|
1
|
Pui CH, Carroll WL, Meshinchi S and Arceci
RJ: Biology, risk stratification, and therapy of pediatric acute
leukemias: An update. J Clin Oncol. 29:551–565. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
2
|
Creutzig U, van den Heuvel-Eibrink MM,
Gibson B, Dworzak MN, Adachi S, de Bont E, Harbott J, Hasle H,
Johnston D, Kinoshita A, et al: Diagnosis and management of acute
myeloid leukemia in children and adolescents: Recommendations from
an international expert panel. Blood. 120:3187–3205. 2012.
View Article : Google Scholar : PubMed/NCBI
|
|
3
|
Rubnitz JE and Inaba H: Childhood acute
myeloid leukaemia. Br J Haematol. 159:259–276. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Elgarten CW and Aplenc R: Pediatric acute
myeloid leukemia: Updates on biology, risk stratification, and
therapy. Curr Opin Pediatr. 32:57–66. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Buldini B, Rizzati F, Masetti R, Fagioli
F, Menna G, Micalizzi C, Putti MC, Rizzari C, Santoro N, Zecca M,
et al: Prognostic significance of flow-cytometry evaluation of
minimal residual disease in children with acute myeloid leukaemia
treated according to the AIEOP-AML 2002/01 study protocol. Br J
Haematol. 177:116–126. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
6
|
Manara E, Basso G, Zampini M, Buldini B,
Tregnago C, Rondelli R, Masetti R, Bisio V, Frison M, Polato K, et
al: Characterization of children with FLT3-ITD acute myeloid
leukemia: A report from the AIEOP AML-2002 study group. Leukemia.
31:18–25. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
7
|
Masetti R, Vendemini F, Zama D, Biagi C,
Pession A and Locatelli F: Acute myeloid leukemia in infants:
Biology and treatment. Front Pediatr. 3:372015. View Article : Google Scholar : PubMed/NCBI
|
|
8
|
Balgobind BV, Raimondi SC, Harbott J,
Zimmermann M, Alonzo TA, Auvrignon A, Beverloo HB, Chang M,
Creutzig U, Dworzak MN, et al: Novel prognostic subgroups in
childhood 11q23/MLL-rearranged acute myeloid leukemia: Results of
an international retrospective study. Blood. 114:2489–2496. 2009.
View Article : Google Scholar : PubMed/NCBI
|
|
9
|
Jiang X, Huang H, Li Z, Li Y, Wang X,
Gurbuxani S, Chen P, He C, You D, Zhang S, et al: Blockade of
miR-150 maturation by MLL-fusion/MYC/LIN-28 is required for
MLL-associated leukemia. Cancer Cell. 22:524–535. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
10
|
Ambros V: The functions of animal
microRNAs. Nature. 431:350–355. 2004. View Article : Google Scholar : PubMed/NCBI
|
|
11
|
Bartel DP: MicroRNAs: Target recognition
and regulatory functions. Cell. 136:215–233. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
12
|
Di Leva G, Garofalo M and Croce CM:
MicroRNAs in cancer. Annu Rev Pathol. 9:287–314. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Marcucci G, Mrózek K, Radmacher MD, Garzon
R and Bloomfield CD: The prognostic and functional role of
microRNAs in acute myeloid leukemia. Blood. 117:1121–1129. 2011.
View Article : Google Scholar : PubMed/NCBI
|
|
14
|
Obulkasim A, Katsman-Kuipers JE, Verboon
L, Sanders M, Touw I, Jongen-Lavrencic M, Pieters R, Klusmann JH,
Michel Zwaan C, van den Heuvel-Eibrink MM and Fornerod M:
Classification of pediatric acute myeloid leukemia based on miRNA
expression profiles. Oncotarget. 8:33078–33085. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
15
|
Danen-van Oorschot AA, Kuipers JE,
Arentsen-Peters S, Schotte D, de Haas V, Trka J, Baruchel A,
Reinhardt D, Pieters R, Zwaan CM and van den Heuvel-Eibrink MM:
Differentially expressed miRNAs in cytogenetic and molecular
subtypes of pediatric acute myeloid leukemia. Pediatr Blood Cancer.
58:715–721. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Wallace JA and O'Connell RM: MicroRNAs and
acute myeloid leukemia: Therapeutic implications and emerging
concepts. Blood. 130:1290–1301. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
17
|
Wu D, Qiu Y, Jiao Y, Qiu Z and Liu D:
Small molecules targeting HATs, HDACs, and BRDs in cancer therapy.
Front Oncol. 10:5604872020. View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Zhu R, Zhao W, Fan F, Tang L, Liu J, Luo
T, Deng J and Hu Y: A 3-miRNA signature predicts prognosis of
pediatric and adolescent cytogenetically normal acute myeloid
leukemia. Oncotarget. 8:38902–38913. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
19
|
Lim EL, Trinh DL, Ries RE, Wang J, Gerbing
RB, Ma Y, Topham J, Hughes M, Pleasance E, Mungall AJ, et al:
MicroRNA expression-based model indicates event-free survival in
pediatric acute myeloid leukemia. J Clin Oncol. 35:3964–3977. 2017.
View Article : Google Scholar : PubMed/NCBI
|
|
20
|
Brondfield S, Umesh S, Corella A, Zuber J,
Rappaport AR, Gaillard C, Lowe SW, Goga A and Kogan SC: Direct and
indirect targeting of MYC to treat acute myeloid leukemia. Cancer
Chemother Pharmacol. 76:35–46. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Benetatos L and Vartholomatos G: MicroRNAs
mark in the MLL-rearranged leukemia. Ann Hematol. 92:1439–1450.
2013. View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Bretones G, Delgado MD and León J: Myc and
cell cycle control. Biochim Biophys Acta. 1849:506–516. 2015.
View Article : Google Scholar : PubMed/NCBI
|
|
23
|
Donati B, Lorenzini E and Ciarrocchi A:
BRD4 and cancer: Going beyond transcriptional regulation. Mol
Cancer. 17:1642018. View Article : Google Scholar : PubMed/NCBI
|
|
24
|
Jiang G, Deng W, Liu Y and Wang C: General
mechanism of JQ1 in inhibiting various types of cancer. Mol Med
Rep. 21:1021–1034. 2020.PubMed/NCBI
|
|
25
|
Wu T, Kamikawa YF and Donohoe ME: Brd4′s
bromodomains mediate histone H3 acetylation and chromatin
remodeling in pluripotent cells through P300 and Brg1. Cell Rep.
25:1756–1771. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
26
|
Fiskus W, Sharma S, Qi J, Shah B, Devaraj
SG, Leveque C, Portier BP, Iyer S, Bradner JE and Bhalla KN: BET
protein antagonist JQ1 is synergistically lethal with FLT3 tyrosine
kinase inhibitor (TKI) and overcomes resistance to FLT3-TKI in AML
cells expressing FLT-ITD. Mol Cancer Ther. 13:2315–2327. 2014.
View Article : Google Scholar : PubMed/NCBI
|
|
27
|
Mio C, Conzatti K, Baldan F, Allegri L,
Sponziello M, Rosignolo F, Russo D, Filetti S and Damante G: BET
bromodomain inhibitor JQ1 modulates microRNA expression in thyroid
cancer cells. Oncol Rep. 39:582–588. 2018.PubMed/NCBI
|
|
28
|
Schick M, Habringer S, Nilsson JA and
Keller U: Pathogenesis and therapeutic targeting of aberrant MYC
expression in haematological cancers. Br J Haematol. 179:724–738.
2017. View Article : Google Scholar : PubMed/NCBI
|
|
29
|
Chen H, Liu H and Qing G: Targeting
oncogenic Myc as a strategy for cancer treatment. Signal Transduct
Target Ther. 3:52018. View Article : Google Scholar : PubMed/NCBI
|
|
30
|
Delmore JE, Issa GC, Lemieux ME, Rahl PB,
Shi J, Jacobs HM, Kastritis E, Gilpatrick T, Paranal RM, Qi J, et
al: BET bromodomain inhibition as a therapeutic strategy to target
c-Myc. Cell. 146:904–917. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
31
|
Marcu MG, Jung YJ, Lee S, Chung EJ, Lee
MJ, Trepel J and Neckers L: Curcumin is an inhibitor of p300
histone acetylatransferase. Med Chem. 2:169–174. 2006. View Article : Google Scholar : PubMed/NCBI
|
|
32
|
Kang SK, Cha SH and Jeon HG:
Curcumin-induced histone hypoacetylation enhances
caspase-3-dependent glioma cell death and neurogenesis of neural
progenitor cells. Stem Cells Dev. 15:165–174. 2006. View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Morimoto T, Sunagawa Y, Kawamura T, Takaya
T, Wada H, Nagasawa A, Komeda M, Fujita M, Shimatsu A, Kita T and
Hasegawa K: The dietary compound curcumin inhibits p300 histone
acetyltransferase activity and prevents heart failure in rats. J
Clin Invest. 118:868–878. 2008.PubMed/NCBI
|
|
34
|
Spriano F, Stathis A and Bertoni F:
Targeting BET bromodomain proteins in cancer: The example of
lymphomas. Pharmacol Ther. 215:1076312020. View Article : Google Scholar : PubMed/NCBI
|
|
35
|
Wang X, Yang Y, Ren D, Xia Y, He W, Wu Q,
Zhang J, Liu M, Du Y, Ren C, et al: JQ1, a bromodomain inhibitor,
suppresses Th17 effectors by blocking p300-mediated acetylation of
RORγt. Br J Pharmacol. 177:2959–2973. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
36
|
Livak KJ and Schmittgen TD: Analysis of
relative gene expression data using real-time quantitative PCR and
the 2(−Delta Delta C(T)) method. Methods. 25:402–408. 2001.
View Article : Google Scholar : PubMed/NCBI
|
|
37
|
Ritchie ME, Phipson B, Wu D, Hu Y, Law CW,
Shi W and Smyth GK: limma powers differential expression analyses
for RNA-sequencing and microarray studies. Nucleic Acids Res.
43:e472015. View Article : Google Scholar : PubMed/NCBI
|
|
38
|
Reich M, Liefeld T, Gould J, Lerner J,
Tamayo P and Mesirov JP: GenePattern 2.0. Nat Genet. 38:500–501.
2006. View Article : Google Scholar : PubMed/NCBI
|
|
39
|
Heberle H, Meirelles GV, da Silva FR,
Telles GP and Minghim R: InteractiVenn: A web-based tool for the
analysis of sets through Venn diagrams. BMC Bioinformatics.
16:1692015. View Article : Google Scholar : PubMed/NCBI
|
|
40
|
Dweep H and Gretz N: miRWalk2.0: A
comprehensive atlas of microRNA-target interactions. Nat Methods.
12:6972015. View Article : Google Scholar : PubMed/NCBI
|
|
41
|
Haferlach C, Kern W, Schindela S, Kohlmann
A, Alpermann T, Schnittger S and Haferlach T: Gene expression of
BAALC, CDKN1B, ERG, and MN1 adds independent prognostic information
to cytogenetics and molecular mutations in adult acute myeloid
leukemia. Genes Chromosomes Cancer. 51:257–265. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
42
|
Zhang H, Luo XQ, Zhang P, Huang LB, Zheng
YS, Wu J, Zhou H, Qu LH, Xu L and Chen YQ: MicroRNA patterns
associated with clinical prognostic parameters and CNS relapse
prediction in pediatric acute leukemia. PLoS One. 4:e78262009.
View Article : Google Scholar : PubMed/NCBI
|
|
43
|
Gaur V, Chaudhary S, Tyagi A, Agarwal S,
Sharawat SK, Sarkar S, Singh H, Bakhshi S, Sharma P and Kumar S:
Dysregulation of miRNA expression and their prognostic significance
in paediatric cytogenetically normal acute myeloid leukaemia. Br J
Haematol. 188:e90–e94. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
44
|
Zampini M, Bisio V, Leszl A, Putti MC,
Menna G, Rizzari C, Pession A, Locatelli F, Basso G, Tregnago C and
Pigazzi M: A three-miRNA-based expression signature at diagnosis
can predict occurrence of relapse in children with t(8;21)
RUNX1-RUNX1T1 acute myeloid leukaemia. Br J Haematol. 183:298–301.
2018. View Article : Google Scholar : PubMed/NCBI
|
|
45
|
Zhu R, Lin W, Zhao W, Fan F, Tang L and Hu
Y: A 4-microRNA signature for survival prognosis in pediatric and
adolescent acute myeloid leukemia. J Cell Biochem. 120:3958–3968.
2019. View Article : Google Scholar : PubMed/NCBI
|
|
46
|
Liu Y, Cheng Z, Pang Y, Cui L, Qian T,
Quan L, Zhao H, Shi J, Ke X and Fu L: Role of microRNAs, circRNAs
and long noncoding RNAs in acute myeloid leukemia. J Hematol Oncol.
12:512019. View Article : Google Scholar : PubMed/NCBI
|
|
47
|
Rupaimoole R and Slack FJ: MicroRNA
therapeutics: Towards a new era for the management of cancer and
other diseases. Nat Rev Drug Discov. 16:203–222. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
48
|
Beg MS, Brenner AJ, Sachdev J, Borad M,
Kang YK, Stoudemire J, Smith S, Bader AG, Kim S and Hong DS: Phase
I study of MRX34, a liposomal miR-34a mimic, administered twice
weekly in patients with advanced solid tumors. Invest New Drugs.
35:180–188. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
49
|
Yan W, Xu L, Sun Z, Lin Y, Zhang W, Chen
J, Hu S and Shen B: MicroRNA biomarker identification for pediatric
acute myeloid leukemia based on a novel bioinformatics model.
Oncotarget. 6:26424–26436. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
50
|
Palma CA, Al Sheikha D, Lim TK, Bryant A,
Vu TT, Jayaswal V and Ma DD: MicroRNA-155 as an inducer of
apoptosis and cell differentiation in acute myeloid leukaemia. Mol
Cancer. 13:792014. View Article : Google Scholar : PubMed/NCBI
|
|
51
|
Marcucci G, Maharry KS, Metzeler KH,
Volinia S, Wu YZ, Mrózek K, Nicolet D, Kohlschmidt J, Whitman SP,
Mendler JH, et al: Clinical role of microRNAs in cytogenetically
normal acute myeloid leukemia: miR-155 upregulation independently
identifies high-risk patients. J Clin Oncol. 31:2086–2093. 2013.
View Article : Google Scholar : PubMed/NCBI
|
|
52
|
Wallace JA, Kagele DA, Eiring AM, Kim CN,
Hu R, Runtsch MC, Alexander M, Huffaker TB, Lee SH, Patel AB, et
al: miR-155 promotes FLT3-ITD-induced myeloproliferative disease
through inhibition of the interferon response. Blood.
129:3074–3086. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
53
|
O'Connell RM, Rao DS, Chaudhuri AA, Boldin
MP, Taganov KD, Nicoll J, Paquette RL and Baltimore D: Sustained
expression of microRNA-155 in hematopoietic stem cells causes a
myeloproliferative disorder. J Exp Med. 205:585–594. 2008.
View Article : Google Scholar : PubMed/NCBI
|
|
54
|
Narayan N, Morenos L, Phipson B, Willis
SN, Brumatti G, Eggers S, Lalaoui N, Brown LM, Kosasih HJ, Bartolo
RC, et al: Functionally distinct roles for different miR-155
expression levels through contrasting effects on gene expression,
in acute myeloid leukaemia. Leukemia. 31:808–820. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
55
|
Huang Y, Zou Y, Lin L, Ma X and Chen H:
Identification of serum miR-34a as a potential biomarker in acute
myeloid leukemia. Cancer Biomark. 22:799–805. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
56
|
Chakraborty C, Sharma AR, Sharma G, Doss
CGP and Lee SS: Therapeutic miRNA and siRNA: Moving from bench to
clinic as next generation medicine. Mol Ther Nucleic Acids.
8:132–143. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
57
|
Frenquelli M, Muzio M, Scielzo C, Fazi C,
Scarfò L, Rossi C, Ferrari G, Ghia P and Caligaris-Cappio F:
MicroRNA and proliferation control in chronic lymphocytic leukemia:
Functional relationship between miR-221/222 cluster and p27. Blood.
115:3949–3959. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
58
|
Hussein K, Theophile K, Büsche G,
Schlegelberger B, Göhring G, Kreipe H and Bock O: Significant
inverse correlation of microRNA-150/MYB and microRNA-222/p27 in
myelodysplastic syndrome. Leuk Res. 34:328–334. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
59
|
Moses BS, Evans R, Slone WL, Piktel D,
Martinez I, Craig MD and Gibson LF: Bone marrow microenvironment
niche regulates miR-221/222 in acute lymphoblastic leukemia. Mol
Cancer Res. 14:909–919. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
60
|
Rommer A, Steinleitner K, Hackl H,
Schneckenleithner C, Engelmann M, Scheideler M, Vlatkovic I,
Kralovics R, Cerny-Reiterer S, Valent P, et al: Overexpression of
primary microRNA 221/222 in acute myeloid leukemia. BMC Cancer.
13:3642013. View Article : Google Scholar : PubMed/NCBI
|
|
61
|
Lee YG, Kim I, Oh S, Shin DY, Koh Y and
Lee KW: Small RNA sequencing profiles of mir-181 and mir-221, the
most relevant microRNAs in acute myeloid leukemia. Korean J Intern
Med. 34:178–183. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
62
|
le Sage C, Nagel R and Agami R: Diverse
ways to control p27Kip1 function: miRNAs come into play. Cell
Cycle. 6:2742–2749. 2007. View Article : Google Scholar : PubMed/NCBI
|
|
63
|
Kohnken R, McNeil B, Wen J, McConnell K,
Grinshpun L, Keiter A, Chen L, William B, Porcu P and Mishra A:
Preclinical targeting of MicroRNA-214 in cutaneous T-cell lymphoma.
J Invest Dermatol. 139:1966–1974.e3. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
64
|
Mensah AA, Cascione L, Gaudio E,
Tarantelli C, Bomben R, Bernasconi E, Zito D, Lampis A, Hahne JC,
Rinaldi A, et al: Bromodomain and extra-terminal domain inhibition
modulates the expression of pathologically relevant microRNAs in
diffuse large B-cell lymphoma. Haematologica. 103:2049–2058. 2018.
View Article : Google Scholar : PubMed/NCBI
|
|
65
|
Quentmeier H, Reinhardt J, Zaborski M and
Drexler HG: FLT3 mutations in acute myeloid leukemia cell lines.
Leukemia. 17:120–124. 2003. View Article : Google Scholar : PubMed/NCBI
|
