Melanoma

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 (205)

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
BRAF 7q34 NS7, BRAF1, RAFB1, B-RAF1 -BRAF and Melanoma
1448
CDKN2A 9p21.3 ARF, MLM, P14, P16, P19, CMM2, INK4, MTS1, TP16, CDK4I, CDKN2, INK4A, MTS-1, P14ARF, P19ARF, P16INK4, P16INK4A, P16-INK4A -CDKN2A and Melanoma
-CDKN2A and Familial Melanoma
740
NRAS 1p13.2 NS6, CMNS, NCMS, ALPS4, N-ras, NRAS1 -NRAS and Melanoma
519
CDK4 12q14 CMM3, PSK-J3 -CDK4 and Melanoma
-CDK4 Germline Mutations in Melanoma Prone Families
208
CTNNB1 3p22.1 CTNNB, MRD19, armadillo -CTNNB1 and Melanoma
256
KIT 4q12 PBT, SCFR, C-Kit, CD117 -KIT and Melanoma
247
MITF 3p14.2-p14.1 MI, WS2, CMM8, WS2A, bHLHe32 -MITF and Melanoma
189
FGF2 4q26 BFGF, FGFB, FGF-2, HBGF-2 -FGF2 and Melanoma
186
AR Xq12 KD, AIS, AR8, TFM, DHTR, SBMA, HYSP1, NR3C4, SMAX1, HUMARA -AR and Melanoma
184
TP53 17p13.1 P53, BCC7, LFS1, TRP53 -TP53 and Melanoma
169
MC1R 16q24.3 CMM5, MSH-R, SHEP2 -MC1R Polymorphisms and Melanoma
165
MCAM 11q23.3 CD146, MUC18 -MCAM and Melanoma
130
MLANA 9p24.1 MART1, MART-1 -MLANA and Melanoma
115
GNAQ 9q21 GAQ, SWS, CMC1, G-ALPHA-q -GNAQ and Melanoma
85
BAP1 3p21.1 UCHL2, hucep-6, HUCEP-13 Germline
-BAP1 and Melanoma
81
CDKN1A 6p21.2 P21, CIP1, SDI1, WAF1, CAP20, CDKN1, MDA-6, p21CIP1 -CDKN1A Expression in Melanoma
73
GNA11 19p13.3 FBH, FBH2, FHH2, HHC2, GNA-11, HYPOC2 -GNA11 and Melanoma
73
HLA-B 6p21.3 AS, HLAB, SPDA1 -HLA-B and Melanoma
60
CXCL1 4q21 FSP, GRO1, GROa, MGSA, NAP-3, SCYB1, MGSA-a -CXCL1 and Melanoma
60
MMP2 16q12.2 CLG4, MONA, CLG4A, MMP-2, TBE-1, MMP-II -MMP2 and Melanoma
53
BRCA2 13q13.1 FAD, FACD, FAD1, GLM3, BRCC2, FANCD, PNCA2, FANCD1, XRCC11, BROVCA2 -BRCA2 and Melanoma
50
HRAS 11p15.5 CTLO, HAMSV, HRAS1, RASH1, p21ras, C-H-RAS, H-RASIDX, C-BAS/HAS, C-HA-RAS1 -HRAS and Melanoma
49
PMEL 12q13-q14 P1, SI, SIL, ME20, P100, SILV, ME20M, gp100, ME20-M, PMEL17, D12S53E -PMEL and Melanoma
45
CTLA4 2q33 CD, GSE, GRD4, ALPS5, CD152, CTLA-4, IDDM12, CELIAC3 -CTLA4 and Melanoma
41
IL24 1q32 C49A, FISP, MDA7, MOB5, ST16, IL10B Down Regulated
-MDA1 Expression in Melanoma
40
IL4 5q31.1 BSF1, IL-4, BCGF1, BSF-1, BCGF-1 -IL4 Gene Therapy for Melanoma (Experimental)
40
TYRP1 9p23 TRP, CAS2, CATB, GP75, OCA3, TRP1, TYRP, b-PROTEIN -TYRP1 and Melanoma
37
MYB 6q22-q23 efg, Cmyb, c-myb, c-myb_CDS -MYB and Melanoma
34
MAGEA3 Xq28 HIP8, HYPD, CT1.3, MAGE3, MAGEA6 -MAGEA3 and Melanoma
34
MAGEA1 Xq28 CT1.1, MAGE1 -MAGEA1 and Melanoma
32
PAX3 2q35 WS1, WS3, CDHS, HUP2 -PAX3 and Melanoma
31
BAD 11q13.1 BBC2, BCL2L8 -BAD and Melanoma
30
CDK6 7q21-q22 MCPH12, PLSTIRE -CDK6 and Melanoma
29
ICAM1 19p13.3-p13.2 BB2, CD54, P3.58 -ICAM1 and Melanoma
28
SOX10 22q13.1 DOM, WS4, PCWH, WS2E, WS4C -SOX10 and Melanoma
27
TERT 5p15.33 TP2, TRT, CMM9, EST2, TCS1, hTRT, DKCA2, DKCB4, hEST2, PFBMFT1 -TERT and Melanoma
27
RAF1 3p25 NS5, CRAF, Raf-1, c-Raf, CMD1NN -RAF1 and Melanoma
27
CD63 12q12-q13 MLA1, ME491, LAMP-3, OMA81H, TSPAN30 -CD63 and Melanoma
25
TFAP2C 20q13.2 ERF1, TFAP2G, hAP-2g, AP2-GAMMA -TFAP2C and Melanoma
25
TFAP2B 6p12 AP-2B, AP2-B -TFAP2B and Melanoma
25
TFAP2A 6p24 AP-2, BOFS, AP2TF, TFAP2, AP-2alpha -TFAP2A and Melanoma
24
STAT1 2q32.2 CANDF7, IMD31A, IMD31B, IMD31C, ISGF-3, STAT91 -STAT1 and Melanoma
23
CD80 3q13.3-q21 B7, BB1, B7-1, B7.1, LAB7, CD28LG, CD28LG1 -CD80 and Melanoma
23
WNT5A 3p21-p14 hWNT5A -WNT5A and Melanoma
22
RAC1 7p22 MIG5, Rac-1, TC-25, p21-Rac1 -RAC1 and Melanoma
22
MMP1 11q22.2 CLG, CLGN Prognostic
-MMP1 and Melanoma
22
FOXP3 Xp11.23 JM2, AIID, IPEX, PIDX, XPID, DIETER -FOXP3 and Melanoma
22
ATF1 12q13 TREB36, EWS-ATF1, FUS/ATF-1 -ATF1 and Melanoma
22
RREB1 6p25 HNT, FINB, LZ321, Zep-1, RREB-1 -RREB1 and Melanoma
21
SPARC 5q31.3-q32 ON -SPARC and Melanoma
21
PIGS 17p13.2 -PIGS and Melanoma
20
TIMP1 Xp11.3-p11.23 EPA, EPO, HCI, CLGI, TIMP Prognostic
-TIMP1 AND Melanoma
20
PARP1 1q41-q42 PARP, PPOL, ADPRT, ARTD1, ADPRT1, PARP-1, ADPRT 1, pADPRT-1 -PARP1 and Melanoma
20
ASIP 20q11.2-q12 ASP, AGSW, AGTI, AGTIL, SHEP9 -ASIP and Melanoma
19
HLA-C 6p21.3 HLC-C, D6S204, PSORS1, HLA-JY3 -HLA-C and Melanoma
18
OCA2 15q P, BEY, PED, BEY1, BEY2, BOCA, EYCL, HCL3, EYCL2, EYCL3, SHEP1, D15S12 -OCA2 and Melanoma
18
HLA-DRB1 6p21.3 SS1, DRB1, DRw10, HLA-DRB, HLA-DR1B -HLA-DRB1 and Melanoma
18
MAP2K2 19p13.3 CFC4, MEK2, MKK2, MAPKK2, PRKMK2 -MAP2K2 and Melanoma
17
MIA 19q13.2 CD-RAP -MIA and Melanoma
17
MTAP 9p21 BDMF, MSAP, DMSFH, LGMBF, DMSMFH, c86fus, HEL-249 -MTAP and Melanoma
16
S100A6 1q21 2A9, PRA, 5B10, CABP, CACY -S100A6 Expression in Melanoma
16
XPC 3p25.1 XP3, RAD4, XPCC, p125 -XPC and Melanoma
16
ABCB5 7p21.1 ABCB5beta, EST422562, ABCB5alpha -ABCB5 and Melanoma
16
FAS 10q24.1 APT1, CD95, FAS1, APO-1, FASTM, ALPS1A, TNFRSF6 -FAS and Melanoma
15
RHOC 1p13.1 H9, ARH9, ARHC, RHOH9 -RHOC and Melanoma
15
CTAG1B Xq28 CTAG, ESO1, CT6.1, CTAG1, LAGE-2, LAGE2B, NY-ESO-1 -CTAG1B and Melanoma
15
CD68 17p13 GP110, LAMP4, SCARD1 -CD68 and Melanoma
14
SF3B1 2q33.1 MDS, PRP10, Hsh155, PRPF10, SAP155, SF3b155 -SF3B1 and Melanoma
14
CIITA 16p13 C2TA, NLRA, MHC2TA, CIITAIV -CIITA and Melanoma
13
APAF1 12q23 CED4, APAF-1 -APAF1 and Melanoma
13
KISS1 1q32 HH13, KiSS-1 -KISS1 and Melanoma
12
PARK2 6q25.2-q27 PDJ, PRKN, AR-JP, LPRS2 -PARK2 and Melanoma
12
IL2 4q26-q27 IL-2, TCGF, lymphokine -IL2 and Melanoma
12
GAST 17q21 GAS -GAST and Melanoma
12
TAP1 6p21.3 APT1, PSF1, ABC17, ABCB2, PSF-1, RING4, TAP1N, D6S114E, TAP1*0102N -TAP1 and Melanoma
11
ERBB4 2q33.3-q34 HER4, ALS19, p180erbB4 -ERBB4 and Melanoma
11
SKI 1p36.33 SGS, SKV -SKI and Melanoma
11
GRM1 6q24 MGLU1, GPRC1A, MGLUR1, SCAR13, PPP1R85 -GRM1 and Melanoma
11
AKT3 1q44 MPPH, PKBG, MPPH2, PRKBG, STK-2, PKB-GAMMA, RAC-gamma, RAC-PK-gamma -AKT3 and Melanoma
11
GSTT1 22q11.23 -GSTT1 Polymorphisms and Melanoma
10
CXCL10 4q21 C7, IFI10, INP10, IP-10, crg-2, mob-1, SCYB10, gIP-10 -CXCL10 and Melanoma
10
CD274 9p24 B7-H, B7H1, PDL1, PD-L1, PDCD1L1, PDCD1LG1 -CD274 and Melanoma
9
ATF2 2q32 HB16, CREB2, TREB7, CREB-2, CRE-BP1 -ATF2 and Melanoma
9
CD86 3q21 B70, B7-2, B7.2, LAB72, CD28LG2 -CD86 and Melanoma
9
MAGEA2 Xq28 CT1.2, MAGE2, MAGEA2A -Melanoma and MAGEA2
9
PTPRD 9p23-p24.3 HPTP, PTPD, HPTPD, HPTPDELTA, RPTPDELTA -PTPRD and Melanoma
9
S100B 21q22.3 NEF, S100, S100-B, S100beta Prognostic
-S100B and Melanoma
8
MAGEB2 Xp21.3 DAM6, CT3.2, MAGE-XP-2 -MAGEB2 and Melanoma
8
CCR7 17q12-q21.2 BLR2, EBI1, CCR-7, CD197, CDw197, CMKBR7, CC-CKR-7 -CCR7 and Melanoma
8
PRAME 22q11.22 MAPE, OIP4, CT130, OIP-4 -PRAME and Melanoma
8
NEDD9 6p24.2 CAS2, CASL, HEF1, CAS-L, CASS2 -NEDD9 and Melanoma
7
L1CAM Xq28 S10, HSAS, MASA, MIC5, SPG1, CAML1, CD171, HSAS1, N-CAML1, NCAM-L1, N-CAM-L1 -L1CAM and Melanoma
7
FLNC 7q32-q35 ABPA, ABPL, FLN2, MFM5, MPD4, ABP-280, ABP280A -FLNC and Melanoma
7
TLR3 4q35 CD283, IIAE2 -TLR3 and Melanoma
7
CD27 12p13 T14, S152, Tp55, TNFRSF7, S152. LPFS2 -CD27 and Melanoma
7
TRB 7q34 TCRB, TRB@ -TRB and Melanoma
7
MAGEA4 Xq28 CT1.4, MAGE4, MAGE4A, MAGE4B, MAGE-41, MAGE-X2 -MAGEA4 and Melanoma
7
CEACAM1 19q13.2 BGP, BGP1, BGPI -CEACAM1 and Melanoma
7
IRF4 6p25-p23 MUM1, LSIRF, SHEP8, NF-EM5 -IRF4 and Melanoma
7
IL18 11q23.1 IGIF, IL-18, IL-1g, IL1F4 -IL18 and Melanoma
7
EDNRB 13q22 ETB, ET-B, ETB1, ETBR, ETRB, HSCR, WS4A, ABCDS, ET-BR, HSCR2 -EDNRB and Melanoma
7
TERC 3q26 TR, hTR, TRC3, DKCA1, PFBMFT2, SCARNA19 -TERC and Melanoma
7
PTPRF 1p34 LAR, BNAH2 -PTPRF and Melanoma
7
GDF15 19p13.11 PDF, MIC1, PLAB, MIC-1, NAG-1, PTGFB, GDF-15 -GDF15 and Melanoma
7
YES1 18p11.31-p11.21 Yes, c-yes, HsT441, P61-YES -Proto-Oncogene Proteins c-yes and Melanoma
7
AIM1 6q21 ST4, CRYBG1 -AIM1 and Melanoma
6
BIRC7 20q13.3 KIAP, LIVIN, MLIAP, RNF50, ML-IAP -BIRC7 and Melanoma
6
PDCD1 2q37.3 PD1, PD-1, CD279, SLEB2, hPD-1, hPD-l, hSLE1 -PDCD1 and Melanoma
6
DDB2 11p11.2 XPE, DDBB, UV-DDB2 -DDB2 and Melanoma
6
TBX2 17q23.2 -TBX2 and Melanoma
6
BCL2A1 15q24.3 GRS, ACC1, ACC2, BFL1, ACC-1, ACC-2, HBPA1, BCL2L5 -BCL2A1 and Melanoma
6
PEBP1 12q24.23 PBP, HCNP, PEBP, RKIP, HCNPpp, PEBP-1, HEL-210, HEL-S-34 -PEBP1 and Melanoma
6
CLPTM1L 5p15.33 CRR9 -CLPTM1L and Melanoma
6
MIRLET7B 22q13.31 LET7B, let-7b, MIRNLET7B, hsa-let-7b -MicroRNA let-7b and Melanoma
6
BAGE 21p11.1 not on ref BAGE1, CT2.1 -BAGE and Melanoma
6
KDM5B 1q32.1 CT31, PLU1, PUT1, PLU-1, JARID1B, PPP1R98, RBBP2H1A -KDM5B and Melanoma
5
SMARCA2 9p22.3 BRM, SNF2, SWI2, hBRM, NCBRS, Sth1p, BAF190, SNF2L2, SNF2LA, hSNF2a -SMARCA2 and Melanoma
5
TRG 7p14 TCRG, TRG@ -TRG and Melanoma
5
STAT2 12q13.3 P113, ISGF-3, STAT113 -STAT2 and Melanoma
5
YY1AP1 1q22 YAP, HCCA1, HCCA2, YY1AP -YY1AP1 and Melanoma
5
EFNB2 13q33 HTKL, EPLG5, Htk-L, LERK5 -EFNB2 expression in Melanoma
5
CXCL9 4q21 CMK, MIG, Humig, SCYB9, crg-10 -CXCL9 and Melanoma
5
CITED1 Xq13.1 MSG1 -CITED1 and Melanoma
5
MXI1 10q24-q25 MXI, MAD2, MXD2, bHLHc11 -MXI1 and Melanoma
5
BMP7 20q13 OP-1 -BMP7 and Melanoma
5
GAGE1 Xp11.23 CT4.1, GAGE-1 -GAGE1 and Melanoma
5
RARB 3p24.2 HAP, RRB2, NR1B2, MCOPS12 -RARB and Melanoma
5
HSPB1 7q11.23 CMT2F, HMN2B, HSP27, HSP28, Hsp25, SRP27, HS.76067, HEL-S-102 -HSPB1 and Melanoma
5
ULBP2 6q25 N2DL2, RAET1H, NKG2DL2, ALCAN-alpha -ULBP2 and Melanoma
5
IRF9 14q11.2 p48, IRF-9, ISGF3, ISGF3G -IRF9 and Melanoma
4
TIMP2 17q25 DDC8, CSC-21K -TIMP2 and Melanoma
4
HSF1 8q24.3 HSTF1 -HSF1 and Melanoma
4
MAP2 2q34-q35 MAP2A, MAP2B, MAP2C -MAP2 and Melanoma
4
PERP 6q24 THW, KCP1, PIGPC1, KRTCAP1, dJ496H19.1 -PERP and Melanoma
4
MAP3K5 6q22.33 ASK1, MEKK5, MAPKKK5 -MAP3K5 and Melanoma
4
DUSP6 12q22-q23 HH19, MKP3, PYST1 -DUSP6 and Melanoma
4
BRMS1 11q13.2 -BRMS1 and Melanoma
4
ITGA4 2q31.3 IA4, CD49D -ITGA4 and Melanoma
4
CD70 19p13 CD27L, CD27LG, TNFSF7 -CD70 and Melanoma
4
YBX1 1p34 YB1, BP-8, CSDB, DBPB, YB-1, CSDA2, NSEP1, NSEP-1, MDR-NF1 -YBX1 and Melanoma
4
POT1 7q31.33 CMM10, HPOT1 Germline
GWS
-POT1 and Predisposition to Familial Melanoma
4
ING4 12p13.31 my036, p29ING4 -ING4 and Melanoma
4
VCAN 5q14.3 WGN, ERVR, GHAP, PG-M, WGN1, CSPG2 -VCAN and Melanoma
4
TRPM8 2q37.1 TRPP8, LTRPC6 -TRPM8 and Melanoma
4
CAST 5q15 BS-17, PLACK -CAST and Melanoma
4
ATF3 1q32.3 -ATF3 and Melanoma
4
CHUK 10q24-q25 IKK1, IKKA, IKBKA, TCF16, NFKBIKA, IKK-alpha -CHUK and Melanoma
4
FABP7 6q22-q23 MRG, BLBP, FABPB, B-FABP, LTR2-FABP7 -FABP7 and Melanoma
4
IGFBP7 4q12 AGM, PSF, TAF, FSTL2, IBP-7, MAC25, IGFBP-7, RAMSVPS, IGFBP-7v, IGFBPRP1 -IGFBP7 and Melanoma
4
HLA-DRA 6p21.3 MLRW, HLA-DRA1 -HLA-DRA and Melanoma
4
ITCH 20q11.22 AIF4, AIP4, ADMFD, NAPP1 -ITCH and Melanoma
4
RAP1GAP 1p36.1-p35 RAPGAP, RAP1GA1, RAP1GAP1, RAP1GAPII -RAP1GAP and Melanoma
4
PTPRK 6q22.2-q22.3 R-PTP-kappa -PTPRK and Melanoma
3
ICOS 2q33 AILIM, CD278, CVID1 -ICOS and Melanoma
3
ASAH1 8p22 AC, PHP, ASAH, PHP32, ACDase, SMAPME -ASAH1 and Melanoma
3
CD163 12p13.3 M130, MM130 -CD163 and Melanoma
3
PPP1R15A 19q13.2 GADD34 -PPP1R15A and Melanoma
3
HSPA8 11q24.1 LAP1, HSC54, HSC70, HSC71, HSP71, HSP73, LAP-1, NIP71, HEL-33, HSPA10, HEL-S-72p -HSPA8 and Melanoma
3
MSN Xq11.1 HEL70 -MSN and Melanoma
3
HPSE 4q21.3 HPA, HPA1, HPR1, HSE1, HPSE1 -HPSE and Melanoma
3
LARS 5q32 LRS, LEUS, LFIS, ILFS1, LARS1, LEURS, PIG44, RNTLS, HSPC192, hr025Cl -LARS and Melanoma
3
HTRA2 2p12 OMI, PARK13, PRSS25 -HTRA2 and Melanoma
3
ISG15 1p36.33 G1P2, IP17, UCRP, IFI15, IMD38, hUCRP -ISG15 and Melanoma
3
CXCL11 4q21.2 IP9, H174, IP-9, b-R1, I-TAC, SCYB11, SCYB9B -CXCL11 and Melanoma
3
NOX4 11q14.3 KOX, KOX-1, RENOX -NOX4 and Melanoma
3
CTSL 9q21.33 MEP, CATL, CTSL1 -CTSL1 and Melanoma
3
CD59 11p13 1F5, EJ16, EJ30, EL32, G344, MIN1, MIN2, MIN3, MIRL, HRF20, MACIF, MEM43, MIC11, MSK21, 16.3A5, HRF-20, MAC-IP, p18-20 -CD59 and Melanoma
3
HOXB7 17q21.3 HOX2, HOX2C, HHO.C1, Hox-2.3 -HOXB7 and Melanoma
3
ARL11 13q14.2 ARLTS1 -ARL11 and Melanoma
3
TNFRSF9 1p36 ILA, 4-1BB, CD137, CDw137 -TNFRSF9 and Melanoma
3
TYRO3 15q15 BYK, Dtk, RSE, Rek, Sky, Tif, Etk-2 -TYRO3 and Melanoma
3
GRASP 12q13.13 TAMALIN -GRASP and Melanoma
3
SPRY4 5q31.3 HH17 -SPRY4 and Melanoma
3
ADRB2 5q31-q32 BAR, B2AR, ADRBR, ADRB2R, BETA2AR -ADRB2 and Melanoma
3
MMP3 11q22.2 SL-1, STMY, STR1, CHDS6, MMP-3, STMY1 -MMP3 and Melanoma
3
MMP8 11q22.2 HNC, CLG1, MMP-8, PMNL-CL -MMP8 and Melanoma
3
TBX3 12q24.21 UMS, XHL, TBX3-ISO -TBX3 and Melanoma
3
ETV1 7p21.3 ER81 Overexpression
-ETV1 overexpression in Melanoma
2
TRIM24 7q32-q34 PTC6, TF1A, TIF1, RNF82, TIF1A, hTIF1, TIF1ALPHA -TRIM24 and Melanoma
2
ING3 7q31 Eaf4, ING2, MEAF4, p47ING3 -ING3 and Melanoma
2
PDCD6 5p15.33 ALG2, ALG-2, PEF1B -PDCD6 and Melanoma
2
PPP2R1A 19q13.41 MRD36, PR65A, PP2AAALPHA, PP2A-Aalpha -PPP2R1A and Melanoma
2
IL12B 5q33.3 CLMF, NKSF, CLMF2, IMD28, IMD29, NKSF2, IL-12B -IL12B and Melanoma
2
RTEL1 20q13.3 NHL, RTEL, DKCA4, DKCB5, PFBMFT3, C20orf41 -RTEL1 and Melanoma
2
HAVCR2 5q33.3 TIM3, CD366, KIM-3, TIMD3, Tim-3, TIMD-3, HAVcr-2 -HAVCR2 and Melanoma
2
MAP3K8 10p11.23 COT, EST, ESTF, TPL2, AURA2, MEKK8, Tpl-2, c-COT -MAP3K8 and Melanoma
2
ARID2 12q12 p200, BAF200 -ARID2 and Melanoma
2
AQP3 9p13 GIL, AQP-3 -AQP3 and Melanoma
2
S100A2 1q21 CAN19, S100L -S100A2 Expression in Melanoma
2
PAEP 9q34 GD, GdA, GdF, GdS, PEP, PAEG, PP14 -PAEP and Melanoma
2
ARNTL 11p15.3 TIC, JAP3, MOP3, BMAL1, PASD3, BMAL1c, bHLHe5 -ARNTL and Melanoma
2
MCM4 8q11.2 NKCD, CDC21, CDC54, NKGCD, hCdc21, P1-CDC21 -MCM4 and Melanoma
2
FLNA Xq28 FLN, FMD, MNS, OPD, ABPX, CSBS, CVD1, FLN1, NHBP, OPD1, OPD2, XLVD, XMVD, FLN-A, ABP-280 -FLNA and Melanoma
2
RIN1 11q13.2 -RIN1 and Melanoma
2
PPP1R3A 7q31.1 GM, PP1G, PPP1R3 -PPP1R3A and Melanoma
1
ADAM7 8p21.2 EAPI, GP83, GP-83, ADAM 7, ADAM-7 -ADAM7 and Melanoma
1
BIN1 2q14 AMPH2, AMPHL, SH3P9 -BIN1 and Melanoma
1
PNN 14q21.1 DRS, DRSP, SDK3, memA -PNN and Melanoma
1
KDM5A 12p11 RBP2, RBBP2, RBBP-2 -KDM5A and Melanoma
1
HOXD11 2q31.1 HOX4, HOX4F -HOXD11 and Melanoma
1
FBXO11 2p16.3 UBR6, VIT1, FBX11, PRMT9, UG063H01 -FBXO11 and Melanoma
1
MAS1 6q25.3-q26 MAS, MGRA -MAS1 and Melanoma
1
CASC5 15q14 D40, CT29, KNL1, Spc7, hKNL-1, AF15Q14, PPP1R55, hSpc105 -CASC5 and Melanoma
1
BLM 15q26.1 BS, RECQ2, RECQL2, RECQL3 -BLM and Melanoma
1
PTPRT 20q12-q13 RPTPrho -PTPRT and Melanoma

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

Latest Research Publications

Sato R, Nakano T, Hosonaga M, et al.
RNA Sequencing Analysis Reveals Interactions between Breast Cancer or Melanoma Cells and the Tissue Microenvironment during Brain Metastasis.
Biomed Res Int. 2017; 2017:8032910 [PubMed] Free Access to Full Article Related Publications
Metastasis is the main cause of treatment failure and death in cancer patients. Metastasis of tumor cells to the brain occurs frequently in individuals with breast cancer, non-small cell lung cancer, or melanoma. Despite recent advances in our understanding of the causes and in the treatment of primary tumors, the biological and molecular mechanisms underlying the metastasis of cancer cells to the brain have remained unclear. Metastasizing cancer cells interact with their microenvironment in the brain to establish metastases. We have now developed mouse models of brain metastasis based on intracardiac injection of human breast cancer or melanoma cell lines, and we have performed RNA sequencing analysis to identify genes in mouse brain tissue and the human cancer cells whose expression is associated specifically with metastasis. We found that the expressions of the mouse genes Tph2, Sspo, Ptprq, and Pole as well as those of the human genes CXCR4, PLLP, TNFSF4, VCAM1, SLC8A2, and SLC7A11 were upregulated in brain tissue harboring metastases. Further characterization of such genes that contribute to the establishment of brain metastases may provide a basis for the development of new therapeutic strategies and consequent improvement in the prognosis of cancer patients.

Hsieh R, Nico MM, Camillo CM, et al.
Mutational Status of NRAS and BRAF Genes and Protein Expression Analysis in a Series of Primary Oral Mucosal Melanoma.
Am J Dermatopathol. 2017; 39(2):104-110 [PubMed] Related Publications
Primary oral mucosal melanoma is an extremely rare and aggressive tumor arising from melanocytes located in the mucosal epithelium of the oral cavity. Although malignant melanoma of oral mucosa shares some clinical features with its cutaneous counterpart, it has been associated with a worst prognosis; its etiopathogenesis are still only partially unraveled as there is no influence of UV radiation. It is known that the mitogen-activated protein kinase pathway mediates cellular responses to growth signals and its activation is an important phenomenon in melanoma. The aim of this study was to evaluate NRAS and BRAF genes, both components of mitogen-activated protein kinase molecular pathway, and compare with their protein expression. Point mutations of NRAS (codons 12, 13, and 61) and BRAF (codon 600) were screened by pyrosequencing method, and its results were associated to the protein expression of RAS and BRAF performed by immunohistochemistry. The authors observed mutation in BRAF 600 (3/14), NRAS codons 12 and 13 (2/14), and NRAS codon 61 (2/8). One case showed positive RAS protein expression, but no mutation was observed. Twelve in 14 cases showed positive BRAF protein expression: 3 cases showed BRAF mutation; 2 cases showed NRAS codon 61 mutation; 2 cases showed NRAS codons 12 and 13 mutation but not simultaneously. Although NRAS and BRAF mutation frequency and RAS protein expression are low, BRAF protein expression was intense; probably, NRAS and BRAF mutations are independent events and alternative molecular mechanisms in the primary oral mucosal melanoma tumorigenesis.

Cicenas J, Tamosaitis L, Kvederaviciute K, et al.
KRAS, NRAS and BRAF mutations in colorectal cancer and melanoma.
Med Oncol. 2017; 34(2):26 [PubMed] Related Publications
Cancers are the group of diseases, which arise because of the uncontrolled behavior of some of the genes in our cells. There are possibilities of gene amplifications, overexpressions, deletions and other anomalies which might lead to the development and spread of cancer. One of the most dangerous ways to the cancers is the mutations of the genes. The mutated genes can start unstoppable proliferation of cells, their uncontrolled motility, protection from apoptosis, the DNA mutation enhancement as well as other anomalies, leading to the cancer. This review focuses on the genes, which are frequently mutated in various cancers and are known to be important in the advance and progression of colorectal cancer and melanoma, namely KRAS, NRAS and BRAF.

Oliveira C, Lourenço GJ, Rinck-Junior JA, et al.
Polymorphisms in apoptosis-related genes in cutaneous melanoma prognosis: sex disparity.
Med Oncol. 2017; 34(2):19 [PubMed] Related Publications
Cutaneous melanoma (CM) cells are resistant to apoptosis, and steroid hormones are involved in this process through regulation of TP53, MDM2, BAX, and BCL2 expression. We analyzed herein sex differences in outcomes of CM patients associated with TP53 c.215G>C, MDM2 c.309T>G, BAX c.-248G>A, and BCL2 c.-717C>A polymorphisms. DNA from 121 men and 116 women patients was analyzed by polymerase chain reaction and enzymatic digestion assays. At 60 months of follow-up, shorter progression-free survival (PFS) was seen in males with MDM2 GG + BCL2 AA (20.0 vs. 62.6%, P = 0.0008) genotype. Men carriers of the genotype had poor PFS (HR 3.78, 95% CI 1.30-11.0) than others. For women, shorter PFS was associated with TP53 GC or CC (61.4 vs. 80.8%, P = 0.01) and TP53 GC or CC + MDM2 TG or GG (59.1 vs. 85.4%, P = 0.01) genotypes at the same time. Women carriers of the genotypes had poor PFS (HR 2.46, 95% CI 1.19-5.09; HR 9.49, 95% CI 1.14-78.50) than others, respectively. Our data present, for the first time, preliminary evidence that inherited abnormalities on TP53, MDM2 and BCL2 genes, enrolled in apoptosis pathways, have a pivotal role in differences of outcomes in women and men with CM.

Carlson JA, Caldeira Xavier JC, Tarasen A, et al.
Next-Generation Sequencing Reveals Pathway Activations and New Routes to Targeted Therapies in Cutaneous Metastatic Melanoma.
Am J Dermatopathol. 2017; 39(1):1-13 [PubMed] Related Publications
BACKGROUND: Comprehensive genomic profiling of clinical samples by next-generation sequencing (NGS) can identify one or more therapy targets for the treatment of metastatic melanoma (MM) with a single diagnostic test.
METHODS: NGS was performed on hybridization-captured, adaptor ligation-based libraries using DNA extracted from 4 formalin-fixed paraffin-embedded sections cut at 10 microns from 30 MM cases. The exons of 182 cancer-related genes were fully sequenced using the Illumina HiSeq 2000 at an average sequencing depth of 1098X and evaluated for genomic alterations (GAs) including point mutations, insertions, deletions, copy number alterations, and select gene fusions/rearrangements. Clinically relevant GAs (CRGAs) were defined as those identifying commercially available targeted therapeutics or therapies in registered clinical trials.
RESULTS: The 30 American Joint Committee on Cancer Stage IV MM included 17 (57%) male and 13 (43%) female patients with a mean age of 59.5 years (range 41-83 years). All MM samples had at least 1 GA, and an average of 2.7 GA/sample (range 1-7) was identified. The mean number of GA did not differ based on age or sex; however, on average, significantly more GAs were identified in amelanotic and poorly differentiated MM. GAs were most commonly identified in BRAF (12 cases, 40%), CDKN2A (6 cases, 20%), NF1 (8 cases, 26.7%), and NRAS (6 cases, 20%). CRGAs were identified in all patients, and represented 77% of the GA (64/83) detected. The median and mean CRGAs per tumor were 2 and 2.1, respectively (range 1-7).
CONCLUSION: Comprehensive genomic profiling of MM, using a single diagnostic test, uncovers an unexpectedly high number of CRGA that would not be identified by standard of care testing. Moreover, NGS has the potential to influence therapy selection and can direct patients to enter relevant clinical trials evaluating promising targeted therapies.

Bai M, Yu NZ, Long F, et al.
Effects of CDKN2A (p16INK4A/p14ARF) Over-Expression on Proliferation and Migration of Human Melanoma A375 Cells.
Cell Physiol Biochem. 2016; 40(6):1367-1376 [PubMed] Related Publications
OBJECTIVE: This study aims to investigate the effects of CDKN2A (p16INK4A/p14ARF) over-expression on the proliferation and migration of human melanoma A375 cells.
METHODS: Melanoma tissues and pigmented nevi tissues were collected. Human melanoma A375 cells were transfected by CDKN2A (p16INK4A) and CDKN2A (p14ARF) over-expressing vectors and then assigned into blank, negative control (NC), p16INK4A and p14ARF groups. The expression of CDKN2A (p16INK4A) and CDKN2A (p14ARF) mRNA and protein was detected by qRT-PCR and Western blotting. CCK-8, flow cytometry and Transwell assays were applied to observe cell proliferation, the cell cycle and apoptosis, and migration and invasion, respectively. The model of subcutaneous xenografts in nude mice was established to measure cell growth in vivo.
RESULTS: Compared with pigmented nevi tissues, CDKN2A (p16INK4A) and CDKN2A (p14ARF) mRNA and protein expression were significantly decreased in melanoma tissues. CDKN2A (p16INK4A) and CDKN2A (p14ARF) over-expression inhibited proliferation, migration, invasion and progression from G0/G1 to S phase of A375 cells and xenograft tumor growth, but promoted apoptosis.
CONCLUSION: Our study demonstrated that over-expression of CDKN2A (p16INK4A) and CDKN2A (p14ARF) suppressed proliferation and migration of human melanoma A375 cells.

Mahalingam M
NF1 and Neurofibromin: Emerging Players in the Genetic Landscape of Desmoplastic Melanoma.
Adv Anat Pathol. 2017; 24(1):1-14 [PubMed] Related Publications
Neurofibromatosis type I (NF1), a monogenic disorder with an autosomal dominant mode of inheritance, is caused by alterations in the NF1 gene which codes for the protein neurofibromin. Functionally, NF1 is a tumor suppressor as it is GTPase-activating protein that negatively regulates the MAPK pathway. More recently, much attention has focused on the role of NF1 and neurofibromin in melanoma as mutations in NF1 have been found to constitute 1 of the 4 distinct genomic categories of melanoma, with the other 3 comprising BRAF, NRAS, and "triple-wild-type" subtypes. In this review, we parse the literature on NF1 and neurofibromin with a view to clarifying and gaining a better understanding of their precise role/s in melanomagenesis. We begin with a historic overview, followed by details regarding structure and function and characterization of neural crest development as a model for genetic reversion in neoplasia. Melanogenesis in NF1 sets the stage for the discussion on the roles of NF1 and neurofibromin in neural crest-derived neoplasms including melanoma with particular emphasis on NF1 and neurofibromin as markers of melanocyte dedifferentiation in desmoplastic melanoma.

Atkinson V, Long GV, Menzies AM, et al.
Optimizing combination dabrafenib and trametinib therapy in BRAF mutation-positive advanced melanoma patients: Guidelines from Australian melanoma medical oncologists.
Asia Pac J Clin Oncol. 2016; 12 Suppl 7:5-12 [PubMed] Related Publications
BRAF mutations occur commonly in metastatic melanomas and inhibition of mutant BRAF and the downstream kinase MEK results in rapid tumor regression and prolonged survival in patients. Combined therapy with BRAF and MEK inhibition improves response rate, progression free survival and overall survival compared with single agent BRAF inhibition, and reduces the skin toxicity that is seen with BRAF inhibitor monotherapy. However, this combination is associated with an increase in other toxicities, particularly drug-related pyrexia, which affects approximately 50% of patients treated with dabrafenib and trametinib (CombiDT). We provide guidance on managing adverse events likely to arise during treatment with combination BRAF and MEK inhibition with CombiDT: pyrexia, skin conditions, fatigue; and discuss management of CombiDT during surgery and radiotherapy. By improving tolerability and in particular preventing unnecessary treatment cessations or reduction in drug exposure, best outcomes can be achieved for patients undergoing CombiDT therapy.

Gambichler T, Kohsik C, Höh AK, et al.
Expression of PIWIL3 in primary and metastatic melanoma.
J Cancer Res Clin Oncol. 2017; 143(3):433-437 [PubMed] Related Publications
PURPOSE: The PIWI-interacting RNA machinery in malignant melanoma (MM) has not been sufficiently studied. We aimed to investigate the PIWIL3 expression profiles in primary melanomas and metastases of MM including a correlation with clinical data.
METHODS: We studied 161 primary melanomas, 45 lymph node metastases, and 16 distant metastases of 183 patients with MM. We used immunohistochemistry to assess PIWIL3 protein expression in situ. The relationship between the immunoreactivity of PIWIL3 and clinical data was statistically evaluated.
RESULTS: We observed a significantly (P = 0.000059) higher median immunoreactivity score in primary melanomas (4.9; range, 0.1-6), lymph node metastases (5.1; range, 3.3-6), and distant metastases (5.6; range, 4.5-6). PIWIL3 was expressed significantly higher (P = 0.0002) in primary nodular melanomas and acral melanomas (5.2; range, 3.4-6) when compared to other melanoma subtypes (4.7; range, 0.1-6). On univariate analysis, a significant positive correlation was observed between primary melanoma PIWIL3 expression and tumor thickness (r = 0.2; P = 0.014). On univariate and multivariate analysis, PIWIL3 did not prove to be an independent predictor for melanoma relapse or death.
CONCLUSIONS: Our data indicate that PIWIL3 protein expression is elevated in more aggressive primary MM and metastatic disease. As also observed in other malignancies, PIWIL3 seems to play a role in MM progression.

Cui L, Li Y, Lv X, et al.
Expression of MicroRNA-301a and its Functional Roles in Malignant Melanoma.
Cell Physiol Biochem. 2016; 40(1-2):230-244 [PubMed] Related Publications
BACKGROUND/AIMS: Although microRNA-301a has been reported to function as an oncogene in many human cancers, the roles of miR-301a in malignant melanoma (MM) is unclear. The present study aims to investigate the functional roles of miR-301a in MM and its possible molecular mechanisms.
METHODS: Quantitative real-time PCR (qRT-PCR) assay was performed to detect the expression of miR-301a in MM tissues, and analyze its correlation with metastasis and prognosis of MM patients. In vitro, miR-301a was ectopically expressed using overexpression and knock-down strategies, and the effects of miR-301a expression on growth, apoptosis, migration, invasion and chemosensitivity of MM cells were further investigated. Furthermore, the potential and functional target gene was identified by luciferase reporter, qRT-PCR, Western blot assays.
RESULTS: We showed that the expression of miR-301a was significantly upregulated in MM tissues, and upregulation of miR-301a correlated with metastasis and poor prognosis of MM patients. Transfection of miR-301a/inhibitor significantly inhibited growth, colony formation, migration, invasion and enhanced apoptosis and chemosensitivity in MM cells, while transfection of miR-301a/mimic could induce the inverse effects on phenotypes of MM cells. Luciferase reporter, qRT-PCR and Western blot assays showed that phosphatase and tensin homolog (PTEN) was a direct and functional target of miR-301a. It was also observed that the Akt and FAK signaling pathways were involved in miR-301/PTEN-promoting MM progression.
CONCLUSION: Taken together, our study suggests that miR-301a may be used as a potential therapeutic target in the treatment of human MM.

Cheng G, He J, Zhang L, et al.
HIC1 modulates uveal melanoma progression by activating lncRNA-numb.
Tumour Biol. 2016; 37(9):12779-12789 [PubMed] Related Publications
Uveal melanoma (UM) is the most common primary intraocular cancer in adults. Although the diagnosis modality of primary UM was improved significantly, there are currently no effective therapies for metastatic UM. Hypermethylated in cancer 1 (HIC1) is frequently deleted or epigenetically silenced in various human cancers. However, the role and mechanism of HIC1 in UM is still unclear. In this study, we found that HIC1 acted as a tumor suppressor and that its expression was downregulated in UM. Functional studies demonstrated that ectopic expression of HIC1 in UM cells inhibited cell proliferation and invasion. Moreover, through long non-coding RNA (lncRNA) microarray and real-time PCR, we found that expression of lncRNA-numb was activated by HIC1 in UM. The results provide evidence that lncRNA-numb is a newly proposed tumor suppressor that is involved in HIC1-induced phenotypes. Taken together, our studies of UM reveal a critical role of HIC1 in the regulation of tumorigenesis, at least partly through its downstream target, lncRNA-numb, and provide a potential therapeutic target for UM.

Cockerell CJ, Tschen J, Evans B, et al.
The influence of a gene expression signature on the diagnosis and recommended treatment of melanocytic tumors by dermatopathologists.
Medicine (Baltimore). 2016; 95(40):e4887 [PubMed] Free Access to Full Article Related Publications
It is well documented that histopathologic examination is sometimes inadequate for accurate and reproducible diagnosis of certain melanocytic neoplasms. Recently, a 23-gene expression signature has been clinically validated as an adjunctive diagnostic test to differentiate benign nevi from malignant melanomas. This study aimed to quantify the impact of this test on diagnosis and treatment recommendations made by dermatopathologists.Diagnostically challenging melanocytic lesions encountered during routine dermatopathology practice were submitted for gene expression testing and received a melanoma diagnostic score (MDS). Submitting dermatopathologists completed a survey documenting pre-test diagnosis, level of diagnostic confidence, and recommendations for treatment. The survey was repeated after receiving the MDS. Changes between the pre- and post-test surveys were analyzed retrospectively.When the MDS was available as part of a comprehensive case evaluation in diagnostically challenging cases, definitive diagnoses were increased by 56.6% for cases that were initially indeterminate and changes in treatment recommendations occurred in 49.1% of cases. Treatment recommendations were changed to align with the test result in 76.6% of diagnostically challenging cases.The MDS impacts diagnosis and treatment recommendations by dermatopathologists confronted with diagnostically challenging melanocytic lesions. Increased data are needed in order to completely understand how use of the MDS will translate from dermatopathology to clinical practice.

Manfredini M, Pellacani G, Losi L, et al.
Desmoplastic melanoma: a challenge for the oncologist.
Future Oncol. 2017; 13(4):337-345 [PubMed] Related Publications
AIM: To evaluate clinical, pathologic and genetic features of desmoplastic melanoma (DM).
MATERIALS & METHODS: Analysis of all DM records from 1991 to 2015.
RESULTS: The most common location of DMs was the head and neck (69%); median age and follow-up were 60.5 and 7.3 years, respectively. A familial predisposition for DMs and others malignancies was analyzed. Thin Breslow thickness (<4.5 mm) was associated with an intraepidermal component or a previous lentigo maligna, whereas high Breslow thickness (>4.5 mm) was observed in 'pure' DM.
CONCLUSION: DM could progress from an early phase, characterized by an intraepidermal component, to late phase, characterized by a dermal nodule. This hypothesis correlates with melanoma genetic and NF1 mutation, which could be an early event in the progression of DM.

Francis JH, Levin AM, Abramson DH
Update on Ophthalmic Oncology 2014: Retinoblastoma and Uveal Melanoma.
Asia Pac J Ophthalmol (Phila). 2016 Sep-Oct; 5(5):368-82 [PubMed] Related Publications
PURPOSE: The aim of this study was to review peer-reviewed articles on ophthalmic oncology (specifically retinoblastoma and uveal melanoma) published from January to December 2014.
DESIGN: This study is a literature review.
METHODS: The terms retinoblastoma and uveal melanoma were used in a MEDLINE literature search. Abstracts were studied, and the most relevant articles were selected for inclusion and further in-depth review.
RESULTS: In retinoblastoma, more eyes are being salvaged due to intravitreal melphalan. The year 2014 marks a deepening in our understanding of the biological basis of the disease and the cell of origin. Knowledge on the genetic underpinnings of uveal melanoma has broadened to include other pathways, interactions, and potential therapeutic targets.
CONCLUSIONS: In 2014, there were valuable advancements in our knowledge of retinoblastoma and uveal melanoma. Some of these resulted in improved patient management.

Luo C, Lim JH, Lee Y, et al.
A PGC1α-mediated transcriptional axis suppresses melanoma metastasis.
Nature. 2016; 537(7620):422-426 [PubMed] Article available free on PMC after 15/03/2017 Related Publications
Melanoma is the deadliest form of commonly encountered skin cancer because of its rapid progression towards metastasis. Although metabolic reprogramming is tightly associated with tumour progression, the effect of metabolic regulatory circuits on metastatic processes is poorly understood. PGC1α is a transcriptional coactivator that promotes mitochondrial biogenesis, protects against oxidative stress and reprograms melanoma metabolism to influence drug sensitivity and survival. Here, we provide data indicating that PGC1α suppresses melanoma metastasis, acting through a pathway distinct from that of its bioenergetic functions. Elevated PGC1α expression inversely correlates with vertical growth in human melanoma specimens. PGC1α silencing makes poorly metastatic melanoma cells highly invasive and, conversely, PGC1α reconstitution suppresses metastasis. Within populations of melanoma cells, there is a marked heterogeneity in PGC1α levels, which predicts their inherent high or low metastatic capacity. Mechanistically, PGC1α directly increases transcription of ID2, which in turn binds to and inactivates the transcription factor TCF4. Inactive TCF4 causes downregulation of metastasis-related genes, including integrins that are known to influence invasion and metastasis. Inhibition of BRAF(V600E) using vemurafenib, independently of its cytostatic effects, suppresses metastasis by acting on the PGC1α-ID2-TCF4-integrin axis. Together, our findings reveal that PGC1α maintains mitochondrial energetic metabolism and suppresses metastasis through direct regulation of parallel acting transcriptional programs. Consequently, components of these circuits define new therapeutic opportunities that may help to curb melanoma metastasis.

Zhao J, Zeng X, Song P, et al.
AKT1 as the PageRank hub gene is associated with melanoma and its functional annotation is highly related to the estrogen signaling pathway that may regulate the growth of melanoma.
Oncol Rep. 2016; 36(4):2087-93 [PubMed] Related Publications
In order to detect the disease-associated genes and their gene interaction function and association with melanoma mechanisms, we identified a total of 1,310 differentially expressed genes (DEGs) from the Gene Expression Omnibus database GSE3189 with FDR <0.01 and |logFC| >2 using the R package. After constructing the gene interaction network by STRING with the selected DEGs, we applied a statistical approach to identify the topological hub genes with PageRank score. Forty-four genes were identified in this network and AKT1 was selected as the most important hub gene. The AKT1 gene encodes a serine‑threonine protein kinase (AKT). High expression of AKT is involved in the resistance of cell apoptosis as well as adaptive resistance to treatment in melanoma. Our results indicated that AKT1 with a higher expression in melanoma showed enriched binding sites in the negative regulation of response to external stimulus, which enables cells to adapt to changes in external stimulation for survival. Another finding was that AKT regulated the lipid metabolic process and may be involved in melanoma progression and promotion of tumor growth through gene enrichment function analysis. Two highlighted pathways were detected in our study: i) the estrogen signaling pathway modulates the immune tolerance and resistance to cell apoptosis, which contributes to the growth of melanoma and ii) the RAP1 signaling pathway which regulates focal adhesion (FA) negative feedback to cell migration and invasion in melanoma. Our studies highlighted the top differentially expressed gene AKT1 and its correlation with the estrogen signaling and RAP1 signaling pathways to alter the proliferation and apoptosis of melanoma cells. Analysis of the enrichment functions of genes associated with melanoma will help us find the exact mechanism of melanoma and advance the full potential of newly targeted cancer therapy.

Chen TL, Chang JW, Hsieh JJ, et al.
A Sensitive Peptide Nucleic Acid Probe Assay for Detection of BRAF V600 Mutations in Melanoma.
Cancer Genomics Proteomics. 2016 09-10; 13(5):381-6 [PubMed] Article available free on PMC after 15/03/2017 Related Publications
Mutated v-Raf murine sarcoma viral oncogene homolog B (BRAF) is an important biomarker for the prediction of therapeutic efficacy of several anticancer drugs. The detection of BRAF mutation faces two challenges: Firstly, there are multiple types of mutations, and secondly, tumor samples usually contain various amounts of wild-type, normal tissues. Here, we describe a newly established method for sensitive detection of multiple types of BRAF V600 mutations in excess wild-type background. The method introduced a fluorophore-tagged peptide nucleic acid (PNA) to serve as both polymerase chain reaction (PCR) clamp and sensor probe, which inhibited the amplification of wild-type templates during PCR and revealed multiple types of mutant signals during melting analysis. We demonstrated the design and optimization process of the method, and applied it in the detection of BRAF mutations in 49 melanoma samples. This PNA probe assay method detected three types of mutations in 17 samples, and was much more sensitive than conventional PCR plus Sanger sequencing.

Rapisuwon S, Busam KJ, Parks K, et al.
Discordance Between Cobas BRAF V600 Testing and VE1 Immunohistochemistry in a Melanoma Patient With Bone Marrow Metastases.
Am J Dermatopathol. 2016; 38(9):687-9 [PubMed] Related Publications
False negative result remains an ongoing problem in direct gene sequencing of cancers. It is important to use the appropriate mutation detection method most appropriate to each circumstance and the available tissue. Here, we report a patient with melanoma of unknown primary with metastases to spleen and bone marrow, who was tested negative for Cobas BRAF V600E mutation, whose cancer progressed on antiprogrammed death 1 (PD1) receptor monoclonal antibody therapy. Subsequent VE1 immunohistochemistry was positive for BRAF V600E mutation, and the tumor responded dramatically to v-Raf murine sarcoma viral oncogene homolog B (BRAF)/Mitogen-activated protein kinase inhibitor combination therapy. This demonstrates how alternative BRAF testing methodology could produce results that can influence treatment choice and the outcome.

Huang WK, Kuo TT, Wu CE, et al.
A comparison of immunohistochemical and molecular methods used for analyzing the BRAF V600E gene mutation in malignant melanoma in Taiwan.
Asia Pac J Clin Oncol. 2016; 12(4):403-408 [PubMed] Related Publications
AIMS: The BRAF V600 mutation has been shown to be clinically meaningful in terms of both the prognosis and sensitivity of BRAF inhibitors in patients with metastatic melanoma. Recently, a BRAF V600E mutation-specific antibody, VE1, was generated for the detection of tumors bearing BRAF V600E mutations. To determine the clinical value of immunohistochemical testing, we compared the prevalence of mutant BRAF detected by VE1 with direct sequencing results.
METHODS: Paraffin-embedded, formalin-fixed melanoma biopsies were analyzed for the BRAF mutation status by immunohistochemistry with the VE1 antibody. Sanger sequencing was applied to verify the immunohistochemical results.
RESULTS: A total of 73 melanoma cases with tumor samples from primary lymph nodes and metastatic sites were selected for this study. Direct sequencing demonstrated that 18 of 73 cases (24.6%) harbored the BRAF V600 mutation: 17 with V600E and one with V600K. All 18 tumors shown to harbor the BRAF V600E/K mutations were VE1-positive. One additional case was false-positive for VE1. The sensitivity and specificity of VE1 was 100% (18/18) and 98% (54/55), respectively. The overall concordance between the immunohistochemical method and direct sequencing was excellent (98.6%).
CONCLUSIONS: Our findings demonstrate that immunohistochemical analysis using VE1 constitutes a highly sensitive test for the detection of BRAF mutations and suggest that this cost-effective method is suitable as a rapid diagnostic approach complementary to molecular testing.

Ding Y, Li X, Hong D, et al.
Silence of MACC1 decreases cell migration and invasion in human malignant melanoma through inhibiting the EMT.
Biosci Trends. 2016; 10(4):258-64 [PubMed] Related Publications
Metastasis-associated colon cancer 1 (MACC1) has been demonstrated to promote metastasis of several cancers via regulating epithelial-mesenchymal transition (EMT). However, its biological behavior in human malignant melanoma remains unclear. In this study, MACC1 downregulation was established in two melanoma cell lines (A375 and G361 cells) using RNA interference, as confirmed by quantitative real time PCR (qRT-PCR) and Western blot analysis. Subsequently, we investigated the effects of MACC1 silencing on cell mobility, migration and invasion using scratch wound and Transwell assays. Our results indicated that knockdown of MACC1 significantly suppressed cell migration and invasion ability of both melanoma cell lines. Moreover, downregulation of MACC1 upregulated E-cadherin, N-cadherin and Vimentin, as confirmed by qRT-PCR, Western blot and immunofluorescent Staining analysis. These findings suggest MACC1 might serve as a new molecular target for the treatment of melanoma by a novel mechanism underlying the metastasis of melanoma cells.

Cavalieri S, Di Guardo L, Cimminiello C, et al.
Combined therapy with dabrafenib and trametinib in BRAF-mutated metastatic melanoma in a real-life setting: the INT Milan experience.
Tumori. 2016; 102(5):501-507 [PubMed] Related Publications
PURPOSE: Combination therapy with dabrafenib and trametinib is safer and more effective than BRAF inhibitor-based monotherapy for metastatic melanoma.
METHODS: We retrospectively analyzed BRAF-mutated metastatic melanoma patients treated at our institution with daily oral dabrafenib 300 mg and trametinib 2 mg from November 2013 to April 2016. This clinical record included both untreated and previously treated stage IV melanomas. Physical examination and laboratory examinations were performed monthly and disease re-evaluations were performed every 3 months.
RESULTS: A total of 48 patients (24 male, 24 female) with BRAF-mutated metastatic melanoma received dabrafenib and trametinib; median age was 48 years (range 23-75). Median follow-up was 362.5 days (range 72-879). Best overall response rate consisted of 6.2% (3 patients) complete response, 64.6% (31) partial response, and 25% (12) stable disease; median time to best response was 11 weeks (range 5.7-125.5). Progression of disease was seen in 19 patients (39.6%), with median time to progression (TTP) of 26 weeks (range 8-54). A total of 15 patients (31.2%) died due to progression of disease. Median progression-free survival and median overall survival were not reached. To date, 30 patients (62.5%) are still under treatment. A total of 27 (56.2%) patients had at least one adverse event (AE); grade 3-4 AEs were seen in 4 cases (8.3%). The main toxicities were fever (25%), skin rash (14.6%), arthralgias (10.4%), and aspartate aminotransferase/alanine aminotransferase increase (8.3%). Treatment dose was reduced in 7 subjects (14.6%), with only one case of discontinuation due to AE.
CONCLUSIONS: Our data, using combined targeted therapy, are in line with the scientific literature in terms of both safety and effectiveness in a real-life setting.

Qiu HJ, Lu XH, Yang SS, et al.
MiR-769 promoted cell proliferation in human melanoma by suppressing GSK3B expression.
Biomed Pharmacother. 2016; 82:117-23 [PubMed] Related Publications
MicroRNAs (miRNAs) are short, non-coding RNAs with post-transcriptional regulatory function, playing crucial roles in cancer development and progression of human melanoma. Previous studies have indicated that miR-769 was implicated in diverse biological processes. However, the underlying mechanism of miR-769 in human melanoma has not been intensively investigated. In this present study, we aimed to investigate the role of miR-769 and its target genes in human melanoma. We found that miR-769 expression was strongly increased in human melanoma cells and clinical tissues compared with their corresponding controls. Overexpression of miR-769 promoted cell proliferation in human melanoma cell line A375, whereas miR-769-in reverses the function. Glycogen synthase kinase-3 Beta (GSK3B), a potential target gene of miR-769, and was validated by luciferase assay. Further studies revealed that miR-769 regulated cell proliferation of human melanoma by directly suppressing GSK3B expression and the knockdown of GSK3B expression reversed the effect of miR-769-in on human melanoma cell proliferation. In summary, our data demonstrated that miR-769 might act as a tumor promoter by targeting GSK3B during development of human melanoma.

Chen X, Yang M, Hao W, et al.
Differentiation-inducing and anti-proliferative activities of isoliquiritigenin and all-trans-retinoic acid on B16F0 melanoma cells: Mechanisms profiling by RNA-seq.
Gene. 2016; 592(1):86-98 [PubMed] Related Publications
Melanoma is a cancer that arises from melanocytes, specialized pigmented cells that are found predominantly in the skin. The incidence of malignant melanoma has significantly increased over the last decade. With the development of therapy, the survival rate of some kind of cancer has been improved greatly. But the treatment of melanoma remains unsatisfactory. Much of melanoma's resistance to traditional chemotherapy is believed to arise intrinsically, by virtue of potent growth and cell survival-promoting genetic alteration. Therefore, significant attention has recently been focused on differentiation therapy, as well as differentiation inducer compounds. In previous study, we found isoliquiritigenin (ISL), a natural product extracted from licorice, could induce B16F0 melanoma cell differentiation. Here we investigated the transcriptional response of melanoma differentiation process induced by ISL and all-trans-retinoic acid (RA). Results showed that 390 genes involves in 201 biochemical pathways were differentially expressed in ISL treatment and 304 genes in 193 pathways in RA treatment. Differential expressed genes (DGEs, fold-change (FC)≥10) with the function of anti-proliferative and differentiation inducing indicated a loss of grade malignancy characteristic. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated glutathione metabolism, glycolysis/gluconeogenesis and pentose phosphate pathway were the top three relative pathway perturbed by ISL, and mitogen-activated protein kinase (MAPK) signaling pathway was the most important pathway in RA treatment. In the analysis of hierarchical clustering of DEGs, we discovered 72 DEGs involved in the process of drug action. We thought Cited1, Tgm2, Xaf1, Cd59a, Fbxo2, Adh7 may have critical role in the differentiation of melanoma. The evidence displayed herein confirms the critical role of reactive oxygen species (ROS) in melanoma pathobiology and provides evidence for future targets in the development of next-generation biomarkers and therapeutics.

Zhao Y, Zhang B, Lei Y, et al.
Knockdown of USP39 induces cell cycle arrest and apoptosis in melanoma.
Tumour Biol. 2016; 37(10):13167-13176 [PubMed] Related Publications
The spliceosome machinery composed of multimeric protein complexes guides precursor messenger RNAs (mRNAs) (pre-mRNAs) splicing in eukaryotic cells. Spliceosome components have been shown to be downregulated in cancer and could be a promising molecular target for anticancer therapy. The ubiquitin-specific protease 39 (USP39) is essential for pre-mRNA splicing, and upregulated USP39 expression is noted in a variety of cancers. However, the role of USP39 in the development and progression of melanoma remains unclear. In the present study, USP39 expression was found to be increased in melanoma tissues compared with that in nevus tissues. USP39 silencing via lentivirus-mediated short hairpin RNA (shRNA) significantly suppressed melanoma cell proliferation, induced G0/G1 cell cycle phase arrest, and increased apoptosis in vitro. Moreover, USP39 knockdown suppressed melanoma tumor growth in a xenograft model. In addition, USP39 silencing was associated with the increased expressions of p21, p27, and Bax. Furthermore, the inhibition of USP39 expression decreased the phosphorylation of extracellular signal-regulated kinase (ERK)1/2, indicating that ERK signaling pathways might be involved in the regulation of melanoma cell proliferation by USP39. Our findings suggest that USP39 may play crucial roles in the development and pathogenesis of melanoma, and it may serve as a potential therapeutic target for melanoma.

Triozzi PL, Achberger S, Aldrich W, et al.
Association of tumor and plasma microRNA expression with tumor monosomy-3 in patients with uveal melanoma.
Clin Epigenetics. 2016; 8:80 [PubMed] Article available free on PMC after 15/03/2017 Related Publications
BACKGROUND: Epigenetic events mediated by methylation and histone modifications have been associated with the development of metastasis in patients with uveal melanoma. The role of epigenetic events mediated by microRNA (miR) is less clear. Tumor and plasma miR expression was examined in patients with primary uveal melanoma with tumor monosomy-3, a predictor of metastasis.
RESULTS: miR profiling of tumors by microarray found six miRs over-expressed and 19 under-expressed in 33 tumors with monosomy-3 compared to 22 without. None of the miRs differentially expressed in tumors with and without monosomy-3 was differentially expressed in tumors with and without tumor infiltrating lymphocytes. Tumors manifesting monosomy-3 were also characterized by higher levels of TARBP2 and DDX17 and by lower levels of XPO5 and HIWI, miR biogenesis factors. miR profiling of plasma by a quantitative nuclease protection assay found elevated levels of 11 miRs and reduction in four in patients with tumor monosomy-3. Only three miRs differentially expressed in the tumor arrays were detectable in plasma. miRs implicated in uveal melanoma development were not differentially expressed. Elevated plasma levels in patients with tumor monosomy-3 of miR-92b, identified in the tumor array, and of miR-199-5p and miR-223, identified in the plasma array, were confirmed by quantitative real-time polymerase chain reaction. Levels were also higher in patients compared to normal controls.
CONCLUSIONS: These results support a role for epigenetic mechanisms in the development of metastasis in patients with uveal melanoma and the analysis of miRs as biomarkers of metastatic risk. They also suggest that potentially useful blood miRs may be derived from the host response as well as the tumor.

Banerjee A, Ray S
Structural insight with mutational impact on tyrosinase and PKC-β interaction from Homo sapiens: Molecular modeling and docking studies for melanogenesis, albinism and increased risk for melanoma.
Gene. 2016; 592(1):99-109 [PubMed] Related Publications
Human tyrosinase, is an important protein for biosynthetic pathway of melanin. It was studied to be phosphorylated and activated by protein kinase-C, β-subunit (PKC-β) through earlier experimentations with in vivo evidences. Documentation documents that mutation in two essentially vital serine residues in C-terminal end of tyrosinase leads to albinism. Due to the deficiency of protective shield like enzyme; melanin, albinos are at an increased peril for melanoma and other skin cancers. So, computational and residue-level insight including a mutational exploration with evolutionary importance into this mechanism lies obligatory for future pathological and therapeutic developments. Therefore, functional tertiary models of the relevant proteins were analyzed after satisfying their stereo-chemical features. Evolutionarily paramount residues for the activation of tyrosinase were perceived via multiple sequence alignment phenomena. Mutant-type tyrosinase protein (S98A and S102A) was thereby modeled, maintaining the wild-type proteins' functionality. Furthermore, this present comparative study discloses the variation in the stable residual participation (for mutant-type and wild-type tyrosinase-PKCβ complex). Mainly, an increased number of polar negatively charged residues from the wild-type tyrosinase participated with PKC-β, predominantly. Fascinatingly supported by evaluation of statistical significances, mutation even led to a destabilizing impact in tyrosinase accompanied by conformational switches with a helix-to-coil transition in the mutated protein. Even the allosteric sites in the protein got poorly hampered upon mutation leading to weaker tendency for binding partners to interact.

Zaretsky JM, Garcia-Diaz A, Shin DS, et al.
Mutations Associated with Acquired Resistance to PD-1 Blockade in Melanoma.
N Engl J Med. 2016; 375(9):819-29 [PubMed] Article available free on PMC after 01/04/2017 Related Publications
BACKGROUND: Approximately 75% of objective responses to anti-programmed death 1 (PD-1) therapy in patients with melanoma are durable, lasting for years, but delayed relapses have been noted long after initial objective tumor regression despite continuous therapy. Mechanisms of immune escape in this context are unknown.
METHODS: We analyzed biopsy samples from paired baseline and relapsing lesions in four patients with metastatic melanoma who had had an initial objective tumor regression in response to anti-PD-1 therapy (pembrolizumab) followed by disease progression months to years later.
RESULTS: Whole-exome sequencing detected clonal selection and outgrowth of the acquired resistant tumors and, in two of the four patients, revealed resistance-associated loss-of-function mutations in the genes encoding interferon-receptor-associated Janus kinase 1 (JAK1) or Janus kinase 2 (JAK2), concurrent with deletion of the wild-type allele. A truncating mutation in the gene encoding the antigen-presenting protein beta-2-microglobulin (B2M) was identified in a third patient. JAK1 and JAK2 truncating mutations resulted in a lack of response to interferon gamma, including insensitivity to its antiproliferative effects on cancer cells. The B2M truncating mutation led to loss of surface expression of major histocompatibility complex class I.
CONCLUSIONS: In this study, acquired resistance to PD-1 blockade immunotherapy in patients with melanoma was associated with defects in the pathways involved in interferon-receptor signaling and in antigen presentation. (Funded by the National Institutes of Health and others.).

Wang A, Papneja A, Hyrcza M, et al.
Gene of the month: BAP1.
J Clin Pathol. 2016; 69(9):750-3 [PubMed] Related Publications
The BAP1 gene (BRCA1-associated protein 1) is a tumour suppressor gene that encodes a deubiquitinating enzyme (DUB), regulating key cellular pathways, including cell cycle, cellular differentiation, transcription and DNA damage response. Germline BAP1 mutations cause a novel cancer syndrome characterised by early onset of multiple atypical Spitz tumours and increased risk of uveal and cutaneous melanoma, mesothelioma, renal cell carcinoma and various other malignancies. Recognising the clinicopathological features of specific BAP1-deficient tumours is crucial for early screening/tumour detection, with significant impact on patient outcome.

Chen Y, Zhang Z, Luo C, et al.
MicroRNA-18b inhibits the growth of malignant melanoma via inhibition of HIF-1α-mediated glycolysis.
Oncol Rep. 2016; 36(1):471-9 [PubMed] Related Publications
MicroRNAs (miRs) have been demonstrated to play critical roles in the development and progression of malignant melanoma (MM). However, the exact role and underlying mechanism of miR-18b in MM growth remains unclear. In the present study, real-time PCR data indicated that miR-18b was significantly downregulated in MM tissues compared to their matched adjacent non-tumor tissues. Low miR-18b expression was significantly associated with the tumor thickness and stage, although no significant association was observed between the miR-18b expression and the age, gender, or lymph node metastasis. Besides, miR-18b was also significantly downregulated in MM B16 and A375 cells compared to normal skin HACAT cells. Ectopic expression of miR-18b decreased the proliferation of A375 and B16 cells, while induced a remarkable cell cycle arrest at G1 stage. Besides, miR-18b overexpression also inhibited the glycolysis in A375 and B16 cells. HIF-1α, a key regulator in glycolysis, was then identified as a target gene of miR-18b, and its expression was negatively mediated by miR-18b in A375 and B16 cells. Overexpression of HIF-1α rescued the suppressive effect of miR-18b on MM cell proliferation and glycolysis. In vivo study further showed that overexpression of miR-18b inhibited the MM growth as well as the tumor-related death, accompanied with HIF-1α downregulation. Taken together, the present study suggests that miR-18b inhibits the growth of MM cells in vitro and in vivo through directly targeting HIF-1α.

Larsen AC
Conjunctival malignant melanoma in Denmark: epidemiology, treatment and prognosis with special emphasis on tumorigenesis and genetic profile.
Acta Ophthalmol. 2016; 94 Thesis 1:1-27 [PubMed] Related Publications
Conjunctival malignant melanoma is a rare disease associated with considerable mortality. Most published data have been based on case reports or series of referred patients. In addition, very little is known about the genetic and epigenetic profile of conjunctival melanoma and the resemblance to uveal, cutaneous and mucosal melanoma. The aim was to determine the incidence rate of conjunctival melanoma, and to relate clinicopathological features and treatment to prognosis. A further aim was to determine the prevalence of BRAF mutations in conjunctival melanoma, to determine whether BRAF mutations are early events in pathogenesis, and relate clinicopathological features and prognosis to BRAF-mutation status. Finally, we wanted to identify tumour-specific and prognostic microRNAs in conjunctival melanoma, and to compare these with the microRNA expression of other melanoma subtypes. In order to investigate these rare tumours, we studied all the conjunctival melanomas that had been surgically removed in Denmark over a period of 52 years (1960-2012). Tissue samples, clinical files, pathology reports and follow-up data were collected and re-evaluated. Using droplet digital polymerase chain reaction and immunohistochemistry, we investigated BRAF mutations; and using microRNA expression profiling, we investigated differentially expressed microRNAs. The overall incidence of conjunctival melanoma was 0.5/1 000 000/year, and it increased in Denmark over 52 years. The increase was mainly caused by an increase in older patients (>65 years) and bulbar lesions. Clinicopathological features significantly associated with a poor prognosis were extrabulbar location, involvement of adjacent tissue structures, tumour thickness exceeding 2 mm and local tumour recurrence. Patients undergoing incisional biopsy and/or treatment involving excision without adjuvant therapy fared worse than patients treated with excision and any type of adjuvant treatment. We found that 35% (39/110) of conjunctival melanomas were BRAF-mutated, and the incidence of BRAF mutations was constant over time. BRAF-mutation status corresponded in conjunctival melanoma and paired premalignant lesions. BRAF mutations were more frequent in males, in young patients, and in tumours with a sun-exposed tumour location (bulbar conjunctiva or caruncle), with a mixed or non-pigmented colour, with absence of primary acquired melanosis, and with origin in a nevus. Immunohistochemistry was able to accurately detect BRAF V600E mutations. In univariate analysis, distant metastatic disease was associated with BRAF mutations. No prognostic associations with BRAF mutations were identified in multivariate analyses. MicroRNA expression analysis revealed 25 tumour-specific microRNAs in conjunctival melanoma. Five possibly oncogenic miRNAs (miR-20b-5p, miR-146b-5p, miR-146a-5p, miR-506-3p and miR-509-3p) were up-regulated. Seven microRNAs (miR-30d-5p, miR-138-5p, miR-146a-5p, miR-500a-5p, miR-501-3p, miR-501-5p and miR-502-3p) were significantly and simultaneously up-regulated in both stage T1 and stage T2 tumours, and were associated with increased tumour thickness. The expression of the 25 tumour-specific microRNAs did not differ significantly between conjunctival melanoma and oral or nasal mucosal melanoma. In conclusion, the incidence of conjunctival melanoma increased in the Danish population from 1960 to 2012. From our findings of a distinct pattern of BRAF mutations and differentially expressed microRNAs, it is evident that conjunctival melanoma is closely related to cutaneous and other mucosal melanomas and bears less resemblance to uveal melanomas. This means that conjunctival melanoma patients may benefit from therapies that are effective for cutaneous and mucosal melanoma. Additionally, the identification of several up-regulated microRNAs may prove to be useful as prognostic or therapeutic targets in conjunctival melanoma.

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