AML - Molecular Biology

Overview

Literature Analysis

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Tag cloud generated 10 March, 2017 using data from PubMed, MeSH and CancerIndex

Mutated Genes and Abnormal Protein Expression (207)

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 FLK2, STK1, CD135, FLK-2 -FLT3 and Acute Myeloid Leukaemia
1006
PML 15q22 MYL, RNF71, PP8675, TRIM19 -PML and Acute Myeloid Leukaemia
887
BCR 22q11.23 ALL, CML, PHL, BCR1, D22S11, D22S662 -BCR and Acute Myeloid Leukaemia
516
NPM1 5q35.1 B23, NPM -NPM1 and Acute Myeloid Leukaemia
496
CD34 1q32 -CD34 and Acute Myeloid Leukaemia
495
KITLG 12q22 SF, MGF, SCF, FPH2, FPHH, KL-1, Kitl, SHEP7 -KITLG and Acute Myeloid Leukaemia
407
CEBPA 19q13.1 CEBP, C/EBP-alpha -CEBPA and Acute Myeloid Leukaemia
343
KIT 4q12 PBT, SCFR, C-Kit, CD117 -KIT and Acute Myeloid Leukaemia
299
WT1 11p13 GUD, AWT1, WAGR, WT33, NPHS4, WIT-2, EWS-WT1 Overexpression
-WT1 and Acute Myeloid Leukaemia
243
CD33 19q13.41 p67, SIGLEC3, SIGLEC-3 -CD33 and Acute Myeloid Leukaemia
219
MLLT10 10p12 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
NRAS 1p13.2 NS6, CMNS, NCMS, ALPS4, N-ras, NRAS1 -NRAS and Acute Myeloid Leukaemia
183
IDH1 2q33.3 IDH, IDP, IDCD, IDPC, PICD, HEL-216, HEL-S-26 -IDH1 and Acute Myeloid Leukaemia
161
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
MYH11 16p13.11 AAT4, FAA4, SMHC, SMMHC Translocation
-t(16;16)(p13q22) CBFB-MYH11 Translocation in AML
-MYH11 and Acute Myeloid Leukaemia
142
RUNX1T1 8q22 CDR, ETO, MTG8, AML1T1, ZMYND2, CBFA2T1, AML1-MTG8 Translocation
- t(8;21)(q22;q22) in Acute Myeloid Leukemia
-RUNX1T1 and Acute Myeloid Leukaemia
126
RB1 13q14.2 RB, pRb, OSRC, pp110, p105-Rb, PPP1R130 -RB1 and Acute Leukaemias
125
GATA1 Xp11.23 GF1, GF-1, NFE1, XLTT, ERYF1, NF-E1, XLANP, XLTDA, GATA-1 -GATA1 and Acute Myeloid Leukaemia
121
TET2 4q24 MDS, KIAA1546 -TET2 and Acute Myeloid Leukaemia
120
DNMT3A 2p23 TBRS, DNMT3A2, M.HsaIIIA -DNMT3A and Acute Myeloid Leukaemia
110
HOXA9 7p15.2 HOX1, ABD-B, HOX1G, HOX1.7 Translocation
-t(7;11)(p15;p15) in Acute Myelogenous Leukaemia
-HOXA9 and Acute Myeloid Leukaemia
82
CD19 16p11.2 B4, CVID3 -CD19 and Acute Myeloid Leukaemia
101
IDH2 15q26.1 IDH, IDP, IDHM, IDPM, ICD-M, D2HGA2, mNADP-IDH -IDH2 and Acute Myeloid Leukaemia
100
NUP214 9q34.1 CAN, CAIN, N214, p250, D9S46E 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
57
CD14 5q31.1 -CD14 and Acute Myeloid Leukaemia
82
PICALM 11q14.2 LAP, CALM, CLTH Translocation
-t(10;11)(p13;q14) AF10-PICALM translocation in Acute Leukaemia
76
ETV6 12p13 TEL, THC5, TEL/ABL Translocation
-t(1;12)(q25;p13) in Leukaemia (AML & ALL)
-ETV6 and Acute Myeloid Leukaemia
54
CSF1R 5q32 FMS, CSFR, FIM2, HDLS, C-FMS, CD115, CSF-1R, M-CSF-R -CSF1R and Acute Myeloid Leukaemia
75
CSF3R 1p35-p34.3 CD114, GCSFR -CSF3R and Acute Myeloid Leukaemia
72
CD38 4p15 T10, ADPRC 1 -CD38 and Acute Myeloid Leukaemia
70
ASXL1 20q11 MDS, BOPS -ASXL1 and Acute Myeloid Leukaemia
63
ITGAM 16p11.2 CR3A, MO1A, CD11B, MAC-1, MAC1A, SLEB6 -ITGAM and Acute Myeloid Leukaemia
62
BAALC 8q22.3 -BAALC and Acute Myeloid Leukaemia
58
TERT 5p15.33 TP2, TRT, CMM9, EST2, TCS1, hTRT, DKCA2, DKCB4, hEST2, PFBMFT1 -TERT and Acute Myeloid Leukemia
57
DEK 6p22.3 D6S231E Translocation
-t(6;9)(p23;q34) DEK-NUP214 in Acute Myeloid Leukaemia and Myelodysplastic Syndrome
57
MPL 1p34 MPLV, TPOR, C-MPL, CD110, THCYT2 -MPL and Acute Myeloid Leukaemia
53
CBL 11q23.3 CBL2, NSLL, C-CBL, RNF55, FRA11B -CBL and Acute Myeloid Leukaemia
48
GALE 1p36-p35 SDR1E1 -GALE and Acute Myeloid Leukaemia
44
GATA2 3q21.3 DCML, IMD21, NFE1B, MONOMAC -GATA2 and Acute Myeloid Leukaemia
41
SET 9q34 2PP2A, IGAAD, TAF-I, I2PP2A, IPP2A2, PHAPII, TAF-IBETA Translocation
-t(9;9)(q34;q34) SET-NUP214 rearrangements in Acute Lyphoblastic Leukaemia
40
MN1 22q12.1 MGCR, MGCR1, MGCR1-PEN, dJ353E16.2 -MN1 and Acute Myeloid Leukaemia
40
MEIS1 2p14 -MEIS1 and Acute Myeloid Leukaemia
36
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
ELL 19p13.1 MEN, ELL1, PPP1R68, C19orf17 Translocation
-ELL and Acute Myeloid Leukaemia
-t(11;19)(q23;p13.1) MLL-ELL translocation in acute leukaemia
18
MLLT3 9p22 AF9, YEATS3 Translocation
-t(9;11) in Acute Myeloid Leukaemia
-MLLT3 and Acute Myeloid Leukaemia
30
RARS 5q35.1 HLD9, ArgRS, DALRD1 -RARS and Acute Myeloid Leukaemia
29
PTPN11 12q24 CFC, NS1, SHP2, BPTP3, PTP2C, PTP-1D, SH-PTP2, SH-PTP3 -PTPN11 and Acute Myeloid Leukaemia
29
EGR1 5q31.1 TIS8, AT225, G0S30, NGFI-A, ZNF225, KROX-24, ZIF-268 -EGR1 and Acute Myeloid Leukaemia
28
KAT6A 8p11 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
ABL2 1q25.2 ARG, ABLL Translocation
-t(1;12)(q25;p13) in Leukaemia (AML & ALL)
21
HOXA10 7p15.2 PL, HOX1, HOX1H, HOX1.8 -HOXA10 and Acute Myeloid Leukaemia
17
CDX2 13q12.3 CDX3, CDX-3, CDX2/AS -CDX2 and Acute Myeloid Leukaemia
16
PRAME 22q11.22 MAPE, OIP4, CT130, OIP-4 -PRAME and Acute Myeloid Leukaemia
16
TFAP2B 6p12 AP-2B, AP2-B -TFAP2B and Acute Myeloid Leukaemia
16
TFAP2A 6p24 AP-2, BOFS, AP2TF, TFAP2, AP-2alpha -TFAP2A and Acute Myeloid Leukaemia
16
TFAP2C 20q13.2 ERF1, TFAP2G, hAP-2g, AP2-GAMMA -TFAP2C and Acute Myeloid Leukaemia
16
NSD1 5q35 STO, KMT3B, SOTOS, ARA267, SOTOS1 -NSD1 and Acute Myeloid Leukaemia
15
PIM1 6p21.2 PIM -PIM1 and Acute Myeloid Leukaemia
14
BRD4 19p13.1 CAP, MCAP, HUNK1, HUNKI -BRD4 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
CRP 1q23.2 PTX1 -CRP and Acute Myeloid Leukaemia
13
CD36 7q11.2 FAT, GP4, GP3B, GPIV, CHDS7, PASIV, SCARB3, BDPLT10 -CD36 and Acute Myeloid Leukaemia
13
CHEK1 11q24.2 CHK1 -CHEK1 and Acute Myeloid Leukaemia
12
CBFA2T3 16q24 ETO2, MTG16, MTGR2, ZMYND4 -CBFA2T3 and Acute Myeloid Leukaemia
12
EPS15 1p32 AF1P, AF-1P, MLLT5 Translocation
-t(1;11)(p32;q23) MLL-EPS15 fusion in Acute Myelogeneous Leukemia
11
U2AF1 21q22.3 RN, FP793, U2AF35, U2AFBP, RNU2AF1 -U2AF1 and Acute Myeloid Leukaemia
11
RBM15 1p13 OTT, OTT1, SPEN -RBM15 and Acute Myeloid Leukaemia
11
BCOR Xp11.4 MAA2, ANOP2, MCOPS2 -BCOR and Acute Myeloid Leukaemia
10
SALL4 20q13.2 DRRS, HSAL4, ZNF797, dJ1112F19.1 -SALL4 and Acute Myeloid Leukaemia
10
SEPT6 Xq24 SEP2, SEPT2 -SEPT6 and Acute Myeloid Leukaemia
10
SRSF2 17q25.1 SC35, PR264, SC-35, SFRS2, SFRS2A, SRp30b -SRSF2 and Acute Myeloid Leukaemia
10
ELN 7q11.23 WS, WBS, SVAS -ELN and Acute Myeloid Leukaemia
10
ETS2 21q22.2 ETS2IT1 -ETS2 and Acute Myeloid Leukaemia
10
DOT1L 19p13.3 DOT1, KMT4 -DOT1L and Acute Myeloid Leukaemia
9
GALM 2p22.1 GLAT, IBD1, BLOCK25, HEL-S-63p -GALM and Acute Myeloid Leukaemia
9
HOXD13 2q31.1 BDE, SPD, BDSD, HOX4I -HOXD13 and Acute Myeloid Leukaemia
9
PRDM16 1p36.23-p33 MEL1, LVNC8, PFM13, CMD1LL -PRDM16 and Acute Myeloid Leukaemia
9
WARS 14q32.31 IFI53, IFP53, GAMMA-2 -WARS and Acute Myeloid Leukaemia
9
MLF1 3q25.1 -MLF1 and Acute Myeloid Leukaemia
9
ABCC1 16p13.1 MRP, ABCC, GS-X, MRP1, ABC29 -ABCC1 (MRP1) Deletion in AML with Inversion of Chromosome 16
8
CEBPB 20q13.1 TCF5, IL6DBP, NF-IL6, C/EBP-beta -CEBPB and Acute Myeloid Leukaemia
8
IL2RG Xq13.1 P64, CIDX, IMD4, CD132, SCIDX, IL-2RG, SCIDX1 -IL2RG and Acute Myeloid Leukaemia
8
PBX3 9q33.3 -PBX3 and Acute Myeloid Leukaemia
8
PAPPA 9q33.2 PAPA, DIPLA1, PAPP-A, PAPPA1, ASBABP2, IGFBP-4ase -PAPPA and Acute Myeloid Leukaemia
8
SEPT9 17q25 MSF, MSF1, NAPB, SINT1, PNUTL4, SeptD1, AF17q25 -SEPT9 and Acute Myeloid Leukaemia
7
HOXA5 7p15.2 HOX1, HOX1C, HOX1.3 -HOXA5 and Acute Myeloid Leukaemia
7
DDX10 11q22.3 HRH-J8 -DDX10 and Acute Myeloid Leukaemia
7
IL21R 16p11 NILR, CD360 -IL21R and Acute Myeloid Leukaemia
7
PHF6 Xq26.3 BFLS, BORJ, CENP-31 -PHF6 and Acute Myeloid Leukaemia
7
MLLT6 17q21 AF17 -MLLT6 and Acute Myeloid Leukaemia
7
MIR10A 17q21.32 MIRN10A, mir-10a, miRNA10A, hsa-mir-10a -miR-10a and Acute Myeloid Leukaemia
7
HOXB4 17q21.32 HOX2, HOX2F, HOX-2.6 -HOXB4 and Acute Myeloid Leukaemia
7
WT1-AS 11p13 WIT1, WIT-1, WT1AS, WT1-AS1 -WT1-AS and Acute Myeloid Leukaemia
7
ARHGAP26 5q31 GRAF, GRAF1, OPHN1L, OPHN1L1 -ARHGAP26 and Acute Myeloid Leukaemia
6
MLLT1 19p13.3 ENL, LTG19, YEATS1 -MLLT1 and Acute Myeloid Leukaemia
6
CDC25B 20p13 -CDC25B and Acute Myeloid Leukaemia
6
JAG1 20p12.1-p11.23 AGS, AHD, AWS, HJ1, CD339, JAGL1 -JAG1 and Acute Myeloid Leukaemia
6
MNX1 7q36 HB9, HLXB9, SCRA1, HOXHB9 -MNX1 and Acute Myeloid Leukaemia
6
RPN1 3q21.3 OST1, RBPH1 -RPN1 and Acute Myeloid Leukaemia
5
HOXA7 7p15.2 ANTP, HOX1, HOX1A, HOX1.1 -HOXA7 and Acute Myeloid Leukaemia
5
SFRP4 7p14.1 FRP-4, FRPHE, sFRP-4 -SFRP4 and Acute Myeloid Leukaemia
5
LARS 5q32 LRS, LEUS, LFIS, ILFS1, LARS1, LEURS, PIG44, RNTLS, HSPC192, hr025Cl -LARS and Acute Myeloid Leukaemia
5
CEBPE 14q11.2 CRP1, C/EBP-epsilon -CEBPE 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
SOCS2 12q CIS2, SSI2, Cish2, SSI-2, SOCS-2, STATI2 -SOCS2 and Acute Myeloid Leukaemia
5
GAB2 11q14.1 -GAB2 and Acute Myeloid Leukaemia
5
PIM2 Xp11.23 -PIM2 and Acute Myeloid Leukaemia
5
SFRP5 10q24.1 SARP3 -SFRP5 and Acute Myeloid Leukaemia
5
HOXA13 7p15.2 HOX1, HOX1J -HOXA13 and Acute Myeloid Leukaemia
4
TOP1 20q12-q13.1 TOPI Translocation
-t(11;20) (p15;q11) NUP98-TOP1 Fusion in AML
4
HAVCR2 5q33.3 TIM3, CD366, KIM-3, TIMD3, Tim-3, TIMD-3, HAVcr-2 -HAVCR2 and Acute Myeloid Leukaemia
4
MSI2 17q22 MSI2H -MSI2 and Acute Myeloid Leukaemia
4
GMPS 3q24 -GMPS and Acute Myeloid Leukaemia
4
CEBPD 8p11.2-p11.1 CELF, CRP3, C/EBP-delta, NF-IL6-beta -CEBPD and Acute Myeloid Leukaemia
4
CBFB 16q22.1 PEBP2B Translocation
-t(16;16)(p13q22) CBFB-MYH11 Translocation in AML
4
HOXA4 7p15.2 HOX1, HOX1D -HOXA4 and Acute Myeloid Leukaemia
4
ULBP2 6q25 N2DL2, RAET1H, NKG2DL2, ALCAN-alpha -ULBP2 and Acute Myeloid Leukaemia
4
ZRSR2 Xp22.1 URP, ZC3H22, U2AF1L2, U2AF1RS2, U2AF1-RS2 -ZRSR2 and Acute Myeloid Leukaemia
4
IRF8 16q24.1 ICSBP, IRF-8, ICSBP1, IMD32A, IMD32B, H-ICSBP -IRF8 and Acute Myeloid Leukaemia
4
SUV39H1 Xp11.23 MG44, KMT1A, SUV39H, H3-K9-HMTase 1 -SUV39H1 and Acute Myeloid Leukaemia
4
STAG2 Xq25 SA2, SA-2, SCC3B, bA517O1.1 -STAG2 and Acute Myeloid Leukaemia
4
RAD21 8q24 HR21, MCD1, NXP1, SCC1, CDLS4, hHR21, HRAD21 -RAD21 and Acute Myeloid Leukaemia
4
HOXB3 17q21.3 HOX2, HOX2G, Hox-2.7 -HOXB3 and Acute Myeloid Leukaemia
4
PLK2 5q12.1-q13.2 SNK, hSNK, hPlk2 -PLK2 and Acute Myeloid Leukaemia
4
MX1 21q22.3 MX, MxA, IFI78, IFI-78K -MX1 and Acute Myeloid Leukaemia
4
HCK 20q11-q12 JTK9, p59Hck, p61Hck -HCK and Acute Myeloid Leukaemia
4
BCL11B 14q32.2 ATL1, RIT1, CTIP2, CTIP-2, ZNF856B, ATL1-beta, ATL1-alpha, ATL1-delta, ATL1-gamma, hRIT1-alpha -BCL11B and Acute Myeloid Leukaemia
4
TET1 10q21 LCX, CXXC6, bA119F7.1 Translocation
-t(10;11) MLL-TET1 rearrangement in acute leukemias
4
SEPT5 22q11.21 H5, CDCREL, PNUTL1, CDCREL1, CDCREL-1, HCDCREL-1 -SEPT5 and Acute Myeloid Leukaemia
3
FUT4 11q21 LeX, CD15, ELFT, FCT3A, FUTIV, SSEA-1, FUC-TIV -FUT4 and Acute Myeloid Leukaemia
3
HOXC11 12q13.3 HOX3H -HOXC11 and Acute Myeloid Leukaemia
3
FLNA Xq28 FLN, FMD, MNS, OPD, ABPX, CSBS, CVD1, FLN1, NHBP, OPD1, OPD2, XLVD, XMVD, FLN-A, ABP-280 -FLNA and Acute Myeloid Leukaemia
3
IL23R 1p31.3 -IL23R and Acute Myeloid Leukaemia
3
GNL3 3p21.1 NS, E2IG3, NNP47, C77032 -GNL3 and Acute Myeloid Leukaemia
3
ELF4 Xq26 MEF, ELFR -ELF4 and Acute Myeloid Leukaemia
3
HOXC13 12q13.3 HOX3, ECTD9, HOX3G -HOXC13 and Acute Myeloid Leukaemia
3
MYH9 22q13.1 MHA, FTNS, EPSTS, BDPLT6, DFNA17, NMMHCA, NMHC-II-A, NMMHC-IIA -MYH9 and Acute Myeloid Leukaemia
3
GUSB 7q21.11 BG, MPS7 -GUSB and Acute Myeloid Leukaemia
3
SMAD5 5q31 DWFC, JV5-1, MADH5 -SMAD5 and Acute Myeloid Leukaemia
3
KLF5 13q22.1 CKLF, IKLF, BTEB2 -KLF5 and Acute Myeloid Leukaemia
3
GAS6 13q34 AXSF, AXLLG -GAS6 and Acute Myeloid Leukaemia
3
HOXA11 7p15.2 HOX1, HOX1I -HOXA11 and Acute Myeloid Leukaemia
3
TXNIP 1q21.1 THIF, VDUP1, HHCPA78, EST01027 -TXNIP and Acute Myeloid Leukaemia
3
SBDS 7q11.21 SDS, SWDS, CGI-97 -SBDS and Acute Myeloid Leukaemia
3
CD200 3q13.2 MRC, MOX1, MOX2, OX-2 -CD200 and Acute Myeloid Leukaemia
3
GLIPR1 12q21.2 GLIPR, RTVP1, CRISP7 -GLIPR1 and Acute Myeloid Leukaemia
3
CCDC26 8q24.21 RAM -CCDC26 and Acute Myeloid Leukaemia
3
PAWR 12q21 PAR4, Par-4 -PAWR and Acute Myeloid Leukaemia
2
MERTK 2q14.1 MER, RP38, c-Eyk, c-mer, Tyro12 -MERTK and Acute Myeloid Leukaemia
2
MBL2 10q11.2 MBL, MBP, MBP1, MBPD, MBL2D, MBP-C, COLEC1, HSMBPC -MBL2 and Acute Myeloid Leukaemia
2
DLEU2 13q14.3 1B4, DLB2, LEU2, BCMSUN, RFP2OS, MIR15AHG, TRIM13OS, LINC00022, NCRNA00022 -DLEU2 and Acute Myeloid Leukaemia
2
CD48 1q21.3-q22 BCM1, BLAST, hCD48, mCD48, BLAST1, SLAMF2, MEM-102 -CD48 and Acute Myeloid Leukaemia
2
TYRO3 15q15 BYK, Dtk, RSE, Rek, Sky, Tif, Etk-2 -TYRO3 and Acute Myeloid Leukaemia
2
CXCL11 4q21.2 IP9, H174, IP-9, b-R1, I-TAC, SCYB11, SCYB9B -CXCL11 and Acute Myeloid Leukaemia
2
HMMR 5q34 CD168, IHABP, RHAMM -HMMR and Acute Myeloid Leukaemia
2
POLI 18q21.1 RAD30B, RAD3OB -POLI and Acute Myeloid Leukaemia
2
KDM4C 9p24.1 GASC1, JHDM3C, JMJD2C, TDRD14C -KDM4C and Acute Myeloid Leukaemia
2
PSIP1 9p22.3 p52, p75, PAIP, DFS70, LEDGF, PSIP2 -PSIP1 and Acute Myeloid Leukaemia
2
IGK 2p12 IGK@ -IGK and Acute Myeloid Leukaemia
2
TLE1 9q21.32 ESG, ESG1, GRG1 -TLE1 and Acute Myeloid Leukaemia
2
HLA-DRA 6p21.3 MLRW, HLA-DRA1 -HLA-DRA and Acute Myeloid Leukaemia
2
MUC3A 7q22 MUC3, MUC-3A -MUC3A and Acute Myeloid Leukaemia
2
HHEX 10q23.33 HEX, PRH, HMPH, PRHX, HOX11L-PEN -HHEX and Acute Myeloid Leukaemia
2
TPMT 6p22.3 -TPMT and Acute Myeloid Leukaemia
2
LAMP1 13q34 LAMPA, CD107a, LGP120 -LAMP1 and Acute Myeloid Leukaemia
2
HLA-DQB1 6p21.3 IDDM1, CELIAC1, HLA-DQB -HLA-DQB1 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
PDCD1LG2 9p24.2 B7DC, Btdc, PDL2, CD273, PD-L2, PDCD1L2, bA574F11.2 -PDCD1LG2 and Acute Myeloid Leukaemia
2
ESPL1 12q ESP1, SEPA -ESPL1 and Acute Myeloid Leukaemia
2
IRF2 4q34.1-q35.1 IRF-2 -IRF2 and Acute Myeloid Leukaemia
2
BLNK 10q23.2-q23.33 bca, AGM4, BASH, LY57, SLP65, BLNK-S, SLP-65 -BLNK and Acute Myeloid Leukaemia
2
CNTRL 9q33.2 FAN, CEP1, CEP110, bA165P4.1 -CNTRL and Acute Myeloid Leukaemia
2
ABI2 2q33 ABI-2, ABI2B, AIP-1, AblBP3, argBP1, SSH3BP2, argBPIA, argBPIB -ABI2 and Acute Myeloid Leukaemia
1
DNM2 19p13.2 DYN2, CMT2M, DYNII, LCCS5, CMTDI1, CMTDIB, DI-CMTB -DNM2 and Acute Myeloid Leukaemia
1
SFPQ 1p34.3 PSF, POMP100, PPP1R140 -SFPQ and Acute Myeloid Leukaemia
1
SH3GL1 19p13.3 EEN, CNSA1, SH3P8, SH3D2B -SH3GL1 and Acute Myeloid Leukaemia
1
LRRC3B 3p24 LRP15 -LRRC3B and Acute Myeloid Leukaemia
1
HSP90AB1 6p12 HSP84, HSPC2, HSPCB, D6S182, HSP90B -HSP90AB1 and Acute Myeloid Leukaemia
1
PDCD7 15q22.31 ES18, HES18 -PDCD7 and Acute Myeloid Leukaemia
1
CTDSPL 3p21.3 PSR1, SCP3, HYA22, RBSP3, C3orf8 -CTDSPL and Acute Myeloid Leukaemia
1
HLA-DQA1 6p21.3 CD, GSE, DQ-A1, CELIAC1, HLA-DQA -HLA-DQA1 and Acute Myeloid Leukaemia
1
PNN 14q21.1 DRS, DRSP, SDK3, memA -PNN and Acute Myeloid Leukaemia
1
HSP90AA1 14q32.33 EL52, HSPN, LAP2, HSP86, HSPC1, HSPCA, Hsp89, Hsp90, LAP-2, HSP89A, HSP90A, HSP90N, HSPCAL1, HSPCAL4 -HSP90AA1 and Acute Myeloid Leukaemia
1
BRD3 9q34 ORFX, RING3L -BRD3 and Acute Myeloid Leukaemia
1
RMI1 9q21.32 BLAP75, FAAP75, C9orf76 -RMI1 and Acute Myeloid Leukaemia
1
DOK2 8p21.3 p56DOK, p56dok-2 -DOK2 and Acute Myeloid Leukaemia
1
PRTN3 19p13.3 MBN, MBT, NP4, P29, PR3, ACPA, AGP7, NP-4, PR-3, CANCA, C-ANCA -PRTN3 and Acute Myeloid Leukaemia
1
ST2 11p14.3-p12 -ST2 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 12p12 NP, CIZ, NMP4, CAGH1, ERDA2, TNRC1, CAGH1A -ZNF384 and Acute Myeloid Leukaemia
1
CBLB 3q13.11 Cbl-b, RNF56, Nbla00127 -CBLB and Acute Myeloid Leukaemia
1
NACA 12q23-q24.1 HSD48, NACA1, skNAC -NACA and Acute Myeloid Leukaemia
1
IL1RL1 2q12 T1, ST2, DER4, ST2L, ST2V, FIT-1, IL33R -IL1RL1 and Acute Myeloid Leukaemia
1
ACSL6 5q31.1 ACS2, FACL6, LACS2, LACS5, LACS 6 -ACSL6 and Acute Myeloid Leukaemia
1
FGFR1OP 6q27 FOP -FGFR1OP and Acute Myeloid Leukaemia
1
DTX2P1-UPK3B 7q11.23 PMSR6, PMS2L11, PMS2P11 -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
MLLT4 6q27 AF6 Translocation
-t(6;11)(q27;q23) in Acute Myeloid Leukemia
MLLT11 1q21 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, PRDM3, MDS1-EVI1, AML1-EVI-1 Translocation
-t(3;21)(q26;q22) in Secondary Leukaemia / MDS
RARA 17q21 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 21q22.3 p55, erg-3 Translocation
-t(16;21)(p11;q22) in Leukemia (ANLL)
-t(16;21)(p11;q22) FUS-ERG in Acute Myelogenous Leukemia
RUNX1 21q22.3 AML1, CBFA2, EVI-1, AMLCR1, PEBP2aB, AML1-EVI-1 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

Konuma T, Kondo T, Yamashita T, et al.
Outcome of allogeneic hematopoietic stem cell transplantation in adult patients with acute myeloid leukemia harboring trisomy 8.
Ann Hematol. 2017; 96(3):469-478 [PubMed] Related Publications
Trisomy 8 (+8) is one of the most common cytogenetic abnormalities in adult patients with acute myeloid leukemia (AML). However, the outcome of allogeneic hematopoietic stem cell transplantation (HSCT) in adult patients with AML harboring +8 remains unclear. To evaluate, the outcome and prognostic factors in patients with AML harboring +8 as the only chromosomal abnormality or in association with other abnormalities, we retrospectively analyzed the Japanese registration data of 631 adult patients with AML harboring +8 treated with allogeneic HSCT between 1990 and 2013. In total, 388 (61%) patients were not in remission at the time of HSCT. With a median follow-up of 38.5 months, the probability of overall survival and the cumulative incidence of relapse at 3 years were 40 and 34%, respectively. In the multivariate analysis, two or more additional cytogenetic abnormalities and not being in remission at the time of HSCT were significantly associated with a higher overall mortality and relapse. Nevertheless, no significant impact on the outcome was observed in cases with one cytogenetic abnormality in addition to +8. Although more than 60% of the patients received HSCT when not in remission, allogeneic HSCT offered a curative option for adult patients with AML harboring +8.

Ebrahim EK, Assem MM, Amin AI, et al.
FLT3 Internal Tandem Duplication Mutation, cMPL and CD34 Expressions Predict Low Survival in Acute Myeloid Leukemia Patients.
Ann Clin Lab Sci. 2016; 46(6):592-600 [PubMed] Related Publications
OBJECTIVES: To detect FMS-like tyrosine kinase-3 internal tandem duplicate (FLT3 ITD) mutation, Myeloproliferative leukemia virus oncogene (cMPL) and Ephrin A 4 receptor (EphA4) expressions in Acute myeloid leukemia (AML) and their correlation to patient's clinicopathological characteristics and survival.
METHODS: RNA was extracted from blood samples of 58 AML patients (39 adults and 19 children) and 20 age and sex matched controls. FLT3 ITD mutation, cMPL and EphA4 expression was studied using RT-PCR and correlated to the clinical and survival data of the patients.
RESULTS: FLT3 ITD mutation, cMPL and EphA4 expression was positive in 35.9%, 76.9% and 56.4% of adult AML patients respectively and in 15.8%, 47.4% and 36.8% of pediatric AML patients respectively. 76.9% of adult and 89.5% of pediatric patients expressed CD33. 64.1 % of adults and 42.1% of children expressed CD34. CD34 expression was significantly associated with both FLT3 ITD mutation and cMPL expression. CD34, FLT3 and cMPL negative cases have significantly higher overall survival than positive cases.
CONCLUSION: CD34 expression is significantly associated with both FLT3 ITD mutation and cMPL expression which could be used as a marker for low survival. Normal FLT3 and negative expression of CD34 and cMPL may predict a longer overall survival. Further studies are needed to investigate the mechanism that may correlate CD34 to both markers.

Shi J, Fu H, Jia Z, et al.
High Expression of CPT1A Predicts Adverse Outcomes: A Potential Therapeutic Target for Acute Myeloid Leukemia.
EBioMedicine. 2016; 14:55-64 [PubMed] Free Access to Full Article Related Publications
Carnitine palmitoyl transferase 1A (CPT1A) protein catalyzes the rate-limiting step of Fatty-acid oxidation (FAO) pathway, which can promote cell proliferation and suppress apoptosis. Targeting CPT1A has shown remarkable anti-leukemia activity. But, its prognostic value remains unclear in Acute Myeloid Leukemia (AML). In two independent cohorts of cytogenetically normal AML (CN-AML) patients, compared to low expression of CPT1A (CPT1A(low)), high expression of CPT1A (CPT1A(high)) was significantly associated with adverse outcomes, which was also shown in European Leukemia Network (ELN) Intermediate-I category. Multivariable analyses adjusting for known factors confirmed CPT1A(high) as a high risk factor. Significant associations between CPT1A(high) and adverse outcomes were further validated whether for all AML patients (OS: P=0.008; EFS: P=0.002, n=334, no M3) or for National Comprehensive Cancer Network (NCCN) Intermediate-Risk subgroup (OS: P=0.021, EFS: P=0.024, n=173). Multiple omics analysis revealed aberrant alterations of genomics and epigenetics were significantly associated with CPT1A expression, including up- and down-regulation of oncogenes and tumor suppressor, activation and inhibition of leukemic (AML, CML) and immune activation pathways, hypermethylation enrichments on CpG island and gene promoter regions. Combined with the previously reported anti-leukemia activity of CPT1A's inhibitor, our results proved CPT1A as a potential prognosticator and therapeutic target for AML.

Inamura J, Ikuta K, Tsukada N, et al.
Acute Promyelocytic Leukemia with i(17)(q10).
Intern Med. 2016; 55(22):3341-3345 [PubMed] Free Access to Full Article Related Publications
We herein report a rare chromosomal abnormality observed in an acute promyelocytic leukemia (APL) patient. She had several APL derivative clones including a clone with i(17)(q10) abnormality, which consists of two kinds of structural abnormalities, a cryptic translocation of t(15;17) and an isochromosome of 17q. Although an obvious microscopic t(15;17) change was not observed on either arms of the isochromosome, PML/RARα fusion signals were detected on an interphase fluorescence in situ hybridization analysis. By several cytogenetic analyses of her bone marrow cells, it was confirmed that the i(17)(q10) clone was derived from the classic t(15;17) clone via another intervening clone, cryptic t(15;17).

Lee JS, Cheong HS, Koh Y, et al.
MCM7 polymorphisms associated with the AML relapse and overall survival.
Ann Hematol. 2017; 96(1):93-98 [PubMed] Related Publications
The minichromosome maintenance complex component 7 (MCM7) encodes a member of MCM complex, which plays a critical role in the initiation of gene replication. Due to the importance of MCM complex, MCM7 gene has been regarded as a candidate gene for cancer development. In the present study, seven MCM7 polymorphisms were genotyped in 344 subjects composed of 103 acute myeloid leukemia (AML) patients and 241 normal controls to examine the possible associations between MCM7 polymorphisms and the risk of AML. MCM7 polymorphisms were not associated with the risk of AML (P > 0.05). However, MCM7 polymorphisms were significantly related to the relapse of AML and overall survival. The rs2070215 (N144S) showed a protective effect to the risk of AML relapse (OR = 0.37; P (corr) = 0.02). In haplotype analyses, the ht1 and ht2 showed significant associations with the risk of AML relapse (P (corr) = 0.02-0.03). In addition, rs1534309 showed an association with the overall survival of AML patients. Patients with major homozygote genotype (CC) of rs1534309 showed a higher survival rate than the patients with other genotypes (CG and GG). The results of the present study indicate that MCM7 polymorphisms may be able to predict the prognosis of AML patients.

Juncà J, Garcia O, Garcia-Caro M, et al.
CD34 expression and the outcome of nucleophosmin 1-mutated acute myeloid leukemia.
Ann Hematol. 2016; 95(12):1949-1954 [PubMed] Related Publications
CD34 positivity has been considered as an adverse prognostic factor in acute myeloid leukemia (AML). Although nucleophosmin 1-mutated (NPM1m) AML is usually CD34 negative, this marker may be expressed at diagnosis or acquired at relapse in a variable number of cases. Our objective was to ascertain if CD34 expression has any influence on the general outcome of this form of acute leukemia. Analysis of clinical outcome (complete remissions, relapses, disease-free survival, and overall survival) was performed depending on the degree of expression of CD34 determined by flow cytometry, in 67 adult patients with NPM1m AML. CD34 expression did not have any influence on the variables analyzed whatever the percentage of blasts expressing this marker. In contrast to other forms of AML, CD34 expression is not an unfavorable prognostic factor in NPM1m AML, neither at diagnosis nor at relapse.

Kumsaen P, Fucharoen G, Sirijerachai C, et al.
FLT3-ITD Mutations in Acute Myeloid Leukemia Patients in Northeast Thailand.
Asian Pac J Cancer Prev. 2016; 17(9):4395-4399 [PubMed] Related Publications
The FLT3-ITD mutation is one of the most frequent genetic abnormalities in acute myeloid leukemia (AML) where it is associated with a poor prognosis. The FLT3-ITD mutation could, therefore, be a potential molecular prognostic marker important for risk-stratified treatment options. We amplified the FLT3 gene at exon 14 and 15 in 52 AML patients (aged between 2 months and 74 years) from 4 referral centers (a university hospital and 3 regional hospitals in Northeast Thailand), using a simple PCR method. FLT3-ITD mutations were found in 10 patients (19.2%), being more common in adults than in children (21.1% vs. 14.3%) and more prevalent in patients with acute promyelocytic leukemia (AML-M3) than AML-non M3 (4 of 10 AML-M3 vs. 6 of 42 AML- non M3 patients). Duplication sequences varied in size-between 27 and 171 nucleotides (median=63.5) and in their location. FLT3-ITD mutations with common duplication sequences accounted for a significant percentage in AML patients in northeastern Thailand. This simple PCR method is feasible for routine laboratory practice and these data could help tailor use of the national protocol for AML.

Allahyari A, Sadeghi M, Ayatollahi H, et al.
Frequency of FLT3 (ITD, D835) Gene Mutations in Acute Myelogenous Leukemia: a Report from Northeastern Iran.
Asian Pac J Cancer Prev. 2016; 17(9):4319-4322 [PubMed] Related Publications
BACKGROUND: FLT3 is mutated in about 1/3 of acute myelogenous leukemia (AML) patients. The aim of the present study was to report the prevalence of FLT3 mutations and comparison with prognostic factors in AML patients in the Northeastern of Iran.
MATERIALS AND METHODS: This cross-sectional study concerned 100 AML cases diagnosed based on bone marrow aspiration and peripheral blood. DNA for every AML patient was extracted and underwent PCR with FLT3-ITD primers.
RESULTS: The mean age at diagnosis was 28.5 years (range, 1-66 years), 52 patients (52%) being male. Out of 100 AML patients, 21 (21%) had FLT3 mutation, (17 with FLT3- ITD, 81%, and 4 with FLT3-D825, 19%). Of the 21, 14 (66.7%) had heterozygous mutation. There was no significant difference between age, sex and organomegaly between patients with FLT3 mutation versus FLT3 wild-type.
CONCLUSIONS: Our frequency of FLT3 is in line with earlier fidnings of approximately 20 to 30% and also the prevalence of FLT3-ITD is more than FLT3-D35 mutation. There was no significant difference between prognostic factors (age and sex) in the patients with FLT3 mutation versus FLT3 wild-type. The prevalence of FLT3 heterozygous mutations is more that homozygous mutations in AML patients.

Yang F, Gong Q, Shi W, et al.
Aberrant DNA methylation of acute myeloid leukemia and colorectal cancer in a Chinese pedigree with a MLL3 germline mutation.
Tumour Biol. 2016; 37(9):12609-12618 [PubMed] Related Publications
Unlike genetic aberrations, epigenetic alterations do not modify the deoxyribonucleic acid (DNA) coding sequence and can be reversed pharmacologically. Identifying a particular epigenetic alteration such as abnormal DNA methylation may provide better understanding of cancers and improve current therapy. In a Chinese pedigree with colorectal carcinoma and acute myeloid leukemia, we examined the genome-wide DNA methylation level of cases and explored the role of methylation in pathogenesis and progression. DNA methylation status in the four cases, which all harbor a MLL3 germline mutation, differed from that of the normal control, and hypermethylation was more prevalent. Also, more CpG sites were hypermethylated in the acute-phase AML patient than in the AML patient in remission. Fifty-nine hyper- or hypomethylated genes were identified as common to all four cases. Genome-wide DNA methylation analysis demonstrated that differentially methylated sites among acute myeloid leukemia and colorectal carcinoma cases and the control were in both promoters (CpG island) and gene body regions (shelf/shore areas). Hypermethylation was more prevalent in cancer cases. The study supports the suggestion that the level of DNA methylation changes in AML progression.

Hemmati PG, Vuong LG, Terwey TH, et al.
Predictive significance of the European LeukemiaNet classification of genetic aberrations in patients with acute myeloid leukaemia undergoing allogeneic stem cell transplantation.
Eur J Haematol. 2017; 98(2):160-168 [PubMed] Related Publications
OBJECTIVES: The purpose of this study was to evaluate the predictive capacity of the European LeukemiaNet (ELN) classification of genetic risk in patients with acute myeloid leukaemia (AML) undergoing allogeneic stem cell transplantation (alloSCT).
METHODS: We retrospectively analysed 274 patients transplanted at our centre between 2004 and 2014.
RESULTS: The ELN grouping is comparable to the Southwest Oncology Group/Eastern Cooperative Oncology Group (SWOG/ECOG) stratification in predicting the outcome after alloSCT [overall P = 0.0064 for disease-free survival (DFS), overall P = 0.003 for relapse]. Patients with an intermediate-1 profile have a significantly elevated 5-yr relapse incidence as compared to favourable risk patients, that is 40% vs. 15%, [hazard ratio (HR) 2.58, P = 0.048]. An intermediate-1 risk profile is an independent predictor for relapse as determined by multivariate Cox regression analysis (HR 3.05, P = 0.023). In intermediate-1 patients, the presence of an FLT3 internal tandem duplication (FLT3-ITD) is associated with a significantly increased relapse incidence (P = 0.0323), and a lower DFS (P = 0.0465). FLT3-ITD is an independent predictor for overall survival, DFS and relapse incidence in the intermediate-1 subgroup.
CONCLUSIONS: The ELN stratification of genetic risk predicts the outcome of patients with AML undergoing alloSCT. Patients with an intermediate-1 profile have a high risk for treatment failure due to relapse, which prompts the development of alternative treatment strategies.

Wang X, Zuo D, Yuan Y, et al.
MicroRNA-183 promotes cell proliferation via regulating programmed cell death 6 in pediatric acute myeloid leukemia.
J Cancer Res Clin Oncol. 2017; 143(1):169-180 [PubMed] Related Publications
PURPOSE: The aim of this study was to investigate roles of microRNA (miR)-183 in pediatric acute myeloid leukemia (AML).
METHODS: miR-183 expression in bone marrow and patients' sera of childhood AML was detected by real-time quantitative PCR. Functions of miR-183 in malignant phenotypes of two leukemia cell lines were then evaluated. Additionally, putative targets of miR-183 were predicted using three miRNA target prediction algorithms and validated by luciferase reporter assay. Clinical relevance of miR-183 and its target gene were further determined.
RESULTS: miR-183 expression in bone marrow and patients' sera of childhood AML was both significantly higher than those in the corresponding normal controls (both P < 0.001). Enforced expression of miR-183 dramatically enhanced cell proliferation and G1/S transition, but inhibited cell apoptosis of leukemia cells. Bioinformatics prediction and luciferase reporter assay identified programmed cell death 6 (PDCD6) as a direct target gene of miR-183. Moreover, high serum miR-183 combined with low serum PDCD6 mRNA was significantly associated with French-American-British classification subtype M7 (P = 0.01) and unfavorable karyotypes (P = 0.006). Further multivariate analysis identified the combination of serum miR-183 and PDCD6 levels as an independent prognostic factor for both relapse-free and overall survivals. Functionally, re-introduction of PDCD6 markedly reversed the effects of miR-183 in cell cycle, proliferation and apoptosis of two leukemia cell lines.
CONCLUSION: Combined serum miR-183 and PDCD6 mRNA may serve as a novel prognostic biomarker for pediatric AML. Interestingly, miR-183 may function as an oncogene and may enhance cell proliferation by targeting PDCD6, implying a potential therapeutic target for this malignancy.

Latif AL, Holyoake TL
Lifting the Differentiation Embargo.
Cell. 2016; 167(1):45-6 [PubMed] Related Publications
Effective differentiation therapy for acute myeloid leukemia (AML) has been restricted to a small subset of patients with one defined genetic abnormality. Using an unbiased small molecule screen, Sykes et al. now identify a mechanism of de-repression of differentiation in several models of AML driven by distinct genetic drivers.

Akhter A, Mughal MK, Elyamany G, et al.
Multiplexed automated digital quantification of fusion transcripts: comparative study with fluorescent in-situ hybridization (FISH) technique in acute leukemia patients.
Diagn Pathol. 2016; 11(1):89 [PubMed] Free Access to Full Article Related Publications
BACKGROUND: The World Health Organization (WHO) classification system defines recurrent chromosomal translocations as the sole diagnostic and prognostic criteria for acute leukemia (AL). These fusion transcripts are pivotal in the pathogenesis of AL. Clinical laboratories universally employ conventional karyotype/FISH to detect these chromosomal translocations, which is complex, labour intensive and lacks multiplexing capacity. Hence, it is imperative to explore and evaluate some newer automated, cost-efficient multiplexed technologies to accommodate the expanding genetic landscape in AL.
METHODS: "nCounter® Leukemia fusion gene expression assay" by NanoString was employed to detect various fusion transcripts in a large set samples (n = 94) utilizing RNA from formalin fixed paraffin embedded (FFPE) diagnostic bone marrow biopsy specimens. This series included AL patients with various recurrent translocations (n = 49), normal karyotype (n = 19), or complex karyotype (n = 21), as well as normal bone marrow samples (n = 5). Fusion gene expression data were compared with results obtained by conventional karyotype and FISH technology to determine sensitivity/specificity, as well as positive /negative predictive values.
RESULTS: Junction probes for PML/RARA; RUNX1-RUNX1T1; BCR/ABL1 showed 100 % sensitivity/specificity. A high degree of correlation was noted for MLL/AF4 (85 sensitivity/100 specificity) and TCF3-PBX1 (75 % sensitivity/100 % specificity) probes. CBFB-MYH11 fusion probes showed moderate sensitivity (57 %) but high specificity (100 %). ETV6/RUNX1 displayed discordance between fusion transcript assay and FISH results as well as rare non-specific binding in AL samples with normal or complex cytogenetics.
CONCLUSIONS: Our study presents preliminary data with high correlation between fusion transcript detection by a throughput automated multiplexed platform, compared to conventional karyotype/FISH technique for detection of chromosomal translocations in AL patients. Our preliminary observations, mandates further vast validation studies to explore automated molecular platforms in diagnostic pathology.

Baljevic M, Dumitriu B, Lee JW, et al.
Telomere Length Recovery: A Strong Predictor of Overall Survival in Acute Promyelocytic Leukemia.
Acta Haematol. 2016; 136(4):210-218 [PubMed] Article available free on PMC after 16/09/2017 Related Publications
Telomeres are the capping ends of chromosomes that protect the loss of genetic material and prevent chromosomal instability. In human tissue-specific stem/progenitor cells, telomere length (TL) is maintained by the telomerase complex, which consists of a reverse transcriptase catalytic subunit (TERT) and an RNA template (TERC). Very short telomeres and loss-of-function mutations in the TERT and TERC genes have been reported in acute myeloid leukemia, but the role of telomeres in acute promyelocytic leukemia (APL) has not been well established. We report the results for a large cohort of 187 PML/RARα-positive APL patients. No germline mutations in the TERT or TERC genes were identified. Codon 279 and 1062 TERT polymorphisms were present at a frequency similar to that in the general population. TL measured in blood or marrow mononuclear cells at diagnosis was significantly shorter in the APL patients than in healthy volunteers, and shorter telomeres at diagnosis were significantly associated with high-risk disease. For patients who achieved complete remission, the median increase in TL from diagnosis to remission (delta TL) was 2.0 kilobase (kb), and we found delta TL to be the most powerful predictor of overall survival when compared with well-established risk factors for poor outcomes in APL.

Endo A, Tomizawa D, Aoki Y, et al.
EWSR1/ELF5 induces acute myeloid leukemia by inhibiting p53/p21 pathway.
Cancer Sci. 2016; 107(12):1745-1754 [PubMed] Article available free on PMC after 16/09/2017 Related Publications
The Ewing sarcoma breakpoint region 1 (EWSR1) gene is known to fuse with various partner genes to promote the development of the Ewing sarcoma family of tumors and other sarcomas. In contrast, the association of EWSR1 chimeric fusion genes with leukemia has rarely been reported. We identified a novel EWSR1-associated chimeric fusion gene in a patient with acute myeloid leukemia harboring 46, XY, t (11; 22) (p13; q12) karyotype abnormality. The patient was refractory to intensified chemotherapy including hematopoietic stem cell transplantation. Total RNA paired-end sequencing identified a novel chimeric fusion gene as EWSR1/ELF5, a member of the E26 transformation-specific transcription factor family. Transduction of EWSR1/ELF5 to NIH3T3 cells induced transformation by attenuating with the p53/p21-dependent pathway. The injection of EWSR1/ELF5-transduced NIH3T3 cells into NSG-SCID mice systematically induced the development of tumors in vivo. These results revealed the oncogenic potency of EWSR1/ELF5.

Abdelhamid E, Besbes S, Renneville A, et al.
Minimal Residual Disease assessment of IDH1/2 mutations in Acute Myeloid Leukemia by LNA-RQ-PCR.
Tunis Med. 2016; 94(3):190-7 [PubMed] Related Publications
BACKGROUND: With the growing importance of minimal residual disease (MRD) monitoring and the recent discover of IDH mutations in acute myeloid leukemia (AML), the quantification of this molecular marker provides the possibility to monitor the disease progression and the therapy efficacy.
OBJECTIVE: The aim of this study is to assess the MRD in AML for the first time with IDH1 and IDH2 gene mutations in 15 AML patients.
METHODS: We have screened R132 IDH1, R140 IDH2 and R172 IDH2 mutations by PCR amplification and direct sequencing and we have quantified them for the first time by RQ-PCR using reverse primers modified by an LNA. A good sensitivity has been obtained. MRD rates obtained by LNA-RQ-PCR were used to draw kinetics of the disease evolution during the follow-up.
RESULTS: IDH1/2 Results were compared to NPM1 mutation and WT1 over expression and have showed coherent kinetic between MRD rates in 7/11 cases. For the rest, the direct sequencing and the high resolution melting (HRM) assay have confirmed the quantification Results in diagnosis but not in residual samples.
CONCLUSION: Some optimization will be necessary to improve the mutated allele amplification. The LNA-RQ-PCR might be an easy and less cost method used in a small laboratory for myeloid leukemia MRD assessment using IDH1/2 mutations.

Medinger M, Lengerke C, Passweg J
Novel Prognostic and Therapeutic Mutations in Acute Myeloid Leukemia.
Cancer Genomics Proteomics. 2016 09-10; 13(5):317-29 [PubMed] Article available free on PMC after 16/09/2017 Related Publications
Acute myeloid leukemia (AML) is a biologically complex and molecularly and clinically heterogeneous disease, and its incidence increases with age. Cytogenetics and mutation testing remain important prognostic tools for treatment after induction therapy. The post-induction treatment is dependent on risk stratification. Despite rapid advances in determination of gene mutations involved in the pathophysiology and biology of AML, and the rapid development of new drugs, treatment improvements changed slowly over the past 30 years, with the majority of patients eventually experiencing relapse and dying of their disease. Allogenic hematopoietic stem cell transplantation remains the best chance of cure for patients with intermediate- or high-risk disease. This review gives an overview about advances in prognostic markers and novel treatment options for AML, focusing on new prognostic and probably therapeutic mutations, and novel drug therapies such as tyrosine kinase inhibitors.

Yoshida K
Genetic abnormalities associated with the relapse of childhood leukemia.
Rinsho Ketsueki. 2016; 57(7):919-24 [PubMed] Related Publications
Acute leukemia, especially acute lymphoblastic leukemia, is the most common tumor in childhood. Survival in pediatric acute leukemia cases has improved significantly, but once a relapse occurs, the long-term survival rates decrease markedly. Recently, SNP array and next-generation sequencing have revealed the relapse mechanism of pediatric leukemia and genetic alterations which drive leukemia recurrence.

Grassilli S, Nika E, Lambertini E, et al.
A network including PU.1, Vav1 and miR-142-3p sustains ATRA-induced differentiation of acute promyelocytic leukemia cells - a short report.
Cell Oncol (Dordr). 2016; 39(5):483-489 [PubMed] Related Publications
PURPOSE: Reduced expression of miR-142-3p has been found to be associated with the development of various subtypes of myeloid leukemia, including acute promyelocytic leukemia (APL). In APL-derived cells, miR-142-3p expression can be restored by all-trans retinoic acid (ATRA), which induces the completion of their maturation program. Here, we aimed to assess whether PU.1, essential for ATRA-induced gene transcription, regulates the expression of miR-142-3p in APL-derived cells and, based on the established cooperation between PU.1 and Vav1 in modulating gene expression, to evaluate the role of Vav1 in restoring the expression of miR-142-3p.
METHODS: ATRA-induced increases in PU.1 and Vav1 expression in APL-derived NB4 cells were counteracted with specific siRNAs, and the expression of miR-142-3p was measured by quantitative real-time PCR (qRT-PCR). The recruitment of PU.1 and/or Vav1 to the regulatory region of miR-142 was assessed by quantitative chromatin immunoprecipitation (Q-ChIP). Synthetic inhibitors or mimics for miR-142-3p were used to assess whether this miRNA plays a role in regulating the expression of PU.1 and/or Vav1.
RESULTS: We found that the expression of miR-142-3p in differentiating APL-derived NB4 cells is dependent on PU.1, and that Vav1 is essential for the recruitment of this transcription factor to its cis-binding element on the miR-142 promoter. In addition, we found that in ATRA-treated NB4 cells miR-142-3p sustains agonist-induced increases in both PU.1 and Vav1.
CONCLUSIONS: Our results suggest the existence of a Vav1/PU.1/miR-142-3p network that supports ATRA-induced differentiation in APL-derived cells. Since selective regulation of miRNAs may play a role in the future treatment of hematopoietic malignancies, our results may provide a basis for the development of new therapeutic strategies to restore the expression of miR-142-3p.

Marjanovic I, Kostic J, Stanic B, et al.
Parallel targeted next generation sequencing of childhood and adult acute myeloid leukemia patients reveals uniform genomic profile of the disease.
Tumour Biol. 2016; 37(10):13391-13401 [PubMed] Related Publications
The age-specific differences in the genetic mechanisms of myeloid leukemogenesis have been observed and studied previously. However, NGS technology has provided a possibility to obtain a large amount of mutation data. We analyzed DNA samples from 20 childhood (cAML) and 20 adult AML (aAML) patients, using NGS targeted sequencing. The average coverage of high-quality sequences was 2981 × per amplicon. A total of 412 (207 cAML, 205 aAML) variants in the coding regions were detected; out of which, only 122 (62 cAML and 60 aAML) were potentially protein-changing. Our results confirmed that AML contains small number of genetic alterations (median 3 mutations/patient in both groups). The prevalence of the most frequent single gene AML associated mutations differed in cAML and aAML patient cohorts: IDH1 (0 % cAML, 5 % aAML), IDH2 (0 % cAML, 10 % aAML), NPM1 (10 % cAML, 35 % aAML). Additionally, potentially protein-changing variants were found in tyrosine kinase genes or genes encoding tyrosine kinase associated proteins (JAK3, ABL1, GNAQ, and EGFR) in cAML, while among aAML, the prevalence is directed towards variants in the methylation and histone modifying genes (IDH1, IDH2, and SMARCB1). Besides uniform genomic profile of AML, specific genetic characteristic was exclusively detected in cAML and aAML.

Kostroma II, Gritsaev SV, Sidorova ZhY, et al.
[Aberrant methylation of the promoter regions of the SOX7 and p15INK4b genes and Wnt signaling pathway antagonists in patients with acute myeloid leukemias].
Ter Arkh. 2016; 88(7):31-6 [PubMed] Related Publications
AIM: to investigate the methylation status of the SOX7 and p15NK4b genes and Wnt signaling pathway antagonists in patients with acute myeloid leukemia (AML) in order to assess the association of the rate of aberrant methylation (AM) with the morphological variant and pattern of chromosomal aberrations, as well as the impact of the methylation status on survival.
SUBJECTS AND METHODS: The data of 57 AML patients aged 20 to 79 years were analyzed. The methylation status of the genes was studied by methylation-specific polymerase chain reaction.
RESULTS: The signs of the AM of ≥1 gene were detected in 52 (91.2%) of the 57 patients. The most common finding was AM of simultaneously 2 or 3 genes: in 29.8 and 21.1% of the patients, respectively. Concurrent methylation of 3-5 genes proved to be a more frequent finding in AML patients with myelodysplasia: in 7 (70%) of 10 patients. The proportion of patients with methylation of 5 genes was considerably higher in a group of patients with a complex karyotype: 50% versus 8.3% among other patients (odds ratio: 11.0; 95% confidence interval 2.0 to 61.6; p=0.01). There were no differences in the median overall and relapse-free survival rates in patients with a normal karyotype and without FLT3 and NPM mutations, who received induction therapy, in relation to the number of genes with AM.
CONCLUSION: AM of the p15NK4b and SOX7 genes and Wnt signaling pathway antagonists is detected in the majority of patients with AML, which allows hypomethylating agents to be recommended for the treatment of patients who cannot use intensive cytostatic therapy for different reasons. The detection of a large number of genes with the aberrant methylation status in most AML patients with myelodysplasia or a complex karyotype serves as the basis for initiating trials to evaluate the efficiency of a combination of 5-azacytidine and cytostatics.

Wu X, Feng X, Zhao X, et al.
Prognostic significance of FLT3-ITD in pediatric acute myeloid leukemia: a meta-analysis of cohort studies.
Mol Cell Biochem. 2016; 420(1-2):121-8 [PubMed] Related Publications
The purpose of the study was to assess the effect of the internal tandem duplication in FMS-like tyrosine kinase 3 (FLT3-ITD) on the outcome in pediatric acute myeloid leukemia (AML) patients. We identified eligible studies from several databases including PubMed, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) (from January 1995 to July 2015). Ten studies of 1661 pediatric patients with AML were included in exploring the relationship between the FLT3-ITD and overall survival (OS)/event free survival (EFS). Pediatric patients with AML with FLT3-ITD had worse OS [HR = 2.19 (1.60-3.01)]/EFS [HR = 1.70 (1.37-2.11)] than those patients without FLT3-ITD. Furthermore, FLT3-ITD had unfavorable effect on OS/EFS in the subgroups of NOS, uni/multivariate model, number of patients, the length of following-up, and patient source. The findings of this meta-analysis indicated that FLT3-ITD had negative impact on pediatric patients with AML.

Orlova NN, Lebedev TD, Spirin PV, Prassolov VS
[Key molecular mechanisms associated with cell malignant transformation in acute myeloid leukemia].
Mol Biol (Mosk). 2016 May-Jun; 50(3):395-405 [PubMed] Related Publications
Cancer, along with cardiovascular disorders, is one of the most important problems of healthcare. Pathologies of the hematopoietic system are the most prevalent in patients under 30 years of age, including acute myeloid leukemia (AML), which is widespread and difficult to treat. The review considers the mechanisms that play a significant role in AML cell malignant transformation and shows the contributions of certain genes to both remission and resistance of AML cells to various treatments.

Wu AY, Yang HC, Lin CM, et al.
The Transcriptome Study of Subtype M2 Acute Myeloblastic Leukemia.
Cell Biochem Biophys. 2015; 72(3):653-6 [PubMed] Related Publications
Our objective is to explore the tumor-specific mutated genes by transcriptome sequencing of patients with acute myeloblastic leukemia. 96 patients with subtype M2 acute myeloid leukemia (AML), admitted during January 2007 to January 2012, were selected. Bone marrow and peripheral blood samples from the patients after the first visit and the patients who were improved or alleviated, were subjected to high-throughput sequencing to compare the gene expression. The single nucleotide mutation related to subtype M2 AML was detected. Meanwhile, real-time fluorescent quantitation RT-PCR was used to detect the AML1/ETO fusion gene and its correlation with prognosis after treatment. Among 96 patients, AML1-ETO fusion gene was positive in 52 cases, the positive rate was 54.17 %. The complete relief (CR) rate of AML1-ETO fusion gene positive patients was 84.62 %, and the CR rate of AML1/ETO fusion gene negative patients was 77.27 %; the CR rate of AML1-ETO positive patients was higher than that of patients without the fusion gene, however there was no statistical difference. In the analysis of recurrent gene mutation in AML-M2 patients, IDH2, ASXL1, TET2, JAK1 and JAK2 gene expressions were not significantly different before treatment and after CR, however, IDHI, JAK3, ABL1 and BCR gene expressions were significantly different. In the study of transcriptome in AML-M2 patients, high-throughput sequencing could effectively detect the difference of the gene expression before treatment and after CR. Furthermore, positive expression of AML1-ETO fusion gene had effect on the prognosis of patients.

Gao S, Xu XJ, Zhang K
[Research Progress on the Role of Chromatin Remodeling Factor BRG1 in Acute Myeloid Leukemia].
Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2016; 24(3):930-3 [PubMed] Related Publications
BRG1 (Brahma-related gene 1, BRG1) is the ATPase subunit of SWI/SNF chromatin remodeling complexes, which plays an important role in cell cycle regulation, DNA repair and tumor development. Unlike the evidence as tumor suppressor genes in the past reports, latest researches show that BRG1 plays an important role in sustaining the growth of leukemia cells in acute myeloid leukemia, and these effects on normal hematopoietic stem cells are dispensable. Further studies of the role and mechanism of BRG1 in acute myeloid leukemia will contribute to the development of a new and promising targeted therapy strategy. This article reviews the role of BRG1 on leukemia cells and leukemia stem cells in AML and discusses the related mechanism, which providing some reference for the targeted treatment strategy of AML.

Zheng YT, Li BX, Sun YJ, et al.
[Expression of WT1 Gene in Bone Marrow of Patients with Acute Myeloid Leukemia and Its Influence on Prognosis].
Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2016; 24(3):649-54 [PubMed] Related Publications
OBJECTIVE: To investigate the expression level of WT1 gene in bone marrow of patients with acute myeloid leukemia (AML) and its relationship with prognosis.
METHODS: The copy numbers of WT1 and internal reference gene in bone marrow samples from 75 newly diagnosed AML patients were detected by using real-time quantitative PCR. The gene WT1 expression level was determined by the ratio of the copy numbers of WT1 to reference gene. And the clinical characteristics, the complete remission (CR) rate after induction chemotherapy, 2-year overall survival (OS) rate and event-free survival (EFS) rate were calculated and analysed.
RESULTS: The expression level of WT1 did not significantly correlate with common clinical parameters such as age, sex, molecular abnormality, FAB classification and risk stratification. The CR rate in the high WT1 expression group before treatment was 65.4%, which was lower than that of 93.9% in the low expression group (χ2=8.25, P<0.01). The 2-year overall survival rate and event-free survival rate of the two groups were statistically significantly different (P<0.05), and the OS and EFS rates in high WT1 expression group were lower than those in low expression group. After the induction chamotheropy for about 1, 3 month and 6 months, the 2-year OS rate significantly increased in patients with decrease of WT1 gene expression level by one log or more (P<0.05).
CONCLUSION: The expression level of WT1 gene in bone marrow may be an effective marker to evaluate therapy efficacy and prognosis for AML patients (non APL).

Fooladinezhad H, Khanahmad H, Ganjalikhani-Hakemi M, Doosti A
Negative regulation of TIM-3 expression in AML cell line (HL-60) using miR-330-5p.
Br J Biomed Sci. 2016; 73(3):129-133 [PubMed] Related Publications
BACKGROUND: Uncontrolled proliferation and accumulation of leukaemic stem cells (LSCs) in bone marrow leads to acute myeloma leukaemia (AML). T cell immunoglobulin and mucine domain (TIM)-3 is a specific surface marker for LSCs and is highly expressed on LSCs compared with normal bone marrow cells, haematopoietic stem cells. Studies have indicated that microRNAs can affect AML progression through targeting different genes expressions like TIM-3. So, based on bioinformatics assessments, we predicted that miR-330-5p may highly inhibit TIM-3 expression. The purpose of the present study was to prove the silencing effect of miR-330-5p on TIM-3 gene expression in AML cell line (HL-60) in vitro.
METHODS: HL-60 cells were cultured in RPMI 1640 supplied with 10% FBS. TIM-3 expression was induced in the cells using phorbol myristate acetate (PMA). The cells were transfected with miR-330-5p and then, the gene and protein expression of TIM-3 were measured using q-RT-PCR and flow-cytometry methods, respectively.
RESULTS: The results of our bioinformatics surveys revealed that miR-330-5p has high predicted ability to silence TIM-3 gene expression. Accordingly, our experiments confirmed that miR-330-5p is able to strongly silence TIM-3 expression (98.15% silencing) in HL-60 cell line (p = 0.0001).
CONCLUSION: According to our results, miR-330-5p has a strong inhibitory effect on TIM-3 expression in AML cell line. Thus, the bioinformatics prediction of Mirwalk and Target Scan softwares for silencing effect of miR-330-5p on TIM-3 is confirmed.

Zhang TJ, Zhou JD, Ma JC, et al.
CDH1 (E-cadherin) expression independently affects clinical outcome in acute myeloid leukemia with normal cytogenetics.
Clin Chem Lab Med. 2017; 55(1):123-131 [PubMed] Related Publications
BACKGROUND: Epithelial-mesenchymal transition (EMT) is a critical process which involves in tumor metastasis. As an important EMT marker gene, CDH1 (E-cadherin) expression and its clinical implication in acute myeloid leukemia (AML) remain largely elusive.
METHODS: Real-time quantitative PCR (RQ-PCR) was carried out to examine CDH1 transcript level in 123 de novo AML patients and 34 controls.
RESULTS: Compared with controls, CDH1 was significantly downregulated in AML (p<0.001). The median level of CDH1 expression divided total AML patients into CDH1 low-expressed (CDH11ow) and CDH1 high-expressed (CDH1high) groups. There were no significant differences between the two groups in age, peripheral blood cell counts, complete remission (CR) rate, and the distribution of FAB/WHO subtypes as well as karyotypes/karyotypic classifications (p>0.05). However, CDH11ow group tended to have a higher bone marrow (BM) blasts (p=0.093). The spearman correlation analysis further illustrated a trend towards a negative correlation between CDH1 expression level and BM blasts (r=-0.214, p=0.052). CDH1low group had a tendency towards a lower frequency of N/K-RAS mutations (p=0.094). Furthermore, CDH1low patients had markedly shorter overall survival (OS) time in cytogenetic normal AML (CN-AML) (p=0.019). Both univariate and multivariate analyses confirmed the prognostic value of CDH1 expression in CN-AML patients (p=0.027 and 0.033, respectively).
CONCLUSIONS: CDH1 downregulation acted as an independent prognostic biomarker in CN-AML patients.

Papaemmanuil E, Gerstung M, Bullinger L, et al.
Genomic Classification and Prognosis in Acute Myeloid Leukemia.
N Engl J Med. 2016; 374(23):2209-21 [PubMed] Article available free on PMC after 16/09/2017 Related Publications
BACKGROUND: Recent studies have provided a detailed census of genes that are mutated in acute myeloid leukemia (AML). Our next challenge is to understand how this genetic diversity defines the pathophysiology of AML and informs clinical practice.
METHODS: We enrolled a total of 1540 patients in three prospective trials of intensive therapy. Combining driver mutations in 111 cancer genes with cytogenetic and clinical data, we defined AML genomic subgroups and their relevance to clinical outcomes.
RESULTS: We identified 5234 driver mutations across 76 genes or genomic regions, with 2 or more drivers identified in 86% of the patients. Patterns of co-mutation compartmentalized the cohort into 11 classes, each with distinct diagnostic features and clinical outcomes. In addition to currently defined AML subgroups, three heterogeneous genomic categories emerged: AML with mutations in genes encoding chromatin, RNA-splicing regulators, or both (in 18% of patients); AML with TP53 mutations, chromosomal aneuploidies, or both (in 13%); and, provisionally, AML with IDH2(R172) mutations (in 1%). Patients with chromatin-spliceosome and TP53-aneuploidy AML had poor outcomes, with the various class-defining mutations contributing independently and additively to the outcome. In addition to class-defining lesions, other co-occurring driver mutations also had a substantial effect on overall survival. The prognostic effects of individual mutations were often significantly altered by the presence or absence of other driver mutations. Such gene-gene interactions were especially pronounced for NPM1-mutated AML, in which patterns of co-mutation identified groups with a favorable or adverse prognosis. These predictions require validation in prospective clinical trials.
CONCLUSIONS: The driver landscape in AML reveals distinct molecular subgroups that reflect discrete paths in the evolution of AML, informing disease classification and prognostic stratification. (Funded by the Wellcome Trust and others; ClinicalTrials.gov number, NCT00146120.).

Higuchi Y, Tokunaga K, Watanabe Y, et al.
Lineage switch with t(6;11)(q27;q23) from T-cell lymphoblastic lymphoma to acute monoblastic leukemia at relapse.
Cancer Genet. 2016; 209(6):267-71 [PubMed] Related Publications
We present a patient with T-cell lymphoblastic lymphoma (T-LBL) harboring t(6;11)(q27;q23) that converted to acute monoblastic leukemia at relapse. A 27-year-old man developed T-LBL with a mediastinal mass. He exhibited several recurrences in the central nervous system and marrow. A fifth relapse occurred in the marrow, with 42.8% blasts with CD4, CD5, CD7, CD10, CD33, CD34, HLA-DR and cytoplasmic (cy) CD3. While achieving complete remission with nelarabine, sixth relapse occurred in the marrow with 6.8% blasts, which had characteristics of monoblastic features, 2 months later. Marrow blasts were positive for myeloperoxidase, CD4, CD33, CD56, CD64, and HLA-DR, but were negative for cyCD3, CD5, CD7, CD10, and CD34. Marrow cells at both the 5th lymphoid and 6th myeloid relapses had t(6;11)(q27;q23) and the same MLL-MLLT4 fusion transcript. In addition, the MLL-MLLT4 fusion sequences documented in the initial mediastinal cells were the same as seen in peripheral blood cells at the 6th relapse. The patient continues 7th remission after one course of gemtuzumab ozogamicin therapy followed by cord blood transplantation for more than 3 years. Sequential phenotypic and cytogenetic studies may yield valuable insights into the mechanism of leukemic recurrence and possible implications for treatment selection.

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)
t(8;21)(q22;q22) in Acute Myeloid LeukemiaTranslocationRUNX1 (21q22.3)RUNX1T1 (8q22)
t(16;16)(p13q22) CBFB-MYH11 Translocation in AMLTranslocationCBFB (16q22.1)MYH11 (16p13.11)
t(16;21)(p11;q22) in Leukemia (ANLL)TranslocationERG (21q22.3)FUS (16p11.2)
t(3;21)(q26;q22) in Secondary Leukaemia / MDSTranslocationMECOM (3q26.2)RUNX1 (21q22.3)
t(16;21)(p11;q22) FUS-ERG in Acute Myelogenous LeukemiaTranslocationFUS (16p11.2)ERG (21q22.3)
t(1;11)(p32;q23) MLL-EPS15 fusion in Acute Myelogeneous LeukemiaTranslocationKMT2A (11q23.3)EPS15 (1p32)
t(11;19)(q23;p13.1) MLL-ELL translocation in acute leukaemiaTranslocationKMT2A (11q23.3)ELL (19p13.1)
t(9;11) in Acute Myeloid LeukaemiaTranslocationKMT2A (11q23.3)MLLT3 (9p22)
t(6;11)(q27;q23) in Acute Myeloid LeukemiaTranslocationMLLT4 (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)ZBTB16 (11q23.2)
t(9;9)(q34;q34) SET-NUP214 rearrangements in Acute Lyphoblastic LeukaemiaTranslocationSET (9q34)NUP214 (9q34.1)
t(11;20) (p15;q11) NUP98-TOP1 Fusion in AMLTranslocationTOP1 (20q12-q13.1)NUP98 (11p15.4)
t(6;9)(p23;q34) DEK-NUP214 in Acute Myeloid Leukaemia and Myelodysplastic SyndromeTranslocationNUP214 (9q34.1)DEK (6p22.3)
t(10;11)(p12;q23) AF10-MLL translocation in Acute LeukaemiaTranslocationMLLT10 (10p12)KMT2A (11q23.3)
t(10;11)(p13;q14) AF10-PICALM translocation in Acute LeukaemiaTranslocationMLLT10 (10p12)PICALM (11q14.2)
t(10;11) MLL-TET1 rearrangement in acute leukemiasTranslocationTET1 (10q21)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:

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