR-21 levels are linked to poor long-term prognosis. Kartika et al. found that miRNA-21 was upregulated 2.14-fold in late compared to early stages, and 6.13-fold compared to healthy controls (p 0.05) [24]. Lou et al. hypothesized that aberrant miR-21 expression affects several biological processes in ovarian cancer cells, including proliferation, migration, and invasion [25]. miR-21 appears to play a role in ovarian carcinogenesis and promotes invasion and metastasis. The precise mechanism of involvement of miRNA 21 in the progression of cancer is still unknown. Lu et al. [25] and Meng et al. [26] suggested that overexpression of miR-21 is closely linked to the negative expression of PTEN protein. Other tumor suppressor genes, such as Pdcd4, which is negatively regulated at the posttranscriptional level by miR-21, may also be involved [27, 28].

We found significant differences in miR-21 expression among serous, mucinous, and endometrioid histology, with the highest expression in the endometrioid type. Nam et al. suggested that miR-21 was the most frequently upregulated miRNA in serous ovarian carcinoma biopsies compared to normal ovarian tissue [29]. Paliwal et al. showed that RT-qPCR-calculated fold changes in miRNA-21 expression were 3.98 times higher in serous ovarian cancer compared to controls [20]. Similarly, elevated levels of 1.99- and 1.34-fold were observed for mucinous and endometrioid ovarian carcinoma, respectively. Lou et al. reported increased miRNA-21 expression in serous, mucinous, and endometrioid subtypes of EOC, but did not observe any significant differences among the three histotypes [25].

Currently, pelvic examination, transvaginal ultrasonography (TVUS), and serum CA-125 levels are standard modalities for detecting ovarian cancer. CA-125 is considered a “gold standard” tumor biomarker for this disease [30, 31]. We consistently found high serum levels in the early stages of ovarian cancer in comparison with controls and higher levels in the late stages.

We also found that sensitivity, specificity, and accuracy of miRNA-21 were superior to CA-125-96%, 88%, and 92% versus 74%, 80%, and 77%, respectively, in addition to a significant positive correlation between CA-125 and miRNA-21 among the studied groups. Consistently, Xu et al. [23] suggested that serum miR-21 could be used as a diagnostic and prognostic marker for EOC, as well as a therapeutic target. Overall, miR-21 can be used for early detection and therapy planning as a tumor biomarker for ovarian cancer.

Our study’s small sample size made it difficult to generalize the findings, which necessitated larger cohort studies. Additionally, the expense of the reagents prevented the study from involving more participants. We recommend future research into various populations, including high population sample sizes, in order to completely elucidate the role of miRNA-21 gene expression in EOC. Additional studies comparing serum miRNA-21 expression with tissue expression would unquestionably support our findings.

Conclusion

miRNA21 gene expression level significantly increases in ovarian cancer cases at higher levels in later stages. Histopathological types of ovarian cancer showed comparatively high expression levels of miR-21. miRNA21 can be used as a diagnostic biomarker for the early detection of ovarian cancer.

Availability of data and materials

Not applicable.

Abbreviations

ALDH1:

Aldehyde dehydrogenase 1

AUC:

Area under the curve

CA-125:

Cancer antigen 125

Ct:

Cycle threshold

ELISA:

Enzyme-linked immunosorbent assay

EOC:

Epithelial ovarian cancer

FIGO:

International Federation of Gynecology and Obstetrics

HE4:

Human epididymis protein 4

IRB:

Institutional Review Board

miRNA-21/miR-21:

Micro-ribonucleic acid-21

PTEN:

Phosphatase and tensin homolog

PV:

Predictive value

ROC:

Receiver operator characteristic

RT-qPCR:

Real-time fluorescence-quantitative polymerase chain reaction

SD:

Standard deviation

SPSS:

Statistical Package for the Social Sciences

TVUS:

Transvaginal ultrasonography

UNG:

Uracil-N-glycosylase gene

US:

Ultrasound

References

  1. Siegel R, Miller K, Jemal A (2018) Cancer statistics, 2018. CA A Cancer J Clin 68(1):7–30. https://doi.org/10.3322/caac.21442

    Article  Google Scholar 

  2. Ibrahim A, Khaled H, Mikhail N, Baraka H, Kamel H (2014) Cancer incidence in Egypt: results of the national population-based cancer registry program. J Cancer Epidemiol 2014:1–18. https://doi.org/10.1155/2014/437971

    Article  Google Scholar 

  3. Qu H, Xu W, Huang Y, Yang S (2011) Circulating miRNAs: promising biomarkers of human cancer. Asian Pac J Cancer Prev 12(5):1117–1125

    PubMed  Google Scholar 

  4. Resnick K, Alder H, Hagan J, Richardson D, Croce C, Cohn D (2009) The detection of differentially expressed microRNAs from the serum of ovarian cancer patients using a novel real-time PCR platform. Gynecol Oncol 112(1):55–59. https://doi.org/10.1016/j.ygyno.2008.08.036

    Article  CAS  PubMed  Google Scholar 

  5. Sölétormos G, Duffy M, Othman Abu Hassan S, Verheijen R, Tholander B, Bast R et al (2016) Clinical use of cancer biomarkers in epithelial ovarian cancer: updated guidelines from the European group on tumor markers. Int J Gynecol Cancer 26(1):43–51. https://doi.org/10.1097/igc.0000000000000586

    Article  PubMed  Google Scholar 

  6. Calin G, Croce C (2006) MicroRNA signatures in human cancers. Nat Rev Cancer 6(11):857–866. https://doi.org/10.1038/nrc1997

    Article  CAS  PubMed  Google Scholar 

  7. Esquela-Kerscher A, Slack F (2006) Oncomirs: microRNAs with a role in cancer. Nat Rev Cancer 6(4):259–269. https://doi.org/10.1038/nrc1840

    Article  CAS  PubMed  Google Scholar 

  8. Wiemer E (2007) The role of microRNAs in cancer: no small matter. Eur J Cancer 43(10):1529–1544. https://doi.org/10.1016/j.ejca.2007.04.002

    Article  CAS  PubMed  Google Scholar 

  9. Lu J, Getz G, Miska E, Alvarez-Saavedra E, Lamb J, Peck D et al (2005) MicroRNA expression profiles classify human cancers. Nature 435(7043):834–838. https://doi.org/10.1038/nature03702

    Article  CAS  PubMed  Google Scholar 

  10. Chevillet J, Lee I, Briggs H, He Y, Wang K (2014) Issues and prospects of microRNA-based biomarkers in blood and other body fluids. Molecules 19(5):6080–6105. https://doi.org/10.3390/molecules19056080

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kanaan Z, Rai S, Eichenberger M, Roberts H, Keskey B, Pan J, Galandiuk S (2012) Plasma MiR-21. Ann Surg 256(3):544–551. https://doi.org/10.1097/sla.0b013e318265bd6f

    Article  PubMed  Google Scholar 

  12. Mishra P (2014) Non-coding RNAs as clinical biomarkers for cancer diagnosis and prognosis. Expert Rev Mol Diagn 14(8):917–919. https://doi.org/10.1586/14737159.2014.971761

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Mitchell P, Parkin R, Kroh E, Fritz B, Wyman S, Pogosova-Agadjanyan E et al (2008) Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci 105(30):10513–10518. https://doi.org/10.1073/pnas.0804549105

    Article  PubMed  PubMed Central  Google Scholar 

  14. Duttagupta R, Jiang R, Gollub J, Getts R, Jones K (2011) Impact of cellular miRNAs on circulating miRNA biomarker signatures. PLoS ONE 6(6):e20769. https://doi.org/10.1371/journal.pone.0020769

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Feng Y, Wu C, Tsao C, Chang J, Lu P, Yeh K et al (2011) Deregulated expression of sprouty2 and microRNA-21 in human colon cancer: correlation with the clinical stage of the disease. Cancer Biol Ther 11(1):111–121. https://doi.org/10.4161/cbt.11.1.13965

    Article  CAS  PubMed  Google Scholar 

  16. Medina P, Nolde M, Slack F (2010) OncomiR addiction in an in vivo model of microRNA-21-induced pre-B-cell lymphoma. Nature 467(7311):86–90. https://doi.org/10.1038/nature09284

    Article  CAS  PubMed  Google Scholar 

  17. Volinia S, Calin G, Liu C, Ambs S, Cimmino A, Petrocca F et al (2006) A microRNA expression signature of human solid tumors defines cancer gene targets. Proc Natl Acad Sci 103(7):2257–2261. https://doi.org/10.1073/pnas.0510565103

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Livak K, Schmittgen T (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 25(4):402–408. https://doi.org/10.1006/meth.2001

    Article  CAS  PubMed  Google Scholar 

  19. Walsh T, Casadei S, Lee M, Pennil C, Nord A, Thornton A et al (2011) Mutations in 12 genes for inherited ovarian, fallopian tube, and peritoneal carcinoma identified by massively parallel sequencing. Proc Natl Acad Sci 108(44):18032–18037. https://doi.org/10.1073/pnas.1115052108

    Article  PubMed  PubMed Central  Google Scholar 

  20. Paliwal N, Vashist M, Chauhan M (2020) Evaluation of miR-22 and miR-21 as diagnostic biomarkers in patients with epithelial ovarian cancer. 3 Biotech. https://doi.org/10.1007/s13205-020-2124-7

    Article  PubMed  PubMed Central  Google Scholar 

  21. Zhang W, Dahlberg J, Tam W (2007) MicroRNAs in tumorigenesis. Am J Pathol 171(3):728–738. https://doi.org/10.2353/ajpath.2007.070070

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Ashrafizadeh M, Hushmandi K, Hashemi M, Akbari M, Kubatka P, Raei M et al (2020) Role of microRNA/Epithelial-to-mesenchymal transition axis in the metastasis of bladder cancer. Biomolecules 10(8):1159. https://doi.org/10.3390/biom10081159

    Article  CAS  PubMed Central  Google Scholar 

  23. Xu Y, Xi Q, Ge W, Zhang X (2013) Identification of serum MicroRNA-21 as a biomarker for early detection and prognosis in human epithelial ovarian cancer. Asian Pac J Cancer Prev 14(2):1057–1060. https://doi.org/10.7314/apjcp.2013.14.2.1057

    Article  PubMed  Google Scholar 

  24. Kartika A, Chasanah S, Fitriawan A, Tanjung D, Trirahmanto A, Pradjatmo H et al (2018) MicroRNA-21 as a biomarker for ovarian cancer detection. Indones J Biotechnol 23(1):35. https://doi.org/10.22146/ijbiotech.35692

    Article  Google Scholar 

  25. Lou (2010) MicroRNA-21 promotes the cell proliferation, invasion, and migration abilities in ovarian epithelial carcinomas through inhibiting the expression of PTEN protein. Int J Mol Med. https://doi.org/10.3892/ijmm_00000530

    Article  PubMed  Google Scholar 

  26. Meng F, Henson R, Wehbe-Janek H, Ghoshal K, Jacob S, Patel T (2007) MicroRNA-21 regulates expression of the PTEN tumor suppressor gene in human hepatocellular cancer. Gastroenterology 133(2):647–658. https://doi.org/10.1053/j.gastro.2007.05.022

    Article  CAS  PubMed  Google Scholar 

  27. Asangani I, Rasheed S, Nikolova D, Leupold J, Colburn N, Post S, Allgayer H (2007) MicroRNA-21 (miR-21) post-transcriptionally downregulates tumor suppressor Pdcd4 and stimulates invasion, intravasation, and metastasis in colorectal cancer. Oncogene 27(15):2128–2136. https://doi.org/10.1038/sj.onc.1210856

    Article  CAS  PubMed  Google Scholar 

  28. Chan J, Blansit K, Kiet T, Sherman A, Wong G, Earle C, Bourguignon L (2014) The inhibition of miR-21 promotes apoptosis and chemosensitivity in ovarian cancer. Gynecol Oncol 132(3):739–744. https://doi.org/10.1016/j.ygyno.2014.01.034

    Article  CAS  PubMed  Google Scholar 

  29. Nam E, Yoon H, Kim S, Kim H, Kim Y, Kim J et al (2008) MicroRNA expression profiles in serous ovarian carcinoma. Clin Cancer Res 14(9):2690–2695. https://doi.org/10.1158/1078-0432.ccr-07-1731

    Article  CAS  PubMed  Google Scholar 

  30. Azzam A, Hashad D, Kamel N (2013) Evaluation of HE4 as an extrabiomarker to CA125 to improve detection of ovarian carcinoma: is it time for a step forward? Arch Gynecol Obstetr 288(1):167–172. https://doi.org/10.1007/s00404-013-2722-2

    Article  CAS  Google Scholar 

  31. Park Y, Lee J, Hong D, Lee E, Kim H (2011) Diagnostic performances of HE4 and CA125 for the detection of ovarian cancer from patients with various gynecologic and non-gynecologic diseases. Clin Biochem 44(10–11):884–888. https://doi.org/10.1016/j.clinbiochem.2011.04.011

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

Not applicable.

Author information

Authors and Affiliations

  1. Medical Biochemistry Department, Faculty of Medicine, Zagazig University, Zagazig, 44512, Egypt

    Aliaa Talaat & Sara F. Saadawy

  2. Department of Obstetrics and Gynecology, Faculty of Medicine, Zagazig University, Zagazig, Egypt

    Mohamed A. Helmy

Authors
  1. Aliaa Talaat
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohamed A. Helmy
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sara F. Saadawy
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

AT prepared the idea and designed the study. SFS did the data statistical analysis. AT and SFS performed all the laboratory investigations and interpreted the patients’ data regarding each studied group. MAH selected the patients and the control group. All authors wrote, read, and approved the final manuscript.

Corresponding author

Correspondence to Sara F. Saadawy.

Ethics declarations

Ethics approval and consent to participate

This study has been approved by the Faculty of Medicine, Zagazig University, IRB, for human studies (reference number is 9066/27-1-2021), and the patients have signed informed written consent.

Consent for publication

Not applicable.

Competing interests

All authors declared that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Talaat, A., Helmy, M.A. & Saadawy, S.F. Evaluation of miRNA-21 and CA-125 as a promising diagnostic biomarker in patients with ovarian cancer. Egypt J Med Hum Genet 23, 123 (2022). https://doi.org/10.1186/s43042-022-00342-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s43042-022-00342-5

Keywords