|
1
|
Hope KJ, Jin L and Dick JE: Acute myeloid
leukemia originates from a hierarchy of leukemic stem cell classes
that differ in self-renewal capacity. Nat Immunol. 5:738–743. 2004.
View Article : Google Scholar : PubMed/NCBI
|
|
2
|
Gentles AJ, Plevritis SK, Majeti R and
Alizadeh AA: Association of a leukemic stem cell gene expression
signature with clinical outcomes in acute myeloid leukemia. JAMA.
304:2706–2715. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
3
|
Ng SW, Mitchell A, Kennedy JA, Chen WC,
McLeod J, Ibrahimova N, Arruda A, Popescu A, Gupta V, Schimmer AD,
et al: A 17-gene stemness score for rapid determination of risk in
acute leukaemia. Nature. 540:433–437. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Licht JD: AML1 and the AML1-ETO fusion
protein in the pathogenesis of t(8;21) AML. Oncogene. 20:5660–5679.
2001. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Huang S, Jiang MM, Chen GF, Qian K, Gao
HH, Guan W, Shi JL, Liu AQ, Liu J, Wang BH, et al: Epigenetic
silencing of eyes absent 4 gene by acute myeloid leukemia
1-eight-twenty-one oncoprotein contributes to leukemogenesis in
t(8;21) acute myeloid leukemia. Chin Med J (Engl). 129:1355–1362.
2016. View Article : Google Scholar : PubMed/NCBI
|
|
6
|
Reikvam H, Hatfield KJ, Kittang AO,
Hovland R and Bruserud O: Acute myeloid leukemia with the t(8;21)
translocation: Clinical consequences and biological implications. J
Biomed Biotechnol. 2011:1046312011. View Article : Google Scholar : PubMed/NCBI
|
|
7
|
Wu AR, Neff NF, Kalisky T, Dalerba P,
Treutlein B, Rothenberg ME, Mburu FM, Mantalas GL, Sim S, Clarke MF
and Quake SR: Quantitative assessment of single-cell RNA-sequencing
methods. Nat Methods. 11:41–46. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
8
|
Verhaak RG, Wouters BJ, Erpelinck CA,
Abbas S, Beverloo HB, Lugthart S, Lowenberg B, Delwel R and Valk
PJ: Prediction of molecular subtypes in acute myeloid leukemia
based on gene expression profiling. Haematologica. 94:131–134.
2009. View Article : Google Scholar : PubMed/NCBI
|
|
9
|
Li Z, Herold T, He C, Valk PJ, Chen P,
Jurinovic V, Mansmann U, Radmacher MD, Maharry KS, Sun M, et al:
Identification of a 24-gene prognostic signature that improves the
European LeukemiaNet risk classification of acute myeloid leukemia:
An international collaborative study. J Clin Oncol. 31:1172–1181.
2013. View Article : Google Scholar : PubMed/NCBI
|
|
10
|
Wang B, Liu Y, Hou G, Wang L, Lv N, Xu Y,
Xu Y, Wang X, Xuan Z, Jing Y, et al: Mutational spectrum and risk
stratification of intermediate-risk acute myeloid leukemia patients
based on next-generation sequencing. Oncotarget. 7:32065–32078.
2016.PubMed/NCBI
|
|
11
|
Pollen AA, Nowakowski TJ, Shuga J, Wang X,
Leyrat AA, Lui JH, Li N, Szpankowski L, Fowler B, Chen P, et al:
Low-coverage single-cell mRNA sequencing reveals cellular
heterogeneity and activated signaling pathways in developing
cerebral cortex. Nat Biotechnol. 32:1053–1058. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
12
|
Dobin A, Davis CA, Schlesinger F, Drenkow
J, Zaleski C, Jha S, Batut P, Chaisson M and Gingeras TR: STAR:
Ultrafast universal RNA-seq aligner. Bioinformatics. 29:15–21.
2013. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Kumar S, Vo AD, Qin F and Li H:
Comparative assessment of methods for the fusion transcripts
detection from RNA-Seq data. Sci Rep. 6:215972016. View Article : Google Scholar : PubMed/NCBI
|
|
14
|
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
|
|
15
|
Bray NL, Pimentel H, Melsted P and Pachter
L: Near-optimal probabilistic RNA-seq quantification. Nat
Biotechnol. 34:525–527. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Emig D, Salomonis N, Baumbach J, Lengauer
T, Conklin BR and Albrecht M: AltAnalyze and DomainGraph: Analyzing
and visualizing exon expression data. Nucleic Acids Res. 38((Web
Server Issue)): W755–W762. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
17
|
Puram SV, Tirosh I, Parikh AS, Patel AP,
Yizhak K, Gillespie S, Rodman C, Luo CL, Mroz EA, Emerick KS, et
al: Single-cell transcriptomic analysis of primary and metastatic
tumor ecosystems in head and neck cancer. Cell. 171:1611–1624 e24.
2017. View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Kim C, Gao R, Sei E, Brandt R, Hartman J,
Hatschek T, Crosetto N, Foukakis T and Navin NE: Chemoresistance
evolution in triple-negative breast cancer delineated by
single-cell sequencing. Cell. 173:879–893 e13. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
19
|
Kiselev VY, Kirschner K, Schaub MT,
Andrews T, Yiu A, Chandra T, Natarajan KN, Reik W, Barahona M,
Green AR and Hemberg M: SC3: Consensus clustering of single-cell
RNA-seq data. Nat Methods. 14:483–486. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
20
|
Thiede C, Steudel C, Mohr B, Schaich M,
Schakel U, Platzbecker U, Wermke M, Bornhauser M, Ritter M,
Neubauer A, et al: Analysis of FLT3-activating mutations in 979
patients with acute myelogenous leukemia: Association with FAB
subtypes and identification of subgroups with poor prognosis.
Blood. 99:4326–4335. 2002. View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Basecke J, Whelan JT, Griesinger F and
Bertrand FE: The MLL partial tandem duplication in acute myeloid
leukaemia. Br J Haematol. 135:438–449. 2006. View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Prasad P, Rönnerblad M, Arner E, Itoh M,
Kawaji H, Lassmann T, Daub CO, Forrest AR, Lennartsson A and Ekwall
K; FANTOM consortium, : High-throughput transcription profiling
identifies putative epigenetic regulators of hematopoiesis. Blood.
123:e46–e57. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
23
|
Kramer OH, Muller S, Buchwald M, Reichardt
S and Heinzel T: Mechanism for ubiquitylation of the leukemia
fusion proteins AML1-ETO and PML-RARalpha. FASEB J. 22:1369–1379.
2008. View Article : Google Scholar : PubMed/NCBI
|
|
24
|
Espadinha AS, Prouzet-Mauleon V, Claverol
S, Lagarde V, Bonneu M, Mahon FX and Cardinaud B: A tyrosine
kinase-STAT5-miR21-PDCD4 regulatory axis in chronic and acute
myeloid leukemia cells. Oncotarget. 8:76174–76188. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
25
|
Meyer C, Burmeister T, Groger D, Tsaur G,
Fechina L, Renneville A, Sutton R, Venn NC, Emerenciano M,
Pombo-de-Oliveira MS, et al: The MLL recombinome of acute leukemias
in 2017. Leukemia. 32:273–284. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
26
|
Zhang Y, Peng L, Hu T, Wan Y, Ren Y, Zhang
J, Wang X, Zhou Y, Yuan W, Wang Q, et al: La-related protein 4B
maintains murine MLL-AF9 leukemia stem cell self-renewal by
regulating cell cycle progression. Exp Hematol. 43:309–318 e2.
2015. View Article : Google Scholar : PubMed/NCBI
|
|
27
|
Zhu N, Chen M, Eng R, DeJong J, Sinha AU,
Rahnamay NF, Koche R, Al-Shahrour F, Minehart JC, Chen CW, et al:
MLL-AF9- and HOXA9-mediated acute myeloid leukemia stem cell
self-renewal requires JMJD1C. J Clin Invest. 126:997–1011. 2016.
View Article : Google Scholar : PubMed/NCBI
|
|
28
|
Vu LP, Prieto C, Amin EM, Chhangawala S,
Krivtsov A, Calvo-Vidal MN, Chou T, Chow A, Minuesa G, Park SM, et
al: Functional screen of MSI2 interactors identifies an essential
role for SYNCRIP in myeloid leukemia stem cells. Nat Genet.
49:866–875. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
29
|
Cheng J, Qu L, Wang J, Cheng L and Wang Y:
High expression of FLT3 is a risk factor in leukemia. Mol Med Rep.
17:2885–2892. 2018.PubMed/NCBI
|
|
30
|
Pan L, Li Y, Zhang HY, Zheng Y, Liu XL, Hu
Z, Wang Y, Wang J, Cai YH, Liu Q, et al: DHX15 is associated with
poor prognosis in acute myeloid leukemia (AML) and regulates cell
apoptosis via the NF-kB signaling pathway. Oncotarget.
8:89643–89654. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
31
|
Chen M, Zhu N, Liu X, Laurent B, Tang Z,
Eng R, Shi Y, Armstrong SA and Roeder RG: JMJD1C is required for
the survival of acute myeloid leukemia by functioning as a
coactivator for key transcription factors. Genes Dev. 29:2123–2139.
2015. View Article : Google Scholar : PubMed/NCBI
|
|
32
|
Yao C, Du W, Chen H, Xiao S, Huang L and
Chen FP: Involvement of Fanconi anemia genes FANCD2 and FANCF in
the molecular basis of drug resistance in leukemia. Mol Med Rep.
11:4605–4610. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Liu L, Wan X, Zhou P, Zhou X, Zhang W, Hui
X, Yuan X, Ding X, Zhu R, Meng G, et al: The chromatin remodeling
subunit Baf200 promotes normal hematopoiesis and inhibits
leukemogenesis. J Hematol Oncol. 11:272018. View Article : Google Scholar : PubMed/NCBI
|
|
34
|
Walker BA, Mavrommatis K, Wardell CP,
Ashby TC, Bauer M, Davies F, Rosenthal A, Wang H, Qu P, Hoering A,
et al: A high-risk, Double-Hit, group of newly diagnosed myeloma
identified by genomic analysis. Leukemia. 33:159–170. 2019.
View Article : Google Scholar : PubMed/NCBI
|
|
35
|
Nakahata S, Saito Y, Hamasaki M, Hidaka T,
Arai Y, Taki T, Taniwaki M and Morishita K: Alteration of enhancer
of polycomb 1 at 10p11.2 is one of the genetic events leading to
development of adult T-cell leukemia/lymphoma. Genes Chromosomes
Cancer. 48:768–776. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
36
|
Christen F, Hoyer K, Yoshida K, Hou HA,
Waldhueter N, Heuser M, Hills RK, Chan W, Hablesreiter R, Blau O,
et al: Genomic landscape and clonal evolution of acute myeloid
leukemia with t(8;21): An international study on 331 patients.
Blood. 133:1140–1151. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
37
|
Mostafavi S, Ray D, Warde-Farley D,
Grouios C and Morris Q: GeneMANIA: A real-time multiple association
network integration algorithm for predicting gene function. Genome
Biol. 9 (Suppl 1):S42008. View Article : Google Scholar : PubMed/NCBI
|
|
38
|
Szklarczyk D, Morris JH, Cook H, Kuhn M,
Wyder S, Simonovic M, Santos A, Doncheva NT, Roth A, Bork P, et al:
The STRING database in 2017: Quality-controlled protein-protein
association networks, made broadly accessible. Nucleic Acids Res.
45(D1): D362–D368. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
39
|
Davis S and Meltzer PS: GEOquery: A bridge
between the gene expression omnibus (GEO) and BioConductor.
Bioinformatics. 23:1846–1847. 2007. View Article : Google Scholar : PubMed/NCBI
|
|
40
|
Zheng GX, Terry JM, Belgrader P, Ryvkin P,
Bent ZW, Wilson R, Ziraldo SB, Wheeler TD, McDermott GP, Zhu J, et
al: Massively parallel digital transcriptional profiling of single
cells. Nat Commun. 8:140492017. View Article : Google Scholar : PubMed/NCBI
|
|
41
|
Zhao X, Gao S, Wu Z, Kajigaya S, Feng X,
Liu Q, Townsley DM, Cooper J, Chen J, Keyvanfar K, et al:
Single-cell RNA-seq reveals a distinct transcriptome signature of
aneuploid hematopoietic cells. Blood. 130:2762–2773. 2017.
View Article : Google Scholar : PubMed/NCBI
|
|
42
|
De Bie J, Demeyer S, Alberti-Servera L,
Geerdens E, Segers H, Broux M, De Keersmaecker K, Michaux L,
Vandenberghe P, Voet T, et al: Single-cell sequencing reveals the
origin and the order of mutation acquisition in T-cell acute
lymphoblastic leukemia. Leukemia. 32:1358–1369. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
43
|
Giustacchini A, Thongjuea S, Barkas N,
Woll PS, Povinelli BJ, Booth CAG, Sopp P, Norfo R, Rodriguez-Meira
A, Ashley N, et al: Single-cell transcriptomics uncovers distinct
molecular signatures of stem cells in chronic myeloid leukemia. Nat
Med. 23:692–702. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
44
|
Yan B, Hu Y, Ban KHK, Tiang Z, Ng C, Lee
J, Tan W, Chiu L, Tan TW, Seah E, et al: Single-cell genomic
profiling of acute myeloid leukemia for clinical use: A pilot
study. Oncol Lett. 13:1625–1630. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
45
|
Zheng C, Zheng L, Yoo JK, Guo H, Zhang Y,
Guo X, Kang B, Hu R, Huang JY, Zhang Q, et al: Landscape of
infiltrating t cells in liver cancer revealed by single-cell
sequencing. Cell. 169:1342–1356.e16. 2017. View Article : Google Scholar : PubMed/NCBI
|
