AML - Molecular Biology

Overview

Literature Analysis

Mouse over the terms for more detail; many indicate links which you can click for dedicated pages about the topic.

Tag cloud generated 29 August, 2019 using data from PubMed, MeSH and CancerIndex

Mutated Genes and Abnormal Protein Expression (215)

How to use this data tableClicking on the Gene or Topic will take you to a separate more detailed page. Sort this list by clicking on a column heading e.g. 'Gene' or 'Topic'.

GeneLocationAliasesNotesTopicPapers
FLT3 13q12.2 FLK2, STK1, CD135, FLK-2 -FLT3 and Acute Myeloid Leukaemia
1190
PML 15q24.1 MYL, RNF71, PP8675, TRIM19 -PML and Acute Myeloid Leukaemia
940
CD34 1q32.2 -CD34 and Acute Myeloid Leukaemia
645
NPM1 5q35.1 B23, NPM -NPM1 and Acute Myeloid Leukaemia
605
BCR 22q11.23 ALL, CML, PHL, BCR1, D22S11, D22S662 -BCR and Acute Myeloid Leukaemia
580
KITLG 12q22 SF, MGF, SCF, FPH2, FPHH, KL-1, Kitl, SHEP7 -KITLG and Acute Myeloid Leukaemia
407
CEBPA 19q13.11 CEBP, C/EBP-alpha -CEBPA and Acute Myeloid Leukaemia
370
KIT 4q12 PBT, SCFR, C-Kit, CD117 -KIT and Acute Myeloid Leukaemia
347
WT1 11p13 GUD, AWT1, WAGR, WT33, NPHS4, WIT-2, EWS-WT1 Overexpression
-WT1 and Acute Myeloid Leukaemia
243
NRAS 1p13.2 NS6, CMNS, NCMS, ALPS4, N-ras, NRAS1 -NRAS and Acute Myeloid Leukaemia
231
CD33 19q13.41 p67, SIGLEC3, SIGLEC-3 -CD33 and Acute Myeloid Leukaemia
219
MLLT10 10p12.31 AF10 Translocation
-t(10;11)(p13;q14) AF10-PICALM translocation in Acute Leukaemia
-t(10;11)(p12;q23) AF10-MLL translocation in Acute Leukaemia
122
IDH1 2q33.3 IDH, IDP, IDCD, IDPC, PICD, HEL-216, HEL-S-26 -IDH1 and Acute Myeloid Leukaemia
161
MYH11 16p13.11 AAT4, FAA4, SMHC, SMMHC Translocation
-t(16;16)(p13q22) CBFB-MYH11 Translocation in AML
-MYH11 and Acute Myeloid Leukaemia
155
KMT2A 11q23.3 HRX, MLL, MLL1, TRX1, ALL-1, CXXC7, HTRX1, MLL1A, WDSTS Translocation
-t(1;11) (q21;q23) in Leukemia
-t(6;11)(q27;q23) in Acute Myeloid Leukemia
-t(9;11) in Acute Myeloid Leukaemia
-t(10;11)(p12;q23) AF10-MLL translocation in Acute Leukaemia
-t(10;11) MLL-TET1 rearrangement in acute leukemias
-t(1;11)(p32;q23) MLL-EPS15 fusion in Acute Myelogeneous Leukemia
-t(11;19)(q23;p13.1) MLL-ELL translocation in acute leukaemia
122
RUNX1T1 8q21.3 CDR, ETO, MTG8, AML1T1, ZMYND2, CBFA2T1, AML1-MTG8 Translocation
- t(8;21)(q22;q22) in Acute Myeloid Leukemia
-RUNX1T1 and Acute Myeloid Leukaemia
145
GATA1 Xp11.23 GF1, GF-1, NFE1, XLTT, ERYF1, NF-E1, XLANP, XLTDA, GATA-1 -GATA1 and Acute Myeloid Leukaemia
141
HOXA9 7p15.2 HOX1, ABD-B, HOX1G, HOX1.7 Translocation
-t(7;11)(p15;p15) in Acute Myelogenous Leukaemia
-HOXA9 and Acute Myeloid Leukaemia
105
IDH2 15q26.1 IDH, IDP, IDHM, IDPM, ICD-M, D2HGA2, mNADP-IDH -IDH2 and Acute Myeloid Leukaemia
131
ASXL1 20q11.21 MDS, BOPS -ASXL1 and Acute Myeloid Leukaemia
129
RB1 13q14.2 RB, pRb, OSRC, pp110, p105-Rb, PPP1R130 -RB1 and Acute Leukaemias
125
TET2 4q24 MDS, KIAA1546 -TET2 and Acute Myeloid Leukaemia
120
DNMT3A 2p23 TBRS, DNMT3A2, M.HsaIIIA -DNMT3A and Acute Myeloid Leukaemia
110
NUP214 9q34.13 CAN, CAIN Translocation
-t(6;9)(p23;q34) DEK-NUP214 in Acute Myeloid Leukaemia and Myelodysplastic Syndrome
-t(9;9)(q34;q34) SET-NUP214 rearrangements in Acute Lyphoblastic Leukaemia
63
CD19 16p11.2 B4, CVID3 -CD19 and Acute Myeloid Leukaemia
104
CSF3R 1p34.3 SCN7, CD114, GCSFR -CSF3R and Acute Myeloid Leukaemia
92
ETV6 12p13.2 TEL, THC5, TEL/ABL Translocation
-t(1;12)(q25;p13) in Leukaemia (AML & ALL)
-ETV6 and Acute Myeloid Leukaemia
64
CD14 5q31.3 -CD14 and Acute Myeloid Leukaemia
84
CD38 4p15.32 ADPRC1, ADPRC 1 -CD38 and Acute Myeloid Leukaemia
83
PICALM 11q14.2 LAP, CALM, CLTH Translocation
-t(10;11)(p13;q14) AF10-PICALM translocation in Acute Leukaemia
76
MPL 1p34.2 MPLV, TPOR, C-MPL, CD110, THPOR, THCYT2 -MPL and Acute Myeloid Leukaemia
68
TERT 5p15.33 TP2, TRT, CMM9, EST2, TCS1, hTRT, DKCA2, DKCB4, hEST2, PFBMFT1 -TERT and Acute Myeloid Leukemia
66
DEK 6p22.3 D6S231E Translocation
-t(6;9)(p23;q34) DEK-NUP214 in Acute Myeloid Leukaemia and Myelodysplastic Syndrome
63
GALE 1p36.11 SDR1E1 -GALE and Acute Myeloid Leukaemia
63
BAALC 8q22.3 -BAALC and Acute Myeloid Leukaemia
61
GATA2 3q21.3 DCML, IMD21, NFE1B, MONOMAC -GATA2 and Acute Myeloid Leukaemia
60
MN1 22q12.1 MGCR, MGCR1, MGCR1-PEN, dJ353E16.2 -MN1 and Acute Myeloid Leukaemia
50
CBL 11q23.3 CBL2, NSLL, C-CBL, RNF55, FRA11B -CBL and Acute Myeloid Leukaemia
48
SET 9q34.11 2PP2A, IGAAD, TAF-I, I2PP2A, IPP2A2, PHAPII, TAF-IBETA Translocation
-t(9;9)(q34;q34) SET-NUP214 rearrangements in Acute Lyphoblastic Leukaemia
46
MEIS1 2p14 -MEIS1 and Acute Myeloid Leukaemia
36
MLLT3 9p21.3 AF9, YEATS3 Translocation
-t(9;11) in Acute Myeloid Leukaemia
-MLLT3 and Acute Myeloid Leukaemia
35
U2AF1 21q22.3 RN, FP793, U2AF35, U2AFBP, RNU2AF1 -U2AF1 and Acute Myeloid Leukaemia
33
ELL 19p13.11 MEN, ELL1, PPP1R68, C19orf17 Translocation
-ELL and Acute Myeloid Leukaemia
-t(11;19)(q23;p13.1) MLL-ELL translocation in acute leukaemia
18
NUP98 11p15.4 ADIR2, NUP96, NUP196 Translocation
-t(7;11)(p15;p15) in Acute Myelogenous Leukaemia
-t(11;20) (p15;q11) NUP98-TOP1 Fusion in AML
27
PTPN11 12q24.13 CFC, NS1, JMML, SHP2, BPTP3, PTP2C, METCDS, PTP-1D, SH-PTP2, SH-PTP3 -PTPN11 and Acute Myeloid Leukaemia
29
RARS 5q34 HLD9, ArgRS, DALRD1 -RARS and Acute Myeloid Leukaemia
29
EGR1 5q31.2 TIS8, AT225, G0S30, NGFI-A, ZNF225, KROX-24, ZIF-268 -EGR1 and Acute Myeloid Leukaemia
28
ABL2 1q25.2 ARG, ABLL Translocation
-t(1;12)(q25;p13) in Leukaemia (AML & ALL)
25
BCOR Xp11.4 MAA2, ANOP2, MCOPS2 -BCOR and Acute Myeloid Leukaemia
24
KAT6A 8p11.21 MOZ, MRD32, MYST3, MYST-3, ZNF220, RUNXBP2, ZC2HC6A -KAT6A and Acute Myeloid Leukaemia
23
MDS1 3q26 PRDM3, MDS1-EVI1 -MDS1 and Acute Myeloid Leukaemia
23
SRSF2 17q25.1 SC35, PR264, SC-35, SFRS2, SFRS2A, SRp30b -SRSF2 and Acute Myeloid Leukaemia
20
NSD1 5q35.3 STO, KMT3B, SOTOS, ARA267, SOTOS1 -NSD1 and Acute Myeloid Leukaemia
20
CRP 1q23.2 PTX1 -CRP and Acute Myeloid Leukaemia
19
ELN 7q11.23 WS, WBS, SVAS -ELN and Acute Myeloid Leukaemia
19
RBM15 1p13.3 OTT, OTT1, SPEN -RBM15 and Acute Myeloid Leukaemia
18
HOXA10 7p15.2 PL, HOX1, HOX1H, HOX1.8 -HOXA10 and Acute Myeloid Leukaemia
17
CDX2 13q12.2 CDX3, CDX-3, CDX2/AS -CDX2 and Acute Myeloid Leukaemia
17
PRAME 22q11.22 MAPE, OIP4, CT130, OIP-4 -PRAME and Acute Myeloid Leukaemia
17
DOT1L 19p13.3 DOT1, KMT4 -DOT1L and Acute Myeloid Leukaemia
16
PRDM16 1p36.32 MEL1, KMT8F, LVNC8, PFM13, CMD1LL -PRDM16 and Acute Myeloid Leukaemia
16
TFAP2A 6p24.3 AP-2, BOFS, AP2TF, TFAP2, AP-2alpha -TFAP2A and Acute Myeloid Leukaemia
16
TFAP2C 20q13.31 ERF1, TFAP2G, hAP-2g, AP2-GAMMA -TFAP2C and Acute Myeloid Leukaemia
16
STAG2 Xq25 SA2, SA-2, SCC3B, NEDXCF, bA517O1.1 -STAG2 and Acute Myeloid Leukaemia
15
BRD4 19p13.12 CAP, MCAP, HUNK1, HUNKI -BRD4 and Acute Myeloid Leukaemia
15
CD36 7q21.11 FAT, GP4, GP3B, GPIV, CHDS7, PASIV, SCARB3, BDPLT10 -CD36 and Acute Myeloid Leukaemia
14
PIM1 6p21.2 PIM -PIM1 and Acute Myeloid Leukaemia
14
SF3B1 2q33.1 MDS, PRP10, Hsh155, PRPF10, SAP155, SF3b155 -SF3B1 and Acute Myeloid Leukaemia
14
FES 15q26.1 FPS -FES and Acute Myeloid Leukaemia
13
CBFA2T3 16q24.3 ETO2, MTG16, MTGR2, ZMYND4, RUNX1T3 -CBFA2T3 and Acute Myeloid Leukaemia
13
EPS15 1p32.3 AF1P, AF-1P, MLLT5 Translocation
-t(1;11)(p32;q23) MLL-EPS15 fusion in Acute Myelogeneous Leukemia
12
CEBPB 20q13.13 TCF5, IL6DBP, NF-IL6, C/EBP-beta -CEBPB and Acute Myeloid Leukaemia
12
SALL4 20q13.2 DRRS, HSAL4, ZNF797 -SALL4 and Acute Myeloid Leukaemia
12
PHF6 Xq26.2 BFLS, BORJ, CENP-31 -PHF6 and Acute Myeloid Leukaemia
12
CHEK1 11q24.2 CHK1 -CHEK1 and Acute Myeloid Leukaemia
12
CSF1R 5q32 FMS, CSFR, FIM2, HDLS, C-FMS, CD115, CSF-1R, M-CSF-R -CSF1R and Acute Myeloid Leukaemia
11
ETS2 21q22.2 ETS2IT1 -ETS2 and Acute Myeloid Leukaemia
11
MLF1 3q25.32 -MLF1 and Acute Myeloid Leukaemia
11
JAG1 20p12.2 AGS, AHD, AWS, HJ1, AGS1, DCHE, CD339, JAGL1 -JAG1 and Acute Myeloid Leukaemia
10
MIR10A 17q21.32 MIRN10A, mir-10a, miRNA10A, hsa-mir-10a -miR-10a and Acute Myeloid Leukaemia
10
HOXA5 7p15.2 HOX1, HOX1C, HOX1.3 -HOXA5 and Acute Myeloid Leukaemia
10
PBX3 9q33.3 -PBX3 and Acute Myeloid Leukaemia
10
HOXB4 17q21.32 HOX2, HOX2F, HOX-2.6 -HOXB4 and Acute Myeloid Leukaemia
9
ITGAM 16p11.2 CR3A, MO1A, CD11B, MAC-1, MAC1A, SLEB6 -ITGAM and Acute Myeloid Leukaemia
9
HOXD13 2q31.1 BDE, SPD, BDSD, HOX4I -HOXD13 and Acute Myeloid Leukaemia
9
GALM 2p22.1 GLAT, IBD1, BLOCK25, HEL-S-63p -GALM and Acute Myeloid Leukaemia
9
IL2RG Xq13.1 P64, CIDX, IMD4, CD132, SCIDX, IL-2RG, SCIDX1 -IL2RG and Acute Myeloid Leukaemia
9
WARS 14q32.2 IFI53, IFP53, GAMMA-2 -WARS and Acute Myeloid Leukaemia
9
PAPPA 9q33.1 PAPA, DIPLA1, PAPP-A, PAPPA1, ASBABP2, IGFBP-4ase -PAPPA and Acute Myeloid Leukaemia
8
ABCC1 16p13.11 MRP, ABCC, GS-X, MRP1, ABC29 -ABCC1 (MRP1) Deletion in AML with Inversion of Chromosome 16
8
IL21R 16p12.1 NILR, CD360 -IL21R and Acute Myeloid Leukaemia
8
SEPT9 17q25.3 MSF, MSF1, NAPB, SINT1, PNUTL4, SeptD1, AF17q25 -SEPT9 and Acute Myeloid Leukaemia
7
SEPTIN6 Xq24 SEP2, SEPT2, SEPT6 -SEPT6 and Acute Myeloid Leukaemia
7
DDX10 11q22.3 HRH-J8 -DDX10 and Acute Myeloid Leukaemia
7
ZRSR2 Xp22.2 URP, ZC3H22, U2AF1L2, U2AF1RS2, U2AF1-RS2 -ZRSR2 and Acute Myeloid Leukaemia
7
PIM2 Xp11.23 -PIM2 and Acute Myeloid Leukaemia
7
WT1-AS 11p13 WIT1, WIT-1, WT1AS, WT1-AS1 -WT1-AS and Acute Myeloid Leukaemia
7
MLLT6 17q12 AF17 -MLLT6 and Acute Myeloid Leukaemia
7
RPN1 3q21.3 OST1, RBPH1 -RPN1 and Acute Myeloid Leukaemia
6
CDC25B 20p13 -CDC25B and Acute Myeloid Leukaemia
6
ARHGAP26 5q31.3 GRAF, GRAF1, OPHN1L, OPHN1L1 -ARHGAP26 and Acute Myeloid Leukaemia
6
HOXB3 17q21.32 HOX2, HOX2G, Hox-2.7 -HOXB3 and Acute Myeloid Leukaemia
6
MLLT1 19p13.3 ENL, LTG19, YEATS1 -MLLT1 and Acute Myeloid Leukaemia
6
HCK 20q11.21 JTK9, p59Hck, p61Hck -HCK and Acute Myeloid Leukaemia
6
IRF8 16q24.1 ICSBP, IRF-8, ICSBP1, IMD32A, IMD32B, H-ICSBP -IRF8 and Acute Myeloid Leukaemia
6
CEBPE 14q11.2 CRP1, C/EBP-epsilon -CEBPE and Acute Myeloid Leukaemia
6
MNX1 7q36.3 HB9, HLXB9, SCRA1, HOXHB9 -MNX1 and Acute Myeloid Leukaemia
6
PTPRC 1q31.3-q32.1 LCA, LY5, B220, CD45, L-CA, T200, CD45R, GP180 -PTPRC and Acute Myeloid Leukaemia
6
HOXA7 7p15.2 ANTP, HOX1, HOX1A, HOX1.1 -HOXA7 and Acute Myeloid Leukaemia
6
HAVCR2 5q33.3 TIM3, CD366, KIM-3, TIMD3, Tim-3, TIMD-3, HAVcr-2 -HAVCR2 and Acute Myeloid Leukaemia
6
LARS 5q32 LRS, LEUS, LFIS, ILFS1, LARS1, LEURS, PIG44, RNTLS, HSPC192, hr025Cl -LARS and Acute Myeloid Leukaemia
6
MX1 21q22.3 MX, MxA, IFI78, IFI-78K -MX1 and Acute Myeloid Leukaemia
6
TXNIP 1q21.1 THIF, VDUP1, ARRDC6, HHCPA78, EST01027 -TXNIP and Acute Myeloid Leukaemia
5
SUV39H1 Xp11.23 MG44, KMT1A, SUV39H, H3-K9-HMTase 1 -SUV39H1 and Acute Myeloid Leukaemia
5
MSI2 17q22 MSI2H -MSI2 and Acute Myeloid Leukaemia
5
NCOA2 8q13.3 SRC2, TIF2, GRIP1, KAT13C, NCoA-2, bHLHe75 -NCOA2 and Acute Myeloid Leukaemia
5
BOLL 2q33 BOULE -BOLL and Acute Myeloid Leukaemia
5
SFRP5 10q24.2 SARP3 -SFRP5 and Acute Myeloid Leukaemia
5
MYH9 22q12.3 MHA, FTNS, EPSTS, BDPLT6, DFNA17, MATINS, NMMHCA, NMHC-II-A, NMMHC-IIA -MYH9 and Acute Myeloid Leukaemia
5
SFRP4 7p14.1 PYL, FRP-4, FRPHE, sFRP-4 -SFRP4 and Acute Myeloid Leukaemia
5
RAD21 8q24.11 HR21, MCD1, NXP1, SCC1, CDLS4, hHR21, HRAD21 -RAD21 and Acute Myeloid Leukaemia
5
HOXA4 7p15.2 HOX1, HOX1D -HOXA4 and Acute Myeloid Leukaemia
5
SOCS2 12q22 CIS2, SSI2, Cish2, SSI-2, SOCS-2, STATI2 -SOCS2 and Acute Myeloid Leukaemia
5
BCL11B 14q32.2 ATL1, RIT1, CTIP2, IMD49, CTIP-2, ZNF856B, ATL1-beta, ATL1-alpha, ATL1-delta, ATL1-gamma, hRIT1-alpha -BCL11B and Acute Myeloid Leukaemia
5
GAB2 11q14.1 -GAB2 and Acute Myeloid Leukaemia
5
HOXA13 7p15.2 HOX1, HOX1J -HOXA13 and Acute Myeloid Leukaemia
4
GAS6 13q34 AXSF, AXLLG -GAS6 and Acute Myeloid Leukaemia
4
TOP1 20q12 TOPI Translocation
-t(11;20) (p15;q11) NUP98-TOP1 Fusion in AML
4
PLK2 5q11.2 SNK, hSNK, hPlk2 -PLK2 and Acute Myeloid Leukaemia
4
GMPS 3q25.31 -GMPS and Acute Myeloid Leukaemia
4
IL2RA 10p15.1 p55, CD25, IL2R, IMD41, TCGFR, IDDM10 -IL2RA and Acute Myeloid Leukaemia
4
CBFB 16q22.1 PEBP2B Translocation
-t(16;16)(p13q22) CBFB-MYH11 Translocation in AML
4
CEBPD 8q11.21 CELF, CRP3, C/EBP-delta, NF-IL6-beta -CEBPD and Acute Myeloid Leukaemia
4
KLF5 13q22.1 CKLF, IKLF, BTEB2 -KLF5 and Acute Myeloid Leukaemia
4
ULBP2 6q25 N2DL2, RAET1H, NKG2DL2, ALCAN-alpha -ULBP2 and Acute Myeloid Leukaemia
4
CCDC26 8q24.21 RAM -CCDC26 and Acute Myeloid Leukaemia
4
IL23R 1p31.3 -IL23R and Acute Myeloid Leukaemia
4
HHEX 10q23.33 HEX, PRH, HMPH, PRHX, HOX11L-PEN -HHEX and Acute Myeloid Leukaemia
4
TET1 10q21.3 LCX, CXXC6, bA119F7.1 Translocation
-t(10;11) MLL-TET1 rearrangement in acute leukemias
4
SPRED1 15q14 NFLS, hSpred1, spred-1, PPP1R147 -SPRED1 and Acute Myeloid Leukaemia
3
SEPTIN5 22q11.21 H5, SEPT5, CDCREL, PNUTL1, CDCREL1, CDCREL-1, HCDCREL-1 -SEPT5 and Acute Myeloid Leukaemia
3
GNL3 3p21.1 NS, E2IG3, NNP47, C77032 -GNL3 and Acute Myeloid Leukaemia
3
GLIPR1 12q21.2 GLIPR, RTVP1, CRISP7 -GLIPR1 and Acute Myeloid Leukaemia
3
GUSB 7q11.21 BG, MPS7 -GUSB and Acute Myeloid Leukaemia
3
HOXC11 12q13.13 HOX3H -HOXC11 and Acute Myeloid Leukaemia
3
SMAD5 5q31.1 DWFC, JV5-1, MADH5 -SMAD5 and Acute Myeloid Leukaemia
3
CD200 3q13.2 MRC, MOX1, MOX2, OX-2 -CD200 and Acute Myeloid Leukaemia
3
ELF4 Xq26.1 MEF, ELFR -ELF4 and Acute Myeloid Leukaemia
3
HOXC13 12q13.13 HOX3, ECTD9, HOX3G -HOXC13 and Acute Myeloid Leukaemia
3
HLA-DQB1 6p21.32 IDDM1, CELIAC1, HLA-DQB -HLA-DQB1 and Acute Myeloid Leukaemia
3
FUT4 11q21 LeX, CD15, ELFT, FCT3A, FUTIV, SSEA-1, FUC-TIV -FUT4 and Acute Myeloid Leukaemia
3
TNFRSF9 1p36.23 ILA, 4-1BB, CD137, CDw137 -TNFRSF9 and Acute Myeloid Leukaemia
3
KDM4C 9p24.1 GASC1, JHDM3C, JMJD2C, TDRD14C -KDM4C and Acute Myeloid Leukaemia
3
HOXA11 7p15.2 HOX1, HOX1I, RUSAT1 -HOXA11 and Acute Myeloid Leukaemia
3
SBDS 7q11.21 SDS, SWDS, CGI-97 -SBDS and Acute Myeloid Leukaemia
3
FLNA Xq28 FLN, FMD, MNS, OPD, ABPX, CSBS, CVD1, FGS2, FLN1, NHBP, OPD1, OPD2, XLVD, XMVD, FLN-A, ABP-280 -FLNA and Acute Myeloid Leukaemia
3
DLX4 17q21.33 BP1, DLX7, DLX8, DLX9, OFC15 -DLX4 and Acute Myeloid Leukaemia
3
HLA-DRA 6p21.32 HLA-DRA1 -HLA-DRA and Acute Myeloid Leukaemia
2
MERTK 2q14.1 MER, RP38, c-Eyk, c-mer, Tyro12 -MERTK and Acute Myeloid Leukaemia
2
MBL2 10q21.1 MBL, MBP, MBP1, MBPD, MBL2D, MBP-C, COLEC1, HSMBPC -MBL2 and Acute Myeloid Leukaemia
2
CHAT 10q11.23 CMS6, CMS1A, CMS1A2, CHOACTASE -CHAT and Acute Myeloid Leukaemia
2
PRTN3 19p13.3 MBN, MBT, NP4, P29, PR3, ACPA, AGP7, NP-4, PR-3, CANCA, C-ANCA -PRTN3 and Acute Myeloid Leukaemia
2
PAWR 12q21 PAR4, Par-4 -PAWR and Acute Myeloid Leukaemia
2
TYRO3 15q15.1 BYK, Dtk, RSE, Rek, Sky, Tif, Etk-2 -TYRO3 and Acute Myeloid Leukaemia
2
ESPL1 12q13.13 ESP1, SEPA -ESPL1 and Acute Myeloid Leukaemia
2
PSIP1 9p22.3 p52, p75, PAIP, DFS70, LEDGF, PSIP2 -PSIP1 and Acute Myeloid Leukaemia
2
CXCL11 4q21.1 IP9, H174, IP-9, b-R1, I-TAC, SCYB11, SCYB9B -CXCL11 and Acute Myeloid Leukaemia
2
IGK 2p12 IGK@ -IGK and Acute Myeloid Leukaemia
2
BLNK 10q24.1 bca, AGM4, BASH, LY57, SLP65, BLNK-S, SLP-65 -BLNK and Acute Myeloid Leukaemia
2
TLE1 9q21.32 ESG, ESG1, GRG1 -TLE1 and Acute Myeloid Leukaemia
2
CTDSPL 3p22.2 PSR1, SCP3, HYA22, RBSP3, C3orf8 -CTDSPL and Acute Myeloid Leukaemia
2
DLEU2 13q14.2 1B4, DLB2, LEU2, BCMSUN, RFP2OS, MIR15AHG, TRIM13OS, LINC00022, NCRNA00022 -DLEU2 and Acute Myeloid Leukaemia
2
CD48 1q23.3 BCM1, BLAST, hCD48, mCD48, BLAST1, SLAMF2, MEM-102 -CD48 and Acute Myeloid Leukaemia
2
MUC3A 7q22.1 MUC3, MUC-3A -MUC3A and Acute Myeloid Leukaemia
2
PDCD1LG2 9p24.1 B7DC, Btdc, PDL2, CD273, PD-L2, PDCD1L2, bA574F11.2 -PDCD1LG2 and Acute Myeloid Leukaemia
2
LAMP1 13q34 LAMPA, CD107a, LGP120 -LAMP1 and Acute Myeloid Leukaemia
2
HMMR 5q34 CD168, IHABP, RHAMM -HMMR and Acute Myeloid Leukaemia
2
HLA-E 6p21.3 MHC, QA1, EA1.2, EA2.1, HLA-6.2 -HLA-E and Acute Myeloid Leukaemia
2
TPMT 6p22.3 TPMTD -TPMT and Acute Myeloid Leukaemia
2
IRF2 4q35.1 IRF-2 -IRF2 and Acute Myeloid Leukaemia
2
CNTRL 9q33.2 FAN, CEP1, CEP110, bA165P4.1 -CNTRL and Acute Myeloid Leukaemia
2
POLI 18q21.2 RAD30B, RAD3OB -POLI and Acute Myeloid Leukaemia
2
HLA-DQA1 6p21.32 DQ-A1, CELIAC1, HLA-DQA -HLA-DQA1 and Acute Myeloid Leukaemia
1
SFPQ 1p34.3 PSF, POMP100, PPP1R140 -SFPQ and Acute Myeloid Leukaemia
1
DNM2 19p13.2 DYN2, CMT2M, DYNII, LCCS5, CMTDI1, CMTDIB, DI-CMTB -DNM2 and Acute Myeloid Leukaemia
1
HSP90AB1 6p21.1 HSP84, HSPC2, HSPCB, D6S182, HSP90B -HSP90AB1 and Acute Myeloid Leukaemia
1
SH3GL1 19p13.3 EEN, CNSA1, SH3P8, SH3D2B -SH3GL1 and Acute Myeloid Leukaemia
1
ABI2 2q33 ABI-2, ABI2B, AIP-1, AblBP3, argBP1, SSH3BP2, argBPIA, argBPIB -ABI2 and Acute Myeloid Leukaemia
1
LRRC3B 3p24.1 LRP15 -LRRC3B and Acute Myeloid Leukaemia
1
PDCD7 15q22.31 ES18, HES18 -PDCD7 and Acute Myeloid Leukaemia
1
ERRFI1 1p36.23 MIG6, RALT, MIG-6, GENE-33 -ERRFI1 and Acute Myeloid Leukaemia
1
HSP90AA1 14q32.31 EL52, HSPN, LAP2, HSP86, HSPC1, HSPCA, Hsp89, Hsp90, LAP-2, HSP89A, HSP90A, HSP90N, Hsp103, HSPCAL1, HSPCAL4, HEL-S-65p -HSP90AA1 and Acute Myeloid Leukaemia
1
BRD3 9q34.2 ORFX, RING3L -BRD3 and Acute Myeloid Leukaemia
1
SERPINB2 18q21.33-q22.1 PAI, PAI2, PAI-2, PLANH2, HsT1201 -SERPINB2 and Acute Myeloid Leukaemia
1
PNN 14q21.1 DRS, DRSP, SDK3, memA -PNN and Acute Myeloid Leukaemia
1
RMI1 9q21.32 BLAP75, FAAP75, C9orf76 -RMI1 and Acute Myeloid Leukaemia
1
ECT2L 6q24.1 LFDH, FBXO49, C6orf91, ARHGEF32, dJ509I19.2, dJ509I19.3, dJ509I19.5 -ECT2L and Acute Myeloid Leukaemia
1
ZNF384 12p13.31 NP, CIZ, NMP4, CAGH1, ERDA2, TNRC1, CAGH1A -ZNF384 and Acute Myeloid Leukaemia
1
DOK2 8p21.3 p56DOK, p56dok-2 -DOK2 and Acute Myeloid Leukaemia
1
CBLB 3q13.11 Cbl-b, RNF56, Nbla00127 -CBLB and Acute Myeloid Leukaemia
1
NACA 12q13.3 HSD48, NACA1, skNAC, NAC-alpha -NACA and Acute Myeloid Leukaemia
1
ACSL6 5q31.1 ACS2, FACL6, LACS2, LACS5, LACS 6 -ACSL6 and Acute Myeloid Leukaemia
1
IL1RL1 2q12 T1, ST2, DER4, ST2L, ST2V, FIT-1, IL33R -IL1RL1 and Acute Myeloid Leukaemia
1
ST2 11p14.3-p12 -ST2 and Acute Myeloid Leukaemia
1
FGFR1OP 6q27 FOP -FGFR1OP and Acute Myeloid Leukaemia
1
TFAP2B 6p12.3 PDA2, AP-2B, AP2-B -TFAP2B and Acute Myeloid Leukaemia
DTX2P1-UPK3B 7q11.23 PMS2L11 -DTX2P1-UPK3B and Acute Myeloid Leukaemia
FUS 16p11.2 TLS, ALS6, ETM4, FUS1, POMP75, HNRNPP2 Translocation
-t(16;21)(p11;q22) in Leukemia (ANLL)
-t(16;21)(p11;q22) FUS-ERG in Acute Myelogenous Leukemia
AFDN 6q27 AF6, MLLT4, MLL-AF6, l-afadin Translocation
-t(6;11)(q27;q23) in Acute Myeloid Leukemia
MLLT11 1q21.3 AF1Q Translocation
-t(1;11) (q21;q23) in Leukemia
-Elevated AF1q/MLLT11 protein expression is an adverse prognostic marker in AML
MECOM 3q26.2 EVI1, MDS1, KMT8E, PRDM3, RUSAT2, MDS1-EVI1, AML1-EVI-1 Translocation
-t(3;21)(q26;q22) in Secondary Leukaemia / MDS
RARA 17q21.2 RAR, NR1B1 Translocation
-t(11;17)(q32;q21) RARA-PLZF in Acute Promyelocytic Leukemia
ZBTB16 11q23.2 PLZF, ZNF145 Translocation
-t(11;17)(q32;q21) RARA-PLZF in Acute Promyelocytic Leukemia
ERG 21q22.2 p55, erg-3 Translocation
-t(16;21)(p11;q22) in Leukemia (ANLL)
-t(16;21)(p11;q22) FUS-ERG in Acute Myelogenous Leukemia
RUNX1 21q22.12 AML1, CBFA2, EVI-1, AMLCR1, PEBP2aB, CBF2alpha, AML1-EVI-1, PEBP2alpha Translocation
- t(8;21)(q22;q22) in Acute Myeloid Leukemia
-t(3;21)(q26;q22) in Secondary Leukaemia / MDS

Note: list is not exhaustive. Number of papers are based on searches of PubMed (click on topic title for arbitrary criteria used).

Latest Publications

Guo Y
Clinical significance of serum MicroRNA-203 in patients with acute myeloid leukemia.
Bioengineered. 2019; 10(1):345-352 [PubMed] Related Publications
This study aimed to detect serum miR-203 expression levels in AML and explore its potential clinical significance. Quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) was performed to measure the serum miR-203 levels in 134 patients with AML and 70 healthy controls. The results demonstrated that serum miR-203 expression was significantly reduced in AML patients compared with healthy controls. Receiver operating characteristic curve (ROC) analysis revealed miR-203 could distinguish AML cases from normal controls. Low serum miR-203 levels were associated with worse clinical features, as well as poorer overall survival and relapse free survival of AML patients. Moreover, multivariate analysis confirmed low serum miR-203 expression to be an independent unfavorable prognostic predictor for AML. The bioinformatics analysis showed that the downstream genes and pathways of miR-203 was closely associated with tumorigenesis. Downregulation of miR-203 in AML cell lines upregulated the expression levels of oncogenic promoters such as CREB1, SRC and HDAC1. Thus, these findings demonstrated that serum miR-203 might be a promising biomarker for the diagnosis and prognosis of AML.

Sanada M
[Precision medicine for acute myeloid leukemia based on genomic profiling].
Rinsho Ketsueki. 2019; 60(7):847-853 [PubMed] Related Publications
Recent advanced high-throughput sequencing technologies have offered insights into the molecular landscape of acute myeloid leukemia (AML), revealing its genetic heterogeneity. As recurrent alterations should be related to the molecular pathogenesis of AML, assessing the mutation profile of each patient would contribute to the precise molecular diagnosis, precise risk stratification, and appropriate treatment decisions. In fact, the most recent WHO classification and clinical guidelines for AML are categorized by genetic alterations. In addition, serial monitoring of genetic markers could be useful to detect minimal residual disease (MRD) at the time of complete remission as well as clonal changes during the disease course. Because large databases of matched clinical genomics data are needed to use complicated genomic data for clinical decision making, we have been constructing an integrated database of hematological malignancies (knonc) supported by the AMED since 2016. Precision medicine for AML based on genetic information will provide optimal target drugs and useful information for the enhancement of clinical outcome.

Yamauchi T
[Exploration of novel therapeutic targets in acute myeloid leukemia via genome-wide CRISPR screening].
Rinsho Ketsueki. 2019; 60(7):810-817 [PubMed] Related Publications
Acute myeloid leukemia (AML) remains a devasting disease. Progress has been made to define molecular mechanisms underlying disease pathogenesis due, in part, to the near-complete understanding of AML genome. Nonetheless, functional studies are necessary to assess the significance of AML-associated mutations and devise urgently needed therapies. Genome-wide knockout screening, employing CRISPR-Cas9 genome editing, is a powerful tool in functional genomics. In this study, genome-wide CRISPR screening was performed using mouse leukemia cell lines developed in our Center, followed by in vivo screening. Among 20,611 genes, 130 AML essential genes were identified, including clinically actionable candidates. It was shown that mRNA decapping enzyme scavenger (DCPS), an enzyme implicated in mRNA decay pathway, is essential for AML survival. ShRNA-mediated gene knockdown and DCPS inhibitor (RG3039) were employed to validate findings. RG3039 induced cell-cycle arrest and apoptosis in vitro. Furthermore, mass spectrometry analysis revealed an association between DCPS and RNA metabolic pathways, and RNA-Seq showed that RG3039 treatment induced aberrant mRNA splicing in AML cells. Importantly, RG3039 exhibited anti-leukemia effects in PDX models. These findings identify DCPS as a novel therapeutic target for AML, shedding new light on the nuclear RNA metabolic pathway in leukemogenesis.

Hosono N
[Genetic defects of chromosome 5q and 7q in myeloid neoplasms].
Rinsho Ketsueki. 2019; 60(7):800-809 [PubMed] Related Publications
In myeloid neoplasms, deletions of the long arm of chromosome 5 del(5q) and 7 (-7/del(7q) ) are common karyotypic abnormalities. The concurrence of del(5q) and -7/del(7q) accounts for poor prognosis in myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML). Comprehensive analysis of copy number abnormalities and genetic mutations related to del(5q) and -7/del(7q) revealed previously cryptic pathophysiology, leading to frequent hemizygous/homozygous mutations and haploinsufficiency. In addition, detailed somatic mutations on chr5q were detected using whole-exome sequencing. CSNK1A1 and G3BP1 are located within the common deleted regions (CDRs) (5q31.1-5q33.1), and another driver gene DDX41 is present in the more telomeric region (5q35.3). All the genes mentioned above exhibited haploinsufficiency because of deletions, and low expression of G3BP1 and DDX41 correlated with poor survival. The related mutational events outside of chr5q, TP53 mutation is most frequently observed in del(5q) cases. Regarding -7/del(7q), 3 CDRs were located in 7q22, 7q34, and 7q35-36. Somatic mutations of the corresponding genes to each CDR (CUX1: 7q22, LUC7L2: 7q34, EZH2: 7q35-36) were identified, indicating that the loss of function or haploinsufficiency might result in the downstream pathological consequences. These recent findings have remarkably offered insights into genetic and clinical consequences in MDS/AML cases with del(5q) and -7/del(7q).

Makishima H
[Genomic aberrations in myelodysplastic syndromes and related disorders].
Rinsho Ketsueki. 2019; 60(6):600-609 [PubMed] Related Publications
Myelodysplastic syndromes (MDS) and myelodysplastic/myeloproliferative neoplasms (MDS/MPN) are heterogeneous myeloid neoplasms that frequently evolve into secondary acute myeloid leukemia (sAML). Recent progress in next-generation sequencing technologies has allowed us to discover frequent mutations throughout the coding regions of MDS, MDS/MPN, and sAML, subsequently providing information on more than 60 driver genes in these diseases. As shown by many study groups recently, such driver mutations are acquired in a gene-specific fashion. DDX41 and SAMD9/SAMD9L mutations are observed in germline cells long before MDS presentation. In blood samples from healthy elderly individuals, somatic DNMT3A, TET2, and ASXL1 mutations are detected as age-related clonal hematopoiesis and supposed to be a risk factor for hematological neoplasms. Recent reports on MDS have shown that mutations in genes such as NRAS and FLT3, designated as Type I genes, were significantly associated with leukemic evolution. Another type (Type II) of genes, including RUNX1 and GATA2, has been shown to be related to the progression from low-risk to high-risk MDS. These driver mutations are significantly concomitant during disease progression. Overall, various types of driver mutations are sequentially acquired in MDS, accounting for the heterogeneity of these disorders.

Umezawa Y, Kawamata N
[Novel therapies for acute myeloid leukemia based on genomic aberrations].
Rinsho Ketsueki. 2019; 60(6):594-599 [PubMed] Related Publications
Standard treatment for acute myeloid leukemia (AML) comprises (1) induction therapy with both cytarabine and anthracycline and (2) consolidation therapy that is modified according to patients' conditions, including prognostic factors. However, this strategy is not satisfactory, especially for elderly patients. Novel technologies have revealed several driver mutations of numerous critical genes in AML, which can be targeted by novel drugs; the discovery of such targetable genes and the development of novel drugs have evolved the treatment strategy for AML. We should always monitor these advances in hematology. In the United States, the FDA has already approved several new drugs for AML, including FLT3 inhibitors and IDH neoenzyme inhibitors. In Japan, gilteritinib, an FLT3 inhibitor, was also approved at the end of 2018. These promising drugs will facilitate performing "precision medicine" on patients with AML soon.

Nakajima H
[Genetic abnormalities in AML].
Rinsho Ketsueki. 2019; 60(6):584-593 [PubMed] Related Publications
Genetic abnormalities of acute myeloid leukemia (AML) include chromosomal translocations and gene mutations. Commonly observed chromosomal abnormalities in AML are t (8;21), t (15;17), inv (16), and 11q23-related translocations. These aberrations produce RUNX1-RUNX1T1, PML-RARA, CBF-MYH11, and MLL-fusion genes, respectively, which promote leukemic stem cell formation by interfering with hematopoietic differentiation and enhancing the self-renewal capacity of hematopoietic cells. Gene mutations recurrently occur in transcription factors, signaling molecules, tumor suppressor genes, epigenetic regulators, RNA splicing factors, and cohesion complexes, with FLT3, NPM1, and DNMT3A being the most frequently mutated genes in AML. Recent studies disclosed the biological function of mutated genes and their correlation with prognosis. Based on these findings, development of novel therapeutic drugs targeting mutated genes or dysregulated genetic pathways is underway.

Arbelbide JA
Advances in the genetic abnormalities involved in the pathogenesis of acute myeloid leukemia
Rev Fac Cien Med Univ Nac Cordoba. 2019; 76(2):77-78 [PubMed] Related Publications

Ye J, Luo D, Yu J, Zhu S
Transcriptome analysis identifies key regulators and networks in Acute myeloid leukemia.
Hematology. 2019; 24(1):487-491 [PubMed] Related Publications
OBJECTIVES: Acute myeloid leukemia (AML) is a heterogeneous and highly recurrent hematological malignancy. Studies have shown an association between microRNAs and drive genes in AMLs. However, the regulatory roles of miRNAs in AML and how they act on downstream targets and the signaling pathway has been little studied.
METHODS: As to understand the mechanism of mRNA-miRNA interaction in the blood malignancy from a large scale of transcriptomic sequencing studies, we applied a comprehensive miRNA-mRNA association, co-expression gene network and ingenuity pathway analysis using TCGA AML datasets.
RESULTS: Our results showed that his-mir-335 was a critical regulatory of homeobox A gene family. PBX3, KAT6A, MEIS1, and COMMD3-BMI1 were predicted as top transcription regulators in the regulatory network of the HOXA family. The most significantly enriched functions were cell growth, proliferation, and survival in the mRNA-miRNA network.
CONCLUSION: Our work revealed that regulation of the HOXA gene family and its regulation played an important role in the development of AML.

Wen C, Xie YK, Chen YJ
[Efflect of miR-34a-Tangeted Regulation of HDACI on Apoptosis of AML Cells].
Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2019; 27(3):790-795 [PubMed] Related Publications
OBJECTIVE: To investigate the regulation of miR-34a on HDAC1 expression and its effect on the apoptosis of acute myeloid leukemia (AML) cells.
METHODS: miR-34a mimics, miR-34a inhibitor and miR-34a scramble were transfected into HL-60 cells. The effects of miR-34a expression levels on proliferation and apoptosis of HL-60 cell were detected by CCK8 assay and flow cytometry respectively. The expression of HDAC1 protein was assessed by Western blot after regulating miR-34a expression, the 3'UTR of HDAC1 was cloned and ligated to construct a dual luciferase reporter vector, and then the dual luciferase reporter assay was applied to verify the target of miR-34a, the expression vector pcDNA3.1-HDAC1 was constructed, the interaction of miR-34a and HDAC1 was analyzed by reversion test.
RESULTS: miR-34a over-expression could inhibit the proliferation of HL-60 cells and induce their apoptosis. Bioinformatics analysis indicated that the HDAC1 was a target gene of miR-34a. Western blot indicated that miR-34a overexpression down-regulated the expression of HDAC1. Dual luciferase reporter assay and reversion test showed that miR-34a could act at the 3-UTR of HDAC1 gene to regulate its expression.
CONCLUSION: miR-34a promotes the apoptosis of HL-60 cells via regulating HDAC1 expression.

Ni J, Shi QQ, Wu W, et al.
[Expression Difference of RhoH Gene in Leukemia and Its Clinical Significance].
Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2019; 27(3):758-762 [PubMed] Related Publications
OBJECTIVE: To investigate the expression and clinical significance of RhoH gene in bone marrow cells of leukemia patients.
METHODS: 31 cases of leukemia and 15 cases of non-tumor as controls were collected. The expression of RhoH in bone marrow cells was detected by real-time quantitative PCR (RQ-PCR). The median expression level of RhoH was used as the cut-off value. The newly diagnosed patients were divided into RhoH high expression group and low expression group. The relationship of different RhoH expression levels with clinical features and prognosis of newly diagnosed patients was analyzed.
RESULTS: The mRNA expression of RhoH in the bone marrow cells of 31 cases of leukemia was significantly lower than that in the control group, mRNA expression of RhoH in the ALL group was significantly lower than that in AML group (P<0.05). Compared with the RhoH high expression group, the proportion of bone marraw blasts and LDH level in the RhoH low expression group was significantly increased (P<0.05), but there were no significant differences in clinical features such as age, white blood cell count, hemoglobin level, platelets count, PCT and CRP level (P>0.05). In AML, the recurrence rate after standard chemotherapy in RhoH low expression group was higher than that in high expression group, while the expression of RhoH not correlated with other prognostic genes of AML. In ALL, the recurrence rate in RhoH low expression group was not statistically significant different from that in high expression group.
CONCLUSION: RhoH may be involved in the genesis of acute leukemia. In AML, RhoH expression negatively correlates with recurrence rate, which can be used as a prognostic indicator independently. In ALL, RhoH may participate in the disease process through other mechanism.

Li Q, Sun RX, Ou Y, et al.
[Role of Pim1 Gene Overexpression in Pathogenesis of Acute Myeloid Leukemia].
Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2019; 27(3):664-672 [PubMed] Related Publications
OBJECTIVE: To investigate the effect of Pim1 expression up-regulation on cell proliferation, apoptosis, chemotaxis and angiogenesis in acute myeloid leukemia (AML) cell line U937, and to explore the possible molecular mechanism involved, finally to estimate the Pim1 expression in primary AML cells.
METHODS: GFP-tagged plasmid for Pim1 overexpression and an empty vector plasmid were constructed, and then a stable Pim1 expressed U937 cell line and a control virus-infected U937 cell line were established by a lentiviral vector system. After confirming Pim1 overexpression in U937 cells, proliferation and apoptosis are determined by CCK-8 Kit and flow cytometry respectively. Transwell chemotaxis assay was used to measure the effect of Pim1 overexpression on AML cells. Flow cytometry and confocal microscopy were applied to detect the influence of Pim1 overexpression on phosphorylated CXCR4 (pCXCR4) and its location. Real-time fluorescence quantitative PCR (qPCR) was used to detect the expression of angiogenesis and adhesion related genes in AML primary cells.
RESULTS: The lentivirus-infected AML cell line with Pim1 overex-pression and the control virusinfected AML cell line were established successfully. The Pim1 overexpression could enhance the proliferation and inhibit the cell apoptosis, moreover accompnied with the increasing expression of cyclin D1, phosphorylated BAD (pBAD) and pCXCR4. After SDF-1 α stimuli, Pim1 overexpression induced AML cell chemotaxis accompanied with p-CXCR4 expression and calcium influx increment. Pim1 overexpression has no effect on angiogenesis. Pim1 mRNA expression was significantly higher in AML patients than the healthy people.
CONCLUSION: Pim1 plays an important role in the pathogenesis of AML, which not only promotes AML cell proliferation and inhibition of apoptosis, but also enhances the chemotactic ability of leukemia cells, which closely relates with Pim1 phosphorylation of CXCR4 and the increase of intracellular calcium ion influx signals.

Lei B, Zhang WG, He AL, et al.
[Cloning of New Antigen Gene MLAA-34 Promoter and Identification of Core Region in Acute Monocytic Leukemia].
Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2019; 27(3):641-645 [PubMed] Related Publications
OBJECTIVE: To clone the promoter sequence of acute monocytic leukemia new antigen gene.MLAA-34 and identify its promoter core region.
METHODS: The full-length fragment of MLAA-34 gene promoter region was amplified by PCR, then was ligated into pGL3-Basic vector, and the recombinant plasmid was cloned. Constructed a series of MLAA-34 gene promoter 5' flanking region truncated plasmid. These recombinant plasmids were transfected into U937 and HEK293 cells, and the dual luciferase reporter gene was used to detect the promoter activity of each fragment to determine the minimum active region. Transcription factor binding sites were analyzed by bioinformatics methods.
RESULTS: The recombinant plasmid containing MLAA-34 promoter sequence and its truncated plasmid were successfully constructed, and the promoter activity was significantly increased as compared with the empty vector (P<0.001). The minimal active region of MLAA-34 located between 402 bp and 200 bp. It contained multiple transcription factor binding sites such as E2F1, MZF-1, SP1, USF2 and STAT3.
CONCLUSION: The promoter of luciferase reporter gene has been successfully constructed with different deletion fragments of MLAA-34, and its core promoter region may contain multiple transcription factor sequence.

Farnaby W, Koegl M, Roy MJ, et al.
BAF complex vulnerabilities in cancer demonstrated via structure-based PROTAC design.
Nat Chem Biol. 2019; 15(7):672-680 [PubMed] Article available free on PMC after 10/12/2019 Related Publications
Targeting subunits of BAF/PBAF chromatin remodeling complexes has been proposed as an approach to exploit cancer vulnerabilities. Here, we develop proteolysis targeting chimera (PROTAC) degraders of the BAF ATPase subunits SMARCA2 and SMARCA4 using a bromodomain ligand and recruitment of the E3 ubiquitin ligase VHL. High-resolution ternary complex crystal structures and biophysical investigation guided rational and efficient optimization toward ACBI1, a potent and cooperative degrader of SMARCA2, SMARCA4 and PBRM1. ACBI1 induced anti-proliferative effects and cell death caused by SMARCA2 depletion in SMARCA4 mutant cancer cells, and in acute myeloid leukemia cells dependent on SMARCA4 ATPase activity. These findings exemplify a successful biophysics- and structure-based PROTAC design approach to degrade high profile drug targets, and pave the way toward new therapeutics for the treatment of tumors sensitive to the loss of BAF complex ATPases.

Capo-Chichi JM, Michaels P, Tremblay-Le May R, et al.
Emerging patterns in clonal haematopoiesis.
J Clin Pathol. 2019; 72(7):453-459 [PubMed] Related Publications
Clonal haematopoiesis (CH) is defined by the presence of acquired mutations and/or cytogenetic abnormalities in haematopoietic cells. By definition, these premalignant clones do not meet criteria for haematopoietic neoplasms listed in the Revised Fourth Edition of the WHO classification. CH is fairly common in elderly individuals and is associated with higher risks for haematological cancers, in particular myelodysplastic syndrome and acute myeloid leukaemia (AML), as well as cardiovascular events. Similar small clones have also been detected during follow-up in patients with AML in morphological remission, in individuals with aplastic anaemia, and in pre-chemotherapy blood samples from patients with other types of cancers. In each of these contexts, the presence of mutations carries different clinical implications, and sometimes demonstrates unique genetic profiles. Emerging research suggests that the number and identity of mutations, the size of the mutant clones and various other factors, including age, immune status and history of exogenous drugs/toxins, are important for disease biology and progression. This review focuses specifically on the subset of CH with gene mutations detected by sequencing, and includes discussions of nomenclature and molecular technologies that detect and quantify gene mutations.

Lange AP, Almeida LY, Araújo Silva CL, et al.
CCAAT/enhancer-binding protein alpha (CEBPA) gene haploinsufficiency does not alter hematopoiesis or induce leukemia in Lck-CALM/AF10 transgenic mice.
Braz J Med Biol Res. 2019; 52(6):e8424 [PubMed] Article available free on PMC after 10/12/2019 Related Publications
Although rare, CALM/AF10 is a chromosomal rearrangement found in immature T-cell acute lymphoblastic leukemia (T-ALL), acute myeloid leukemia, and mixed phenotype acute leukemia of T/myeloid lineages with poor prognosis. Moreover, this translocation is detected in 50% of T-ALL patients with gamma/delta T cell receptor rearrangement, frequently associated with low expression of transcription factor CCAAT/enhancer-binding protein alpha (CEBPA). However, the relevance of CEBPA low expression for CALM/AF10 leukemogenesis has not yet been evaluated. We generated double mutant mice, which express the Lck-CALM/AF10 fusion gene and are haploinsufficient for the Cebpa gene. To characterize the hematopoiesis, we quantified hematopoietic stem cells, myeloid progenitor cells, megakaryocyte-erythrocyte progenitor cells, common myeloid progenitor cells, and granulocyte-macrophage progenitor cells. No significant difference was detected in any of the progenitor subsets. Finally, we tested if Cebpa haploinsufficiency would lead to the expansion of Mac-1+/B220+/c-Kit+ cells proposed as the CALM/AF10 leukemic progenitor. Less than 1% of bone marrow cells expressed Mac-1, B220, and c-Kit with no significant difference between groups. Our results showed that the reduction of Cebpa gene expression in Lck-CALM/AF10 mice did not affect their hematopoiesis or induce leukemia. Our data corroborated previous studies suggesting that the CALM/AF10 leukemia-initiating cells are early progenitors with lymphoid/myeloid differentiating potential.

Du D, Zhu L, Wang Y, Ye X
[Expression of
Zhejiang Da Xue Xue Bao Yi Xue Ban. 2019; 48(1):50-57 [PubMed] Related Publications
OBJECTIVE: To investigate the expression of Wilms'tumor 1 (
METHODS: One hundred and sixty-seven newly diagnosed AML patients(exclued M3 type) were enrolled in this study. The survival of patients were analyzed with Kaplan-Meier method. The clinical data, laboratory findings and the survival of patients were analyzed and compared between patients with high
RESULTS: The overall response rates (ORR) in high-

Masetti R, Guidi V, Ronchini L, et al.
The changing scenario of non-Down syndrome acute megakaryoblastic leukemia in children.
Crit Rev Oncol Hematol. 2019; 138:132-138 [PubMed] Related Publications
Pediatric non-Down-syndrome acute megakaryoblastic leukemia (non-DS-AMKL) is a heterogeneous subtype of leukemia that has historically been associated with poor prognosis. Until the advent of large-scale genomic sequencing, the management of patients with non-DS-AMKL was very difficult due to the absence of reliable biological prognostic markers. The sequencing of large cohort of pediatric non-DS-AMKL samples led to the discovery of novel genetic aberrations, including high-frequency fusions, such as CBFA2T3-GLIS2 and NUP98-KDM5 A, as well as less frequent aberrations, such as HOX rearrangements. These new insights into the genetic landscape of pediatric non-DS-AMKL has allowed refining the risk-group stratification, leading to important changes in the prognostic scenario of these patients. This review summarizes the most important molecular pathogenic mechanisms of pediatric non-DS-AMKL. A critical discussion on how novel genetic abnormalities have refined the risk profile assessment and changed the management of these patients in clinical practice is also provided.

Wang X, Wang J, Zhang L
Characterization of atypical acute promyelocytic leukaemia: Three cases report and literature review.
Medicine (Baltimore). 2019; 98(19):e15537 [PubMed] Article available free on PMC after 10/12/2019 Related Publications
RATIONALE: The vast majority of acute promyelocytic leukemia (APL) is characterized with a specific chromosomal translocation t (15, 17) (q22, q21), which fuses PML-RARα leading to a good response to all-trans retinoic acid (ATRA) and arsenic trioxide (ATO). However, there are few cases of atypical APL, including PLZF-RARα, F1P1L1-RARα, STAT5b-RARα, et al. Neither PLZF-RARα nor STAT5b-RARα are sensitive to ATRA and ATO, and the prognosis is poor.
PATIENT CONCERNS: Here we have 3 cases (PLZF-RARα, n = 2; STAT5b-RARα, n = 1). Case A, A 53-year-old Chinese female had suffered ecchymosis in both legs for 3 days. Case B, A 44 years old male suffered pain from lower limbs and hip. Case C, 52-year-old male patient presented with fever for 3 weeks invalid to antibiotics and gingival bleeding for 1 week.
DIAGNOSES: With RT-PCR and karyotype, Case A is diagnosed with STAT5b-RARα-positive APL.Case B, C are diagnosed with PLZF-RARα-positive APL.
INTERVENTIONS: In case A, ATO, and ATRA were used for induction treatment. In Case B, ATO, and chemotherapy with DA were given in the first induction treatment. In Case C, ATRA, and ATO were used immediately, subsequently, chemotherapy was added with DA, ATRA, and CAG combination treatment, and medium-dose cytarabine with daunorubicin were given regularly.
OUTCOMES: In Case A, the patient refused the following treatment and discharged on day 25. In Case B, the patient got the disseminated intravascular coagulation (DIC).In Case C, the patient has survived for 7 months and remains CR.
LESSONS: Both STAT5b-RARα-positive APL and PLZF-RARα-positive APL appear to be resistant to both ATRA and ATO, so combined chemotherapy and allo-HSCT should be considered. Since the prognosis and long-term outcome are poor, more clinical trials, and researches should be taken.

Galera P, Dulau-Florea A, Calvo KR
Inherited thrombocytopenia and platelet disorders with germline predisposition to myeloid neoplasia.
Int J Lab Hematol. 2019; 41 Suppl 1:131-141 [PubMed] Related Publications
Advances in molecular genetic sequencing techniques have contributed to the elucidation of previously unknown germline mutations responsible for inherited thrombocytopenia (IT). Regardless of age of presentation and severity of symptoms related to thrombocytopenia and/or platelet dysfunction, a subset of patients with IT are at increased risk of developing myeloid neoplasms during their life time, particularly those with germline autosomal dominant mutations in RUNX1, ANKRD26, and ETV6. Patients may present with isolated thrombocytopenia and megakaryocytic dysmorphia or atypia on baseline bone marrow evaluation, without constituting myelodysplasia (MDS). Bone marrow features may overlap with idiopathic thrombocytopenic purpura (ITP) or sporadic MDS leading to misdiagnosis. Progression to myelodysplastic syndrome/ acute myeloid leukemia (MDS/AML) may be accompanied by progressive bi- or pancytopenia, multilineage dysplasia, increased blasts, cytogenetic abnormalities, acquisition of bi-allelic mutations in the underlying gene with germline mutation, or additional somatic mutations in genes associated with myeloid malignancy. A subset of patients may present with MDS/AML at a young age, underscoring the growing concern for evaluating young patients with MDS/AML for germline mutations predisposing to myeloid neoplasm. Early recognition of germline mutation and predisposition to myeloid malignancy permits appropriate treatment, adequate monitoring for disease progression, proper donor selection for hematopoietic stem cell transplantation, as well as genetic counseling of the affected patients and their family members. Herein, we describe the clinical and diagnostic features of IT with germline mutations predisposing to myeloid neoplasms focusing on mutations involving RUNX1, ANKRD26, and ETV6.

Cocciardi S, Dolnik A, Kapp-Schwoerer S, et al.
Clonal evolution patterns in acute myeloid leukemia with NPM1 mutation.
Nat Commun. 2019; 10(1):2031 [PubMed] Article available free on PMC after 10/12/2019 Related Publications
Mutations in the nucleophosmin 1 (NPM1) gene are considered founder mutations in the pathogenesis of acute myeloid leukemia (AML). To characterize the genetic composition of NPM1 mutated (NPM1

Su L, Gao S, Tan Y, et al.
CSF3R mutations were associated with an unfavorable prognosis in patients with acute myeloid leukemia with CEBPA double mutations.
Ann Hematol. 2019; 98(7):1641-1646 [PubMed] Related Publications
The aim of this study was to explore the clinical features and prognostic significance of CSF3R mutations in AML patients with CEBPA double mutations (CEBPA

Wang R, Gao X, Yu L
The prognostic impact of tet oncogene family member 2 mutations in patients with acute myeloid leukemia: a systematic-review and meta-analysis.
BMC Cancer. 2019; 19(1):389 [PubMed] Article available free on PMC after 10/12/2019 Related Publications
BACKGROUND: The impact of Tet oncogene family member 2 (TET2) mutations on the prognosis of acute myeloid leukemia (AML) is still controversial. A meta analysis is needed in order to assess the prognostic significance of TET2 mutation in AML.
METHODS: Five databases including PubMed, Cochrane, EMBase, China National Knowledge Internet (CNKI) and Wanfang database were retrieved to search studies that investigated the correlation between TET2 mutations and outcomes of AML patients. Pooled hazard ratios (HRs) and odds ratios (ORs) were used to assess the effects of TET2 mutations.
RESULTS: Sixteen studies were included. TET2 mutation was an unfavorable prognostic factor for overall survival (OS: HR = 1.386; P < 0.001) and event-free survival (EFS: HR = 1.594; P = 0.002) in patients with AML. For patients under 65 years of age, TET2 mutation predicted an inferior OS (HR = 1.310, P = 0.051) and EFS (HR = 1.429, P = 0.027). For patients with intermediate-risk cytogenetics (IR-AML), mutant TET2 had a significant association with adverse OS (HR = 0.474; P < 0.001). For patients with normal cytogenetics (CN-AML), mutant TET2 also conferred adverse OS (HR = 1.425; P < 0.001) and EFS (HR = 1.450, P < 0.001). Further, among patients with CN-AML, mutant TET2 was associated with inferior OS (HR = 2.034, P < 0.001) and EFS (HR = 2.140, P < 0.001) in the ELN favorable-risk subgroup and an inferior EFS (HR = 1.487; P < 0.001) in the ELN intermediate-Isubgroup. With respect to treatment outcome, TET2 mutation predicted a significantly lower rate of complete remission (CR) in cases with ELN favorable-risk cytogenetics (OR = 0.460, P = 0.011).
CONCLUSIONS: TET2 mutation had adverse impacts on survival and treatment response in AML patients and will contribute to risk-stratification, prognosis prediction and therapy guidance.

Smith MA, Choudhary GS, Pellagatti A, et al.
U2AF1 mutations induce oncogenic IRAK4 isoforms and activate innate immune pathways in myeloid malignancies.
Nat Cell Biol. 2019; 21(5):640-650 [PubMed] Article available free on PMC after 10/12/2019 Related Publications
Spliceosome mutations are common in myelodysplastic syndromes (MDS) and acute myeloid leukaemia (AML), but the oncogenic changes due to these mutations have not been identified. Here a global analysis of exon usage in AML samples revealed distinct molecular subsets containing alternative spliced isoforms of inflammatory and immune genes. Interleukin-1 receptor-associated kinase 4 (IRAK4) was the dominant alternatively spliced isoform in MDS and AML and is characterized by a longer isoform that retains exon 4, which encodes IRAK4-long (IRAK4-L), a protein that assembles with the myddosome, results in maximal activation of nuclear factor kappa-light-chain-enhancer of B cells (NF-κB) and is essential for leukaemic cell function. Expression of IRAK4-L is mediated by mutant U2 small nuclear RNA auxiliary factor 1 (U2AF1) and is associated with oncogenic signalling in MDS and AML. Inhibition of IRAK4-L abrogates leukaemic growth, particularly in AML cells with higher expression of the IRAK4-L isoform. Collectively, mutations in U2AF1 induce expression of therapeutically targetable 'active' IRAK4 isoforms and provide a genetic link to activation of chronic innate immune signalling in MDS and AML.

Huang CY, Zha XF, Wen WR
[Expression and Clinical Significance of PD-L1 and MicroRNA-138-5p in Patients with Acute Myeloid Leukemia].
Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2019; 27(2):373-378 [PubMed] Related Publications
OBJECTIVE: To investigate the expression and clinical significance of PD-L1 and microRNA-138-5p in the peripheral blood mononuclear cells of patients with acute myeloid leukemia.
METHODS: The SYBR GreenⅠreal-time PCR was used to detect the expression levels of PD-L1 mRNA and miR-138 in 20 cases of primary AML, 9 cases of relapsed/refractory AML and 8 cases of complete remission. The samples of peripheral blood of 20 healthy peoples were used as controls.
RESULTS: The expression levels of PD-L1 in both the primary AML and the relapsed/refractory AML groups were significantly higher than those in the healthy control group (P<0.01), and the expression level of PD-L1 in the relapsed/refractory AML group was significantly higher than that in the primary AML group (P<0.01). The expression level of miR-138 in both the primary AML and the relapsed/refractory AML groups were significantly lower than that in the healthy control group (P<0.01). The 8 sampes out of 20 cases of primary AML patients achieved complete remission (CR) were collected and detected. The results showed that the expression level of miR-138 in the complete remission group was higher than that in the primary AML group (P<0.05), but the expression level of PD-L1 mRNA in the CR group was not significantly different from that in the primary AML group (P>0.05). and there was a negative correlation between PD-L1 mRNA and miR-138 in primary AML patients (P<0.05).
CONCLUSION: The expression of PD-L1 increases and the expression of miR-138 down-regulates in PBMNCs of AML patients, furthermore, both correlate each other.

Hou JX, Wang SJ, Liu YF, et al.
[NPM1 High Mutant Allele Burden is an Adverse Prognostic Factor for AML Patients with Mutated NPM1].
Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2019; 27(2):365-372 [PubMed] Related Publications
OBJECTIVE: To investigate the clinical features, accompanying gene mutation characteristics and prognostic factors of adult patients with acute myeloid leukemia with mutated NPM1 (NPM1
METHODS: Seventy-three patients with newly diagnosed adult NPM1
RESULTS: A total of 74 NPM1 site mutations were detected in 73 patients with NPM1
CONCLUSION: The NPM1 gene mutation in AML patients often is accompanied by other gene mutations, while the coexistence of fusion genes is rare; high NPM1 mutant allele burden is an independent prognostic factor for adult AML patients with mutated NPM1.

Capela de Matos RR, Ney Garcia DR, Othman MAK, et al.
A New Complex Karyotype Involving a KMT2A-r Variant Three-Way Translocation in a Rare Clinical Presentation of a Pediatric Patient with Acute Myeloid Leukemia.
Cytogenet Genome Res. 2019; 157(4):213-219 [PubMed] Related Publications
Patients with childhood acute myeloid leukemia (AML) with complex karyotypes (CKs) have a dismal outcome. However, for patients with a KMT2A rearrangement (KMT2A-r), the prognosis appears to depend on the fusion partner gene rather than the karyotype structure. Thus, a precise characterization of KMT2A-r and the fusion partner genes, especially in CKs, is of interest for managing AML. We describe the clinical and molecular features of a child who presented with a large abdominal mass, AML, and a new CK, involving chromosomes 11, 16, and 19 leading to a KMT2A-MLLT1 fusion and 2 extra copies of the ELL gene, thus resulting in the concurrent overexpression of MLLT1 and ELL. Molecular cytogenetic studies defined the karyotype as 47,XY,der(11)t(11;16)(q23.3;p11.2),der(16)t(16;19)(p11.2;p13.3),der(19)t(11;19)(q23.3;p13.3),+der(19)t(16;19)(16pter→p11.2::19p13.3→19q11::19p11→19p13.3::16p11.2→16pter). Array CGH revealed a gain of 30.5 Mb in the 16p13.3p11.2 region and a gain of 18.1 Mb in the 19p13.3p12 region. LDI-PCR demonstrated the KMT2A-MLLT1 fusion. Reverse sequence analysis showed that the MLLT1 gene was fused to the 16p11.2 region. RT-qPCR quantification revealed that ELL and MLLT1 were overexpressed (4- and 10-fold, respectively). In summary, this is a pediatric case of AML presenting a novel complex t(11;16;19) variant with overexpression of ELL and MLLT1.

Xue YM, Cheng HC, Wang JH, et al.
Cytosine 5-hydroxymethylation regulated kit gene expression in acute myeloid leukemia.
J Biol Regul Homeost Agents. 2019 Mar-Apr; 33(2):345-353 [PubMed] Related Publications
5-methyl cytosine (5mC) can be oxidized to 5-hydroxymethyl cytosine (5hmC) under the action of TET protein family, and 5hmC plays important roles in the pathogenesis of various tumors including acute myeloid leukemia (AML). In this study, we evaluated the role of 5mC and 5hmC levels in HL60 AML cells and bone marrow samples from AML patients for KIT gene expression to analyze 5hmC level in AML pathogenesis. Results showed that the expression and 5hmC level increased significantly of the KIT gene but the change of its 5mC level was not obvious after being treated by decitabine (DAC) in HL60 cells. IDH1 and IDH2 expression increased followed by increased KIT 5hmC level. In AML patients with IDH1 or IDH2 mutation, KIT expression and 5hmC were much lower than in those without mutation. The study indicated that the expression of KIT gene was regulated by 5hmC level in HL60 cells, and the 5hmC level was regulated by IDH1 and IDH2.

Kubota S, Tokunaga K, Umezu T, et al.
Lineage-specific RUNX2 super-enhancer activates MYC and promotes the development of blastic plasmacytoid dendritic cell neoplasm.
Nat Commun. 2019; 10(1):1653 [PubMed] Article available free on PMC after 10/12/2019 Related Publications
Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is an aggressive subtype of acute leukemia, the cell of origin of which is considered to be precursors of plasmacytoid dendritic cells (pDCs). Since translocation (6;8)(p21;q24) is a recurrent anomaly for BPDCN, we demonstrate that a pDC-specific super-enhancer of RUNX2 is associated with the MYC promoter due to t(6;8). RUNX2 ensures the expression of pDC-signature genes in leukemic cells, but also confers survival and proliferative properties in BPDCN cells. Furthermore, the pDC-specific RUNX2 super-enhancer is hijacked to activate MYC in addition to RUNX2 expression, thereby promoting the proliferation of BPDCN. We also demonstrate that the transduction of MYC and RUNX2 is sufficient to initiate the transformation of BPDCN in mice lacking Tet2 and Tp53, providing a model that accurately recapitulates the aggressive human disease and gives an insight into the molecular mechanisms underlying the pathogenesis of BPDCN.

Schittenhelm MM, Walter B, Tsintari V, et al.
Alternative splicing of the tumor suppressor ASPP2 results in a stress-inducible, oncogenic isoform prevalent in acute leukemia.
EBioMedicine. 2019; 42:340-351 [PubMed] Article available free on PMC after 10/12/2019 Related Publications
BACKGROUND: Apoptosis-stimulating Protein of TP53-2 (ASPP2) is a tumor suppressor enhancing TP53-mediated apoptosis via binding to the TP53 core domain. TP53 mutations found in cancers disrupt ASPP2 binding, arguing for an important role of ASPP2 in TP53-mediated tumor suppression. We now identify an oncogenic splicing variant, ASPP2κ, with high prevalence in acute leukemia.
METHODS: An mRNA screen to detect ASPP2 splicing variants was performed and ASPP2κ was validated using isoform-specific PCR approaches. Translation into a genuine protein isoform was evaluated after establishing epitope-specific antibodies. For functional studies cell models with forced expression of ASPP2κ or isoform-specific ASPP2κ-interference were created to evaluate proliferative, apoptotic and oncogenic characteristics of ASPP2κ.
FINDINGS: Exon skipping generates a premature stop codon, leading to a truncated C-terminus, omitting the TP53-binding sites. ASPP2κ translates into a dominant-negative protein variant impairing TP53-dependent induction of apoptosis. ASPP2κ is expressed in CD34+ leukemic progenitor cells and functional studies argue for a role in early oncogenesis, resulting in perturbed proliferation and impaired induction of apoptosis, mitotic failure and chromosomal instability (CIN) - similar to TP53 mutations. Importantly, as expression of ASPP2κ is stress-inducible it defines a novel class of dynamic oncogenes not represented by genomic mutations.
INTERPRETATION: Our data demonstrates that ASPP2κ plays a distinctive role as an antiapoptotic regulator of the TP53 checkpoint, rendering cells to a more aggressive phenotype as evidenced by proliferation and apoptosis rates - and ASPP2κ expression results in acquisition of genomic mutations, a first initiating step in leukemogenesis. We provide proof-of-concept to establish ASPP2κ as a clinically relevant biomarker and a target for molecule-defined therapy. FUND: Unrestricted grant support from the Wilhelm Sander Foundation for Cancer Research, the IZKF Program of the Medical Faculty Tübingen, the Brigitte Schlieben-Lange Program and the Margarete von Wrangell Program of the State Ministry Baden-Wuerttemberg for Science, Research and Arts and the Athene Program of the excellence initiative of the Eberhard-Karls University, Tübingen.

Recurrent Structural Abnormalities

Selected list of common recurrent structural abnormalities

Abnormality Type Gene(s)
t(1;12)(q25;p13) in Leukaemia (AML & ALL)TranslocationABL2 (1q25.2)ETV6 (12p13.2)
t(8;21)(q22;q22) in Acute Myeloid LeukemiaTranslocationRUNX1 (21q22.12)RUNX1T1 (8q21.3)
t(16;16)(p13q22) CBFB-MYH11 Translocation in AMLTranslocationCBFB (16q22.1)MYH11 (16p13.11)
t(16;21)(p11;q22) in Leukemia (ANLL)TranslocationERG (21q22.2)FUS (16p11.2)
t(3;21)(q26;q22) in Secondary Leukaemia / MDSTranslocationMECOM (3q26.2)RUNX1 (21q22.12)
t(16;21)(p11;q22) FUS-ERG in Acute Myelogenous LeukemiaTranslocationFUS (16p11.2)ERG (21q22.2)
t(1;11)(p32;q23) MLL-EPS15 fusion in Acute Myelogeneous LeukemiaTranslocationKMT2A (11q23.3)EPS15 (1p32.3)
t(11;19)(q23;p13.1) MLL-ELL translocation in acute leukaemiaTranslocationKMT2A (11q23.3)ELL (19p13.11)
t(9;11) in Acute Myeloid LeukaemiaTranslocationKMT2A (11q23.3)MLLT3 (9p21.3)
t(6;11)(q27;q23) in Acute Myeloid LeukemiaTranslocationAFDN (6q27)KMT2A (11q23.3)
t(7;11)(p15;p15) in Acute Myelogenous LeukaemiaTranslocationNUP98 (11p15.4)HOXA9 (7p15.2)
t(11;17)(q32;q21) RARA-PLZF in Acute Promyelocytic LeukemiaTranslocationRARA (17q21.2)ZBTB16 (11q23.2)
t(9;9)(q34;q34) SET-NUP214 rearrangements in Acute Lyphoblastic LeukaemiaTranslocationSET (9q34.11)NUP214 (9q34.13)
t(11;20) (p15;q11) NUP98-TOP1 Fusion in AMLTranslocationTOP1 (20q12)NUP98 (11p15.4)
t(6;9)(p23;q34) DEK-NUP214 in Acute Myeloid Leukaemia and Myelodysplastic SyndromeTranslocationNUP214 (9q34.13)DEK (6p22.3)
t(10;11)(p12;q23) AF10-MLL translocation in Acute LeukaemiaTranslocationMLLT10 (10p12.31)KMT2A (11q23.3)
t(10;11)(p13;q14) AF10-PICALM translocation in Acute LeukaemiaTranslocationMLLT10 (10p12.31)PICALM (11q14.2)
t(10;11) MLL-TET1 rearrangement in acute leukemiasTranslocationTET1 (10q21.3)KMT2A (11q23.3)

This is a highly selective list aiming to capture structural abnormalies which are frequesnt and/or significant in relation to diagnosis, prognosis, and/or characterising specific cancers. For a much more extensive list see the Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer.

Disclaimer: This site is for educational purposes only; it can not be used in diagnosis or treatment.

Cite this page: Cotterill SJ. Acute Myeloid Leukemia, Cancer Genetics Web: http://www.cancer-genetics.org/X1206.htm Accessed:

Creative Commons License
This page in Cancer Genetics Web by Simon Cotterill is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Note: content of abstracts copyright of respective publishers - seek permission where appropriate.

 [Home]    Page last revised: 29 August, 2019     Cancer Genetics Web, Established 1999