Skip to main content
Log in

Global miRNA expression of bone marrow mesenchymal stem/stromal cells derived from Fanconi anemia patients

  • Research Article
  • Published:
Human Cell Aims and scope Submit manuscript

Abstract

Fanconi anemia (FA) is a rare genetic disorder characterized by genomic instability, developmental defects, and bone marrow (BM) failure. Hematopoietic stem cells (HSCs) in BM interact with the mesenchymal stem/stromal cells (MSCs); and this partly sustains the tissue homeostasis. MicroRNAs (miRNAs) can play a critical role during these interactions possibly via paracrine mechanisms. This is the first study addressing the miRNA profile of FA BM–MSCs obtained before and after BM transplantation (preBMT and postBMT, respectively). Non-coding RNA expression profiling and quality control analyses were performed in Donors (n = 13), FA preBMT (n = 11), and FA postBMT (n = 6) BM–MSCs using GeneChip miRNA 2.0 Array. Six Donor-FA preBMT pairs were used to identify a differentially expressed miRNA expression signature containing 50 miRNAs, which exhibited a strong correlation with the signature obtained from unpaired samples. Five miRNAs (hsa-miR-146a-5p, hsa-miR-148b-3p, hsa-miR-187-3p, hsa-miR-196b-5p, and hsa-miR-25-3p) significantly downregulated in both the paired and unpaired analyses were used to generate the BM–MSCs’ miRNA—BM mononuclear mRNA networks upon integration of a public dataset (GSE16334; studying Donor versus FA samples). Functionally enriched KEGG pathways included cellular senescence, miRNAs, and pathways in cancer. Here, we showed that hsa-miR-146a-5p and hsa-miR-874-3p were rescued upon BMT (n = 3 triplets). The decrease in miR-146a-5p was also validated using RT-qPCR and emerged as a strong candidate as a modulator of BM mRNAs in FA patients.

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

Access this article

Subscribe and save

Springer+
from $39.99 /Month
  • Starting from 10 chapters or articles per month
  • Access and download chapters and articles from more than 300k books and 2,500 journals
  • Cancel anytime
View plans

Buy Now

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

Similar content being viewed by others

References

  1. Bushati N, Cohen SM. microRNA functions. Annu Rev Cell Dev Biol. 2007;23:175–205. https://doi.org/10.1146/annurev.cellbio.23.090506.123406.

    Article  CAS  PubMed  Google Scholar 

  2. Li Y, Kowdley KV. MicroRNAs in common human diseases. Genom Proteom Bioinform. 2012;10(5):246–53. https://doi.org/10.1016/j.gpb.2012.07.005.

    Article  CAS  Google Scholar 

  3. Degan P, Cappelli E, Longobardi M, Pulliero A, Cuccarolo P, Dufour C, et al. A global MicroRNA profile in Fanconi anemia: a pilot study. Metab Syndr Relat Disord. 2019;17(1):53–9. https://doi.org/10.1089/met.2018.0085.

    Article  CAS  PubMed  Google Scholar 

  4. Rio P, Agirre X, Garate L, Banos R, Alvarez L, San Jose-Eneriz E, et al. Down-regulated expression of hsa-miR-181c in Fanconi anemia patients: implications in TNFalpha regulation and proliferation of hematopoietic progenitor cells. Blood. 2012;119(13):3042–9. https://doi.org/10.1182/blood-2011-01-331017.

    Article  CAS  PubMed  Google Scholar 

  5. Suresh B, Kumar AM, Jeong HS, Cho YH, Ramakrishna S, Kim KS. Regulation of Fanconi anemia protein FANCD2 monoubiquitination by miR-302. Biochem Biophys Res Commun. 2015;466(2):180–5. https://doi.org/10.1016/j.bbrc.2015.08.127.

    Article  CAS  PubMed  Google Scholar 

  6. Knies K, Inano S, Ramirez MJ, Ishiai M, Surralles J, Takata M, et al. Biallelic mutations in the ubiquitin ligase RFWD3 cause Fanconi anemia. J Clin Invest. 2017;127(8):3013–27. https://doi.org/10.1172/JCI92069.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Mamrak NE, Shimamura A, Howlett NG. Recent discoveries in the molecular pathogenesis of the inherited bone marrow failure syndrome Fanconi anemia. Blood Rev. 2017;31(3):93–9. https://doi.org/10.1016/j.blre.2016.10.002.

    Article  CAS  PubMed  Google Scholar 

  8. D’Andrea AD, Grompe M. The Fanconi anaemia/BRCA pathway. Nat Rev Cancer. 2003;3(1):23–34. https://doi.org/10.1038/nrc970.

    Article  CAS  PubMed  Google Scholar 

  9. Kee Y, D’Andrea AD. Molecular pathogenesis and clinical management of Fanconi anemia. J Clin Invest. 2012;122(11):3799–806. https://doi.org/10.1172/JCI58321.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Wagner JE, Eapen M, MacMillan ML, Harris RE, Pasquini R, Boulad F, et al. Unrelated donor bone marrow transplantation for the treatment of Fanconi anemia. Blood. 2007;109(5):2256–62. https://doi.org/10.1182/blood-2006-07-036657.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kastrinaki MC, Pavlaki K, Batsali AK, Kouvidi E, Mavroudi I, Pontikoglou C, et al. Mesenchymal stem cells in immune-mediated bone marrow failure syndromes. Clin Dev Immunol. 2013;2013: 265608. https://doi.org/10.1155/2013/265608.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Morrison SJ, Scadden DT. The bone marrow niche for haematopoietic stem cells. Nature. 2014;505(7483):327–34. https://doi.org/10.1038/nature12984.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Muguruma Y, Yahata T, Miyatake H, Sato T, Uno T, Itoh J, et al. Reconstitution of the functional human hematopoietic microenvironment derived from human mesenchymal stem cells in the murine bone marrow compartment. Blood. 2006;107(5):1878–87. https://doi.org/10.1182/blood-2005-06-2211.

    Article  CAS  PubMed  Google Scholar 

  14. Zhou Y, He Y, Xing W, Zhang P, Shi H, Chen S, et al. An abnormal bone marrow microenvironment contributes to hematopoietic dysfunction in Fanconi anemia. Haematologica. 2017;102(6):1017–27. https://doi.org/10.3324/haematol.2016.158717.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Chotinantakul K, Leeanansaksiri W. Hematopoietic stem cell development, niches, and signaling pathways. Bone Marrow Res. 2012;2012: 270425. https://doi.org/10.1155/2012/270425.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Giudice V, Banaszak LG, Gutierrez-Rodrigues F, Kajigaya S, Panjwani R, Ibanez M, et al. Circulating exosomal microRNAs in acquired aplastic anemia and myelodysplastic syndromes. Haematologica. 2018;103(7):1150–9. https://doi.org/10.3324/haematol.2017.182824.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Fujii S, Miura Y, Fujishiro A, Shindo T, Shimazu Y, Hirai H, et al. Graft-versus-host disease amelioration by human bone marrow mesenchymal stromal/stem cell-derived extracellular vesicles is associated with peripheral preservation of naive T cell populations. Stem Cells. 2018;36(3):434–45. https://doi.org/10.1002/stem.2759.

    Article  CAS  PubMed  Google Scholar 

  18. Reis M, Mavin E, Nicholson L, Green K, Dickinson AM, Wang XN. Mesenchymal stromal cell-derived extracellular vesicles attenuate dendritic cell maturation and function. Front Immunol. 2018;9:2538. https://doi.org/10.3389/fimmu.2018.02538.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Wu H, Fan H, Shou Z, Xu M, Chen Q, Ai C, et al. Extracellular vesicles containing miR-146a attenuate experimental colitis by targeting TRAF6 and IRAK1. Int Immunopharmacol. 2019;68:204–12. https://doi.org/10.1016/j.intimp.2018.12.043.

    Article  CAS  PubMed  Google Scholar 

  20. Kundrotas G, Gasperskaja E, Slapsyte G, Gudleviciene Z, Krasko J, Stumbryte A, et al. Identity, proliferation capacity, genomic stability and novel senescence markers of mesenchymal stem cells isolated from low volume of human bone marrow. Oncotarget. 2016;7(10):10788–802. https://doi.org/10.18632/oncotarget.7456.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Pan Q, Fouraschen SM, de Ruiter PE, Dinjens WN, Kwekkeboom J, Tilanus HW, et al. Detection of spontaneous tumorigenic transformation during culture expansion of human mesenchymal stromal cells. Exp Biol Med (Maywood). 2014;239(1):105–15. https://doi.org/10.1177/1535370213506802.

    Article  CAS  Google Scholar 

  22. Jung M, Mehta PA, Jiang CS, Rosti RO, Usleaman G, Correa da Rosa JM, et al. Comparison of the clinical phenotype and haematological course of siblings with Fanconi anaemia. Br J Haematol. 2021;193(5):971–5. https://doi.org/10.1111/bjh.17061.

    Article  CAS  PubMed  Google Scholar 

  23. Cagnan I. HOX and TALE transcription factors in Fanconi anemia bonemarrow mesenchymal stem cells: gene expression and protein interactions. Ankara: Hacettepe University; 2018.

    Google Scholar 

  24. Cagnan I, Gunel-Ozcan A, Aerts-Kaya F, Ameziane N, Kuskonmaz B, Dorsman J, et al. Bone marrow mesenchymal stem cells carrying FANCD2 mutation differ from the other Fanconi anemia complementation groups in terms of TGF-beta1 production. Stem Cell Rev Rep. 2018;14(3):425–37. https://doi.org/10.1007/s12015-017-9794-5.

    Article  CAS  PubMed  Google Scholar 

  25. Cagnan I, Aerts-Kaya F, Çetinkaya FD, Özcan A. Stably expressed reference genes during differentiation of bone marrow-derived mesenchymal stromal cells. Turk J Biol. 2017;41:88–97. https://doi.org/10.3906/biy-1511-93.

    Article  CAS  Google Scholar 

  26. Coste E, Rouleux-Bonnin F. The crucial choice of reference genes: identification of miR-191-5p for normalization of miRNAs expression in bone marrow mesenchymal stromal cell and HS27a/HS5 cell lines. Sci Rep. 2020;10(1):17728. https://doi.org/10.1038/s41598-020-74685-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Brettschneider J, Collin F, Bolstad BM, Speed TP. Quality assessment for short oligonucleotide microarray data. Technometrics. 2008;50(3):241–64. https://doi.org/10.1198/004017008000000334.

    Article  Google Scholar 

  28. Pearson FRSK. LIII. On lines and planes of closest fit to systems of points in space. Lond Edinb Dublin Philos Mag J Sci. 1901;2(11):559–72. https://doi.org/10.1080/14786440109462720.

    Article  Google Scholar 

  29. Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7): e47. https://doi.org/10.1093/nar/gkv007.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32(18):2847–9. https://doi.org/10.1093/bioinformatics/btw313.

    Article  CAS  PubMed  Google Scholar 

  31. Carvalho BS, Irizarry RA. A framework for oligonucleotide microarray preprocessing. Bioinformatics. 2010;26(19):2363–7. https://doi.org/10.1093/bioinformatics/btq431.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Vanderwerf SM, Svahn J, Olson S, Rathbun RK, Harrington C, Yates J, et al. TLR8-dependent TNF-(alpha) overexpression in Fanconi anemia group C cells. Blood. 2009;114(26):5290–8. https://doi.org/10.1182/blood-2009-05-222414.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Chang L, Zhou G, Soufan O, Xia J. miRNet 2.0: network-based visual analytics for miRNA functional analysis and systems biology. Nucleic Acids Res. 2020;48(W1):W244–51. https://doi.org/10.1093/nar/gkaa467.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504. https://doi.org/10.1101/gr.1239303.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607–13. https://doi.org/10.1093/nar/gky1131.

    Article  CAS  PubMed  Google Scholar 

  36. Szklarczyk D, Gable AL, Nastou KC, Lyon D, Kirsch R, Pyysalo S, et al. The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 2021;49(D1):D605–12. https://doi.org/10.1093/nar/gkaa1074.

    Article  CAS  PubMed  Google Scholar 

  37. Bioinformatics & Evolutionary Genomics. 2021. http://bioinformatics.psb.ugent.be/webtools/Venn/. Accessed 30 Aug 2021.

  38. Li J, Du W, Maynard S, Andreassen PR, Pang Q. Oxidative stress-specific interaction between FANCD2 and FOXO3a. Blood. 2010;115(8):1545–8. https://doi.org/10.1182/blood-2009-07-234385.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Oppezzo A, Bourseguin J, Renaud E, Pawlikowska P, Rosselli F. Microphthalmia transcription factor expression contributes to bone marrow failure in Fanconi anemia. J Clin Invest. 2020;130(3):1377–91. https://doi.org/10.1172/JCI131540.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Zhang X, Lu X, Akhter S, Georgescu MM, Legerski RJ. FANCI is a negative regulator of Akt activation. Cell Cycle. 2016;15(8):1134–43. https://doi.org/10.1080/15384101.2016.1158375.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Briot D, Mace-Aime G, Subra F, Rosselli F. Aberrant activation of stress-response pathways leads to TNF-alpha oversecretion in Fanconi anemia. Blood. 2008;111(4):1913–23. https://doi.org/10.1182/blood-2007-07-099218.

    Article  CAS  PubMed  Google Scholar 

  42. Svahn J, Lanza T, Rathbun K, Bagby G, Ravera S, Corsolini F, et al. p38 Mitogen-activated protein kinase inhibition enhances in vitro erythropoiesis of Fanconi anemia, complementation group A-deficient bone marrow cells. Exp Hematol. 2015;43(4):295–9. https://doi.org/10.1016/j.exphem.2014.11.010.

    Article  CAS  PubMed  Google Scholar 

  43. Zhang H, Kozono DE, O’Connor KW, Vidal-Cardenas S, Rousseau A, Hamilton A, et al. TGF-beta inhibition rescues hematopoietic stem cell defects and bone marrow failure in Fanconi anemia. Cell Stem Cell. 2016;18(5):668–81. https://doi.org/10.1016/j.stem.2016.03.002.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Gu H, Xu J, Huang Z, Wu L, Zhou K, Zhang Y, et al. Identification and differential expression of microRNAs in 1, 25-dihydroxyvitamin D3-induced osteogenic differentiation of human adipose-derived mesenchymal stem cells. Am J Transl Res. 2017;9(11):4856–71.

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Han X, Yang H, Liu H, Zhang C, Cao Y, Fan Z, et al. miR-196b-5p inhibits proliferation of Wharton’s jelly umbilical cord stem cells. FEBS Open Bio. 2021;11(1):278–88. https://doi.org/10.1002/2211-5463.13043.

    Article  CAS  PubMed  Google Scholar 

  46. Mollazadeh S, Fazly Bazzaz BS, Neshati V, de Vries AAF, Naderi-Meshkin H, Mojarad M, et al. Overexpression of MicroRNA-148b-3p stimulates osteogenesis of human bone marrow-derived mesenchymal stem cells: the role of MicroRNA-148b-3p in osteogenesis. BMC Med Genet. 2019;20(1):117. https://doi.org/10.1186/s12881-019-0854-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Peng Y, Zhao JL, Peng ZY, Xu WF, Yu GL. Exosomal miR-25-3p from mesenchymal stem cells alleviates myocardial infarction by targeting pro-apoptotic proteins and EZH2. Cell Death Dis. 2020;11(5):317. https://doi.org/10.1038/s41419-020-2545-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Zhang X, Sejas DP, Qiu Y, Williams DA, Pang Q. Inflammatory ROS promote and cooperate with the Fanconi anemia mutation for hematopoietic senescence. J Cell Sci. 2007;120(Pt 9):1572–83. https://doi.org/10.1242/jcs.003152.

    Article  CAS  PubMed  Google Scholar 

  49. Suh N. MicroRNA controls of cellular senescence. BMB Rep. 2018;51(10):493–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Meng X, Xue M, Xu P, Hu F, Sun B, Xiao Z. MicroRNA profiling analysis revealed different cellular senescence mechanisms in human mesenchymal stem cells derived from different origin. Genomics. 2017;109(3–4):147–57. https://doi.org/10.1016/j.ygeno.2017.02.003.

    Article  CAS  PubMed  Google Scholar 

  51. Su YL, Wang X, Mann M, Adamus TP, Wang D, Moreira DF, et al. Myeloid cell-targeted miR-146a mimic inhibits NF-kappaB-driven inflammation and leukemia progression in vivo. Blood. 2020;135(3):167–80. https://doi.org/10.1182/blood.2019002045.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Epanchintsev A, Shyamsunder P, Verma RS, Lyakhovich A. IL-6, IL-8, MMP-2, MMP-9 are overexpressed in Fanconi anemia cells through a NF-kappaB/TNF-alpha dependent mechanism. Mol Carcinog. 2015;54(12):1686–99. https://doi.org/10.1002/mc.22240.

    Article  CAS  PubMed  Google Scholar 

  53. Kontou M, Adelfalk C, Hirsch-Kauffmann M, Schweiger M. Suboptimal action of NF-kappaB in Fanconi anemia cells results from low levels of thioredoxin. Biol Chem. 2003;384(10–11):1501–7. https://doi.org/10.1515/BC.2003.166.

    Article  CAS  PubMed  Google Scholar 

  54. Li Y, Li X, Cole A, McLaughlin S, Du W. Icariin improves Fanconi anemia hematopoietic stem cell function through SIRT6-mediated NF-kappa B inhibition. Cell Cycle. 2018;17(3):367–76. https://doi.org/10.1080/15384101.2018.1426413.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Sundaravinayagam D, Kim HR, Wu T, Kim HH, Lee HS, Jun S, et al. miR146a-mediated targeting of FANCM during inflammation compromises genome integrity. Oncotarget. 2016;7(29):45976–94. https://doi.org/10.18632/oncotarget.10275.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Sundaravinayagam D, Kim HR, Wu T, Kim HH, Lee HS, Jun S, et al. Correction: miR146a-mediated targeting of FANCM during inflammation compromises genome integrity. Oncotarget. 2020;11(21):2024–5. https://doi.org/10.18632/oncotarget.27481.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Jing H, Lee S. NF-kappaB in cellular senescence and cancer treatment. Mol Cells. 2014;37(3):189–95. https://doi.org/10.14348/molcells.2014.2353.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Moussa Agha D, Rouas R, Najar M, Bouhtit F, Naamane N, Fayyad-Kazan H, et al. Identification of acute myeloid leukemia bone marrow circulating MicroRNAs. Int J Mol Sci. 2020. https://doi.org/10.3390/ijms21197065.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Skov V, Larsen TS, Thomassen M, Riley CH, Jensen MK, Bjerrum OW, et al. Whole-blood transcriptional profiling of interferon-inducible genes identifies highly upregulated IFI27 in primary myelofibrosis. Eur J Haematol. 2011;87(1):54–60. https://doi.org/10.1111/j.1600-0609.2011.01618.x.

    Article  CAS  PubMed  Google Scholar 

  60. Li Y, Zhu H, Wei X, Li H, Yu Z, Zhang H, et al. LPS induces HUVEC angiogenesis in vitro through miR-146a-mediated TGF-beta1 inhibition. Am J Transl Res. 2017;9(2):591–600.

    PubMed  PubMed Central  Google Scholar 

  61. Arvey A, Larsson E, Sander C, Leslie CS, Marks DS. Target mRNA abundance dilutes microRNA and siRNA activity. Mol Syst Biol. 2010;6:363. https://doi.org/10.1038/msb.2010.24.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Raaijmakers MH, Mukherjee S, Guo S, Zhang S, Kobayashi T, Schoonmaker JA, et al. Bone progenitor dysfunction induces myelodysplasia and secondary leukaemia. Nature. 2010;464(7290):852–7. https://doi.org/10.1038/nature08851.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Ozdogan H, Gur Dedeoglu B, Oztemur Islakoglu Y, Aydos A, Kose S, Atalay A, et al. DICER1 gene and miRNA dysregulation in mesenchymal stem cells of patients with myelodysplastic syndrome and acute myeloblastic leukemia. Leuk Res. 2017;63:62–71. https://doi.org/10.1016/j.leukres.2017.10.006.

    Article  CAS  PubMed  Google Scholar 

  64. Bai Y, Qiu GR, Zhou F, Gong LY, Gao F, Sun KL. Overexpression of DICER1 induced by the upregulation of GATA1 contributes to the proliferation and apoptosis of leukemia cells. Int J Oncol. 2013;42(4):1317–24. https://doi.org/10.3892/ijo.2013.1831.

    Article  CAS  PubMed  Google Scholar 

  65. Xie K, Cai Y, Yang P, Du F, Wu K. Upregulating microRNA-874-3p inhibits CXCL12 expression to promote angiogenesis and suppress inflammatory response in ischemic stroke. Am J Physiol Cell Physiol. 2020;319(3):C579–88. https://doi.org/10.1152/ajpcell.00001.2020.

    Article  CAS  PubMed  Google Scholar 

  66. Chabanon A, Desterke C, Rodenburger E, Clay D, Guerton B, Boutin L, et al. A cross-talk between stromal cell-derived factor-1 and transforming growth factor-beta controls the quiescence/cycling switch of CD34(+) progenitors through FoxO3 and mammalian target of rapamycin. Stem Cells. 2008;26(12):3150–61. https://doi.org/10.1634/stemcells.2008-0219.

    Article  CAS  PubMed  Google Scholar 

  67. Sugiyama T, Kohara H, Noda M, Nagasawa T. Maintenance of the hematopoietic stem cell pool by CXCL12-CXCR4 chemokine signaling in bone marrow stromal cell niches. Immunity. 2006;25(6):977–88. https://doi.org/10.1016/j.immuni.2006.10.016.

    Article  CAS  PubMed  Google Scholar 

  68. Flores-Figueroa E, Varma S, Montgomery K, Greenberg PL, Gratzinger D. Distinctive contact between CD34+ hematopoietic progenitors and CXCL12+ CD271+ mesenchymal stromal cells in benign and myelodysplastic bone marrow. Lab Invest. 2012;92(9):1330–41. https://doi.org/10.1038/labinvest.2012.93.

    Article  CAS  PubMed  Google Scholar 

  69. Huang Y, Han Y, Guo R, Liu H, Li X, Jia L, et al. Long non-coding RNA FER1L4 promotes osteogenic differentiation of human periodontal ligament stromal cells via miR-874-3p and vascular endothelial growth factor A. Stem Cell Res Ther. 2020;11(1):5. https://doi.org/10.1186/s13287-019-1519-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Kushwaha P, Khedgikar V, Sharma D, Yuen T, Gautam J, Ahmad N, et al. MicroRNA 874–3p exerts skeletal anabolic effects epigenetically during weaning by suppressing Hdac1 expression. J Biol Chem. 2016;291(8):3959–66. https://doi.org/10.1074/jbc.M115.687152.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This study was supported by The Scientific and Technological Research Council of Turkey (TUBITAK; project no: 110S021) in conjunction with EU COST Action BM0805 designated as ‘HOX and TALE transcription factors in Development and Disease’.

Funding

This work was supported by The Scientific and Technological Research Council of Turkey (TUBITAK; project no: 110S021) in conjunction with EU COST Action BM0805 designated as ‘HOX and TALE transcription factors in Development and Disease’.

Author information

Authors and Affiliations

Authors

Contributions

AGO designed the study and supervised the experiments. OK supervised the bioinformatics analysis. AGO, OK, IC, and MK drafted the introduction and discussion. IC, MK, AGK, MT, OBS, and FAK performed the experiments and/or data analysis. IC, MK, AGK, and MT drafted methods and results. DUC provided the bone marrow samples. All the authors approved the final version of manuscript.

Corresponding authors

Correspondence to Ozlen Konu or Aysen Gunel-Ozcan.

Ethics declarations

Conflict of interest

The authors have no relevant financial or non-financial interests to disclose.

Ethics approval

This study was performed in line with the principles of the Declaration of Helsinki. This study was approved by the Local Ethical Committee (Number 14, 24/08/2009).

Informed consent

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

Additional information

Publisher's Note

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

Supplementary Information

Below is the link to the electronic supplementary material.

13577_2021_626_MOESM1_ESM.eps

Online Resource 1 Representative images of FA postBMT BM–MSCs (i.e. HUSCS-FA11) showing a) flow cytometry analysis of CD29, CD44, CD166, CD90, CD106, CD146, CD144, CD200, CD133, CD34, CD105, CD45, CD14, CD73, HLA-ABC, HLA-DR, CD140b, CD31 surface markers, and b) differentiation potential of postBMT BM–MSCs on day 21 following induction; image on the left depicts control (undifferentiated) BM–MSCs; image at the middle depicts BM–MSCs differentiated to adipogenic lineage and stained with Oil-Red O dye; image on the right depicts BM–MSCs differentiated to osteogenic lineage and stained with Alizarin Red S dye). Intriguingly, postBMT samples obtained from HUSCS-FA04, HUSCS-FA09a and HUSCS-FA10 did not show any osteogenic differentiation potential (data not shown). Due to low cell number, CD133, CD34, CD45, CD14, HLA-ABC and HLA-DR levels were not analyzed for HUSCS-FA09a (EPS 53829 KB)

Supplementary File2 (Online Resource 2) (DOCX 25 KB)

13577_2021_626_MOESM3_ESM.eps

Online Resource 3 Quality Control analysis of the microarray data (n = 30). a) Boxplot of NUSE values. Outliers were labeled with red. b) Multidimensional scaling (MDS) plot for the microarray data. Outliers were labelled. Samples were colored according to the patient group. ‘T’ in the labelling designates postBMT samples. FA09a and FA09b are affected siblings from the same family (EPS 104129 KB)

13577_2021_626_MOESM4_ESM.eps

Online Resource 4 Heatmap of paired samples (a) and samples without pairs (b) created by 50 miRNAs that have been obtained to be significantly differentially expressed in paired analysis (EPS 63032 KB)

13577_2021_626_MOESM5_ESM.eps

Online Resource 5 Boxplots of the expression values of the five significantly altered miRNAs obtained from the paired samples analysis (a) and samples without pairs (b). P-values obtained from limma analysis were reported on the plot (EPS 112573 KB)

13577_2021_626_MOESM6_ESM.eps

Online Resource 6 miRNAs commonly downregulated in FA MSCs in paired and unpaired analyses integrated with FA bone marrow mononuclear cells. BM–MNC mRNAs downregulated at least 0.5 log FC. The miRNA-mRNA interaction data obtained from miRnet.ca were used in Cytoscape (v3.8.2) and coloring and size of mRNAs indicate the degree of downregulation. The edge width indicates the number of experimental evidence for the gene targets (EPS 61046 KB)

Supplementary File2 (Online Resource 7) (DOCX 15 KB)

13577_2021_626_MOESM8_ESM.eps

Online Resource 8 Upregulated targets of hsa-miR-146a-5p and hsa-miR-874-3p in FA bone marrow mononuclear cells. mRNAs were upregulated at least 0.5 log FC. The miRNA-mRNA interaction data obtained from miRnet.ca were used in Cytoscape (v3.8.2) and coloring and size of mRNAs indicate the degree of upregulation. The edge width indicates the number of experimental evidence for the gene targets (EPS 52343 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cagnan, I., Keles, M., Keskus, A.G. et al. Global miRNA expression of bone marrow mesenchymal stem/stromal cells derived from Fanconi anemia patients. Human Cell 35, 111–124 (2022). https://doi.org/10.1007/s13577-021-00626-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1007/s13577-021-00626-9

Keywords

Profiles

  1. Ozge Burcu Sahan
  2. Fatima Aerts-Kaya