Skip to main content
Log in

Modulatory Role of Vaginal-Isolated Lactococcus lactis on the Expression of miR-21, miR-200b, and TLR-4 in CAOV-4 Cells and In Silico Revalidation

  • Published:
Probiotics and Antimicrobial Proteins Aims and scope Submit manuscript

Abstract

Ovarian cancer (OC) is a leading cause of death among women worldwide. Various evidences suggest that oncomiRs and Toll-like receptor 4 (TLR-4) signaling pathways appear to be key players in the initiation and progression of OC. It seems there exists a continuous intercommunication between cancer cells and normal microbiota of the vagina. The biological impacts of vaginal isolated lactococcus lactis on CAOV-4 cells were investigated using several molecular biology experiments, including flow cytometry, DAPI staining, DNA ladder, and scratch assay. The expression of microRNAs (miRNAs/miRs) 21, 200b, and TLR-4 in the CAOV-4 cells was also evaluated by the real-time RT-PCR assay. Furthermore, an integrative in silico analysis was conducted using normalized web-available microarray data (GSE14407) to revalidate the experimental findings and identify potential biomarkers in ovarian cancer. Protein-protein interactions (PPIs) network was studied by means of the STRING database using Cytoscape v3.6.1. The miRNA target genes were identified using the dbDEMC v2.0, miRTarBase, and miRDB databases. Our data demonstrated that L. lactis probiotic candidate downregulates TLR-4, miR-21, and miR-200b expression levels, which correlates with induction of apoptosis as confirmed by DAPI staining, DNA ladder assay, annexin V/PI staining, and inhibition of migration validated by scratch assay. By in silico analysis, several targets (miR-17-5p-BCL2, miR-21-5p-MKNK2, miR-129-5p-CDK6) were identified, while BCL2, CCNB1, and VEGFA were found as the hub proteins in the miRNA-target and PPI networks. Further, downregulation of the TLR-4, miR-21, and miR-200b was partially validated by the in silico analysis. Based on our findings, the vaginal isolated probiotic strain presents great potential to control the ovarian cancer which may provide beneficial impact on the clinical management of ovarian cancer.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Albert R (2005) Scale-free networks in cell biology. J Cell Sci 118(21):4947–4957

    CAS  PubMed  Google Scholar 

  2. Asgharzadeh MR, Pourseif MM, Barar J, Eskandani M, Jafari Niya M, Mashayekhi MR, Omidi Y (2019) Functional expression and impacts of testis-specific gene antigen 10 in breast cancer: a combination in vitro and in silico approach. Bioimpacts 9(3):149–160

    Google Scholar 

  3. Atashpaz S, Khani S, Barzegari A, Barar J, Vahed SZ, Azarbaijani R, Omidi Y (2010) A robust universal method for extraction of genomic DNA from bacterial species. Mikrobiologiia 79(4):562–566

    PubMed  Google Scholar 

  4. Baghaei K, Hosseinkhan N, Aghdaei HA, Zali MR (2017) Investigation of a common gene expression signature in gastrointestinal cancers using systems biology approaches. Mol Biosyst 13(11):2277–2288

    CAS  PubMed  Google Scholar 

  5. Bai Y, Li LD, Li J, Lu X (2016) Targeting of topoisomerases for prognosis and drug resistance in ovarian cancer. J Ovarian Res 9(1):35

    PubMed  PubMed Central  Google Scholar 

  6. Balekar N, Katkam NG, Nakpheng T, Jehtae K, Srichana T (2012) Evaluation of the wound healing potential of Wedelia trilobata (L.) leaves. J Ethnopharmacol 141(3):817–824

    PubMed  Google Scholar 

  7. Banno K, Yanokura M, Iida M, Adachi M, Nakamura K, Nogami Y, Umene K, Masuda K, Kisu I, Nomura H, Kataoka F (2014) Application of microRNA in diagnosis and treatment of ovarian cancer. Biomed Res Int 2014:232817

    PubMed  PubMed Central  Google Scholar 

  8. Barrett T, Edgar R (2006) Mining microarray data at NCBI’s Gene Expression Omnibus (GEO). Methods Mol Biol 338:175–190

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Basith S, Manavalan B, Yoo TH, Kim SG, Choi S (2012) Roles of toll-like receptors in cancer: a double-edged sword for defense and offense. Arch Pharm Res 35(8):1297–1316

    CAS  PubMed  Google Scholar 

  10. Bernardes N, Seruca R, Chakrabarty AM, Fialho AM (2010) Microbial-based therapy of cancer: current progress and future prospects. Bioeng Bugs 1(3):178–190

    PubMed  Google Scholar 

  11. Bowen NJ, Walker LD, Matyunina LV, Logani S, Totten KA, Benigno BB, McDonald JF (2009) Gene expression profiling supports the hypothesis that human ovarian surface epithelia are multipotent and capable of serving as ovarian cancer initiating cells. BMC Med Genomics 2(1):71

    PubMed  PubMed Central  Google Scholar 

  12. Cao Q, Lu K, Dai S, Hu Y, Fan W (2014) Clinicopathological and prognostic implications of the miR-200 family in patients with epithelial ovarian cancer. Int J Clin Exp Pathol 7(5):2392–2401

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Chan JK, Blansit K, Kiet T, Sherman A, Wong G, Earle C, Bourguignon LY (2014) The inhibition of miR-21 promotes apoptosis and chemosensitivity in ovarian cancer. Gynecol Oncol 132(3):739–744

    CAS  PubMed  Google Scholar 

  14. Chin CH, Chen SH, Wu HH, Ho CW, Ko MT, Lin CY (2014) cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Syst Biol 8(Suppl 4):S11

    PubMed  PubMed Central  Google Scholar 

  15. Chou CH, Shrestha S, Yang CD, Chang NW, Lin YL, Liao KW, Huang WC, Sun TH, Tu SJ, Lee WH, Chiew MY (2018) miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions. Nucleic Acids Res 46(D1):D296–D302

    CAS  PubMed  Google Scholar 

  16. Cline MS, Smoot M, Cerami E, Kuchinsky A, Landys N, Workman C, Christmas R, Avila-Campilo I, Creech M, Gross B, Hanspers K (2007) Integration of biological networks and gene expression data using Cytoscape. Nat Protoc 2(10):2366–2382

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Cribby S, Taylor M, Reid G (2008) Vaginal microbiota and the use of probiotics. Interdiscip Perspect Infect Dis 2008:256490

    PubMed  Google Scholar 

  18. Davidson B, Tropé CG, Reich R (2014) The clinical and diagnostic role of microRNAs in ovarian carcinoma. Gynecol Oncol 133(3):640–646

    CAS  PubMed  Google Scholar 

  19. Erriquez J, Becco P, Olivero M, Ponzone R, Maggiorotto F, Ferrero A, Scalzo MS, Canuto EM, Sapino A, Di Cantogno LV, Bruna P (2015) TOP2A gene copy gain predicts response of epithelial ovarian cancers to pegylated liposomal doxorubicin: TOP2A as marker of response to PLD in ovarian cancer. Gynecol Oncol 138(3):627–633

    CAS  PubMed  Google Scholar 

  20. Fang Y, Xu C, Fu Y (2015) MicroRNA-17-5p induces drug resistance and invasion of ovarian carcinoma cells by targeting PTEN signaling. J Biol Res (Thessalon) 22(1):12

    CAS  Google Scholar 

  21. Francescone R, Hou V, Grivennikov SI (2014) Microbiome, inflammation, and cancer. Cancer J 20(3):181–189

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Fraser M, Leung B, Jahani-Asl A, Yan X, Thompson WE, Tsang BK (2003) Chemoresistance in human ovarian cancer: the role of apoptotic regulators. Reprod Biol Endocrinol 1(1):66

    PubMed  PubMed Central  Google Scholar 

  23. Gaikwad SM, Thakur B, Sakpal A, Singh RK, Ray P (2015) Differential activation of NF-kappaB signaling is associated with platinum and taxane resistance in MyD88 deficient epithelial ovarian cancer cells. Int J Biochem Cell Biol 61:90–102

    CAS  PubMed  Google Scholar 

  24. Han JD, Bertin N, Hao T, Goldberg DS, Berriz GF, Zhang LV, Dupuy D, Walhout AJ, Cusick ME, Roth FP, Vidal M (2004) Evidence for dynamically organized modularity in the yeast protein-protein interaction network. Nature 430(6995):88–93

    CAS  PubMed  Google Scholar 

  25. Hye-Mi JI, Young-Nan CH, Seung-Jung KE, Shin-Seok LE, Yong-Wook PA, Tae-Jong KI (2016) Micro-ribonucleic acid profiles from microarray in ankylosing spondylitis. Arch Rheumatol 31(2):121–126

    Google Scholar 

  26. Kelly MG, Alvero AB, Chen R, Silasi DA, Abrahams VM, Chan S, Visintin I, Rutherford T, Mor G (2006) TLR-4 signaling promotes tumor growth and paclitaxel chemoresistance in ovarian cancer. Cancer Res 66(7):3859–3868

    CAS  PubMed  Google Scholar 

  27. Khanghah SM, Ganbarov K (2014) Lactobacillus with probiotic potential from homemade cheese in Azerbijan. Bioimpacts 4(1):49–52

    CAS  Google Scholar 

  28. Kim KH, Jo MS, Suh DS, Yoon MS, Shin DH, Lee JH, Choi KU (2012) Expression and significance of the TLR4/MyD88 signaling pathway in ovarian epithelial cancers. World J Surg Oncol 10(1):193

    PubMed  PubMed Central  Google Scholar 

  29. Koutsaki M, Spandidos DA, Zaravinos A (2014) 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 351(2):173–181

    CAS  PubMed  Google Scholar 

  30. Liang CC, Park AY, Guan JL (2007) In vitro scratch assay: a convenient and inexpensive method for analysis of cell migration in vitro. Nat Protoc 2(2):329–333

    CAS  PubMed  Google Scholar 

  31. Liu MX, Siu MK, Liu SS, Yam JW, Ngan HY, Chan DW (2014) Epigenetic silencing of microRNA-199b-5p is associated with acquired chemoresistance via activation of JAG1-Notch1 signaling in ovarian cancer. Oncotarget 5(4):944–958

    PubMed  Google Scholar 

  32. Liu G, Du P, Zhang Z (2015) Myeloid differentiation factor 88 promotes cisplatin chemoresistance in ovarian cancer. Cell Biochem Biophys 71(2):963–969

    CAS  PubMed  Google Scholar 

  33. Lou Y, Yang X, Wang F, Cui Z, Huang Y (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 26(6):819–827

    CAS  PubMed  Google Scholar 

  34. Morelli L, Capurso L (2012) FAO/WHO guidelines on probiotics: 10 years later. J Clin Gastroenterol 46(Suppl):S1–S2

    PubMed  Google Scholar 

  35. Muccioli M, Benencia F (2014) Toll-like receptors in ovarian cancer as targets for immunotherapies. Front Immunol 5:341

    PubMed  PubMed Central  Google Scholar 

  36. Naniwa J, Kigawa J, Kanamori Y, Itamochi H, Oishi T, Shimada M, Shimogai R, Kawaguchi W, Sato S, Terakawa N (2007) Genetic diagnosis for chemosensitivity with drug-resistance genes in epithelial ovarian cancer. Int J Gynecol Cancer 17(1):76–82

    CAS  PubMed  Google Scholar 

  37. Nguyen HT, Tian G, Murph MM (2014) Molecular epigenetics in the management of ovarian cancer: are we investigating a rational clinical promise? Front Oncol 4:71

    PubMed  PubMed Central  Google Scholar 

  38. Rahbar Saadat Y, Saeidi N, Zununi Vahed S, Barzegari A, Barar J (2015) An update to DNA ladder assay for apoptosis detection. Bioimpacts 5(1):25–28

    PubMed  PubMed Central  Google Scholar 

  39. Ran J, Li H, Fu J, Liu L, Xing Y, Li X, Shen H, Chen Y, Jiang X, Li Y, Li H (2013) Construction and analysis of the protein-protein interaction network related to essential hypertension. BMC Syst Biol 7(1):32

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Rao VS, Srinivas K, Sujini GN, Kumar GN (2014) Protein-protein interaction detection: methods and analysis. Int J Proteomics 2014:147648

    PubMed  PubMed Central  Google Scholar 

  41. Reid G (2001) Probiotic agents to protect the urogenital tract against infection. Am J Clin Nutr 73(2 Suppl):437S–443S

    CAS  PubMed  Google Scholar 

  42. Schwikowski B, Uetz P, Fields S (2000) A network of protein-protein interactions in yeast. Nat Biotechnol 18(12):1257–1261

    CAS  PubMed  Google Scholar 

  43. Shuang T, Wang M, Zhou Y, Shi C (2016) Over-expression of nuclear NF-kappaB1 and c-Rel correlates with chemoresistance and prognosis of serous epithelial ovarian cancer. Exp Mol Pathol 100(1):139–144

    CAS  PubMed  Google Scholar 

  44. Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, Santos A, Doncheva NT, Roth A, Bork P, Jensen LJ (2017) The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res 45(D1):D362–D368

    CAS  PubMed  Google Scholar 

  45. Verhaak RG, Sanders MA, Bijl MA, Delwel R, Horsman S, Moorhouse MJ, van der Spek PJ, Löwenberg B, Valk PJ (2006) HeatMapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristics. BMC Bioinformatics 7(1):337

    PubMed  PubMed Central  Google Scholar 

  46. Wang X (2016) Improving microRNA target prediction by modeling with unambiguously identified microRNA-target pairs from CLIP-ligation studies. Bioinformatics 32(9):1316–1322

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Wang J, Duncan D, Shi Z, Zhang B (2013) WEB-based GEne SeT AnaLysis Toolkit (WebGestalt): update 2013. Nucleic Acids Res 41(W1):W77–W83

    PubMed  PubMed Central  Google Scholar 

  48. Wang AC, Ma YB, Wu FX, Ma ZF, Liu NF, Gao R, Gao YS, Sheng XG (2014) TLR4 induces tumor growth and inhibits paclitaxel activity in MyD88-positive human ovarian carcinoma in vitro. Oncol Lett 7(3):871–877

    CAS  PubMed  Google Scholar 

  49. Wettenhall JM, Simpson KM, Satterley K, Smyth GK (2006) affylmGUI: a graphical user interface for linear modeling of single channel microarray data. Bioinformatics 22(7):897–899

    CAS  PubMed  Google Scholar 

  50. Xie B, Ding Q, Han H, Wu D (2013) miRCancer: a microRNA-cancer association database constructed by text mining on literature. Bioinformatics 29(5):638–644

    CAS  PubMed  Google Scholar 

  51. Xie Z, Cao L, Zhang J (2013) miR-21 modulates paclitaxel sensitivity and hypoxia-inducible factor-1alpha expression in human ovarian cancer cells. Oncol Lett 6(3):795–800

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Yang Z, Wu L, Wang A, Tang W, Zhao Y, Zhao H, Teschendorff AE (2017) dbDEMC 2.0: updated database of differentially expressed miRNAs in human cancers. Nucleic Acids Res 45(D1):D812–D818

    CAS  PubMed  Google Scholar 

  53. Zhao H, Xu H, Xue L (2017) Regulatory network involving miRNAs and genes in serous ovarian carcinoma. Oncol Lett 14(5):6259–6268

    PubMed  PubMed Central  Google Scholar 

  54. Zununi Vahed S, Barzegari A, Rahbar Saadat Y, Mohammadi S, Samadi N (2016) A microRNA isolation method from clinical samples. Bioimpacts 6(1):25–31

    PubMed  PubMed Central  Google Scholar 

  55. Zununi Vahed S, Barzegari A, Rahbar Saadat Y, Goreyshi A, Omidi Y (2017) Leuconostoc mesenteroides-derived anticancer pharmaceuticals hinder inflammation and cell survival in colon cancer cells by modulating NF-kappaB/AKT/PTEN/MAPK pathways. Biomed Pharmacother 94:1094–1100

    CAS  PubMed  Google Scholar 

Download references

Funding

The Research Center for Pharmaceutical Nanotechnology (RCPN) at the Biomedicine Institute, Tabriz University of Medical Sciences, provided financial support.

Author information

Authors and Affiliations

Authors

Contributions

Y.O., A.B., and J.B. designed the research. Y.R.S. and S.Z.V. performed experiments. A.B. performed the bacterial characterization and western blot assay. M.M.P. performed in silico analysis. YO reviewed the in silico data. Y.R.S. and S.Z.V. analyzed the data. All the authors discussed the results. Y.R.S. and M.M.P. drafted the manuscript. J.B. critically revised the manuscript for important intellectual content. All authors read and gave final approval of the submission of the last version of the paper.

Corresponding authors

Correspondence to Abolfazl Barzegari or Jaleh Barar.

Ethics declarations

Ethical Approval

The present study was approved by the Ethics and Human Rights Committee of Tabriz University of Medical Sciences, Tabriz, Iran (Ethical code: IR.TBZMED.REC.1397.1051) and written informed consent was obtained after enough explanation about the purpose of the study.

Conflict of Interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s Note

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

Electronic supplementary material

ESM 1

(DOCX 3108 kb).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rahbar Saadat, Y., Pourseif, M.M., Zununi Vahed, S. et al. Modulatory Role of Vaginal-Isolated Lactococcus lactis on the Expression of miR-21, miR-200b, and TLR-4 in CAOV-4 Cells and In Silico Revalidation. Probiotics & Antimicro. Prot. 12, 1083–1096 (2020). https://doi.org/10.1007/s12602-019-09596-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12602-019-09596-9

Keywords

Navigation