Open Access

Prognostic significance of deregulated microRNAs in uveal melanomas

  • Authors:
    • Luca Falzone
    • Giovanni L. Romano
    • Rossella Salemi
    • Claudio Bucolo
    • Barbara Tomasello
    • Gabriella Lupo
    • Carmelina D. Anfuso
    • Demetrios A. Spandidos
    • Massimo Libra
    • Saverio Candido
  • View Affiliations

  • Published online on: February 11, 2019     https://doi.org/10.3892/mmr.2019.9949
  • Pages: 2599-2610
  • Copyright: © Falzone et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

Uveal melanoma (UM) represents the most frequent primary tumor of the eye. Despite the development of new drugs and screening programs, the prognosis of patients with UM remains poor and no effective prognostic biomarkers are yet able to identify high‑risk patients. Therefore, in the present study, microRNA (miRNA or miR) expression data, contained in the TCGA UM (UVM) database, were analyzed in order to identify a set of miRNAs with prognostic significance to be used as biomarkers in clinical practice. Patients were stratified into 2 groups, including tumor stage (high‑grade vs. low‑grade) and status (deceased vs. alive); differential analyses of miRNA expression among these groups were performed. A total of 20 deregulated miRNAs for each group were identified. In total 7 miRNAs were common between the groups. The majority of common miRNAs belonged to the miR‑506‑514 cluster, known to be involved in UM development. The prognostic value of the 20 selected miRNAs related to tumor stage was assessed. The deregulation of 12 miRNAs (6 upregulated and 6 downregulated) was associated with a worse prognosis of patients with UM. Subsequently, miRCancerdb and microRNA Data Integration Portal bioinformatics tools were used to identify a set of genes associated with the 20 miRNAs and to establish their interaction levels. By this approach, 53 different negatively and positively associated genes were identified. Finally, DIANA‑mirPath prediction pathway and Gene Ontology enrichment analyses were performed on the lists of genes previously generated to establish their functional involvement in biological processes and molecular pathways. All the miRNAs and genes were involved in molecular pathways usually altered in cancer, including the mitogen‑activated protein kinase (MAPK) pathway. Overall, the findings of the presents study demonstrated that the miRNAs of the miR‑506‑514 cluster, hsa‑miR‑592 and hsa‑miR‑199a‑5p were the most deregulated miRNAs in patients with high‑grade disease compared to those with low‑grade disease and were strictly related to the overall survival (OS) of the patients. However, further in vitro and translational approaches are required to validate these preliminary findings.

References

1 

Shields CL, Kaliki S, Furuta M, Mashayekhi A and Shields JA: Clinical spectrum and prognosis of uveal melanoma based on age at presentation in 8,033 cases. Retina. 1363–1372. 2012. View Article : Google Scholar : PubMed/NCBI

2 

Nayman T, Bostan C, Logan P and Burnier MN Jr: Uveal melanoma risk factors: A systematic review of meta-analyses. Curr Eye Res. 42:1085–1093. 2017. View Article : Google Scholar : PubMed/NCBI

3 

Weis E, Shah CP, Lajous M, Shields JA and Shields CL: The association between host susceptibility factors and uveal melanoma: A meta-analysis. Arch Ophthalmol. 124:54–60. 2006. View Article : Google Scholar : PubMed/NCBI

4 

Falzone L, Marconi A, Loreto C, Franco S, Spandidos DA and Libra M: Occupational exposure to carcinogens: Benzene, pesticides and fibers (Review). Mol Med Rep. 14:4467–4474. 2016. View Article : Google Scholar : PubMed/NCBI

5 

Griewank KG, Murali R, Schilling B, Scholz S, Sucker A, Song M, Süsskind D, Grabellus F, Zimmer L, Hillen U, et al: TERT promoter mutations in ocular melanoma distinguish between conjunctival and uveal tumours. Br J Cancer. 109:497–501. 2013. View Article : Google Scholar : PubMed/NCBI

6 

Onken MD, Worley LA, Long MD, Duan S, Council ML, Bowcock AM and Harbour JW: Oncogenic mutations in GNAQ occur early in uveal melanoma. Invest Ophthalmol Vis Sci. 49:5230–5234. 2008. View Article : Google Scholar : PubMed/NCBI

7 

Urtatiz O and Van Raamsdonk CD: Gnaq and Gna11 in the Endothelin Signaling Pathway and Melanoma. Front Genet. 7:592016. View Article : Google Scholar : PubMed/NCBI

8 

Masoomian B, Shields JA and Shields CL: Overview of BAP1 cancer predisposition syndrome and the relationship to uveal melanoma. J Curr Ophthalmol. 30:102–109. 2018. View Article : Google Scholar : PubMed/NCBI

9 

Ehlers JP, Worley L, Onken MD and Harbour JW: Integrative genomic analysis of aneuploidy in uveal melanoma. Clin Cancer Res. 14:115–122. 2008. View Article : Google Scholar : PubMed/NCBI

10 

Sun Y, Tran BN, Worley LA, Delston RB and Harbour JW: Functional analysis of the p53 pathway in response to ionizing radiation in uveal melanoma. Invest Ophthalmol Vis Sci. 46:1561–1564. 2005. View Article : Google Scholar : PubMed/NCBI

11 

Shields CL, Kaliki S, Furuta M, Fulco E, Alarcon C and Shields JA: American Joint Committee on Cancer classification of posterior uveal melanoma (tumor size category) predicts prognosis in 7731 patients. Ophthalmology. 120:2066–2071. 2013. View Article : Google Scholar : PubMed/NCBI

12 

Macfarlane LA and Murphy PR: MicroRNA: Biogenesis, function and role in cancer. Curr Genomics. 11:537–561. 2010. View Article : Google Scholar : PubMed/NCBI

13 

Vivarelli S, Salemi R, Candido S, Falzone L, Santagati M, Stefani S, Torino F, Banna GL, Tonini G and Libra M: Gut microbiota and cancer: From pathogenesis to therapy. Cancers (Basel). 11:E382019. View Article : Google Scholar : PubMed/NCBI

14 

Tan W, Liu B, Qu S, Liang G, Luo W and Gong C: MicroRNAs and cancer: Key paradigms in molecular therapy. Oncol Lett. 15:2735–2742. 2018.PubMed/NCBI

15 

Banna GL, Torino F, Marletta F, Santagati M, Salemi R, Cannarozzo E, Falzone L, Ferraù F and Libra M: Lactobacillus rhamnosus GG: An Overview to Explore the Rationale of Its Use in Cancer. Front Pharmacol. 8:6032017. View Article : Google Scholar : PubMed/NCBI

16 

Baxter E, Windloch K, Gannon F and Lee JS: Epigenetic regulation in cancer progression. Cell Biosci. 4:452014. View Article : Google Scholar : PubMed/NCBI

17 

Tomczak K, Czerwińska P and Wiznerowicz M: The Cancer Genome Atlas (TCGA): An immeasurable source of knowledge. Contemp Oncol (Pozn). 19:A68–A77. 2015.PubMed/NCBI

18 

Yang Y, Dong X, Xie B, Ding N, Chen J, Li Y, Zhang Q, Qu H and Fang X: Databases and web tools for cancer genomics study. Genomics Proteomics Bioinformatics. 13:46–50. 2015. View Article : Google Scholar : PubMed/NCBI

19 

Falzone L, Scola L, Zanghì A, Biondi A, Di Cataldo A, Libra M and Candido S: Integrated analysis of colorectal cancer microRNA datasets: Identification of microRNAs associated with tumor development. Aging (Albany NY). 10:1000–1014. 2018. View Article : Google Scholar : PubMed/NCBI

20 

Falzone L, Candido S, Salemi R, Basile MS, Scalisi A, McCubrey JA, Torino F, Signorelli SS, Montella M and Libra M: Computational identification of microRNAs associated to both epithelial to mesenchymal transition and NGAL/MMP-9 pathways in bladder cancer. Oncotarget. 7:72758–72766. 2016. View Article : Google Scholar : PubMed/NCBI

21 

Hafsi S, Candido S, Maestro R, Falzone L, Soua Z, Bonavida B, Spandidos DA and Libra M: Correlation between the overexpression of Yin Yang 1 and the expression levels of miRNAs in Burkitt's lymphoma: A computational study. Oncol Lett. 11:1021–1025. 2016. View Article : Google Scholar : PubMed/NCBI

22 

Ahmed M, Nguyen H, Lai T and Kim DR: miRCancerdb: A database for correlation analysis between microRNA and gene expression in cancer. BMC Res Notes. 11:1032018. View Article : Google Scholar : PubMed/NCBI

23 

Tokar T, Pastrello C, Rossos AEM, Abovsky M, Hauschild AC, Tsay M, Lu R and Jurisica I: mirDIP 4.1-integrative database of human microRNA target predictions. Nucleic Acids Res. 46:D360–D370. 2018. View Article : Google Scholar : PubMed/NCBI

24 

Vlachos IS, Zagganas K, Paraskevopoulou MD, Georgakilas G, Karagkouni D, Vergoulis T, Dalamagas T and Hatzigeorgiou AG: DIANA-miRPath v3.0: Deciphering microRNA function with experimental support. Nucleic Acids Res. 43:W460–6. 2015. View Article : Google Scholar : PubMed/NCBI

25 

Leonardi GC, Falzone L, Salemi R, Zanghì A, Spandidos DA, Mccubrey JA, Candido S and Libra M: Cutaneous melanoma: From pathogenesis to therapy (Review). Int J Oncol. 52:1071–1080. 2018.PubMed/NCBI

26 

Falzone L, Salomone S and Libra M: Evolution of cancer pharmacological treatments at the turn of the third millennium. Front Pharmacol. 9:13002018. View Article : Google Scholar : PubMed/NCBI

27 

Tandler N, Mosch B and Pietzsch J: Protein and non-protein biomarkers in melanoma: A critical update. Amino Acids. 43:2203–2230. 2012. View Article : Google Scholar : PubMed/NCBI

28 

Salemi R, Falzone L, Madonna G, Polesel J, Cinà D, Mallardo D, Ascierto PA, Libra M and Candido S: MMP-9 as a Candidate Marker of Response to BRAF Inhibitors in Melanoma Patients With BRAFV600E Mutation Detected in Circulating-Free DNA. Front Pharmacol. 9:8562018. View Article : Google Scholar : PubMed/NCBI

29 

Field MG, Decatur CL, Kurtenbach S, Gezgin G, van der Velden PA, Jager MJ, Kozak KN and Harbour JW: PRAME as an independent biomarker for metastasis in uveal melanoma. Clin Cancer Res. 22:1234–1242. 2016. View Article : Google Scholar : PubMed/NCBI

30 

Falzone L, Salemi R, Travali S, Scalisi A, McCubrey JA, Candido S and Libra M: MMP-9 overexpression is associated with intragenic hypermethylation of MMP9 gene in melanoma. Aging (Albany NY). 8:933–944. 2016. View Article : Google Scholar : PubMed/NCBI

31 

Rezayi M, Farjami Z, Hosseini ZS, Ebrahimi N and Abouzari-Lotf E: MicroRNA-based biosensors for early detection of cancers. Curr Pharm. Jan 11–2019.(Epub ahead of print). doi: 10.2174/1381612825666190111144525. View Article : Google Scholar

32 

Battaglia R, Palini S, Vento ME, La Ferlita A, Lo Faro MJ, Caroppo E, Borzì P, Falzone L, Barbagallo D, Ragusa M, et al: Identification of extracellular vesicles and characterization of miRNA expression profiles in human blastocoel fluid. Sci Rep. 9:842019. View Article : Google Scholar : PubMed/NCBI

33 

Armand-Labit V and Pradines A: Circulating cell-free microRNAs as clinical cancer biomarkers. Biomol Concepts. 8:61–81. 2017. View Article : Google Scholar : PubMed/NCBI

34 

Hasin Y, Seldin M and Lusis A: Multi-omics approaches to disease. Genome Biol. 18:832017. View Article : Google Scholar : PubMed/NCBI

35 

Xin X, Zhang Y, Ling F, Wang L, Sheng X, Qin L and Zhao X: Identification of a nine-miRNA signature for the prognosis of Uveal Melanoma. Exp Eye Res. 180:242–249. 2019. View Article : Google Scholar : PubMed/NCBI

36 

Wan Q, Tang J, Han Y and Wang D: Co-expression modules construction by WGCNA and identify potential prognostic markers of uveal melanoma. Exp Eye Res. 166:13–20. 2018. View Article : Google Scholar : PubMed/NCBI

37 

Stark MS, Bonazzi VF, Boyle GM, Palmer JM, Symmons J, Lanagan CM, Schmidt CW, Herington AC, Ballotti R, Pollock PM, et al: miR-514a regulates the tumour suppressor NF1 and modulates BRAFi sensitivity in melanoma. Oncotarget. 6:17753–17763. 2015. View Article : Google Scholar : PubMed/NCBI

38 

Streicher KL, Zhu W, Lehmann KP, Georgantas RW, Morehouse CA, Brohawn P, Carrasco RA, Xiao Z, Tice DA, Higgs BW, et al: A novel oncogenic role for the miRNA-506-514 cluster in initiating melanocyte transformation and promoting melanoma growth. Oncogene. 31:1558–1570. 2012. View Article : Google Scholar : PubMed/NCBI

39 

Hanniford D, Zhong J, Koetz L, Gaziel-Sovran A, Lackaye DJ, Shang S, Pavlick A, Shapiro R, Berman R, Darvishian F, et al: A miRNA-Based Signature Detected in Primary Melanoma Tissue Predicts Development of Brain Metastasis. Clin Cancer Res. 21:4903–4912. 2015. View Article : Google Scholar : PubMed/NCBI

40 

Nguyen T, Kuo C, Nicholl MB, Sim MS, Turner RR, Morton DL and Hoon DS: Downregulation of microRNA-29c is associated with hypermethylation of tumor-related genes and disease outcome in cutaneous melanoma. Epigenetics. 6:388–394. 2011. View Article : Google Scholar : PubMed/NCBI

41 

Zhang K and Guo L: MiR-767 promoted cell proliferation in human melanoma by suppressing CYLD expression. Gene. 641:272–278. 2018. View Article : Google Scholar : PubMed/NCBI

42 

Hwang HW, Baxter LL, Loftus SK, Cronin JC, Trivedi NS, Borate B and Pavan WJ: Distinct microRNA expression signatures are associated with melanoma subtypes and are regulated by HIF1A. Pigment Cell Melanoma Res. 27:777–787. 2014. View Article : Google Scholar : PubMed/NCBI

43 

Luke JJ, Triozzi PL, McKenna KC, Van Meir EG, Gershenwald JE, Bastian BC, Gutkind JS, Bowcock AM, Streicher HZ, Patel PM, et al: Biology of advanced uveal melanoma and next steps for clinical therapeutics. Pigment Cell Melanoma Res. 28:135–147. 2015. View Article : Google Scholar : PubMed/NCBI

44 

Zhang Y, Yang Y, Chen L and Zhang J: Expression analysis of genes and pathways associated with liver metastases of the uveal melanoma. BMC Med Genet. 15:292014. View Article : Google Scholar : PubMed/NCBI

45 

Brantley MA Jr and Harbour JW: Deregulation of the Rb and p53 pathways in uveal melanoma. Am J Pathol. 157:1795–1801. 2000. View Article : Google Scholar : PubMed/NCBI

46 

Polo A, Crispo A, Cerino P, Falzone L, Candido S, Giudice A, De Petro G, Ciliberto G, Montella M, Budillon A, et al: Environment and bladder cancer: Molecular analysis by interaction networks. Oncotarget. 8:65240–65252. 2017. View Article : Google Scholar : PubMed/NCBI

47 

Guarneri C, Bevelacqua V, Polesel J, Falzone L, Cannavò PS, Spandidos DA, Malaponte G and Libra M: NF κB inhibition is associated with OPN/MMP 9 downregulation in cutaneous melanoma. Oncol Rep. 37:737–746. 2017. View Article : Google Scholar : PubMed/NCBI

48 

McCubrey JA, Fitzgerald TL, Yang LV, Lertpiriyapong K, Steelman LS, Abrams SL, Montalto G, Cervello M, Neri LM, Cocco L, et al: Roles of GSK-3 and microRNAs on epithelial mesenchymal transition and cancer stem cells. Oncotarget. 8:14221–14250. 2017. View Article : Google Scholar : PubMed/NCBI

49 

Helgadottir H and Höiom V: The genetics of uveal melanoma: Current insights. Appl Clin Genet. 9:147–155. 2016. View Article : Google Scholar : PubMed/NCBI

50 

Yoshida M, Selvan S, McCue PA, DeAngelis T, Baserga R, Fujii A, Rui H, Mastrangelo MJ and Sato T: Expression of insulin-like growth factor-1 receptor in metastatic uveal melanoma and implications for potential autocrine and paracrine tumor cell growth. Pigment Cell Melanoma Res. 27:297–308. 2014. View Article : Google Scholar : PubMed/NCBI

Related Articles

Journal Cover

April 2019
Volume 19 Issue 4

Print ISSN: 1791-2997
Online ISSN:1791-3004

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
APA
Falzone, L., Romano, G.L., Salemi, R., Bucolo, C., Tomasello, B., Lupo, G. ... Candido, S. (2019). Prognostic significance of deregulated microRNAs in uveal melanomas. Molecular Medicine Reports, 19, 2599-2610. https://doi.org/10.3892/mmr.2019.9949
MLA
Falzone, L., Romano, G. L., Salemi, R., Bucolo, C., Tomasello, B., Lupo, G., Anfuso, C. D., Spandidos, D. A., Libra, M., Candido, S."Prognostic significance of deregulated microRNAs in uveal melanomas". Molecular Medicine Reports 19.4 (2019): 2599-2610.
Chicago
Falzone, L., Romano, G. L., Salemi, R., Bucolo, C., Tomasello, B., Lupo, G., Anfuso, C. D., Spandidos, D. A., Libra, M., Candido, S."Prognostic significance of deregulated microRNAs in uveal melanomas". Molecular Medicine Reports 19, no. 4 (2019): 2599-2610. https://doi.org/10.3892/mmr.2019.9949