Pancreatic Cancer

Overview

Pancreatic cancers are frequently associated with mutation of the KRAS oncogene and inactivating mutations of multiple tumor suppressor genes, particularly TP53, MADH4 (DPC4), CDKN2A (P16), and BRCA2. Also, overexpression of growth factors (EGF, TGF alpha, TGF beta 1-3, aFGF, bTGF) and their associated receptors are also common.

Familial clustering of pancreatic cancer has been reported, germline mutations of BRCA2 and CDKN2A predispose to pancreatic cancer. Mutations in the STk11gene also predisopse to pancreatic cancer in patients with Peutz-Jeghers Syndrome.

See also: Cancer of the Pancreas - clinical resources (22)

Literature Analysis

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

Tag cloud generated 08 August, 2015 using data from PubMed, MeSH and CancerIndex

Mutated Genes and Abnormal Protein Expression (188)

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
CDKN2A 9p21 ARF, MLM, P14, P16, P19, CMM2, INK4, MTS1, TP16, CDK4I, CDKN2, INK4A, MTS-1, P14ARF, P19ARF, P16INK4, P16INK4A, P16-INK4A Germline
-CDKN2A Mutation in Familial Pancreatic Cancer
-CDKN2A Mutation in Pancreatic Cancer
329
KRAS 12p12.1 NS, NS3, CFC2, KRAS1, KRAS2, RASK2, KI-RAS, C-K-RAS, K-RAS2A, K-RAS2B, K-RAS4A, K-RAS4B -KRAS and Pancreatic Cancer
383
MEN1 11q13 MEAI, SCG2 -MEN1 and Pancreatic Cancer
279
SMAD4 18q21.1 JIP, DPC4, MADH4, MYHRS -SMAD4 and Pancreatic Cancer
237
BRCA2 13q12.3 FAD, FACD, FAD1, GLM3, BRCC2, FANCD, PNCA2, FANCD1, XRCC11, BROVCA2 Germline
-BRCA2 mutations in Pancreatic Cancer
196
TP53 17p13.1 P53, BCC7, LFS1, TRP53 -TP53 and Pancreatic Cancer
126
MUC1 1q21 EMA, MCD, PEM, PUM, KL-6, MAM6, MCKD, PEMT, CD227, H23AG, MCKD1, MUC-1, ADMCKD, ADMCKD1, CA 15-3, MUC-1/X, MUC1/ZD, MUC-1/SEC Prognostic
-MUC1 overexpression in Pancreatic Cancer
85
CEACAM5 19q13.1-q13.2 CEA, CD66e -CEACAM5 and Pancreatic Cancer
79
MUC6 11p15.5 MUC-6 -MUC6 and Pancreatic Cancer
47
ACHE 7q22 YT, ACEE, ARACHE, N-ACHE -ACHE and Pancreatic Cancer
41
SSTR2 17q24 -SSTR2 and Pancreatic Cancer
40
CXCR4 2q21 FB22, HM89, LAP3, LCR1, NPYR, WHIM, CD184, LAP-3, LESTR, NPY3R, NPYRL, WHIMS, HSY3RR, NPYY3R, D2S201E -CXCR4 and Pancreatic Cancer
35
CCK 3p22.1 -CCK and Pancreatic Cancer
33
MUC4 3q29 ASGP, MUC-4, HSA276359 -MUC4 and Pancreatic Cancer
33
SMAD2 18q21.1 JV18, MADH2, MADR2, JV18-1, hMAD-2, hSMAD2 -SMAD2 and Pancreatic Cancer
31
GLI1 12q13.2-q13.3 GLI -GLI1 and Pancreatic Cancer
29
PRSS1 7q34 TRP1, TRY1, TRY4, TRYP1 -PRSS1 and Pancreatic Cancer
29
STK11 19p13.3 PJS, LKB1, hLKB1 -STK11 and Pancreatic Cancer
28
CFTR 7q31.2 CF, MRP7, ABC35, ABCC7, CFTR/MRP, TNR-CFTR, dJ760C5.1 -CFTR and Pancreatic Cancer
27
MUC5AC 11p15.5 TBM, leB, MUC5 -MUC5AC and Pancreatic Cancer
26
TGFBR1 9q22 AAT5, ALK5, ESS1, LDS1, MSSE, SKR4, ALK-5, LDS1A, LDS2A, TGFR-1, ACVRLK4, tbetaR-I -TGFBR1 and Pancreatic Cancer
26
SPINK1 5q32 TCP, PCTT, PSTI, TATI, Spink3 -SPINK1 and Pancreatic Cancer
25
PDX1 13q12.1 GSF, IPF1, IUF1, IDX-1, MODY4, PDX-1, STF-1, PAGEN1 -PDX1 and Pancreatic Cancer
24
GNAS 20q13.3 AHO, GSA, GSP, POH, GPSA, NESP, GNAS1, PHP1A, PHP1B, PHP1C, C20orf45 -GNAS and Pancreatic Cancer
23
TGFBR2 3p22 AAT3, FAA3, LDS2, MFS2, RIIC, LDS1B, LDS2B, TAAD2, TGFR-2, TGFbeta-RII -TGFBR2 and Pancreatic Cancer
23
ZEB1 10p11.2 BZP, TCF8, AREB6, FECD6, NIL2A, PPCD3, ZFHEP, ZFHX1A, DELTAEF1 -ZEB1 and Pancreatic Cancer
22
SPARC 5q31.3-q32 ON -SPARC and Pancreatic Cancer
18
S100A4 1q21 42A, 18A2, CAPL, FSP1, MTS1, P9KA, PEL98 -S100A4 and Pancreatic Cancer
17
EPCAM 2p21 ESA, KSA, M4S1, MK-1, DIAR5, EGP-2, EGP40, KS1/4, MIC18, TROP1, EGP314, HNPCC8, TACSTD1 -EPCAM and Pancreatic Cancer
17
RRM1 11p15.5 R1, RR1, RIR1 -RRM1 and Pancreatic Cancer
17
ANXA8 10q11.22 ANX8, CH17-360D5.2 -ANXA8 and Pancreatic Cancer
17
FHIT 3p14.2 FRA3B, AP3Aase -FHIT and Pancreatic Cancer
17
SLC29A1 6p21.1 ENT1 -SLC29A1 and Pancreatic Cancer
16
SIRT1 10q21.3 SIR2, hSIR2, SIR2L1 -SIRT1 and Pancreatic Cancer
16
CDX2 13q12.3 CDX3, CDX-3, CDX2/AS -CDX2 and Pancreatic Cancer
15
DAXX 6p21.3 DAP6, EAP1, BING2 -DAXX and Pancreatic Cancer
14
ATRX Xq21.1 JMS, SHS, XH2, XNP, ATR2, SFM1, RAD54, MRXHF1, RAD54L, ZNF-HX -ATRX and Pancreatic Cancer
14
ABCG2 4q22 MRX, MXR, ABCP, BCRP, BMDP, MXR1, ABC15, BCRP1, CD338, GOUT1, CDw338, UAQTL1, EST157481 -ABCG2 and Pancreatic Cancer
14
SMO 7q32.3 Gx, SMOH, FZD11 -SMO and Pancreatic Cancer
12
S100P 4p16 MIG9 -S100P and Pancreatic Cancer
12
PSCA 8q24.2 PRO232 -PSCA and Pancreatic Cancer
11
MAP2K4 17p12 JNKK, MEK4, MKK4, SEK1, SKK1, JNKK1, SERK1, MAPKK4, PRKMK4, SAPKK1, SAPKK-1 -MAP2K4 and Pancreatic Cancer
10
GATA6 18q11.1-q11.2 -GATA6 and Pancreatic Cancer
10
MARCO 2q14.2 SCARA2 -MARCO and Pancreatic Cancer
10
DUSP6 12q22-q23 HH19, MKP3, PYST1 -DUSP6 and Pancreatic Cancer
10
CCKBR 11p15.4 GASR, CCK-B, CCK2R -CCKBR and Pancreatic Cancer
10
CEACAM6 19q13.2 NCA, CEAL, CD66c -CEACAM6 and Pancreatic Cancer
9
VIP 6q25 PHM27 -VIP and Pancreatic Cancer
9
SSTR5 16p13.3 SS-5-R -SSTR5 and Pancreatic Cancer
9
SOX9 17q24.3 CMD1, SRA1, CMPD1 -SOX9 and Pancreatic Cancer
8
RHOC 1p13.1 H9, ARH9, ARHC, RHOH9 -RHOC expression in Pancreatic Cancer
8
RRM2 2p25-p24 R2, RR2, RR2M -RRM2 and Pancreatic Cancer
8
GADD45A 1p31.2 DDIT1, GADD45 -GADD45A and Pancreatic Cancer
8
ANXA5 4q27 PP4, ANX5, ENX2, RPRGL3, HEL-S-7 -ANXA5 and Pancreatic Cancer
7
L1CAM Xq28 S10, HSAS, MASA, MIC5, SPG1, CAML1, CD171, HSAS1, N-CAML1, NCAM-L1, N-CAM-L1 -L1CAM and Pancreatic Cancer
7
VAV1 19p13.2 VAV -VAV1 and Pancreatic Cancer
7
LGALS1 22q13.1 GBP, GAL1 -LGALS1 and Pancreatic Cancer
7
BNIP3 10q26.3 NIP3 -BNIP3 and Pancreatic Cancer
7
MUC5B 11p15.5 MG1, MUC5, MUC9, MUC-5B -MUC5B and Pancreatic Cancer
7
ADRB2 5q31-q32 BAR, B2AR, ADRBR, ADRB2R, BETA2AR -ADRB2 and Pancreatic Cancer
7
RALA 7p15-p13 RAL -RALA and Pancreatic Cancer
7
MUC16 19p13.2 CA125 -MUC16 and Pancreatic Cancer
7
SSTR1 14q13 SS1R, SS1-R, SRIF-2, SS-1-R -SSTR1 and Pancreatic Cancer
7
HBEGF 5q23 DTR, DTS, DTSF, HEGFL -HBEGF and Pancreatic Cancer
7
MBD1 18q21 RFT, PCM1, CXXC3 -MBD1 and Pancreatic Cancer
6
MIR126 9q34.3 MIRN126, mir-126, miRNA126 -MIRN126 microRNA, human and Pancreatic Cancer
6
S100A6 1q21 2A9, PRA, 5B10, CABP, CACY -S100A6 and Pancreatic Cancer
6
TGFB2 1q41 LDS4, TGF-beta2 -TGFB2 and Pancreatic Cancer
6
STRADA 17q23.3 LYK5, PMSE, Stlk, STRAD, NY-BR-96 -STRADA and Pancreatic Cancer
6
NAT1 8p22 AAC1, MNAT, NATI, NAT-1 -NAT1 and Pancreatic Cancer
6
UCHL1 4p14 NDGOA, PARK5, PGP95, PGP9.5, Uch-L1, HEL-117, PGP 9.5 -UCHL1 and Pancreatic Cancer
6
CD68 17p13 GP110, LAMP4, SCARD1 -CD68 and Pancreatic Cancer
6
NR5A2 1q32.1 B1F, CPF, FTF, B1F2, LRH1, LRH-1, FTZ-F1, hB1F-2, FTZ-F1beta -NR5A2 and Pancreatic Cancer
6
RHOB 2p24 ARH6, ARHB, RHOH6, MST081, MSTP081 -RHOB and Pancreatic Cancer
6
AGR2 7p21.3 AG2, GOB-4, HAG-2, XAG-2, PDIA17, HEL-S-116 -AGR2 and Pancreatic Cancer
6
ADAM9 8p11.22 MCMP, MDC9, CORD9, Mltng -ADAM9 and Pancreatic Cancer
5
CLDN4 7q11.23 CPER, CPE-R, CPETR, CPETR1, WBSCR8, hCPE-R -CLDN4 and Pancreatic Cancer
5
NDRG1 8q24.3 GC4, RTP, DRG1, NDR1, NMSL, TDD5, CAP43, CMT4D, DRG-1, HMSNL, RIT42, TARG1, PROXY1 -NDRG1 and Pancreatic Cancer
5
SMAD6 15q22.31 AOVD2, MADH6, MADH7, HsT17432 -SMAD6 and Pancreatic Cancer
5
MSLN 16p13.3 MPF, SMRP -MSLN and Pancreatic Cancer
5
MIRLET7C 21q21.1 LET7C, let-7c, MIRNLET7C, hsa-let-7c -MicroRNA let-7cand Pancreatic Cancer
5
TFPI 2q32 EPI, TFI, LACI, TFPI1 -TFPI and Pancreatic Cancer
5
NR4A1 12q13 HMR, N10, TR3, NP10, GFRP1, NAK-1, NGFIB, NUR77 -NR4A1 and Pancreatic Cancer
5
ROBO1 3p12 SAX3, DUTT1 -ROBO1 and Pancreatic Cancer
5
CXCR2 2q35 CD182, IL8R2, IL8RA, IL8RB, CMKAR2, CDw128b -CXCR2 and Pancreatic Cancer
5
MIR107 10q23.31 MIRN107, miR-107 -MicroRNA mir-107 and Pancreatic Cancer
4
GHRH 20q11.2 GRF, INN, GHRF -GHRH and Pancreatic Cancer
4
CXCL5 4q13.3 SCYB5, ENA-78 -CXCL5 and Pancreatic Cancer
4
LAMC2 1q25-q31 B2T, CSF, EBR2, BM600, EBR2A, LAMB2T, LAMNB2 -LAMC2 and Pancreatic Cancer
4
HOXB7 17q21.3 HOX2, HOX2C, HHO.C1, Hox-2.3 -HOXB7 and Pancreatic Cancer
4
TFPI2 7q22 PP5, REF1, TFPI-2 -TFPI2 and Pancreatic Cancer
4
KRT7 12q13.13 K7, CK7, SCL, K2C7 -KRT7 and Pancreatic Cancer
4
CCNG1 5q32-q34 CCNG -CCNG1 and Pancreatic Cancer
4
HHIP 4q28-q32 HIP -HHIP and Pancreatic Cancer
4
NEUROD1 2q32 BETA2, BHF-1, MODY6, NEUROD, bHLHa3 -NEUROD1 and Pancreatic Cancer
4
MUC17 7q22.1 MUC3 -MUC17 and Pancreatic Cancer
4
RREB1 6p25 HNT, FINB, LZ321, Zep-1, RREB-1 -RREB1 and Pancreatic Cancer
4
GADD45B 19p13.3 MYD118, GADD45BETA -GADD45B and Pancreatic Cancer
4
CAST 5q15 BS-17, PLACK -CAST and Pancreatic Cancer
4
NFATC2 20q13.2 NFAT1, NFATP -NFATC2 and Pancreatic Cancer
4
ABCC4 13q32 MRP4, MOATB, MOAT-B -ABCC4 and Pancreatic Cancer
4
RALGDS 9q34.3 RGF, RGDS, RalGEF -RALGDS and Pancreatic Cancer
4
RALB 2q14.2 -RALB and Pancreatic Cancer
4
LCN2 9q34 24p3, MSFI, NGAL -LCN2 and Pancreatic Cancer
4
AGTR2 Xq22-q23 AT2, ATGR2, MRX88 -AGTR2 and Pancreatic Cancer
4
CD276 15q23-q24 B7H3, B7-H3, B7RP-2, 4Ig-B7-H3 -CD276 and Pancreatic Cancer
3
PAK4 19q13.2 -PAK4 and Pancreatic Cancer
3
ING4 12p13.31 my036, p29ING4 -ING4 and Pancreatic Cancer
3
SUV39H1 Xp11.23 MG44, KMT1A, SUV39H, H3-K9-HMTase 1 -SUV39H1 and Pancreatic Cancer
3
MIR10A 17q21.32 MIRN10A, mir-10a, miRNA10A, hsa-mir-10a -miR-10a and Pancreatic Cancer
3
PBRM1 3p21 PB1, BAF180 -PBRM1 and Pancreatic Cancer
3
UPRT Xq13.3 UPP, FUR1 -UPRT and Pancreatic Cancer
3
CDH3 16q22.1 CDHP, HJMD, PCAD -CDH3 and Pancreatic Cancer
3
AMFR 16q21 GP78, RNF45 -AMFR and Pancreatic Cancer
3
TP53INP1 8q22 SIP, Teap, p53DINP1, TP53DINP1, TP53INP1A, TP53INP1B -TP53INP1 and Pancreatic Cancer
3
MIR1290 1 MIRN1290, hsa-mir-1290 -miR-1290 and Pancreatic Cancer
3
OCLN 5q13.1 BLCPMG, PPP1R115 -OCLN and Pancreatic Cancer
3
PARK7 1p36.23 DJ1, DJ-1, HEL-S-67p -PARK7 and Pancreatic Cancer
3
PLAU 10q22.2 ATF, QPD, UPA, URK, u-PA, BDPLT5 -PLAU and Pancreatic Cancer
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 Pancreatic Cancer
3
RAD54L 1p32 HR54, hHR54, RAD54A, hRAD54 -RAD54L and Pancreatic Cancer
3
CLDN7 17p13.1 CLDN-7, CEPTRL2, CPETRL2, Hs.84359, claudin-1 -CLDN7 and Pancreatic Cancer
3
TGFBI 5q31 CSD, CDB1, CDG2, CSD1, CSD2, CSD3, EBMD, LCD1, BIGH3, CDGG1 -TGFBI and Pancreatic Cancer
3
FGF7 15q21.2 KGF, HBGF-7 -FGF7 and Pancreatic Cancer
3
ITGB4 17q25 CD104 -ITGB4 and Pancreatic Cancer
3
UCP2 11q13 UCPH, BMIQ4, SLC25A8 -UCP2 and Pancreatic Cancer
3
ID2 2p25 GIG8, ID2A, ID2H, bHLHb26 Overexpression
-ID2 Overexpression in Pancreatic Cancer
3
FOXE1 9q22 TTF2, FOXE2, HFKH4, HFKL5, TITF2, TTF-2, FKHL15 -FOXE1 and Pancreatic Cancer
3
SLCO1B3 12p12 LST3, HBLRR, LST-2, OATP8, OATP-8, OATP1B3, SLC21A8, LST-3TM13 -SLCO1B3 and Pancreatic Cancer
3
NOX4 11q14.2-q21 KOX, KOX-1, RENOX -NOX4 and Pancreatic Cancer
3
DEC1 9q32 CTS9 -DEC1 and Pancreatic Cancer
3
TRPM8 2q37.1 TRPP8, LTRPC6 -TRPM8 and Pancreatic Cancer
3
MIRLET7D 9q22.32 LET7D, let-7d, MIRNLET7D, hsa-let-7d -MicroRNA let-d and Pancreatic Cancer
3
MUC7 4q13.3 MG2 -MUC7 and Pancreatic Cancer
3
TNFRSF10C 8p22-p21 LIT, DCR1, TRID, CD263, TRAILR3, TRAIL-R3, DCR1-TNFR -TNFRSF10C and Pancreatic Cancer
3
REG1A 2p12 P19, PSP, PTP, REG, ICRF, PSPS, PSPS1 -REG1A and Pancreatic Cancer
2
MTA2 11q12-q13.1 PID, MTA1L1 -MTA2 and Pancreatic Cancer
2
LYVE1 11p15 HAR, XLKD1, LYVE-1, CRSBP-1 -LYVE1 and Pancreatic Cancer
2
HLA-B 6p21.3 AS, HLAB, SPDA1 -HLA-B and Pancreatic Cancer
2
IER3 6p21.3 DIF2, IEX1, PRG1, DIF-2, GLY96, IEX-1, IEX-1L -IER3 and Pancreatic Cancer
2
LGALS4 19q13.2 GAL4, L36LBP -LGALS4 and Pancreatic Cancer
2
SULF1 8q13.2 SULF-1, HSULF-1 -SULF1 and Pancreatic Cancer
2
TBX2 17q23.2 -TBX2 and Pancreatic Cancer
2
CX3CR1 3p21.3 V28, CCRL1, GPR13, CMKDR1, GPRV28, CMKBRL1 -CX3CR1 and Pancreatic Cancer
2
SLC9A1 1p36.1-p35 APNH, NHE1, LIKNS, NHE-1, PPP1R143 -SLC9A1 and Pancreatic Cancer
2
SSTR3 22q13.1 SS3R, SS3-R, SS-3-R, SSR-28 -SSTR3 and Pancreatic Cancer
2
PROX1 1q41 -PROX1 and Pancreatic Cancer
2
PVT1 8q24 LINC00079, NCRNA00079 -PVT1 and Pancreatic Cancer
2
SERPINA1 14q32.1 PI, A1A, AAT, PI1, A1AT, PRO2275, alpha1AT -SERPINA1 and Pancreatic Cancer
2
MMP10 11q22.3 SL-2, STMY2 -MMP10 and Pancreatic Cancer
2
HPSE 4q21.3 HPA, HPA1, HPR1, HSE1, HPSE1 -HPSE and Pancreatic Cancer
2
CX3CL1 16q13 NTN, NTT, CXC3, CXC3C, SCYD1, ABCD-3, C3Xkine, fractalkine, neurotactin -CX3CL1 and Pancreatic Cancer
2
CSF1 1p13.3 MCSF, CSF-1 -CSF1 and Pancreatic Cancer
2
NEDD4 15q RPF1, NEDD4-1 -NEDD4 and Pancreatic Cancer
2
TNFRSF6B 20q13.3 M68, TR6, DCR3, M68E, DJ583P15.1.1 Amplification
-TNFRSF6B Amplification and Overexpression in Pancreatic Cancer
2
OLFM4 13q14.3 GC1, OLM4, OlfD, GW112, hGC-1, hOLfD, UNQ362, bA209J19.1 -OLFM4 and Pancreatic Cancer
2
CDCP1 3p21.31 CD318, TRASK, SIMA135 -CDCP1 and Pancreatic Cancer
2
CHGA 14q32 CGA -CHGA and Pancreatic Cancer
2
TNFRSF25 1p36.2 DR3, TR3, DDR3, LARD, APO-3, TRAMP, WSL-1, WSL-LR, TNFRSF12 -TNFRSF25 and Pancreatic Cancer
2
CYBA 16q24 p22-PHOX -CYBA and Pancreatic Cancer
2
TM4SF1 3q21-q25 L6, H-L6, M3S1, TAAL6 -TM4SF1 and Pancreatic Cancer
2
ULBP2 6q25 N2DL2, RAET1H, NKG2DL2, ALCAN-alpha -ULBP2 and Pancreatic Cancer
2
HSPA1B 6p21.3 HSP70-2, HSP70-1B -HSPA1B and Pancreatic Cancer
2
RPS6 9p21 S6 -RPS6 and Pancreatic Cancer
2
ARL11 13q14.2 ARLTS1 -ARL11 and Pancreatic Cancer
2
NFATC1 18q23 NFAT2, NFATc, NF-ATC -NFATC1 and Pancreatic Cancer
2
INHBA 7p15-p13 EDF, FRP -INHBA and Pancreatic Cancer
2
RALBP1 18p11.3 RIP1, RLIP1, RLIP76 -RALBP1 and Pancreatic Cancer
2
IRAK1 Xq28 IRAK, pelle -IRAK1 and Pancreatic Cancer
2
POLB 8p11.2 -POLB and Pancreatic Cancer
2
SST 3q28 SMST -SST and Pancreatic Cancer
2
ST14 11q24-q25 HAI, MTSP1, SNC19, ARCI11, MT-SP1, PRSS14, TADG15, TMPRSS14 -ST14 and Pancreatic Cancer
2
GAGE1 Xp11.23 CT4.1, GAGE-1 -GAGE1 and Pancreatic Cancer
2
KL 13q12 -KL and Pancreatic Cancer
2
ADAMTS1 21q21.2 C3-C5, METH1 -ADAMTS1 and Pancreatic Cancer
2
XPO1 2p15 emb, CRM1, exp1 -XPO1 and Pancreatic Cancer
2
IL1RL1 2q12 T1, ST2, DER4, ST2L, ST2V, FIT-1, IL33R -IL1RL1 and Pancreatic Cancer
1
FOXN3 14q31.3 CHES1, PRO1635, C14orf116 -FOXN3 and Pancreatic Cancer
1
HLA-C 6p21.3 HLC-C, D6S204, PSORS1, HLA-JY3 -HLA-C and Pancreatic Cancer
1
RAB8A 19p13.1 MEL, RAB8 -RAB8A and Pancreatic Cancer
1
ARID2 12q12 p200, BAF200 -ARID2 and Pancreatic Cancer
1
ADAMTS9 3p14.1 -ADAMTS9 and Pancreatic Cancer
1
KDM5C Xp11.22-p11.21 MRXJ, SMCX, MRX13, MRXSJ, XE169, MRXSCJ, JARID1C, DXS1272E -KDM5C and Pancreatic Cancer
1
ANP32A 15q23 LANP, MAPM, PP32, HPPCn, PHAP1, PHAPI, I1PP2A, C15orf1 -ANP32A and Pancreatic Cancer
1
ST2 11p14.3-p12 -ST2 and Pancreatic Cancer
1
FBXO11 2p16.3 UBR6, VIT1, FBX11, PRMT9, UG063H01 -FBXO11 and Pancreatic Cancer
1
NOV 8q24.1 CCN3, NOVh, IBP-9, IGFBP9, IGFBP-9 -NOV and Pancreatic Cancer
1
SMAD7 18q21.1 CRCS3, MADH7, MADH8 -SMAD7 and Pancreatic Cancer

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

Latest Publications

Frank TS, Sun X, Zhang Y, et al.
Genomic profiling guides the choice of molecular targeted therapy of pancreatic cancer.
Cancer Lett. 2015; 363(1):1-6 [PubMed] Article available free on PMC after 10/07/2016 Related Publications
Pancreatic cancer has the worst five-year survival rate of all malignancies due to its aggressive progression and resistance to therapy. Current therapies are limited to gemcitabine-based chemotherapeutics, surgery, and radiation. The current trend toward "personalized genomic medicine" has the potential to improve the treatment options for pancreatic cancer. Gene identification and genetic alterations like single nucleotide polymorphisms and mutations will allow physicians to predict the efficacy and toxicity of drugs, which could help diagnose pancreatic cancer, guide neoadjuvant or adjuvant treatment, and evaluate patients' prognosis. This article reviews the multifaceted roles of genomics and pharmacogenomics in pancreatic cancer.

Pandita A, Manvati S, Singh SK, et al.
Combined effect of microRNA, nutraceuticals and drug on pancreatic cancer cell lines.
Chem Biol Interact. 2015; 233:56-64 [PubMed] Related Publications
AIM: We proposed to investigate the combination effect of microRNA, nutraceuticals and drug (MND), in two pancreatic cancer cell lines to assess the therapeutic potential.
MATERIALS AND METHODS: MIA PaCa-2 and PANC-1 cells transfected with miR-101 or miR-24-2 were treated with Betulinic acid or Thymoquinone and gemcitabine independently and in combination and assessed for the extent of synergism in both experimental and control conditions, considering significance at the p value of <0.05.
RESULTS: miR-101 or miR-24-2 over-expressing cells when treated with lower than IC50 doses of the dietary compounds and drug showed a reduced (37-50%) viability in two cell lines with differential synergistic effect and the outcome for Pro-caspase3, Poly (ADP-ribose) polymerase (PARP) cleavage and PKM2 expression.
CONCLUSION: Two independent microRNA backgrounds showed promise in therapeutic intervention of gemcitabine sensitive, MIA PaCa-2 and resistant, PANC-1 pancreatic cancer cells, in combination with dietary agents and drug.

Tan MC, Basturk O, Brannon AR, et al.
GNAS and KRAS Mutations Define Separate Progression Pathways in Intraductal Papillary Mucinous Neoplasm-Associated Carcinoma.
J Am Coll Surg. 2015; 220(5):845-54.e1 [PubMed] Article available free on PMC after 01/05/2016 Related Publications
BACKGROUND: Intraductal papillary mucinous neoplasms (IPMN) are being increasingly recognized as important precursors to pancreatic adenocarcinoma. Elucidation of the genetic changes underlying IPMN carcinogenesis may improve the diagnosis and management of IPMN. We sought to determine whether different histologic subtypes of IPMN would exhibit different frequencies of specific genetic mutations.
STUDY DESIGN: Patients with resected IPMN-associated invasive carcinoma (IPMN-INV) between 1997 and 2012 were reviewed. Areas of carcinoma, high-grade dysplasia, and low-grade dysplasia were micro-dissected from each pathologic specimen. Targeted, massively parallel sequencing was then performed on a panel of 275 genes (including KRAS, GNAS, and RNF43).
RESULTS: Thirty-eight patients with resected IPMN-INV and sufficient tissue for micro-dissection were identified. Median follow-up was 2.6 years. Mutations in GNAS were more prevalent in colloid-type IPMN-INV than tubular-type IPMN-INV (89% vs 32% respectively; p = 0.0003). Conversely, KRAS mutations were more prevalent in tubular-type than colloid-type IPMN-INV (89% vs 52%, respectively; p = 0.01). For noninvasive IPMN subtypes, GNAS mutations were more prevalent in intestinal (74%) compared with pancreatobiliary (31%) and gastric (50%) subtypes (p = 0.02). The presence of these mutations did not vary according to the degree of dysplasia (GNAS: invasive 61%, high-grade 59%, low-grade 53%; KRAS: invasive 71%, high-grade 62%, low-grade 74%), suggesting that mutations in these genes occur early in IPMN carcinogenesis.
CONCLUSIONS: Colloid carcinoma associated with IPMN and its intestinal-type preinvasive precursor are associated with high frequencies of GNAS mutations. The mutation profile of tubular carcinoma resembles that of conventional pancreatic adenocarcinoma. Preoperative determination of mutational status may assist with clinical treatment decisions.

Cromer MK, Choi M, Nelson-Williams C, et al.
Neomorphic effects of recurrent somatic mutations in Yin Yang 1 in insulin-producing adenomas.
Proc Natl Acad Sci U S A. 2015; 112(13):4062-7 [PubMed] Article available free on PMC after 01/05/2016 Related Publications
Insulinomas are pancreatic islet tumors that inappropriately secrete insulin, producing hypoglycemia. Exome and targeted sequencing revealed that 14 of 43 insulinomas harbored the identical somatic mutation in the DNA-binding zinc finger of the transcription factor Yin Yang 1 (YY1). Chromatin immunoprecipitation sequencing (ChIP-Seq) showed that this T372R substitution changes the DNA motif bound by YY1. Global analysis of gene expression demonstrated distinct clustering of tumors with and without YY1(T372R) mutations. Genes showing large increases in expression in YY1(T372R) tumors included ADCY1 (an adenylyl cyclase) and CACNA2D2 (a Ca(2+) channel); both are expressed at very low levels in normal β-cells and show mutation-specific YY1 binding sites. Both gene products are involved in key pathways regulating insulin secretion. Expression of these genes in rat INS-1 cells demonstrated markedly increased insulin secretion. These findings indicate that YY1(T372R) mutations are neomorphic, resulting in constitutive activation of cAMP and Ca(2+) signaling pathways involved in insulin secretion.

Rishi A, Goggins M, Wood LD, Hruban RH
Pathological and molecular evaluation of pancreatic neoplasms.
Semin Oncol. 2015; 42(1):28-39 [PubMed] Article available free on PMC after 01/02/2016 Related Publications
Pancreatic neoplasms are morphologically and genetically heterogeneous and include a wide variety of tumors ranging from benign to malignant with an extremely poor clinical outcome. Our understanding of these pancreatic neoplasms has improved significantly with recent advances in cancer sequencing. Awareness of molecular pathogenesis brings new opportunities for early detection, improved prognostication, and personalized gene-specific therapies. Here we review the pathological classification of pancreatic neoplasms from the molecular and genetic perspectives.

Waddell N, Pajic M, Patch AM, et al.
Whole genomes redefine the mutational landscape of pancreatic cancer.
Nature. 2015; 518(7540):495-501 [PubMed] Article available free on PMC after 01/02/2016 Related Publications
Pancreatic cancer remains one of the most lethal of malignancies and a major health burden. We performed whole-genome sequencing and copy number variation (CNV) analysis of 100 pancreatic ductal adenocarcinomas (PDACs). Chromosomal rearrangements leading to gene disruption were prevalent, affecting genes known to be important in pancreatic cancer (TP53, SMAD4, CDKN2A, ARID1A and ROBO2) and new candidate drivers of pancreatic carcinogenesis (KDM6A and PREX2). Patterns of structural variation (variation in chromosomal structure) classified PDACs into 4 subtypes with potential clinical utility: the subtypes were termed stable, locally rearranged, scattered and unstable. A significant proportion harboured focal amplifications, many of which contained druggable oncogenes (ERBB2, MET, FGFR1, CDK6, PIK3R3 and PIK3CA), but at low individual patient prevalence. Genomic instability co-segregated with inactivation of DNA maintenance genes (BRCA1, BRCA2 or PALB2) and a mutational signature of DNA damage repair deficiency. Of 8 patients who received platinum therapy, 4 of 5 individuals with these measures of defective DNA maintenance responded.

Shi S, Ji S, Qin Y, et al.
Metabolic tumor burden is associated with major oncogenomic alterations and serum tumor markers in patients with resected pancreatic cancer.
Cancer Lett. 2015; 360(2):227-33 [PubMed] Related Publications
Pancreatic cancer is an aggressive and lethal disease with an overall 5-year survival rate of only 5%. Studies have demonstrated the ability of (18)F-fludrodeoxyglucose ((18)F-FDG) positron emission tomography/computed tomography (PET/CT) to measure the metabolic tumor burden in patients with various tumors, including pancreatic cancer. In a previous study, we investigated the predictive significance of the metabolic tumor burden in terms of the metabolic tumor volume (MTV) and total lesion glycolysis (TLG). In this study, we analyzed the correlation between metabolic tumor burden and the status of the KRAS, TP53, CDKN2A/p16, and SMAD4/DPC4 genes. Our results showed that the metabolic tumor burden was associated with oncogenomic alterations that reflected the abnormal expression of carbohydrate metabolic enzymes (GLUT1, ALDOA and FBP1). We also identified a linear correlation between serum tumor markers and the metabolic tumor burden. To estimate the metabolic tumor burden when (18)F-FDG PET/CT is not available, we used the linear regression models to establish equations for MTV and TLG using CA19-9 and CA125 as independent variables. Our results suggest that the metabolic tumor burden, as evaluated by (18)F-FDG PET/CT or estimated by serum tumor markers, may be suitable for monitoring treatment response and disease progression of pancreatic cancer. Further research is needed to better understand why pancreatic cancer patients with abnormal expressions of TP53, CDKN2A/p16, and SMAD4/DPC4 get high metabolic tumor burden.

Singh N, Gupta S, Pandey RM, et al.
High levels of cell-free circulating nucleic acids in pancreatic cancer are associated with vascular encasement, metastasis and poor survival.
Cancer Invest. 2015; 33(3):78-85 [PubMed] Related Publications
Pancreatic cancer is a highly aggressive disease with rapid invasion and early encasement of blood vessels. Hence, levels of circulating nucleic acids and tumor-associated mutations in them may have clinical importance. We analyzed the levels of circulating tumor DNA and oncogenic k-ras mutation in plasma of patients with pancreatic cancer and correlated their levels with survival and clinicopathological parameters. Higher levels of plasma DNA (>62 ng/mL) was found to associate significantly with lower overall survival time (p=.002), presence of vascular encasement (p=.030) and metastasis (p=.001). However, k-ras mutation status did not correlate with any of the clinicopathological parameters or survival. We conclude that circulating DNA in plasma can be an important predictor of prognosis in pancreatic cancer.

Masugi Y, Yamazaki K, Emoto K, et al.
Upregulation of integrin β4 promotes epithelial-mesenchymal transition and is a novel prognostic marker in pancreatic ductal adenocarcinoma.
Lab Invest. 2015; 95(3):308-19 [PubMed] Related Publications
Pancreatic ductal adenocarcinoma (PDA) is a highly aggressive and often lethal malignant tumor. Several studies have shown that epithelial-mesenchymal transition (EMT) is frequently observed in clinical samples of PDA and is related to high metastatic rates and poor outcomes. To identify candidate molecules regulating EMT in PDA, we previously used cDNA microarray analysis and identified integrin β4 (ITGB4) as one of the genes upregulated in high-EMT xenografts derived from PDA patients. The aim of the current study was to clarify the clinicopathological and functional significance of ITGB4 overexpression in PDA. ITGB4 upregulation in high-EMT xenografts was confirmed by immunohistochemistry. Immunohistochemical analyses of 134 surgically resected PDA cases revealed intratumoral heterogeneity with respect to ITGB4 expression and showed that cancer cells undergoing EMT often display strong diffuse ITGB4 expression. High levels of ITGB4 expression were significantly correlated with the hallmarks of EMT (solitary cell infiltration, reduced E-cadherin expression, and increased vimentin expression), with high tumor grade, and with the presence of lymph node metastasis, and showed an independent prognostic effect. Immunocytochemical analyses of PDA cell lines revealed that localization of ITGB4 changed from regions of cell-cell contact to diffuse cytoplasm and cell edges with occasional localization in filopodia during EMT. Knockdown of ITGB4 reduced the migratory and invasive ability of PDA cells. Overexpression of ITGB4 promoted cell scattering and cell motility in combination with downregulation of E-cadherin and upregulation of vimentin expression. In conclusion, we elucidated the prognostic and clinicopathological significance of ITGB4 overexpression in PDA and also the potential role for ITGB4 in the regulation of cancer invasion and EMT.

Jiang J, Liu HL, Liu ZH, et al.
Identification of cystatin SN as a novel biomarker for pancreatic cancer.
Tumour Biol. 2015; 36(5):3903-10 [PubMed] Related Publications
Cystatin SN (cystatin 1, CST1) is a member of the cystatin superfamily that inhibits the proteolytic activity of cysteine proteases. CST1 is a tumor biomarker that provides useful information for the diagnosis of esophageal, gastric, and colorectal carcinomas. However, the significance of CST1 in pancreatic cancer is unknown. The aim of this study was to assess whether CST1 is a potential biomarker for early diagnosis of malignant pancreatic neoplasms. Microarray analysis of mRNA extracted from pancreatic cancer and pancreatic normal tissues was performed. Bioinformatics revealed that CST1 was one of the highest expressed genes on the array in pancreatic cancer, compared with normal tissue. In addition, the upregulation of CST1 in pancreatic cancer and several pancreatic cancer cell lines was confirmed using real-time PCR (RT-PCR), immunohistochemistry, and Western blotting. Next, CST1 knockdown using siRNA reduced the expression of the proliferation-related proteins p-AKT and PCNA significantly, as well as colony formation and xenograft development in vitro. Consistent with this, CST1 mRNA overexpression was correlated closely with malignancy-associated proteins such as PCNA, cyclin D1, cyclin A2, and cyclin E in pancreatic cancer cell lines. In conclusion, our data suggest that CST1 might contribute to the proliferation of pancreatic cancer cells and could be a potential biomarker for the early detection of pancreatic cancer.

Gurevich LE, Kazantseva IA, Sokolova IN, et al.
[Solid pseudopapillary tumors of the pancreas: clinical and morphological characteristics, specific features of their immunophenotype, and diagnostic problems].
Arkh Patol. 2014 Sep-Oct; 76(5):44-54 [PubMed] Related Publications
OBJECTIVE: To analyze 60 cases of solid pseudopapillary tumors (SPTs) of the pancreas, to reveal their most characteristic clinical and morphological features, and to study their possible histogenesis.
MATERIAL AND METHODS: Sixty cases of SPTs of the pancreas underwent clinical, morphological, and immunohistochemical (IHC) examinations; a comparison group consisted of 86 pancreatic tumors of other histogenesis.
RESULTS: It has been shown for the first time that SPTs are characterized by the nuclear expression of claudin 3 and the cytoplasmic expression of claudin 7. It has been also ascertained that the aberrant perinuclear (dot-like) expression of CD99 is a unique feature of these tumors.
CONCLUSION: SPTs of the pancreas are distinguished by a diversity of clinical manifestations and morphological features, but have a unique immunophenotype, which can differentiate them from other types of pancreatic tumors.

Tamura K, Ohtsuka T, Matsunaga T, et al.
Assessment of clonality of multisegmental main duct intraductal papillary mucinous neoplasms of the pancreas based on GNAS mutation analysis.
Surgery. 2015; 157(2):277-84 [PubMed] Related Publications
BACKGROUND: Main duct intraductal papillary mucinous neoplasms (MD-IPMNs) may occur in 1 or multiple segments of the pancreatic duct. Unlike multifocal branch duct (BD)-IPMNs, the clonality of multisegmental MD-IPMNs remains unclear. GNAS mutations are common and specific for IPMNs, and mutational assessment might be useful to determine the clonality of IPMNs as well as to detect high-risk IPMN with distinct ductal adenocarcinoma (pancreatic ductal adenocarcinoma [PDAC]). Our aim was to clarify clonality using GNAS status in multisegmental MD-IPMNs.
METHODS: We retrospectively reviewed the medical records of 70 patients with MD-IPMN. Histologic subtypes and KRAS/GNAS mutations were investigated, and the clonal relationships among multisegmental MD-IPMNs were assessed. Mutational analysis was performed using high-resolution melting analysis and subsequent Sanger/pyrosequencing.
RESULTS: Thirteen patients had multiple synchronous and/or metachronous lesions. Seven of these 13 patients had multiple MD-IPMNs; 3 had multiple MD-IPMNs and distinct BD-IPMNs; 1 had multiple MD-IPMNs and a distinct PDAC; 1 had a solitary MD-IPMN, BD-IPMN, and PDAC; and 1 had a solitary MD-IPMN and PDAC. KRAS/GNAS mutations were consistent in 10 of 11 multisegmental MD-IPMNs, whereas MD-IPMNs, BD-IPMNs, and PDACs tended to show different mutational patterns. The frequency of malignant IPMNs was significantly higher in the multisegment cohort; malignant IPMNs constituted 90% (9/10) of the multiple cohort and 56% (32/57) of the solitary cohort (P = .04). Mutant GNAS was more frequently observed in the intestinal subtype (94%) than the others.
CONCLUSION: MD-IPMNs can be characterized by monoclonal skip progression. Close attention should be paid to the possible presence of skip areas during or after partial pancreatectomy.

Miyabe K, Hori Y, Nakazawa T, et al.
Locus/chromosome aberrations in intraductal papillary mucinous neoplasms analyzed by fluorescence in situ hybridization.
Am J Surg Pathol. 2015; 39(4):512-20 [PubMed] Related Publications
Locus and chromosome abnormalities have not been well clarified in intraductal papillary mucinous neoplasms (IPMNs). The aim of this study was to retrospectively examine these abnormalities using fluorescence in situ hybridization. IPMNs (n=28) were histopathologically classified into noninvasive IPMN (n=17) and IPMN with an associated invasive carcinoma (invasive IPMN, n=11) groups. Noninvasive IPMNs possessed non-neoplastic and noninvasive spots in their tissues, and invasive IPMN cases possessed non-neoplastic, noninvasive, and invasive spots. Non-neoplastic (n=28), noninvasive (n=28), and invasive (n=11) spots were then analyzed for aneuploidy of chromosomes 3, 6, 7, 8, 17, and 18 and deletions of p16 and p53 loci. Polysomy 6 and p16 deletion were significantly more frequent in noninvasive than in non-neoplastic spots. Polysomy 7, polysomy 18, p16 deletion, and p53 deletion were significantly more frequent in invasive than in noninvasive spots. Detection of polysomy 7 and p53 deletion gave a high diagnostic accuracy for invasive IPMN (sensitivity, 90.9%; specificity, 94.1%; and accuracy, 92.5%). Our study suggests that: (1) polysomy 6 and p16 deletion may contribute to adenomatous change of IPMN; (2) polysomy 7, polysomy 18, p16 deletion, and p53 deletion play roles in malignant transformation of noninvasive IPMN; and (3) polysomy 7 and p53 deletion may be excellent diagnostic markers for invasive IPMN.

Rad R, Rad L, Wang W, et al.
A conditional piggyBac transposition system for genetic screening in mice identifies oncogenic networks in pancreatic cancer.
Nat Genet. 2015; 47(1):47-56 [PubMed] Related Publications
Here we describe a conditional piggyBac transposition system in mice and report the discovery of large sets of new cancer genes through a pancreatic insertional mutagenesis screen. We identify Foxp1 as an oncogenic transcription factor that drives pancreatic cancer invasion and spread in a mouse model and correlates with lymph node metastasis in human patients with pancreatic cancer. The propensity of piggyBac for open chromatin also enabled genome-wide screening for cancer-relevant noncoding DNA, which pinpointed a Cdkn2a cis-regulatory region. Histologically, we observed different tumor subentities and discovered associated genetic events, including Fign insertions in hepatoid pancreatic cancer. Our studies demonstrate the power of genetic screening to discover cancer drivers that are difficult to identify by other approaches to cancer genome analysis, such as downstream targets of commonly mutated human cancer genes. These piggyBac resources are universally applicable in any tissue context and provide unique experimental access to the genetic complexity of cancer.

Pang EJ, Yang R, Fu XB, Liu YF
Overexpression of long non-coding RNA MALAT1 is correlated with clinical progression and unfavorable prognosis in pancreatic cancer.
Tumour Biol. 2015; 36(4):2403-7 [PubMed] Related Publications
Long non-coding RNAs (lncRNAs) have been proved to serve as a critical role in cancer development and progression. However, little is known about the pathological role of lncRNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) in pancreatic cancer patients. The aims of this study are to measure the expression of lncRNA MALAT1 in pancreatic cancer patients and to explore the clinical significance of the lncRNA MALAT1. Using qRT-PCR, the expression of lncRNA MALAT1 was measured in 126 pancreatic cancer tissues and 15 adjacent non-cancerous tissues. In the present study, our results indicated that lncRNA MALAT1 was highly expressed in pancreatic cancer compared with adjacent non-cancerous tissues (P < 0.001), and positively correlated with clinical stage (early stages vs. advanced stages, P < 0.001), tumor size (<2 vs. ≥2 cm, P = 0.004), lymph node metastasis (negative vs. positive, P < 0.001), and distant metastasis (absent vs. present, P = 0.001) in pancreatic cancer patients. Furthermore, we also found that lncRNA MALAT1 overexpression was an unfavorable prognostic factor in pancreatic cancer patients (P < 0.001), regardless of clinical stage, tumor size, lymph node metastasis, and distant metastasis. Finally, increased lncRNA MALAT1 expression was an independent poor prognostic factor for pancreatic patients through multivariate analysis (P = 0.018). In conclusion, overexpression of lncRNA MALAT1 serves as an unfavorable prognostic biomarker in pancreatic cancer patients.

Grant RC, Selander I, Connor AA, et al.
Prevalence of germline mutations in cancer predisposition genes in patients with pancreatic cancer.
Gastroenterology. 2015; 148(3):556-64 [PubMed] Article available free on PMC after 01/03/2016 Related Publications
BACKGROUND & AIMS: We investigated the prevalence of germline mutations in APC, ATM, BRCA1, BRCA2, CDKN2A, MLH1, MSH2, MSH6, PALB2, PMS2, PRSS1, STK11, and TP53 in patients with pancreatic cancer.
METHODS: The Ontario Pancreas Cancer Study enrolls consenting participants with pancreatic cancer from a province-wide electronic pathology database; 708 probands were enrolled from April 2003 through August 2012. To improve the precision of BRCA2 prevalence estimates, 290 probands were selected from 3 strata, based on family history of breast and/or ovarian cancer, pancreatic cancer, or neither. Germline DNA was analyzed by next-generation sequencing using a custom multiple-gene panel. Mutation prevalence estimates were calculated from the sample for the entire cohort.
RESULTS: Eleven pathogenic mutations were identified: 3 in ATM, 1 in BRCA1, 2 in BRCA2, 1 in MLH1, 2 in MSH2, 1 in MSH6, and 1 in TP53. The prevalence of mutations in all 13 genes was 3.8% (95% confidence interval, 2.1%-5.6%). Carrier status was associated significantly with breast cancer in the proband or first-degree relative (P < .01), and with colorectal cancer in the proband or first-degree relative (P < .01), but not family history of pancreatic cancer, age at diagnosis, or stage at diagnosis. Of patients with a personal or family history of breast and colorectal cancer, 10.7% (95% confidence interval, 4.4%-17.0%) and 11.1% (95% confidence interval, 3.0%-19.1%) carried pathogenic mutations, respectively.
CONCLUSIONS: A small but clinically important proportion of pancreatic cancer is associated with mutations in known predisposition genes. The heterogeneity of mutations identified in this study shows the value of using a multiple-gene panel in pancreatic cancer.

Shteyer E, Edvardson S, Wynia-Smith SL, et al.
Truncating mutation in the nitric oxide synthase 1 gene is associated with infantile achalasia.
Gastroenterology. 2015; 148(3):533-536.e4 [PubMed] Related Publications
Nitric oxide is thought to have a role in the pathogenesis of achalasia. We performed a genetic analysis of 2 siblings with infant-onset achalasia. Exome analysis revealed that they were homozygous for a premature stop codon in the gene encoding nitric oxide synthase 1. Kinetic analyses and molecular modeling showed that the truncated protein product has defects in folding, nitric oxide production, and binding of cofactors. Heller myotomy had no effect in these patients, but sildenafil therapy increased their ability to drink. The finding recapitulates the previously reported phenotype of nitric oxide synthase 1-deficient mice, which have achalasia. Nitric oxide signaling appears to be involved in the pathogenesis of achalasia in humans.

Markwick LJ, Riva A, Ryan JM, et al.
Blockade of PD1 and TIM3 restores innate and adaptive immunity in patients with acute alcoholic hepatitis.
Gastroenterology. 2015; 148(3):590-602.e10 [PubMed] Related Publications
BACKGROUND & AIMS: Susceptibility to bacterial infection is a feature of alcohol-related liver disease. Programmed cell death 1 (PD1), the T-cell immunoglobulin and mucin domain-containing protein 3 (TIM3, also known as hepatitis A virus cellular receptor 2), and their respective ligands-CD274 (also known as PD ligand 1 [PDL1]) and galectin-9-are inhibitory receptors that regulate the balance between protective immunity and host immune-mediated damage. However, their sustained hyperexpression promotes immune exhaustion and paralysis. We investigated the role of these immune inhibitory receptors in driving immune impairments in patients with alcoholic liver disease.
METHODS: In a prospective study, we collected blood samples from 20 patients with acute alcoholic hepatitis (AAH), 16 patients with stable advanced alcohol-related cirrhosis, and 12 healthy individuals (controls). Whole blood or peripheral blood mononuclear cells were assessed for expression of PD1, PDL1, TIM3, galectin-9, and Toll-like receptors on subsets of innate and adaptive immune effector cells. We measured antibacterial immune responses to lipopolysaccharide (endotoxin) using ELISpot assays, and used flow cytometry to quantify cytokine production, phagocytosis, and oxidative burst in the presence or absence of blocking antibodies against PD1 or TIM3.
RESULTS: Antibacterial innate and adaptive immune responses were greatly reduced in patients with AAH, compared with controls, and patients with alcohol-related cirrhosis had less severe dysfunctions in innate immune effector cells and preserved functional T-cell responses. Fewer T cells from patients with AAH produced interferon gamma in response to lipopolysaccharide, compared with controls. In addition, patients with AAH had greater numbers of interleukin 10-producing T cells, and reduced levels of neutrophil phagocytosis and oxidative burst in response to Escherichia coli stimulation, compared with controls. T cells from patients with AAH, but not alcohol-related cirrhosis, expressed higher levels of PD1 and PDL1, or TIM3 and galectin-9, than T cells from controls. Antibodies against PD1 and TIM3 restored T-cell production of interferon gamma, reduced the numbers of interleukin 10-producing T cells, and increased neutrophil antimicrobial activities. Circulating levels of endotoxin in plasma from patients with AAH caused over expression of immune inhibitory receptors on T cells via Toll-like receptor 4 binding to CD14(+) monocytes.
CONCLUSIONS: Antibacterial immune responses are impaired in patients with AAH. Lymphocytes from these patients express high levels of immune inhibitory receptors, produce lower levels of interferon gamma, and have increased IL10 production due to chronic endotoxin exposure. These effects can be reversed by blocking PD1 and TIM3, which increase the antimicrobial activities of T cells and neutrophils.

Li C, Zhao Z, Zhou Z, Liu R
Augmented TGFβ receptor signaling induces apoptosis of pancreatic carcinoma cells.
Tumour Biol. 2015; 36(4):2815-9 [PubMed] Related Publications
Pancreatic ductal adenocarcinoma (PDAC) is an extremely malignant tumor in humans. Thus, understanding the tumorigenesis of PDAC appears to help develop efficient therapy. Here, we show that activated TGFβ receptor signaling induces apoptosis of pancreatic carcinoma cells in vitro and in vivo, suggesting that activation of TGFβ receptor signaling may prevent development of PDAC.

Wong RJ, Aguilar M, Cheung R, et al.
Nonalcoholic steatohepatitis is the second leading etiology of liver disease among adults awaiting liver transplantation in the United States.
Gastroenterology. 2015; 148(3):547-55 [PubMed] Related Publications
BACKGROUND & AIMS: Nonalcoholic steatohepatitis (NASH) has been predicted to become the leading indication for liver transplantation (LT) in the United States. However, few studies have evaluated changes in the etiology of liver diseases among patients awaiting LT, and none have focused on the effects of NASH on liver transplant waitlists in the United States.
METHODS: We collected data from the United Network for Organ Sharing and Organ Procurement and Transplantation Network registry from 2004 through 2013, on liver transplant waitlist registrants with hepatitis C virus (HCV) infection, NASH, alcoholic liver disease (ALD), or a combination of HCV infection and ALD. We compared differences in survival within 90 days of registration (90-day survival) and probability of LT among patients with different diseases using Kaplan-Meier and multivariate logistic regression models.
RESULTS: Between 2004 and 2013, new waitlist registrants with NASH increased by 170% (from 804 to 2174), with ALD increased by 45% (from 1400 to 2024), and with HCV increased by 14% (from 2887 to 3291); registrants with HCV and ALD decreased by 9% (from 880 to 803). In 2013, NASH became the second-leading disease among liver transplant waitlist registrants, after HCV. Patients with ALD had a significantly higher mean Model for End-Stage Liver Disease score at time of waitlist registration than other registrants. However, after multivariate adjustment, patients with ALD were less likely to die within 90 days when compared with patients with NASH (odds ratio [OR] = 0.77; 95% confidence interval [CI]: 0.67-0.89; P < .001); patients with HCV infection or HCV and ALD had similar odds for 90-day survival compared with NASH patients. Compared with patients with NASH, patients with HCV (OR = 1.45; 95% CI: 1.35-1.55; P < .001), ALD (OR = 1.15; 95% CI: 1.06-1.24; P < .001), or HCV and ALD (OR = 1.29; 95% CI: 1.18-1.42; P < .001) had higher odds for 90-day survival.
CONCLUSIONS: Based on data from US adult LT databases, since 2004 the number of adults with NASH awaiting LTs has almost tripled. However, patients with NASH are less likely to undergo LT and less likely to survive for 90 days on the waitlist than patients with HCV, ALD, or HCV and ALD.

Rachagani S, Macha MA, Heimann N, et al.
Clinical implications of miRNAs in the pathogenesis, diagnosis and therapy of pancreatic cancer.
Adv Drug Deliv Rev. 2015; 81:16-33 [PubMed] Article available free on PMC after 01/01/2016 Related Publications
Despite considerable progress being made in understanding pancreatic cancer (PC) pathogenesis, it still remains the 10th most often diagnosed malignancy in the world and 4th leading cause of cancer related deaths in the United States with a five year survival rate of only 6%. The aggressive nature, lack of early diagnostic and prognostic markers, late clinical presentation, and limited efficacy of existing treatment regimens make PC a lethal cancer with high mortality and poor prognosis. Therefore, novel reliable biomarkers and molecular targets are urgently needed to combat this deadly disease. MicroRNAs (miRNAs) are short (19-24 nucleotides) non-coding RNA molecules implicated in the regulation of gene expression at post-transcriptional level and play significant roles in various physiological and pathological conditions. Aberrant expression of miRNAs has been reported in several cancers including PC and is implicated in PC pathogenesis and progression, suggesting their utility in diagnosis, prognosis and therapy. In this review, we summarize the role of several miRNAs that regulate various oncogenes (KRAS) and tumor suppressor genes (p53, p16, SMAD4, etc.) involved in PC development, their prospective roles as diagnostic and prognostic markers and as a therapeutic targets.

Sarkar S, Quinn BA, Shen X, et al.
Reversing translational suppression and induction of toxicity in pancreatic cancer cells using a chemoprevention gene therapy approach.
Mol Pharmacol. 2015; 87(2):286-95 [PubMed] Article available free on PMC after 01/02/2016 Related Publications
Pancreatic cancer is an aggressive disease with limited therapeutic options. Melanoma differentiation-associated gene-7/interleukin-24 (mda-7/IL-24), a potent antitumor cytokine, shows cancer-specific toxicity in a vast array of human cancers, inducing endoplasmic reticulum stress and apoptosis, toxic autophagy, an antitumor immune response, an antiangiogenic effect, and a significant "bystander" anticancer effect that leads to enhanced production of this cytokine through autocrine and paracrine loops. Unfortunately, mda-7/IL-24 application in pancreatic cancer has been restricted because of a "translational block" occurring after Ad.5-mda-7 gene delivery. Our previous research focused on developing approaches to overcome this block and increase the translation of the MDA-7/IL-24 protein, thereby promoting its subsequent toxic effects in pancreatic cancer cells. We demonstrated that inducing reactive oxygen species (ROS) after adenoviral infection of mda-7/IL-24 leads to greater translation into MDA-7/IL-24 protein and results in toxicity in pancreatic cancer cells. In this study we demonstrate that a novel chimeric serotype adenovirus, Ad.5/3-mda-7, displays greater efficacy in delivering mda-7/IL-24 compared with Ad.5-mda-7, although overall translation of the protein still remains low. We additionally show that d-limonene, a dietary monoterpene known to induce ROS, is capable of overcoming the translational block when used in combination with adenoviral gene delivery. This novel combination results in increased polysome association of mda-7/IL-24 mRNA, activation of the preinitiation complex of the translational machinery in pancreatic cancer cells, and culminates in mda-7/IL-24-mediated toxicity.

Baer R, Cintas C, Dufresne M, et al.
Pancreatic cell plasticity and cancer initiation induced by oncogenic Kras is completely dependent on wild-type PI 3-kinase p110α.
Genes Dev. 2014; 28(23):2621-35 [PubMed] Article available free on PMC after 01/02/2016 Related Publications
Increased PI 3-kinase (PI3K) signaling in pancreatic ductal adenocarcinoma (PDAC) correlates with poor prognosis, but the role of class I PI3K isoforms during its induction remains unclear. Using genetically engineered mice and pharmacological isoform-selective inhibitors, we found that the p110α PI3K isoform is a major signaling enzyme for PDAC development induced by a combination of genetic and nongenetic factors. Inactivation of this single isoform blocked the irreversible transition of exocrine acinar cells into pancreatic preneoplastic ductal lesions by oncogenic Kras and/or pancreatic injury. Hitting the other ubiquitous isoform, p110β, did not prevent preneoplastic lesion initiation. p110α signaling through small GTPase Rho and actin cytoskeleton controls the reprogramming of acinar cells and regulates cell morphology in vivo and in vitro. Finally, p110α was necessary for pancreatic ductal cancers to arise from Kras-induced preneoplastic lesions by increasing epithelial cell proliferation in the context of mutated p53. Here we identify an in vivo context in which p110α cellular output differs depending on the epithelial transformation stage and demonstrate that the PI3K p110α is required for PDAC induced by oncogenic Kras, the key driver mutation of PDAC. These data are critical for a better understanding of the development of this lethal disease that is currently without efficient treatment.

Jiang J, Li Z, Yu C, et al.
MiR-1181 inhibits stem cell-like phenotypes and suppresses SOX2 and STAT3 in human pancreatic cancer.
Cancer Lett. 2015; 356(2 Pt B):962-70 [PubMed] Related Publications
Recent studies have shown that cancer stem cells (CSCs) play an important role in the development of pancreatic cancer. Multiple oncogenes and signaling pathways have been confirmed to participate in the stemness maintenance and tumorigenicity of CSCs, including sex-determining region Y-box 2 (SOX2) and signal transduction and activation of transcription 3 (STAT3), which may provide novel therapeutic targets on pancreatic cancer. Here, we reported in pancreatic cancer tissues and cells that miR-1181 expression was markedly downregulated, and the low miR-1181 expression was associated with poorer overall survival and disease-free survival in pancreatic cancer patients. Furthermore, overexpression of miR-1181 inhibited, whereas downregulation of miR-1181 promoted, CSCs-like phenotypes in vitro and tumorigenicity in vivo in pancreatic cancer cells. Moreover, we demonstrated that miR-1181 directly suppressed SOX2 and STAT3 expression, resulting in downregulation of SOX2 and inhibition of the STAT3 pathway. Hence, our results suggest that miR-1181 plays a vital role in inhibiting the CSCs-like phenotypes in pancreatic cancer and might represent a potential target for anti-pancreatic cancer.

Shi C, Klimstra DS
Pancreatic neuroendocrine tumors: pathologic and molecular characteristics.
Semin Diagn Pathol. 2014; 31(6):498-511 [PubMed] Related Publications
Pancreatic neuroendocrine neoplasms include mainly well-differentiated neuroendocrine tumors but also rare poorly differentiated neuroendocrine carcinomas. Molecular mechanisms underlying pancreatic neuroendocrine tumorigenesis have recently been elucidated. While alterations in the chromatin remodeling and PI3K/Akt/mTOR pathways are present in most well-differentiated pancreatic neuroendocrine tumors, mutations in TP53 and RB may contribute to the development of pancreatic poorly differentiated neuroendocrine carcinomas. With these discoveries, new molecular targeted therapies have become available and show promise in some patients with pancreatic well-differentiated neuroendocrine tumor.

Fukushima N, Zamboni G
Mucinous cystic neoplasms of the pancreas: update on the surgical pathology and molecular genetics.
Semin Diagn Pathol. 2014; 31(6):467-74 [PubMed] Related Publications
Mucinous cystic neoplasms (MCNs) of the pancreas are primary pancreatic cyst-forming neoplasms that can be a precursor to invasive adenocarcinoma of the pancreas. MCNs occur almost exclusively in the distal pancreas of middle-aged women. MCNs typically show a "cyst-in-cyst" pattern of growth and are well encapsulated by a thick fibrous wall. MCNs are composed of mucin-producing neoplastic epithelial cells and "ovarian-type" subepithelial stroma. The epithelium is dysplastic and the grade can range from low to high grade; some MCNs have an associated invasive carcinoma. It is this associated invasive carcinoma that determines prognosis. MCNs harbor several characteristic genetic and epigenetic alterations, some of which are shared with conventional invasive pancreatic ductal adenocarcinoma. Furthermore, several studies reveal characteristic patterns of gene expression in the ovarian-type stroma that suggest steroidogenesis in the ovarian-type stroma. Better knowledge of the molecular alterations could help in the management of patients with this type of precursor of invasive carcinoma.

Wood LD, Klimstra DS
Pathology and genetics of pancreatic neoplasms with acinar differentiation.
Semin Diagn Pathol. 2014; 31(6):491-7 [PubMed] Article available free on PMC after 01/02/2016 Related Publications
Pancreatic neoplasms with acinar differentiation, including acinar cell carcinoma, pancreatoblastoma, and carcinomas with mixed differentiation, are distinctive pancreatic neoplasms with a poor prognosis. These neoplasms are clinically, pathologically, and genetically unique when compared to other more common pancreatic neoplasms. Most occur in adults, although pancreatoblastomas usually affect children under 10 years old. All of these neoplasms exhibit characteristic histologic features including a solid or acinar growth pattern, dense neoplastic cellularity, uniform nuclei with prominent nucleoli, and granular eosinophilic cytoplasm. Exocrine enzymes are detectable by immunohistochemistry and, for carcinomas with mixed differentiation, neuroendocrine or ductal lineage markers are also expressed. The genetic alterations of this family of neoplasms largely differ from conventional ductal adenocarcinomas, with only rare mutations in TP53, KRAS, and p16, but no single gene or neoplastic pathway is consistently altered in acinar neoplasms. Instead, there is striking genomic instability, and a subset of cases has mutations in the APC/β-catenin pathway, mutations in SMAD4, RAF gene family fusions, or microsatellite instability. Therapeutically targetable mutations are often present. This review summarizes the clinical and pathologic features of acinar neoplasms and reviews the current molecular data on these uncommon tumors.

Ding L, Han L, Li Y, et al.
Neurogenin 3-directed cre deletion of Tsc1 gene causes pancreatic acinar carcinoma.
Neoplasia. 2014; 16(11):909-17 [PubMed] Article available free on PMC after 01/02/2016 Related Publications
The role of tuberous sclerosis complex (TSC) in the pathogenesis of pancreatic cancers remains largely unknown. The present study shows that neurogenin 3 directed Cre deletion of Tsc1 gene induces the development of pancreatic acinar carcinoma. By cross-breeding the Neurog3-cre mice with Tsc1 (loxp/loxp) mice, we generated the Neurog3-Tsc1-/- transgenic mice in which Tsc1 gene is deleted and mTOR signaling activated in the pancreatic progenitor cells. All Neurog3-Tsc1-/- mice developed notable adenocarcinoma-like lesions in pancreas starting from the age of 100 days old. The tumor lesions are composed of cells with morphological and molecular resemblance to acinar cells. Metastasis of neoplasm to liver and lung was detected in 5% of animals. Inhibition of mTOR signaling by rapamycin significantly attenuated the growth of the neoplasm. Relapse of the neoplasm occurred within 14 days upon cessation of rapamycin treatment. Our studies indicate that activation of mTOR signaling in the pancreatic progenitor cells may trigger the development of acinar carcinoma. Thus, mTOR may serve as a potential target for treatment of pancreatic acinar carcinoma.

Listing H, Mardin WA, Wohlfromm S, et al.
MiR-23a/-24-induced gene silencing results in mesothelial cell integration of pancreatic cancer.
Br J Cancer. 2015; 112(1):131-9 [PubMed] Article available free on PMC after 06/01/2016 Related Publications
BACKGROUND: Invasion of the surrounding tissue is part of the metastatic cascade. Here, we examined the invasion of pancreatic ductal adenocarcinoma (PDAC) cells into the mesothelial barrier and identified the related microRNA (miRNA) expression profiles.
METHODS: The interactions between PDAC cells and mesothelial monolayers were characterised and quantified using a specific time-lapse videomicroscopy assay. Pancreatic ductal adenocarcinoma cells were further evaluated using the adhesion assay, and miRNA, mRNA and protein expressions were determined using microarray, q-RT-PCR and western blots, respectively. These data were correlated with in vivo dissemination scores.
RESULTS: Two groups of PDAC cell lines were distinguished by their integration capacity into the mesothelial monolayer using mean elongation factors (MEFs). Adhesion assays showed a concordant relation between adhesive properties and integration capacity. The distant metastases scores were reverse correlated with MEFs. Microarray analysis of these groups revealed that miR-23a and/or miR-24 target for FZD5, HNF1B and/or TMEM92, respectively, and that they are significantly deregulated.
CONCLUSIONS: MiR-23a and/or miR-24 overexpression leads to gene silencing of FZD5, TMEM92 and/or HNF1B. Their downregulation induces deregulated expression and degradation of E-cadherin and β-catenin causing destabilisation of the cadherin/catenin complex, and altered the expression of Wnt-related genes. We propose a molecular (epi)genetic mechanism by which increased EMT-like cell shape transformation and integration into mesothelial monolayers of PDAC cells can be observed.

Pilarsky C, Grützmann R
Analysis of DNA methylation in pancreatic cancer: an update.
Methods Mol Biol. 2015; 1238:173-81 [PubMed] Related Publications
Pancreatic ductal adenocarcinoma (PDAC) is an aggressive tumor and the fourth common cause of cancer death in the Western world. The lack of effective therapeutic strategies is due to the late diagnosis of this disease. Methylation markers could improve early detection and help in the surveillance of PDAC after treatment. Analysis of hypermethylation in the tumor tissue might help to identify new therapeutic strategies and aid in the understanding of the pathophysiological changes occurring in pancreatic cancer. There are several methods for the detection of methylated events, but methylation-specific PCR (MSP-PCR) is the method of choice if a small number of genes will be tested in a larger set of patients samples. After isolation of the DNA by standard procedure, the DNA is then modified using sodium bisulfide.

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