460
Views
21
CrossRef citations to date
0
Altmetric
Original Articles: Research

MicroRNAs and tRNA-derived fragments predict the transformation of myelodysplastic syndromes to acute myeloid leukemia

, , , , , , , & ORCID Icon show all
Pages 2144-2155 | Received 21 Jul 2016, Accepted 10 Dec 2016, Published online: 13 Jan 2017

References

  • Ma X, Does M, Raza A, et al. Myelodysplastic syndromes: incidence and survival in the United States. Cancer. 2007;109:1536–1542.
  • Swerdlow SH, Campo E, Harris NL, et al. World Health Organization classification of tumours of haematopoietic and lymphoid tissues , vol. 2, 4th ed. Lyon, France: IARC Press; 2008.
  • Greenberg P, Cox C, LeBeau MM, et al. International scoring system for evaluating prognosis in myelodysplastic syndromes. Blood. 1997;89:2079–2088.
  • Greenberg PL, Tuechler H, Schanz J, et al. Revised international prognostic scoring system for myelodysplastic syndromes. Blood. 2012;120:2454–2465.
  • Greenberg PL. The multifaceted nature of myelodysplastic syndromes: clinical, molecular, and biological prognostic features. J Natl Compr Cancer Netw. 2013;11:877–885.
  • Haferlach T, Nagata Y, Grossmann V, et al. Landscape of genetic lesions in 944 patients with myelodysplastic syndromes. Leukemia. 2014;28:241–247.
  • Kuendgen A, Seidler J, Lauseker M, et al. Prognostic impact of molecular mutations in 182 patients with myelodysplastic syndromes. Blood. 2013;122:2758.
  • Lindsley RC, Mar BG, Mazzola E, et al. Acute myeloid leukemia ontogeny is defined by distinct somatic mutations. Blood. 2015;125:1367–1376.
  • Bejar R, Stevenson KE, Caughey BA, et al. Validation of a prognostic model and the impact of mutations in patients with lower-risk myelodysplastic syndromes. J Clin Oncol. 2012;30:3376–3382.
  • Starczynowski DT, Kuchenbauer F, Argiropoulos B, et al. Identification of miR-145 and miR-146a as mediators of the 5q- syndrome phenotype. Nat Med. 2010;16:49–58.
  • Dostalova Merkerova M, Krejcik Z, Votavova H, et al. Distinctive microRNA expression profiles in CD34+ bone marrow cells from patients with myelodysplastic syndrome. Eur J Hum Genet. 2011;19:313–319.
  • Erdogan B, Facey C, Qualtieri J, et al. Diagnostic microRNAs in myelodysplastic syndrome. Exp Hematol. 2011;39:915–926. e2.
  • Hussein K, Theophile K, Busche G, et al. Aberrant microRNA expression pattern in myelodysplastic bone marrow cells. Leuk Res. 2010;34:1169–1174.
  • Pons A, Nomdedeu B, Navarro A, et al. Hematopoiesis-related microRNA expression in myelodysplastic syndromes. Leuk Lymphoma. 2009;50:1854–1859.
  • Sokol L, Caceres G, Volinia S, et al. Identification of a risk dependent microRNA expression signature in myelodysplastic syndromes. Br J Haematol. 2011;153:24–32.
  • Xu F, Zhu Y, He Q, et al. Identification of microRNA-regulated pathways using an integration of microRNA-mRNA microarray and bioinformatics analysis in CD34+ cells of myelodysplastic syndromes. Sci Rep. 2016;6:32232.
  • Cammarata G, Augugliaro L, Salemi D, et al. Differential expression of specific microRNA and their targets in acute myeloid leukemia. Am J Hematol. 2010;85:331–339.
  • Cattaneo M, Pelosi E, Castelli G, et al. A miRNA signature in human cord blood stem and progenitor cells as potential biomarker of specific acute myeloid leukemia subtypes. J Cell Physiol. 2015;230:1770–1780.
  • Eyholzer M, Schmid S, Schardt JA, et al. Complexity of miR-223 regulation by CEBPA in human AML. Leuk Res. 2010;34:672–676.
  • Garzon R, Volinia S, Liu CG, et al. MicroRNA signatures associated with cytogenetics and prognosis in acute myeloid leukemia. Blood. 2008;111:3183–3189.
  • Garzon R, Garofalo M, Martelli MP, et al. Distinctive microRNA signature of acute myeloid leukemia bearing cytoplasmic mutated nucleophosmin. Proc Natl Acad Sci USA. 2008;105:3945–3950.
  • Marcucci G, Mrozek K, Radmacher MD, et al. The prognostic and functional role of microRNAs in acute myeloid leukemia. Blood. 2011;117:1121–1129.
  • Enright AJ, John B, Gaul U, et al. MicroRNA targets in Drosophila. Genome Biol. 2003;5:R1.
  • Lewis BP, Shih IH, Jones-Rhoades MW, et al. Prediction of mammalian microRNA targets. Cell. 2003;115:787–798.
  • Stark A, Brennecke J, Russell RB, et al. Identification of Drosophila MicroRNA targets. PLoS Biol. 2003;1:E60.
  • Kozomara A, Griffiths-Jones S. miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res. 2014;42:D68–D73.
  • Fu Y, Lee I, Lee YS, et al. Small non-coding transfer RNA-derived RNA fragments (tRFs): their biogenesis, function and implication in human diseases. Genomics Inform. 2015;13:94.
  • Fu H, Feng J, Liu Q, et al. Stress induces tRNA cleavage by angiogenin in mammalian cells. FEBS Lett. 2009;583:437–442.
  • Diebel KW, Zhou K, Clarke AB, et al. Beyond the ribosome: extra-translational functions of tRNA fragments. Biomarker Insights. 2016;11:1–8.
  • Goodarzi H, Liu X, Nguyen HCB, et al. Endogenous tRNA-derived fragments suppress breast cancer progression via YBX1 displacement. Cell. 2015;161:790–802.
  • Kumar P, Anaya J, Mudunuri SB, et al. Meta-analysis of tRNA derived RNA fragments reveals that they are evolutionarily conserved and associate with AGO proteins to recognize specific RNA targets. BMC Biol. 2014;12:78.
  • Olvedy M, Scaravilli M, Hoogstrate Y, et al. A comprehensive repertoire of tRNA-derived fragments in prostate cancer. Oncotarget. 2016;7:24766–24777.
  • Venkatesh T, Suresh PS, Tsutsumi R. TRFs: MiRNAs in disguise. Gene. 2016;579:133–138.
  • Arber DA, Orazi A, Hasserjian R, et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood. 2016;127:2391–2405.
  • Guo Y, Bosompem A, Mohan S, et al. Transfer RNA detection by small RNA deep sequencing and disease association with myelodysplastic syndromes. BMC Genomics. 2015;16:727–737.
  • Vickers KC, Roteta LA, Hucheson-Dilks H, et al. Mining diverse small RNA species in the deep transcriptome. Trends Biochem Sci. 2015;40:4–7.
  • Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 2011;17:10–12.
  • Guo Y, Zhao S, Sheng Q, et al. Multi-perspective quality control of Illumina exome sequencing data using QC3. Genomics. 2014;103:323–328.
  • Langmead B, Trapnell C, Pop M, et al. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10:R25.
  • Berezikov E, Robine N, Samsonova A, et al. Deep annotation of Drosophila melanogaster microRNAs yields insights into their processing, modification, and emergence. Genome Res. 2011;21:203–215.
  • Larter CZ, Yeh MM. Animal models of NASH: getting both pathology and metabolic context right. J Gastroenterol Hepatol. 2008;23:1635–1648.
  • Rajagopalan R, Vaucheret H, Trejo J, et al. A diverse and evolutionarily fluid set of microRNAs in Arabidopsis thaliana. Genes Dev. 2006;20:3407–3425.
  • Westholm JO, Ladewig E, Okamura K, et al. Common and distinct patterns of terminal modifications to mirtrons and canonical microRNAs. RNA. 2012;18:177–192.
  • Chan PP, Lowe TM. GtRNAdb: a database of transfer RNA genes detected in genomic sequence. Nucleic Acids Res. 2009;37:D93–D97.
  • Flicek P, Amode MR, Barrell D, et al. Ensembl 2014. Nucleic Acids Res. 2014;42:D749–D755.
  • Guo Y, Zhao S, Ye F, et al. MultiRankSeq: multiperspective approach for RNAseq differential expression analysis and quality control. Biomed Res Int. 2014;2014:8.
  • Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.
  • Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodological. 1995;57:289–300.
  • Su R, Lin HS, Zhang XH, et al. MiR-181 family: regulators of myeloid differentiation and acute myeloid leukemia as well as potential therapeutic targets. Oncogene. 2015;34:3226–3239.
  • Xiong Q, Yang Y, Wang H, et al. Characterization of miRNomes in acute and chronic myeloid leukemia cell lines. Genomics Proteomics Bioinformatics. 2014;12:79–91.
  • Yoshizawa S, Ohyashiki JH, Ohyashiki M, et al. Downregulated plasma miR-92a levels have clinical impact on multiple myeloma and related disorders. Blood Cancer J. 2012;2:e53. doi: 10.1038/bcj.2011.51.
  • Ovcharenko D, Stolzel F, Poitz D, et al. miR-10a overexpression is associated with NPM1 mutations and MDM4 downregulation in intermediate-risk acute myeloid leukemia. Exp Hematol. 2011;39:1030–1042.
  • Qian J, Lin J, Qian W, et al. Overexpression of miR-378 is frequent and may affect treatment outcomes in patients with acute myeloid leukemia. Leuk Res. 2013;37:765–768.
  • Marcucci G, Maharry K, Wu YZ, et al. IDH1 and IDH2 gene mutations identify novel molecular subsets within de novo cytogenetically normal acute myeloid leukemia: a Cancer and Leukemia Group B study. J Clin Oncol. 2010;28:2348–2355.
  • Marcucci G, Metzeler KH, Schwind S, et al. Age-related prognostic impact of different types of DNMT3A mutations in adults with primary cytogenetically normal acute myeloid leukemia. J Clin Oncol. 2012;30:742–750.
  • Li Z, Chen J. In vitro functional study of miR-126 in leukemia. Methods Mol Biol. 2011;676:185–195.
  • Wang XS, Gong JN, Yu J, et al. MicroRNA-29a and microRNA-142-3p are regulators of myeloid differentiation and acute myeloid leukemia. Blood. 2012;119:4992–5004.
  • Whitman SP, Maharry K, Radmacher MD, et al. FLT3 internal tandem duplication associates with adverse outcome and gene- and microRNA-expression signatures in patients 60 years of age or older with primary cytogenetically normal acute myeloid leukemia: a Cancer and Leukemia Group B study. Blood. 2010;116:3622–3626.
  • Vlachos IS, Kostoulas N, Vergoulis T, et al. DIANA miRPath v.2.0: investigating the combinatorial effect of microRNAs in pathways. Nucleic Acids Res. 2012;40:W498–504.
  • Weng H, Lal K, Yang FF, et al. The pathological role and prognostic impact of miR-181 in acute myeloid leukemia. Cancer Genet. 2015;208:225–229.
  • Favreau AJ, Duarte CW, Sathyanarayana P. Mir-199b, a novel tumor suppressor miRNA in acute myeloid leukemia with prognostic implications in FAB-M5 subtype. Blood. 2013;122.
  • Favreau AJ, McGlauflin RE, Duarte CW, Sathyanarayana P. miR-199b, a novel tumor suppressor miRNA in acute myeloid leukemia with prognostic implications. Exp Hematol Oncol. 2013;38:984–997.
  • Williams A, Henao-Mejia J, Harman CCD, et al. miR-181 and metabolic regulation in the immune system. Cold Spring Harb Symp Quant Biol. 2013;78:223–230.
  • Martelli AM, Nyåkern M, Tabellini G, et al. Phosphoinositide 3-kinase/Akt signaling pathway and its therapeutical implications for human acute myeloid leukemia. Leuk Off J Leuk Soc Am Leuk Res Fund UK. 2006;20:911–928.
  • Ivanov P, O’Day E, Emara MM, et al. G-quadruplex structures contribute to the neuroprotective effects of angiogenin-induced tRNA fragments. Proc Natl Acad Sci USA. 2014;111:18201–18206.
  • Newman MA, Mani V, Hammond SM. Deep sequencing of microRNA precursors reveals extensive 3' end modification. RNA. 2011;17:1795–1803.
  • Wyman SK, Knouf EC, Parkin RK, et al. Post-transcriptional generation of miRNA variants by multiple nucleotidyl transferases contributes to miRNA transcriptome complexity. Genome Res. 2011;21:1450–1461.
  • Xu L, Xu Y, Jing Z, et al. Altered expression pattern of miR-29a, miR-29b and the target genes in myeloid leukemia. Exp Hematol Oncol. 2014;3:17.
  • Seyyedi SS, Soleimani M, Yaghmaie M, et al. Deregulation of miR-1, miR486, and let-7a in cytogenetically normal acute myeloid leukemia: association with NPM1 and FLT3 mutation and clinical characteristics. Tumor Biol. 2016;37:4841–4847.
  • Zhi YJ, Xie XB, Wang R, et al. Serum level of miR-10-5p as a prognostic biomarker for acute myeloid leukemia. Int J Hematol. 2015;102:296–303.
  • Wang Y, Li Z, He C, et al. MicroRNAs expression signatures are associated with lineage and survival in acute leukemias. Blood Cells Mol Dis. 2010;44:191–197.
  • Chim CS, Wong KY, Leung CY, et al. Epigenetic inactivation of the hsa-miR-203 in haematological malignancies. J Cell Mol Med. 2011;15:2760–2767.
  • De Leeuw DC, Van Den Ancker W, Denkers F, et al. MicroRNA profiling can classify acute leukemias of ambiguous lineage as either acute myeloid leukemia or acute lymphoid leukemia. Clin Cancer Res. 2013;19:2187–2196.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.