Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Molecular Diagnostics

miRNA-seq and clinical evaluation in multiple myeloma: miR-181a overexpression predicts short-term disease progression and poor post-treatment outcome

British Journal of Cancer volume 126, pages 79–90 (2022)Cite this article

Subjects

Abstract

Background

Despite significant advances in multiple myeloma (MM) therapy, disease relapse and treatment resistance remain major obstacles in clinical management. Herein, we have studied the clinical utility of miRNAs in improving patients’ risk-stratification and prognosis.

Methods

miRNA-seq was performed in CD138+ plasma cells of MM, smoldering multiple myeloma (sMM) and monoclonal gammopathy of undetermined significance (MGUS) patients. The screening MM cohort consisted of 138 patients. miRNA levels of CD138+ plasma cells were quantified by RT-qPCR following 3′-end RNA polyadenylation. Disease progression and patients’ death were used as clinical end-point events. Internal validation was conducted by bootstrap analysis. Clinical net benefit on disease prognosis was assessed by decision curve analysis. Kruykov et al. 2016 served as validation cohort (n = 151).

Results

miRNA-seq highlighted miR-181a to be upregulated in MM vs. sMM/MGUS, and R-ISS III vs. I patients. Screening and validation cohorts confirmed the significantly higher risk for short-term progression and worse survival of the patients overexpressing miR-181a. Multivariate models integrating miR-181a with disease established markers led to superior risk-stratification and clinical benefit for MM prognosis.

Conclusions

CD138+ overexpression of miR-181a was strongly correlated with inferior disease outcome and contributed to superior prediction of MM patients early progression, supporting personalised prognosis and treatment decisions.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: miRNAs profile of CD138+ plasma cells.
Fig. 2: CD138+ overexpression of miR-181a is strongly correlated with worse survival outcome following treatment.
Fig. 3: Patients overexpressing miR-181a are at significantly higher risk for short-term disease progression.
Fig. 4: Evaluation of CD138+ miR-181a levels increases risk-stratification efficacy and results to superior clinical benefit in MM prognosis.
Fig. 5: Decision curve analysis demonstrated the improved clinical net benefit of multivariate models integrating miR-181a with the established clinical markers.

Similar content being viewed by others

Data availability

All the data are available from the corresponding authors on reasonable request.

References

  1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin. 2020;70:7–30.

    Article  PubMed  Google Scholar 

  2. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71:209–49.

  3. Rajkumar SV. Multiple myeloma: 2020 update on diagnosis, risk-stratification and management. Am J Hematol. 2020;95:548–67.

    Article  CAS  PubMed  Google Scholar 

  4. Boyle EM, Deshpande S, Tytarenko R, Ashby C, Wang Y, Bauer MA, et al. The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma. Nat Commun. 2021;12:293.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Dimopoulos MA, Moreau P, Terpos E, Mateos MV, Zweegman S, Cook G, et al. Multiple myeloma: EHA-ESMO Clinical Practice Guidelines for Diagnosis, Treatment and Follow-up. Hemasphere. 2021;5:e528.

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Papanota AM, Karousi P, Kontos CK, Ntanasis-Stathopoulos I, Scorilas A, Terpos E. Multiple myeloma bone disease: implication of MicroRNAs in its molecular background. Int J Mol Sci. 2021;22:2375.

  7. Kumar SK, Rajkumar V, Kyle RA, van Duin M, Sonneveld P, Mateos MV, et al. Multiple myeloma. Nat Rev Dis Prim. 2017;3:17046.

    Article  PubMed  Google Scholar 

  8. Gonzalez-Calle V, Slack A, Keane N, Luft S, Pearce KE, Ketterling RP, et al. Evaluation of revised international staging system (R-ISS) for transplant-eligible multiple myeloma patients. Ann Hematol. 2018;97:1453–62.

    Article  PubMed  Google Scholar 

  9. Gebert LFR, MacRae IJ. Regulation of microRNA function in animals. Nat Rev Mol Cell Biol. 2019;20:21–37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Croce CM, Calin GA. miRNAs, cancer, and stem cell division. Cell. 2005;122:6–7.

    Article  CAS  PubMed  Google Scholar 

  11. Diamantopoulos MA, Tsiakanikas P, Scorilas A. Non-coding RNAs: the riddle of the transcriptome and their perspectives in cancer. Ann Transl Med. 2018;6:241.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Di Leva G, Garofalo M, Croce CM. MicroRNAs in cancer. Annu Rev Pathol. 2014;9:287–314.

    Article  PubMed  Google Scholar 

  13. Chen D, Yang X, Liu M, Zhang Z, Xing E. Roles of miRNA dysregulation in the pathogenesis of multiple myeloma. Cancer Gene Ther. 2021. https://www.nature.com/articles/s41417-020-00291-4.

  14. Rajkumar SV, Dimopoulos MA, Palumbo A, Blade J, Merlini G, Mateos MV, et al. International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol. 2014;15:e538–48.

    Article  PubMed  Google Scholar 

  15. Kumar S, Paiva B, Anderson KC, Durie B, Landgren O, Moreau P, et al. International Myeloma Working Group consensus criteria for response and minimal residual disease assessment in multiple myeloma. Lancet Oncol. 2016;17:e328–e46.

    Article  PubMed  Google Scholar 

  16. Kryukov F, Nemec P, Radova L, Kryukova E, Okubote S, Minarik J, et al. Centrosome associated genes pattern for risk sub-stratification in multiple myeloma. J Transl Med. 2016;14:150.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Friedlander MR, Mackowiak SD, Li N, Chen W, Rajewsky N. miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res. 2012;40:37–52.

    Article  PubMed  Google Scholar 

  18. Wong N, Wang X. miRDB: an online resource for microRNA target prediction and functional annotations. Nucleic Acids Res. 2015;43:D146–52.

    Article  CAS  PubMed  Google Scholar 

  19. Kuleshov MV, Jones MR, Rouillard AD, Fernandez NF, Duan Q, Wang Z, et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 2016;44:W90–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Supek F, Bosnjak M, Skunca N, Smuc T. REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS ONE. 2011;6:e21800.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Mak. 2006;26:565–74.

    Article  Google Scholar 

  22. Chen CZ, Li L, Lodish HF, Bartel DP. MicroRNAs modulate hematopoietic lineage differentiation. Science. 2004;303:83–6.

    Article  CAS  PubMed  Google Scholar 

  23. Schmidt TM, Barwick BG, Joseph N, Heffner LT, Hofmeister CC, Bernal L, et al. Gain of Chromosome 1q is associated with early progression in multiple myeloma patients treated with lenalidomide, bortezomib, and dexamethasone. Blood Cancer J. 2019;9:94.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Schmidt TM, Fonseca R, Usmani SZ. Chromosome 1q21 abnormalities in multiple myeloma. Blood Cancer J. 2021;11:83.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Landgren O, Rajkumar SV. New developments in diagnosis, prognosis, and assessment of response in multiple myeloma. Clin Cancer Res. 2016;22:5428–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Dimopoulos MA, Jakubowiak AJ, McCarthy PL, Orlowski RZ, Attal M, Blade J, et al. Developments in continuous therapy and maintenance treatment approaches for patients with newly diagnosed multiple myeloma. Blood Cancer J. 2020;10:17.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Rasche L, Chavan SS, Stephens OW, Patel PH, Tytarenko R, Ashby C, et al. Spatial genomic heterogeneity in multiple myeloma revealed by multi-region sequencing. Nat Commun. 2017;8:268.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Rupaimoole R, Slack FJ. MicroRNA therapeutics: towards a new era for the management of cancer and other diseases. Nat Rev Drug Discov. 2017;16:203–22.

    Article  CAS  PubMed  Google Scholar 

  29. Avgeris M, Panoutsopoulou K, Papadimitriou MA, Scorilas A. Circulating exosomal miRNAs: clinical significance in human cancers. Expert Rev Mol Diagn. 2019;19:979–95.

    Article  CAS  PubMed  Google Scholar 

  30. Morelli E, Leone E, Cantafio ME, Di Martino MT, Amodio N, Biamonte L, et al. Selective targeting of IRF4 by synthetic microRNA-125b-5p mimics induces anti-multiple myeloma activity in vitro and in vivo. Leukemia. 2015;29:2173–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Yin Y, Yang W, Zhang L, Liu K, Luo Z. Long non-coding RNA ANRIL and its target microRNAs (microRNA-34a, microRNA-125a and microRNA-186) relate to risk stratification and prognosis in multiple myeloma. Hematology. 2021;26:160–9.

    Article  CAS  PubMed  Google Scholar 

  32. Misso G, Zarone MR, Lombardi A, Grimaldi A, Cossu AM, Ferri C, et al. miR-125b upregulates miR-34a and sequentially activates stress adaption and cell death mechanisms in multiple myeloma. Mol Ther Nucleic Acids. 2019;16:391–406.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Di Martino MT, Leone E, Amodio N, Foresta U, Lionetti M, Pitari MR, et al. Synthetic miR-34a mimics as a novel therapeutic agent for multiple myeloma: in vitro and in vivo evidence. Clin Cancer Res. 2012;18:6260–70.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Leone E, Morelli E, Di Martino MT, Amodio N, Foresta U, Gulla A, et al. Targeting miR-21 inhibits in vitro and in vivo multiple myeloma cell growth. Clin Cancer Res. 2013;19:2096–106.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Rossi M, Altomare E, Botta C, Gallo Cantafio ME, Sarvide S, Caracciolo D, et al. miR-21 antagonism abrogates Th17 tumor promoting functions in multiple myeloma. Leukemia. 2021;35:823–34.

    Article  CAS  PubMed  Google Scholar 

  36. Amodio N, Di Martino MT, Foresta U, Leone E, Lionetti M, Leotta M, et al. miR-29b sensitizes multiple myeloma cells to bortezomib-induced apoptosis through the activation of a feedback loop with the transcription factor Sp1. Cell Death Dis. 2012;3:e436.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Pan Y, Zhang Y, Liu W, Huang Y, Shen X, Jing R, et al. LncRNA H19 overexpression induces bortezomib resistance in multiple myeloma by targeting MCL-1 via miR-29b-3p. Cell Death Dis. 2019;10:106.

  38. Xu J, Su Y, Xu A, Fan F, Mu S, Chen L, et al. miR-221/222-mediated inhibition of autophagy promotes dexamethasone resistance in multiple myeloma. Mol Ther. 2019;27:559–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Zhao JJ, Chu ZB, Hu Y, Lin J, Wang Z, Jiang M, et al. Targeting the miR-221-222/PUMA/BAK/BAX pathway abrogates dexamethasone resistance in multiple myeloma. Cancer Res. 2015;75:4384–97.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Qin Y, Zhang S, Deng S, An G, Qin X, Li F, et al. Epigenetic silencing of miR-137 induces drug resistance and chromosomal instability by targeting AURKA in multiple myeloma. Leukemia. 2017;31:1123–35.

    Article  CAS  PubMed  Google Scholar 

  41. Yang N, Chen J, Zhang H, Wang X, Yao H, Peng Y, et al. LncRNA OIP5-AS1 loss-induced microRNA-410 accumulation regulates cell proliferation and apoptosis by targeting KLF10 via activating PTEN/PI3K/AKT pathway in multiple myeloma. Cell Death Dis. 2017;8:e2975.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Emming S, Chirichella M, Monticelli S. MicroRNAs as modulators of T cell functions in cancer. Cancer Lett. 2018;430:172–8.

    Article  CAS  PubMed  Google Scholar 

  43. Pichiorri F, Suh SS, Ladetto M, Kuehl M, Palumbo T, Drandi D, et al. MicroRNAs regulate critical genes associated with multiple myeloma pathogenesis. Proc Natl Acad Sci USA. 2008;105:12885–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Roccaro AM, Sacco A, Thompson B, Leleu X, Azab AK, Azab F, et al. MicroRNAs 15a and 16 regulate tumor proliferation in multiple myeloma. Blood. 2009;113:6669–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Li YJ, Li DP, Yan ZL, Qi KM, Chen LL, Zhang ZY, et al. Potential relationship and clinical significance of miRNAs and Th17 cytokines in patients with multiple myeloma. Leuk Res. 2014;38:1130–5.

    Article  CAS  PubMed  Google Scholar 

  46. Giri S, Huntington SF, Wang R, Zeidan AM, Podoltsev N, Gore SD, et al. Chromosome 1 abnormalities and survival of patients with multiple myeloma in the era of novel agents. Blood Adv. 2020;4:2245–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Abdallah N, Greipp P, Kapoor P, Gertz MA, Dispenzieri A, Baughn LB, et al. Clinical characteristics and treatment outcomes of newly diagnosed multiple myeloma with chromosome 1q abnormalities. Blood Adv. 2020;4:3509–19.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Peng J, Thakur A, Zhang S, Dong YF, Wang XQ, Yuan RL, et al. Expressions of miR-181a and miR-20a in RPMI8226 cell line and their potential as biomarkers for multiple myeloma. Tumor Biol. 2015;36:8545–52.

    Article  CAS  Google Scholar 

  49. Liu N, Yang J, Yuan R, Peng J, Liu L, Guo X. Effects of miR181a on the biological function of multiple myeloma. Oncol Rep. 2019;42:291–300.

    CAS  PubMed  Google Scholar 

  50. Shen XX, Bai H, Zhu HY, Yan Q, Yang Y, Yu WJ, et al. Long non-coding RNA MEG3 functions as a competing endogenous RNA to regulate HOXA11 expression by sponging miR-181a in multiple myeloma. Cell Physiol Biochem. 2018;49:87–100.

    Article  CAS  PubMed  Google Scholar 

  51. Panoutsopoulou K, Avgeris M, Magkou P, Mavridis K, Dreyer T, Dorn J, et al. miR-181a overexpression predicts the poor treatment response and early-progression of serous ovarian cancer patients. Int J Cancer. 2020;147:3560–73.

    Article  CAS  PubMed  Google Scholar 

  52. Taylor MA, Sossey-Alaoui K, Thompson CL, Danielpour D, Schiemann WP. TGF-beta upregulates miR-181a expression to promote breast cancer metastasis. J Clin Invest. 2013;123:150–63.

    Article  CAS  PubMed  Google Scholar 

  53. Nishimura J, Handa R, Yamamoto H, Tanaka F, Shibata K, Mimori K, et al. microRNA-181a is associated with poor prognosis of colorectal cancer. Oncol Rep. 2012;28:2221–6.

    Article  CAS  PubMed  Google Scholar 

  54. Meijer LL, Garajova I, Caparello C, Le Large TYS, Frampton AE, Vasile E, et al. Plasma miR-181a-5p downregulation predicts response and improved survival after FOLFIRINOX in pancreatic ductal adenocarcinoma. Ann Surg. 2020;271:1137–47.

    Article  PubMed  Google Scholar 

  55. Mi Y, Zhang D, Jiang W, Weng J, Zhou C, Huang K, et al. miR-181a-5p promotes the progression of gastric cancer via RASSF6-mediated MAPK signalling activation. Cancer Lett. 2017;389:11–22.

    Article  CAS  PubMed  Google Scholar 

  56. Liu X, Liao W, Peng H, Luo X, Luo Z, Jiang H, et al. miR-181a promotes G1/S transition and cell proliferation in pediatric acute myeloid leukemia by targeting ATM. J Cancer Res Clin Oncol. 2016;142:77–87.

    Article  CAS  PubMed  Google Scholar 

  57. Lyu X, Li J, Yun X, Huang R, Deng X, Wang Y, et al. miR-181a-5p, an inducer of Wnt-signaling, facilitates cell proliferation in acute lymphoblastic leukemia. Oncol Rep. 2017;37:1469–76.

    Article  CAS  PubMed  Google Scholar 

  58. Fragoso R, Mao T, Wang S, Schaffert S, Gong X, Yue S, et al. Modulating the strength and threshold of NOTCH oncogenic signals by mir-181a-1/b-1. PLoS Genet. 2012;8:e1002855.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Haque S, Vaiselbuh SR. Silencing of exosomal miR-181a reverses pediatric acute lymphocytic leukemia cell proliferation. Pharmaceuticals (Basel). 2020;13:241.

Download references

Acknowledgements

We thank all patients and families for their participation. We thank IEMBITHEK (Greece) for partially funded the study. We thank Bodossaki Foundation (Athens, Greece) for partially supported the study by fellowship to PGA.

Author information

Author notes

  1. These authors contributed equally: Maria-Alexandra Papadimitriou, Aristea-Maria Papanota.

  2. These authors jointly supervised this work: Evangelos Terpos, Andreas Scorilas.

Authors and Affiliations

  1. Department of Biochemistry and Molecular Biology, Faculty of Biology, National and Kapodistrian University of Athens, Athens, Greece

    Maria-Alexandra Papadimitriou, Panagiotis G. Adamopoulos, Katerina-Marina Pilala, Margaritis Avgeris & Andreas Scorilas

  2. Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, “Alexandra” General Hospital, Athens, Greece

    Aristea-Maria Papanota, Christine-Ivy Liacos, Panagiotis Malandrakis, Nefeli Mavrianou-Koutsoukou, Dimitrios Patseas, Evangelos Eleutherakis-Papaiakovou, Maria Gavriatopoulou, Efstathios Kastritis, Meletios-Athanasios Dimopoulos & Evangelos Terpos

  3. Laboratory of Clinical Biochemistry—Molecular Diagnostics, Second Department of Pediatrics, School of Medicine, National and Kapodistrian University of Athens, “P. & A. Kyriakou” Children’s Hospital, Athens, Greece

    Margaritis Avgeris

Authors
  1. Maria-Alexandra Papadimitriou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aristea-Maria Papanota
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Panagiotis G. Adamopoulos
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Katerina-Marina Pilala
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Christine-Ivy Liacos
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Panagiotis Malandrakis
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Nefeli Mavrianou-Koutsoukou
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Dimitrios Patseas
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Evangelos Eleutherakis-Papaiakovou
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Maria Gavriatopoulou
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Efstathios Kastritis
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Margaritis Avgeris
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Meletios-Athanasios Dimopoulos
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Evangelos Terpos
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Andreas Scorilas
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conception and design: AS, ET, MAD, MA; Development of methodology: MAP, AMP, MA; Acquisition of data: MAP, AMP, PGA, KMP, CIL, PM, NMK, DP, EEP, MG, EK, MA; Analysis and interpretation of data: MAP, AMP, PGA, KMP, MA, MAD, ET, AS; Acquired and managed patients: AMP, MG, EK, MAD, ET; Drafting of the manuscript: MAP, AMP, PGA, MA; Critical revision of the manuscript: MAD, ET, AS; Study supervision: AS, ET, MAD, MA; Approval of the submitted and final version: All authors.

Corresponding authors

Correspondence to Evangelos Terpos or Andreas Scorilas.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

The study was approved by the Ethics Committee of “Alexandra” Hospital, Athens, Greece, and all patients who participated were informed and signed an informed consent according to 1975 Declaration of Helsinki ethical standards, as revised in 2008.

Consent for publication

Not applicable.

Additional information

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

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Papadimitriou, MA., Papanota, AM., Adamopoulos, P.G. et al. miRNA-seq and clinical evaluation in multiple myeloma: miR-181a overexpression predicts short-term disease progression and poor post-treatment outcome. Br J Cancer 126, 79–90 (2022). https://doi.org/10.1038/s41416-021-01602-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41416-021-01602-8

This article is cited by

Search

Advanced search

Quick links