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

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

Mutated Genes and Abnormal Protein Expression (229)

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
KRAS 12p12.1 NS, NS3, CFC2, RALD, KRAS1, KRAS2, RASK2, KI-RAS, C-K-RAS, K-RAS2A, K-RAS2B, K-RAS4A, K-RAS4B, c-Ki-ras2 -KRAS and Pancreatic Cancer
548
CDKN2A 9p21.3 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
376
MEN1 11q13.1 MEAI, SCG2 -MEN1 and Pancreatic Cancer
298
SMAD4 18q21.2 JIP, DPC4, MADH4, MYHRS -SMAD4 and Pancreatic Cancer
284
BRCA2 13q13.1 FAD, FACD, FAD1, GLM3, BRCC2, FANCD, PNCA2, FANCD1, XRCC11, BROVCA2 Germline
-BRCA2 mutations in Pancreatic Cancer
242
TP53 17p13.1 P53, BCC7, LFS1, TRP53 -TP53 and Pancreatic Cancer
180
MTOR 1p36.22 SKS, FRAP, FRAP1, FRAP2, RAFT1, RAPT1 -MTOR and Pancreatic Cancer
114
MUC1 1q22 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
110
CEACAM5 19q13.2 CEA, CD66e -CEACAM5 and Pancreatic Cancer
85
GNAS 20q13.32 AHO, GSA, GSP, POH, GPSA, NESP, SCG6, SgVI, GNAS1, PITA3, C20orf45 -GNAS and Pancreatic Cancer
67
HIF1A 14q23.2 HIF1, MOP1, PASD8, HIF-1A, bHLHe78, HIF-1alpha, HIF1-ALPHA, HIF-1-alpha -HIF1A and Pancreatic Cancer
65
MUC6 11p15.5 MUC-6 -MUC6 and Pancreatic Cancer
53
CCK 3p22.1 -CCK and Pancreatic Cancer
49
ACHE 7q22.1 YT, ACEE, ARACHE, N-ACHE -ACHE and Pancreatic Cancer
46
SSTR2 17q25.1 -SSTR2 and Pancreatic Cancer
46
AR Xq12 KD, AIS, AR8, TFM, DHTR, SBMA, HYSP1, NR3C4, SMAX1, HUMARA -AR and Pancreatic Cancer
45
MUC4 3q29 ASGP, MUC-4, HSA276359 -MUC4 and Pancreatic Cancer
44
ATRX Xq21.1 JMS, XH2, XNP, MRX52, RAD54, RAD54L, ZNF-HX -ATRX and Pancreatic Cancer
39
CXCR4 2q21 FB22, HM89, LAP3, LCR1, NPYR, WHIM, CD184, LAP-3, LESTR, NPY3R, NPYRL, WHIMS, HSY3RR, NPYY3R, D2S201E -CXCR4 and Pancreatic Cancer
35
PDX1 13q12.2 GSF, IPF1, IUF1, IDX-1, MODY4, PDX-1, STF-1, PAGEN1 -PDX1 and Pancreatic Cancer
34
SMAD2 18q21.1 JV18, MADH2, MADR2, JV18-1, hMAD-2, hSMAD2 -SMAD2 and Pancreatic Cancer
33
ZEB1 10p11.22 BZP, TCF8, AREB6, FECD6, NIL2A, PPCD3, ZFHEP, ZFHX1A, DELTAEF1 -ZEB1 and Pancreatic Cancer
33
STK11 19p13.3 PJS, LKB1, hLKB1 -STK11 and Pancreatic Cancer
32
PRSS1 7q34 TRP1, TRY1, TRY4, TRYP1 -PRSS1 and Pancreatic Cancer
32
TGFBR1 9q22.33 AAT5, ALK5, ESS1, LDS1, MSSE, SKR4, ALK-5, LDS1A, LDS2A, TGFR-1, ACVRLK4, tbetaR-I -TGFBR1 and Pancreatic Cancer
31
XIAP Xq25 API3, ILP1, MIHA, XLP2, BIRC4, IAP-3, hIAP3, hIAP-3 -XIAP and Pancreatic Cancer
30
CFTR 7q31.2 CF, MRP7, ABC35, ABCC7, CFTR/MRP, TNR-CFTR, dJ760C5.1 -CFTR and Pancreatic Cancer
29
GLI1 12q13.2-q13.3 GLI -GLI1 and Pancreatic Cancer
29
SPINK1 5q32 TCP, PCTT, PSTI, TATI, Spink3 -SPINK1 and Pancreatic Cancer
28
TGFBR2 3p24.1 AAT3, FAA3, LDS2, MFS2, RIIC, LDS1B, LDS2B, TAAD2, TGFR-2, TGFbeta-RII -TGFBR2 and Pancreatic Cancer
27
MUC5AC 11p15.5 TBM, leB, MUC5, mucin -MUC5AC and Pancreatic Cancer
27
DAXX 6p21.32 DAP6, EAP1, BING2 -DAXX and Pancreatic Cancer
23
SPARC 5q33.1 ON, OI17, BM-40 -SPARC and Pancreatic Cancer
23
ARID1A 1p36.11 ELD, B120, CSS2, OSA1, P270, hELD, BM029, MRD14, hOSA1, BAF250, C1orf4, BAF250a, SMARCF1 -ARID1A and Pancreatic Cancer
23
RRM1 11p15.4 R1, RR1, RIR1 -RRM1 and Pancreatic Cancer
22
CD24 6q21 CD24A -CD24 and Pancreatic Cancer
22
ABCG2 4q22.1 MRX, MXR, ABCP, BCRP, BMDP, MXR1, ABC15, BCRP1, CD338, GOUT1, MXR-1, CDw338, UAQTL1, EST157481 -ABCG2 and Pancreatic Cancer
20
SLC29A1 6p21.1 ENT1 -SLC29A1 and Pancreatic Cancer
20
SIRT1 10q21.3 SIR2, SIR2L1, SIR2alpha -SIRT1 and Pancreatic Cancer
20
S100A4 1q21.3 42A, 18A2, CAPL, FSP1, MTS1, P9KA, PEL98 -S100A4 and Pancreatic Cancer
20
SOX10 22q13.1 DOM, WS4, PCWH, WS2E, WS4C -SOX10 and Pancreatic Cancer
20
FHIT 3p14.2 FRA3B, AP3Aase -FHIT and Pancreatic Cancer
18
NR5A2 1q32.1 B1F, CPF, FTF, B1F2, LRH1, LRH-1, FTZ-F1, hB1F-2, FTZ-F1beta -NR5A2 and Pancreatic Cancer
17
SOX9 17q24.3 CMD1, SRA1, CMPD1, SRXX2, SRXY10 -SOX9 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
SMO 7q32.1 Gx, CRJS, SMOH, FZD11 -SMO and Pancreatic Cancer
16
CDX2 13q12.2 CDX3, CDX-3, CDX2/AS -CDX2 and Pancreatic Cancer
16
GATA6 18q11.2 -GATA6 and Pancreatic Cancer
13
S100P 4p16.1 MIG9 -S100P and Pancreatic Cancer
13
PSCA 8q24.3 PRO232 -PSCA and Pancreatic Cancer
13
RHOC 1p13.2 H9, ARH9, ARHC, RHOH9 -RHOC expression in Pancreatic Cancer
12
L1CAM Xq28 S10, HSAS, MASA, MIC5, SPG1, CAML1, CD171, HSAS1, N-CAML1, NCAM-L1, N-CAM-L1 -L1CAM and Pancreatic Cancer
12
RUNX3 1p36.11 AML2, CBFA3, PEBP2aC -RUNX3 and Pancreatic Cancer
12
MARCO 2q14.2 SCARA2 -MARCO and Pancreatic Cancer
10
MUC16 19p13.2 CA125 -MUC16 and Pancreatic Cancer
10
MAP2K4 17p12 JNKK, MEK4, MKK4, SEK1, SKK1, JNKK1, SERK1, MAPKK4, PRKMK4, SAPKK1, SAPKK-1 -MAP2K4 and Pancreatic Cancer
10
DUSP6 12q21.33 HH19, MKP3, PYST1 -DUSP6 and Pancreatic Cancer
10
GADD45A 1p31.3 DDIT1, GADD45 -GADD45A and Pancreatic Cancer
10
LGALS1 22q13.1 GBP, GAL1 -LGALS1 and Pancreatic Cancer
10
ADRB2 5q32 BAR, B2AR, ADRBR, ADRB2R, BETA2AR -ADRB2 and Pancreatic Cancer
9
CEACAM6 19q13.2 NCA, CEAL, CD66c -CEACAM6 and Pancreatic Cancer
9
VIP 6q25.2 PHM27 -VIP and Pancreatic Cancer
9
TGFB2 1q41 LDS4, G-TSF, TGF-beta2 -TGFB2 and Pancreatic Cancer
9
SMAD7 18q21.1 CRCS3, MADH7, MADH8 -SMAD7 and Pancreatic Cancer
9
SSTR5 16p13.3 SS-5-R -SSTR5 and Pancreatic Cancer
9
TNFRSF10A 8p21.3 DR4, APO2, CD261, TRAILR1, TRAILR-1 -TNFRSF10A and Pancreatic Cancer
8
CD68 17p13.1 GP110, LAMP4, SCARD1 -CD68 and Pancreatic Cancer
8
VAV1 19p13.3 VAV -VAV1 and Pancreatic Cancer
8
MUC5B 11p15.5 MG1, MUC5, MUC9, MUC-5B -MUC5B and Pancreatic Cancer
8
KDM6A Xp11.3 UTX, KABUK2, bA386N14.2 -KDM6A and Pancreatic Cancer
8
NFATC2 20q13.2 NFAT1, NFATP -NFATC2 and Pancreatic Cancer
8
RRM2 2p25-p24 R2, RR2, RR2M -RRM2 and Pancreatic Cancer
8
PIGS 17q11.2 -PIGS and Pancreatic Cancer
8
S100A6 1q21.3 2A9, PRA, 5B10, CABP, CACY, S10A6 -S100A6 and Pancreatic Cancer
8
MIR126 9q34.3 MIRN126, mir-126, miRNA126 -MIRN126 microRNA, human and Pancreatic Cancer
7
LAMC2 1q25.3 B2T, CSF, EBR2, BM600, EBR2A, LAMB2T, LAMNB2 -LAMC2 and Pancreatic Cancer
7
NDRG1 8q24.22 GC4, RTP, DRG1, NDR1, NMSL, TDD5, CAP43, CMT4D, DRG-1, HMSNL, RIT42, TARG1, PROXY1 -NDRG1 and Pancreatic Cancer
7
MBD1 18q21.1 RFT, PCM1, CXXC3 -MBD1 and Pancreatic Cancer
7
AGR2 7p21.1 AG2, AG-2, HPC8, GOB-4, HAG-2, XAG-2, PDIA17, HEL-S-116 -AGR2 and Pancreatic Cancer
7
RALA 7p14.1 RAL -RALA and Pancreatic Cancer
7
TFF2 21q22.3 SP, SML1 -TFF2 and Pancreatic Cancer
7
SSTR1 14q21.1 SS1R, SS1-R, SRIF-2, SS-1-R -SSTR1 and Pancreatic Cancer
7
MIRLET7C 21q21.1 LET7C, let-7c, MIRNLET7C, hsa-let-7c -MicroRNA let-7cand Pancreatic Cancer
7
BNIP3 10q26.3 NIP3 -BNIP3 and Pancreatic Cancer
7
HBEGF 5q31.3 DTR, DTS, DTSF, HEGFL -HBEGF and Pancreatic Cancer
6
UCHL1 4p13 NDGOA, PARK5, PGP95, SPG79, PGP9.5, Uch-L1, HEL-117, PGP 9.5, HEL-S-53 -UCHL1 and Pancreatic Cancer
6
CAST 5q15 BS-17, PLACK -CAST and Pancreatic Cancer
6
IMP3 15q24.2 BRMS2, MRPS4, C15orf12 -IMP3 and Pancreatic Cancer
6
NR4A1 12q13 HMR, N10, TR3, NP10, GFRP1, NAK-1, NGFIB, NUR77 -NR4A1 and Pancreatic Cancer
6
NOTCH4 6p21.32 INT3 -NOTCH4 and Pancreatic Cancer
6
RHOB 2p24 ARH6, ARHB, RHOH6, MST081, MSTP081 -RHOB and Pancreatic Cancer
6
NAT1 8p22 AAC1, MNAT, NATI, NAT-1 -NAT1 and Pancreatic Cancer
6
ACCS 11p11.2 ACS, PHACS -ACCS and Pancreatic Cancer
6
REG4 1p12 GISP, RELP, REG-IV -REG4 and Pancreatic Cancer
6
MIR1290 1p36.13 MIRN1290, hsa-mir-1290 -miR-1290 and Pancreatic Cancer
6
MSLN 16p13.3 MPF, SMRP -MSLN and Pancreatic Cancer
6
AGTR2 Xq23 AT2, ATGR2, MRX88 -AGTR2 and Pancreatic Cancer
6
MICB 6p21.33 PERB11.2 -MICB and Pancreatic Cancer
6
PDPK1 16p13.3 PDK1, PDPK2, PDPK2P, PRO0461 -PDPK1 and Pancreatic Cancer
6
STRADA 17q23.3 LYK5, PMSE, Stlk, STRAD, NY-BR-96 -STRADA and Pancreatic Cancer
6
TP53INP1 8q22.1 SIP, Teap, p53DINP1, TP53DINP1, TP53INP1A, TP53INP1B -TP53INP1 and Pancreatic Cancer
5
SMAD6 15q22.31 AOVD2, MADH6, MADH7, HsT17432 -SMAD6 and Pancreatic Cancer
5
ABCC4 13q32.1 MRP4, MOATB, MOAT-B -ABCC4 and Pancreatic Cancer
5
ROBO1 3p12 SAX3, DUTT1 -ROBO1 and Pancreatic Cancer
5
TFPI 2q32 EPI, TFI, LACI, TFPI1 -TFPI and Pancreatic Cancer
5
ADAM9 8p11.22 MCMP, MDC9, CORD9, Mltng -ADAM9 and Pancreatic Cancer
5
CXCR2 2q35 CD182, IL8R2, IL8RA, IL8RB, CMKAR2, CDw128b -CXCR2 and Pancreatic Cancer
5
HOXB7 17q21.32 HOX2, HOX2C, HHO.C1, Hox-2.3 -HOXB7 and Pancreatic Cancer
5
PAK4 19q13.2 -PAK4 and Pancreatic Cancer
5
CLDN4 7q11.23 CPER, CPE-R, CPETR, CPETR1, WBSCR8, hCPE-R -CLDN4 and Pancreatic Cancer
5
NEUROD1 2q32 BETA2, BHF-1, MODY6, NEUROD, bHLHa3 -NEUROD1 and Pancreatic Cancer
4
RREB1 6p24.3 HNT, FINB, LZ321, Zep-1, RREB-1 -RREB1 and Pancreatic Cancer
4
TM4SF1 3q25.1 L6, H-L6, M3S1, TAAL6 -TM4SF1 and Pancreatic Cancer
4
MIR107 10q23.31 MIRN107, miR-107 -MicroRNA mir-107 and Pancreatic Cancer
4
LCN2 9q34.11 p25, 24p3, MSFI, NGAL -LCN2 and Pancreatic Cancer
4
RALGDS 9q34.13-q34.2 RGF, RGDS, RalGEF -RALGDS and Pancreatic Cancer
4
PARK7 1p36.23 DJ1, DJ-1, GATD2, HEL-S-67p -PARK7 and Pancreatic Cancer
4
RALB 2q14.2 -RALB and Pancreatic Cancer
4
MUC17 7q22.1 MUC3, MUC-3, MUC-17 -MUC17 and Pancreatic Cancer
4
GHRH 20q11.23 GRF, INN, GHRF -GHRH and Pancreatic Cancer
4
CCKBR 11p15.4 GASR, CCK-B, CCK2R -CCKBR and Pancreatic Cancer
4
CASP9 1p36.21 MCH6, APAF3, APAF-3, PPP1R56, ICE-LAP6 -CASP9 and Pancreatic Cancer
4
KRT7 12q13.13 K7, CK7, SCL, K2C7 -KRT7 and Pancreatic Cancer
4
TNFRSF10C 8p21.3 LIT, DCR1, TRID, CD263, TRAILR3, TRAIL-R3, DCR1-TNFR -TNFRSF10C and Pancreatic Cancer
4
MAPK3 16p11.2 ERK1, ERT2, ERK-1, PRKM3, P44ERK1, P44MAPK, HS44KDAP, HUMKER1A, p44-ERK1, p44-MAPK -MAPK3 and Pancreatic Cancer
4
CXCL5 4q13.3 SCYB5, ENA-78 -CXCL5 and Pancreatic Cancer
4
PBRM1 3p21.1 PB1, BAF180 -PBRM1 and Pancreatic Cancer
4
PTPRC 1q31.3-q32.1 LCA, LY5, B220, CD45, L-CA, T200, CD45R, GP180 -PTPRC and Pancreatic Cancer
4
TFPI2 7q21.3 PP5, REF1, TFPI-2 -TFPI2 and Pancreatic Cancer
4
CCNG1 5q34 CCNG -CCNG1 and Pancreatic Cancer
4
AKR1B10 7q33 HIS, HSI, ARL1, ARL-1, ALDRLn, AKR1B11, AKR1B12 -AKR1B10 and Pancreatic Cancer
4
GADD45B 19p13.3 MYD118, GADD45BETA -GADD45B and Pancreatic Cancer
4
HHIP 4q31.21 HIP -HHIP and Pancreatic Cancer
4
RAD54L 1p34.1 HR54, hHR54, RAD54A, hRAD54 -RAD54L and Pancreatic Cancer
3
TGFBI 5q31.1 CSD, CDB1, CDG2, CSD1, CSD2, CSD3, EBMD, LCD1, BIGH3, CDGG1 -TGFBI and Pancreatic Cancer
3
CDH3 16q22.1 CDHP, HJMD, PCAD -CDH3 and Pancreatic Cancer
3
SLCO1B3 12p12.2 LST3, HBLRR, LST-2, OATP8, OATP-8, OATP1B3, SLC21A8, LST-3TM13 -SLCO1B3 and Pancreatic Cancer
3
LYVE1 11p15.4 HAR, XLKD1, LYVE-1, CRSBP-1 -LYVE1 and Pancreatic Cancer
3
ID2 2p25 GIG8, ID2A, ID2H, bHLHb26 Overexpression
-ID2 Overexpression in Pancreatic Cancer
3
WNT3A 1q42.13 -WNT3A and Pancreatic Cancer
3
ING4 12p13.31 my036, p29ING4 -ING4 and Pancreatic Cancer
3
OCLN 5q13.2 BLCPMG, PPP1R115 -OCLN and Pancreatic Cancer
3
LGALS4 19q13.2 GAL4, L36LBP -LGALS4 and Pancreatic Cancer
3
FGF7 15q21.2 KGF, HBGF-7 -FGF7 and Pancreatic Cancer
3
PCDH10 4q28.3 PCDH19, OL-PCDH -PCDH10 and Pancreatic Cancer
3
CHGA 14q32.12 CGA -CHGA and Pancreatic Cancer
3
CLDN7 17p13.1 CLDN-7, CEPTRL2, CPETRL2, Hs.84359, claudin-1 -CLDN7 and Pancreatic Cancer
3
TNFRSF25 1p36.31 DR3, TR3, DDR3, LARD, APO-3, TRAMP, WSL-1, GEF720, WSL-LR, PLEKHG5, TNFRSF12 -TNFRSF25 and Pancreatic Cancer
3
MUC7 4q13.3 MG2 -MUC7 and Pancreatic Cancer
3
MCM7 7q22.1 MCM2, CDC47, P85MCM, P1CDC47, PNAS146, PPP1R104, P1.1-MCM3 -MCM7 and Pancreatic Cancer
3
MIR10A 17q21.32 MIRN10A, mir-10a, miRNA10A, hsa-mir-10a -miR-10a and Pancreatic Cancer
3
UPRT Xq13.3 UPP, FUR1 -UPRT and Pancreatic Cancer
3
ACTN4 19q13.2 FSGS, FSGS1, ACTININ-4 -ACTN4 and Pancreatic Cancer
3
UCP2 11q13.4 UCPH, BMIQ4, SLC25A8 -UCP2 and Pancreatic Cancer
3
FOXE1 9q22.33 TTF2, FOXE2, HFKH4, HFKL5, NMTC4, TITF2, TTF-2, FKHL15 -FOXE1 and Pancreatic Cancer
3
NOX4 11q14.3 KOX, KOX-1, RENOX -NOX4 and Pancreatic Cancer
3
PLAU 10q22.2 ATF, QPD, UPA, URK, u-PA, BDPLT5 -PLAU and Pancreatic Cancer
3
TRPM8 2q37.1 TRPP8, LTRPC6 -TRPM8 and Pancreatic Cancer
3
ECT2 3q26.31 ARHGEF31 -ECT2 and Pancreatic Cancer
3
HLA-B 6p21.33 AS, HLAB, B-4901 -HLA-B and Pancreatic Cancer
3
CXCL13 4q21.1 BLC, BCA1, ANGIE, BCA-1, BLR1L, ANGIE2, SCYB13 -CXCL13 and Pancreatic Cancer
3
IRAK1 Xq28 IRAK, pelle -IRAK1 and Pancreatic Cancer
3
SUV39H1 Xp11.23 MG44, KMT1A, SUV39H, H3-K9-HMTase 1 -SUV39H1 and Pancreatic Cancer
3
AMFR 16q13 GP78, RNF45 -AMFR and Pancreatic Cancer
3
S100A11 1q21.3 MLN70, S100C, HEL-S-43 -S100A11 and Pancreatic Cancer
3
CD276 15q24.1 B7H3, B7-H3, B7RP-2, 4Ig-B7-H3 -CD276 and Pancreatic Cancer
3
NFATC1 18q23 NFAT2, NFATc, NF-ATC, NF-ATc1.2 -NFATC1 and Pancreatic Cancer
3
DEC1 9q33.1 CTS9 -DEC1 and Pancreatic Cancer
3
IER3 6p21.3 DIF2, IEX1, PRG1, DIF-2, GLY96, IEX-1, IEX-1L -IER3 and Pancreatic Cancer
3
TLR7 Xp22.2 TLR7-like -TLR7 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
MAPKAPK2 1q32.1 MK2, MK-2, MAPKAP-K2 -MAPKAPK2 and Pancreatic Cancer
3
PROX1 1q32.3 -PROX1 and Pancreatic Cancer
3
MIRLET7D 9q22.32 LET7D, let-7d, MIRNLET7D, hsa-let-7d -MicroRNA let-d and Pancreatic Cancer
3
MTA2 11q12.3 PID, MTA1L1 -MTA2 and Pancreatic Cancer
2
TCF7 5q31.1 TCF-1 -TCF7 and Pancreatic Cancer
2
MMP10 11q22.2 SL-2, STMY2 -MMP10 and Pancreatic Cancer
2
HPSE 4q21.23 HPA, HPA1, HPR1, HSE1, HPSE1 -HPSE and Pancreatic Cancer
2
NEDD4 15q21.3 RPF1, NEDD4-1 -NEDD4 and Pancreatic Cancer
2
OLFM4 13q14.3 GC1, OLM4, OlfD, GW112, hGC-1, hOLfD, UNQ362, bA209J19.1 -OLFM4 and Pancreatic Cancer
2
PVT1 8q24.21 MYC, LINC00079, NCRNA00079, onco-lncRNA-100 -PVT1 and Pancreatic Cancer
2
ITGB4 17q25.1 CD104, GP150 -ITGB4 and Pancreatic Cancer
2
CYBA 16q24.2 p22-PHOX -CYBA and Pancreatic Cancer
2
SST 3q27.3 SMST -SST and Pancreatic Cancer
2
ADAMTS1 21q21.3 C3-C5, METH1 -ADAMTS1 and Pancreatic Cancer
2
ULBP2 6q25 N2DL2, RAET1H, NKG2DL2, ALCAN-alpha -ULBP2 and Pancreatic Cancer
2
ARL11 13q14.2 ARLTS1 -ARL11 and Pancreatic Cancer
2
XPO1 2p15 emb, CRM1, exp1 -XPO1 and Pancreatic Cancer
2
CXCL16 17p13.2 SRPSOX, CXCLG16, SR-PSOX -CXCL16 and Pancreatic Cancer
2
ARID2 12q12 p200, BAF200 -ARID2 and Pancreatic Cancer
2
REG1A 2p12 P19, PSP, PTP, REG, ICRF, PSPS, PSPS1 -REG1A and Pancreatic Cancer
2
SERPINA1 14q32.13 PI, A1A, AAT, PI1, A1AT, PRO2275, alpha1AT -SERPINA1 and Pancreatic Cancer
2
RPS6 9p22.1 S6 -RPS6 and Pancreatic Cancer
2
ANXA8 10q11.22 ANX8, CH17-360D5.2 -ANXA8 and Pancreatic Cancer
2
RALBP1 18p11.22 RIP1, RLIP1, RLIP76 -RALBP1 and Pancreatic Cancer
2
POLB 8p11.21 -POLB and Pancreatic Cancer
2
KL 13q13.1 -KL and Pancreatic Cancer
2
ST14 11q24.3 HAI, MTSP1, SNC19, ARCI11, MT-SP1, PRSS14, TADG15, TMPRSS14 -ST14 and Pancreatic Cancer
2
ZNF331 19q13.42 RITA, ZNF361, ZNF463 -ZNF331 and Pancreatic Cancer
2
CDCP1 3p21.31 CD318, TRASK, SIMA135 -CDCP1 and Pancreatic Cancer
2
GAGE1 Xp11.23 CT4.1, CT4.4, GAGE4, GAGE-1, GAGE-4 -GAGE1 and Pancreatic Cancer
2
IGF2-AS 11p15.5 PEG8, IGF2AS, IGF2-AS1 -IGF2-AS and Pancreatic Cancer
2
PLAT 8p11.21 TPA, T-PA -PLAT and Pancreatic Cancer
2
CX3CL1 16q21 NTN, NTT, CXC3, CXC3C, SCYD1, ABCD-3, C3Xkine, fractalkine, neurotactin -CX3CL1 and Pancreatic Cancer
2
HSPA1B 6p21.3 HSP70-2, HSP70.2, HSP70-1B -HSPA1B and Pancreatic Cancer
2
CSF1 1p13.3 MCSF, CSF-1 -CSF1 and Pancreatic Cancer
2
SULF1 8q13.2-q13.3 SULF-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
HAVCR2 5q33.3 TIM3, CD366, KIM-3, TIMD3, Tim-3, TIMD-3, HAVcr-2 -HAVCR2 and Pancreatic Cancer
2
INHBA 7p14.1 EDF, FRP -INHBA and Pancreatic Cancer
2
SLC9A1 1p36.11 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
TNFRSF6B 20q13.33 M68, TR6, DCR3, M68E, DJ583P15.1.1 Amplification
-TNFRSF6B Amplification and Overexpression in Pancreatic Cancer
2
FOXN3 14q31.3-q32.11 CHES1, PRO1635, C14orf116 -FOXN3 and Pancreatic Cancer
1
MIR1271 5q35.2 MIRN1271, hsa-mir-1271 -MIRN1271 microRNA, human and Pancreatic Cancer
1
BNIP3L 8p21.2 NIX, BNIP3a -BNIP3L and Pancreatic Cancer
1
RAB8A 19p13.11 MEL, RAB8 -RAB8A and Pancreatic Cancer
1
ADAMTS9 3p14.1 -ADAMTS9 and Pancreatic Cancer
1
KDM5C Xp11.22 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
IL1RL1 2q12 T1, ST2, DER4, ST2L, ST2V, FIT-1, IL33R -IL1RL1 and Pancreatic Cancer
1
FBXO11 2p16.3 UBR6, VIT1, FBX11, PRMT9, UG063H01 -FBXO11 and Pancreatic Cancer
1
HLA-C 6p21.33 MHC, HLAC, HLC-C, D6S204, PSORS1, HLA-JY3 -HLA-C and Pancreatic Cancer
1
NOV 8q24.12 CCN3, NOVh, IBP-9, IGFBP9, IGFBP-9 -NOV and Pancreatic Cancer
1
ZNF521 18q11.2 EHZF, Evi3 -ZNF521 and Pancreatic Cancer
1
CEACAM7 19q13.2 CGM2 -CEACAM7 and Pancreatic Cancer
1
ANXA5 4q27 PP4, ANX5, ENX2, RPRGL3, HEL-S-7 -ANXA5 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

Wu X, Zhuo S, Zheng C, Gao G
[MicroRNA-21 correlates TGF-β1 pathway of pancreatic ductal adenocarcinoma].
Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2019; 44(7):749-756 [PubMed] Related Publications
OBJECTIVE: To conduct genetic analysis of pancreatic ductal adenocarcinoma tissues and analyze the correlation between targeted microRNA (miRNA) and pathways in pancreatic ductal adenocarcinoma.
 Methods: We collected 19 samples of peripheral venous blood serum from patients with pancreatic ductal adenocarcinoma in Hainan Provincial Hospital of Chinese Medicine, and also collected 21 blood serum samples as a control group of non-pancreatic ductal adenocarcinoma. We used the bioinformatics analysis of literature GCBI data platform for screening and analyzing the genetics of pancreatic ductal adenocarcinoma samples. Through GCBI data platform of hierarchy clustering analysis and the enrichment of gene function analysis, the relevant miRNA was screened as a research object in patients with pancreatic ductal adenocarcinoma. The miRNA was screened by literature analysis and pancreatic cancer gene analysis. Real-time PCR and Western blotting were carried out to study the relationship between the selected miRNA and TGF-β1 by overexpression and suppression of the gene in pancreatic ductal adenocarcinoma cells.
 Results: MiRNA-21 was screened as a gene associated with pancreatic ductal carcinoma via hierarchy clustering analysis and gene function analysis. MiRNA-21 was highly expressed in the pancreatic ductal carcinoma patients. Expressions of TGF-β1 were inhibired in miRNA-21 overexpressed PANC-1. While the expression of miRNA-21 was inhibited, TGF-β1 expression increased obviously.
 Conclusion: MiRNA-21 is highly expressed in patients with pancreatic ductal adenocarcinoma, can regulate the expression of TGF-β1, which may be a mechanism of miRNA-21 in pancreatic ductal adenocarcinoma.

Akashi M, Hisaka T, Sakai H, et al.
Expression of Matrix Metalloproteinases in Intraductal Papillary Mucinous Neoplasm of the Pancreas.
Anticancer Res. 2019; 39(8):4485-4490 [PubMed] Related Publications
BACKGROUND/AIM: Intraductal papillary mucinous neoplasm (IPMN) has a variety of histological and morphological appearances. Matrix metalloproteinases (MMPs) have been considered to be associated with tumor progression or poor prognosis. The aim of this study was to elucidate the molecular basis of IPMN variation in different types of lesions.
MATERIALS AND METHODS: The expression of MMP-1,2,7,9 in 51 cases of IPMN were investigated. The MMP score was calculated as the sum of the score of staining distribution and the score of the intensity staining.
RESULTS: MMP scores were correlated with histological grade, histological subtype, and type of invasion. MMP high expression groups (MMP score ≥5) had worse prognosis than low-expression groups.
CONCLUSION: MMP expression varied between different types of IPMN, a result supporting differences in molecular basis of malignancies. These considerations may be helpful for optimal management or treatment according to various types of IPMN.

Aguirre AJ
Oncogenic NRG1 Fusions: A New Hope for Targeted Therapy in Pancreatic Cancer.
Clin Cancer Res. 2019; 25(15):4589-4591 [PubMed] Article available free on PMC after 01/02/2020 Related Publications
Approximately 8%-10% of pancreatic ductal adenocarcinoma cases are

Chen L, Xu X, Wen X, et al.
Targeting PIN1 exerts potent antitumor activity in pancreatic ductal carcinoma via inhibiting tumor metastasis.
Cancer Sci. 2019; 110(8):2442-2455 [PubMed] Article available free on PMC after 01/02/2020 Related Publications
The human prolyl isomerase PIN1, best known for its association with carcinogenesis, has recently been indicated in the disease of pancreatic ductal adenocarcinoma (PDAC). However, the functions of PIN1 and the feasibility of targeting PIN1 in PDAC remain elusive. For this purpose, we examined the expression of PIN1 in cancer, related paracarcinoma and metastatic cancer tissues by immunohistochemistry and analyzed the associations with the pathogenesis of PDAC in 173 patients. The functional roles of PIN1 in PDAC were explored in vitro and in vivo using both genetic and chemical PIN1 inhibition. We showed that PIN1 was upregulated in pancreatic cancer and metastatic tissues. High PIN1 expression is significantly association with poor clinicopathological features and shorter overall survival and disease-free survival. Further stratified analysis showed that PIN1 phenotypes refined prognostication in PDAC. Inhibition of PIN1 expression with RNA interference or with all trans retinoic acid decreased not only the growth but also the migration and invasion of PDAC cells through regulating the key molecules of multiple cancer-driving pathways, simultaneously resulting in cell cycle arrest and mesenchymal-epithelial transition in vitro. Furthermore, genetic and chemical PIN1 ablation showed dramatic inhibition of the tumorigenesis and metastatic spread and then reduced the tumor burden in vivo. We provided further evidence for the use of PIN1 as a promising therapeutic target in PDAC. Genetic and chemical PIN1 ablation exerted potent antitumor effects through blocking multiple cancer-driving pathways in PDAC. More potent and specific PIN1 targeted inhibitors could be exploited to treat this aggressive cancer.

Yang W, Liu H, Duan B, et al.
Three novel genetic variants in NRF2 signaling pathway genes are associated with pancreatic cancer risk.
Cancer Sci. 2019; 110(6):2022-2032 [PubMed] Article available free on PMC after 01/02/2020 Related Publications
Pancreatic cancer (PanC) is one of the most lethal solid malignancies, and metastatic PanC is often present at the time of diagnosis. Although several high- and low-penetrance genes have been implicated in PanC, their roles in carcinogenesis remain only partially elucidated. Because the nuclear factor erythroid2-related factor2 (NRF2) signaling pathway is involved in human cancers, we hypothesize that genetic variants in NRF2 pathway genes are associated with PanC risk. To test this hypothesis, we assessed associations between 31 583 common single nucleotide polymorphisms (SNP) in 164 NRF2-related genes and PanC risk using three published genome-wide association study (GWAS) datasets, which included 8474 cases and 6944 controls of European descent. We also carried out expression quantitative trait loci (eQTL) analysis to assess the genotype-phenotype correlation of the identified significant SNP using publicly available data in the 1000 Genomes Project. We found that three novel SNP (ie, rs3124761, rs17458086 and rs1630747) were significantly associated with PanC risk (P = 5.17 × 10

Lin T, Ren Q, Zuo W, et al.
Valproic acid exhibits anti-tumor activity selectively against EGFR/ErbB2/ErbB3-coexpressing pancreatic cancer via induction of ErbB family members-targeting microRNAs.
J Exp Clin Cancer Res. 2019; 38(1):150 [PubMed] Article available free on PMC after 01/02/2020 Related Publications
BACKGROUND: Deregulated ErbB signaling plays an important role in tumorigenesis of pancreatic cancer. However, patients with pancreatic cancer benefit little from current existed therapies targeting the ErbB signaling. Here, we explore the potential anti-tumor activity of Valproic acid against pancreatic cancer via targeting ErbB family members.
METHODS: Cell viability assay and apoptosis evaluation were carried out to determine the efficacy of VPA on pancreatic cancer cells. Western blot analyses were performed to determine the expression and activation of proteins. Apoptosis enzyme-linked immunosorbent assay was used to quantify cytoplasmic histone associated DNA fragments. Lentiviral expression system was used to introduce overexpression of exogeneous genes or gene-targeting short hairpin RNAs (shRNAs). qRT-PCR was carried out to analyze the mRNAs and miRNAs expression levels. Tumor xenograft model was established to evaluate the in vivo anti-pancreatic cancer activity of VPA.
RESULTS: VPA preferentially inhibited cell proliferation/survival of, and induced apoptosis in EGFR/ErbB2/ErbB3-coexpressing pancreatic cancer cells within its clinically achievable range [40~100 mg/L (0.24~0.6 mmol/L)]. Mechanistic investigations revealed that VPA treatment resulted in simultaneous significant down-regulation of EGFR, ErbB2, and ErbB3 in pancreatic cancer cells likely via induction of ErbB family members-targeting microRNAs. Moreover, the anti-pancreatic cancer activity of VPA was further validated in tumor xenograft model.
CONCLUSIONS: Our data strongly suggest that VPA may be added to the treatment regimens for pancreatic cancer patients with co-overexpression of the ErbB family members.

Singh RR, Goldberg J, Varghese AM, et al.
Genomic profiling in pancreatic ductal adenocarcinoma and a pathway towards therapy individualization: A scoping review.
Cancer Treat Rev. 2019; 75:27-38 [PubMed] Article available free on PMC after 01/05/2020 Related Publications
CONTEXT: Pancreatic cancer (PDAC) is one of the most challenging cancers to treat with modest recent improvements in survival from new systemic therapies. There is growing interest in individualized therapy underpinned by somatic and germline genomic alterations.
OBJECTIVE: A systematic review of data on therapies targeting somatic and germline alterations, and their downstream pathways in PDAC.
METHOD: A systematic literature search was conducted using PRISMA guidelines to include relevant results published after January 1, 2008.
RESULTS: A total of 71 relevant studies were included. We identified 36 studies targeting the KRAS-pathway, the most common being with MEK-inhibitor therapy. Twenty-two studies were identified that evaluated platinum-based chemotherapy and PARP inhibitors in patients with deleterious mutations in DNA damage repair genes and have shown encouraging results. Immunotherapy has demonstrated activity in patients with mismatch repair deficiency/microsatellite instability.
CONCLUSION: Evidence from translational and clinical research presents an exciting platform for genomic targeted therapy in PDAC. Validity for targeting BRCA with platinum and PARP inhibitors and microsatellite instability with immune therapy has been established, nonetheless, evidence for targeting the common driver oncogenes is lacking and much work is needed. Of importance is identifying the subgroup of KRAS -wild type PDAC (approximately 5%) where there is enrichment for targetable opportunities.

Bakke J, Wright WC, Zamora AE, et al.
Genome-wide CRISPR screen reveals PSMA6 to be an essential gene in pancreatic cancer cells.
BMC Cancer. 2019; 19(1):253 [PubMed] Article available free on PMC after 01/05/2020 Related Publications
BACKGROUND: Despite its relatively low incidence, pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer deaths because of the aggressive growth/metastasis of the tumor, the lack of early symptoms, and the poor treatment options. Basic research to identify potential therapeutic targets for PDAC is greatly needed.
METHODS: We used a negative-selection genome-wide CRISPR screen to identify essential genes in the PANC-1 human pancreatic carcinoma cell line. We validated the top hits with follow-up siRNA screens, using the HPNE, HPAF-II, AsPC-1, and Mia PaCa-2 cell lines.
RESULTS: The PSMA6 gene was an identified candidate hit after the CRISPR screen, siRNA validation screen, and siRNA deconvolution screen. Spheroid formation assays and flow cytometry analysis showed that PSMA6 is critical for survival in many pancreatic ductal carcinoma cell models. Lastly, as PSMA6 protein is a proteosomal subunit of the 20S core complex, we showed that bortezomib, a proteasome inhibitor, was especially toxic in PANC-1 cells.
CONCLUSIONS: Further study of PSMA6 and the proteasome subunit that it encodes, along with other hits identified in our CRISPR screens, may provide valuable insights into potential therapeutic targets for PDAC.

Raman S, Beilschmidt M, To M, et al.
Structure-guided design fine-tunes pharmacokinetics, tolerability, and antitumor profile of multispecific frizzled antibodies.
Proc Natl Acad Sci U S A. 2019; 116(14):6812-6817 [PubMed] Article available free on PMC after 20/09/2019 Related Publications
Aberrant activation of Wnt/β-catenin signaling occurs frequently in cancer. However, therapeutic targeting of this pathway is complicated by the role of Wnt in stem cell maintenance and tissue homeostasis. Here, we evaluated antibodies blocking 6 of the 10 human Wnt/Frizzled (FZD) receptors as potential therapeutics. Crystal structures revealed a common binding site for these monoclonal antibodies (mAbs) on FZD, blocking the interaction with the Wnt palmitoleic acid moiety. However, these mAbs displayed gastrointestinal toxicity or poor plasma exposure in vivo. Structure-guided engineering was used to refine the binding of each mAb for FZD receptors, resulting in antibody variants with improved in vivo tolerability and developability. Importantly, the lead variant mAb significantly inhibited tumor growth in the HPAF-II pancreatic tumor xenograft model. Taken together, our data demonstrate that anti-FZD cancer therapeutic antibodies with broad specificity can be fine-tuned to navigate in vivo exposure and tolerability while driving therapeutic efficacy.

Mou T, Xie F, Zhong P, et al.
MiR-345-5p functions as a tumor suppressor in pancreatic cancer by directly targeting CCL8.
Biomed Pharmacother. 2019; 111:891-900 [PubMed] Related Publications
BACKGROUND: Increasing evidence has demonstrated that microRNAs (miRNAs) are key regulators of human diseases and can serve as prognostic markers for several cancers, such as pancreatic ductal adenocarcinoma (PDAC). Previous studies have revealed various functions for miR-345-5p in several cancers. However, the role and potential mechanism of miR-345-5p in PDAC have not been resolved.
METHODS: Quantitative RT-PCR was performed to investigate the expression levels of miR-345-5p in pancreatic cancer tissues and cell lines, and the effect of miR-345-5p on the proliferation and invasiveness of pancreatic cancer was examined in Transwell assays with miR-345-5p overexpression. We used Western blot assay to explore the underlying mechanisms. Immunofluorescence staining was performed to examine changes in the cytoskeleton of PANC-1 cells in response to miR-345-5p. Luciferase assays were used to clarify the target and regulation mechanism of miR-345-5p.
RESULTS: miR-345-5p expression was downregulated in PDAC cells and tissues. Upregulated miR-345-5p expression inhibited the proliferation and metastasis of PDAC cells. We identified CCL8 as a direct target of miR-345-5p and found CCL8 expression was inversely correlated with miR-345-5p expression in PDAC samples. CCL8 could activate the NF-κB signaling pathway to promote the proliferation and invasiveness of PDAC cells. These results suggested that miR-345-5p inhibited PDAC progression by inactivating NF-κB signaling.
CONCLUSIONS: Here we demonstrated that miR-345-5p was a tumor-suppressive miRNA in pancreatic cancer progression by targeting CCL8. Our results suggest miR-345-5p may be a potential therapeutic biomarker for pancreatic cancer treatment.

Xu J, Song J, Yang X, et al.
ProNGF siRNA inhibits cell proliferation and invasion of pancreatic cancer cells and promotes anoikis.
Biomed Pharmacother. 2019; 111:1066-1073 [PubMed] Related Publications
BACKGROUND: Precursor of nerve growth factor (proNGF) was previously considered biologically inactive; however, it has recently been identified as having important roles in the pathology of cancer development.
AIM: This study aimed to explore the therapeutic effects of proNGF siRNA on the proliferation, invasion, and anoikis of pancreatic cancer cells and determine the functions of proNGF.
METHODS: Pancreatic ductal adenocarcinoma (PDAC) and paired paracancerous tissue samples were collected from 60 patients for evaluation of proNGF expression by immunohistochemistry staining, qPCR, and western blotting. PDAC cell proliferation, migration, apoptosis, and anoikis following proNGF siRNA knockdown were investigated in two pancreatic cancer cell lines, Panc-1 and Bxpc-3, using BrdU incorporation assays, EdU staining, Ki-67 immunofluorescence (IF) staining, wound-healing assays, transwell invasion assays, and EthD-1 IF staining. Autophagy-related proteins were also measured by western blotting.
RESULTS: Levels of proNGF protein were higher in pancreatic cancer tissues and cells lines than those in paracancerous tissues and normal pancreatic duct epithelial cells, respectively. In vitro, ProNGF knockdown by siRNA led to significantly reduced cell proliferation, remarkably inhibited wound-healing, and reduced the number of invaded PDAC cells in migration and transwell assays. Treatment with proNGF siRNA also downregulated ATG5 and Beclin 1 protein levels, increased those of P62, and increased EthD-1 staining in PDAC cells.
CONCLUSION: ProNGF expression is elevated in PDAC tissues and cell lines, and proNGF siRNA can inhibit cell proliferation, migration, and invasion, and promote anoikis of pancreatic cancer cells, in which decreased proNGF may participate.

Xu B, Gong X, Zi L, et al.
Silencing of DLEU2 suppresses pancreatic cancer cell proliferation and invasion by upregulating microRNA-455.
Cancer Sci. 2019; 110(5):1676-1685 [PubMed] Article available free on PMC after 20/09/2019 Related Publications
Long noncoding RNA (lncRNA) DLEU2 has been shown to be dysregulated in several type of tumor. However, the potential biological roles and molecular mechanisms of DLEU2 in pancreatic cancer (PC) progression are poorly understood. In this study, we found that the DLEU2 level was substantially upregulated in PC tissues and PC cell lines, and significantly associated with poor clinical outcomes in PC patients. Overexpression of DLEU2 significantly induced PC cell proliferation and invasion, whereas knockdown of DLEU2 impaired cell proliferation and invasion in vitro. Furthermore, bioinformatics analysis, luciferase reporter assay, and RNA immunoprecipitation assay revealed that DLEU2 directly bond to microRNA-455 (miR-455) and functioned as an endogenous sponge for miR-455, which could remarkably suppress cell growth and invasion. We also determined that SMAD2 was a direct target of miR-455, and the restoration of SMAD2 rescued cell growth and invasion that were reduced by DLEU2 knockdown or miR-455 overexpression. In addition, low miR-455 expression and high SMAD2 expression was correlated with poor patient survival. These results indicate that DLEU2 is an important promoter of PC development, and targeting the DLEU2/miR-455/SMAD2 pathway could be a promising therapeutic approach in the treatment of PC.

Wang G, Yin L, Peng Y, et al.
Insulin promotes invasion and migration of KRAS
Cell Prolif. 2019; 52(3):e12575 [PubMed] Related Publications
OBJECTIVES: Hyperinsulinemia is a risk factor for pancreatic cancer, but the function of insulin in carcinogenesis is unclear, so this study aimed to elucidate the carcinogenic effects of insulin and the synergistic effect with the KRAS mutation in the early stage of pancreatic cancer.
MATERIALS AND METHODS: A pair of immortalized human pancreatic duct-derived cells, hTERT-HPNE E6/E7/st (HPNE) and its oncogenic KRAS
RESULTS: The migration and invasion ability of HPNE cells was increased after the introduction of the mutated KRAS gene, together with an increased expression of MMP-2. These effects were further enhanced by the simultaneous administration of insulin. The use of MMP-2 siRNA confirmed that MMP-2 was involved in the regulation of cell invasion. Furthermore, there was a concentration- and time-dependent increase in gelatinase activity after insulin treatment, which could be reversed by an insulin receptor tyrosine kinase inhibitor (HNMPA-(AM)
CONCLUSIONS: Taken together, these results suggest that insulin induced migration and invasion in HPNE and HPNE-mut-KRAS through PI3K/AKT and ERK1/2 activation, with MMP-2 gelatinolytic activity playing a vital role in this process. These findings may provide a new therapeutic target for preventing carcinogenesis and the evolution of pancreatic cancer with a background of hyperinsulinemia.

Singhi AD, George B, Greenbowe JR, et al.
Real-Time Targeted Genome Profile Analysis of Pancreatic Ductal Adenocarcinomas Identifies Genetic Alterations That Might Be Targeted With Existing Drugs or Used as Biomarkers.
Gastroenterology. 2019; 156(8):2242-2253.e4 [PubMed] Related Publications
BACKGROUND & AIMS: It has been a challenge to select treatment for patients with pancreatic ductal adenocarcinomas (PDACs) based on genome alterations. We performed targeted genomic profile analyses of a large number of PDACs to assess the full spectrum of actionable genomic alterations.
METHODS: We performed targeted genomic profile analyses of 3594 PDAC samples from an international cohort, including capture-based targeted genomic profiling of as many as 315 cancer-associated genes and intron regions of 28 genes that are rearranged in cancer cells. Tumor mutation burden (TMB) and microsatellite instability (MSI) status were also assessed. TMB was calculated across a 1.14-megabase region; TMB-high was defined as ≥20 mutations/megabase. MSI-high status was assigned based on analysis of 114 intron homopolymer loci.
RESULTS: KRAS, TP53, CDKN2A, and SMAD4 were the most frequently altered genes in PDAC. We found KRAS mutations in 88% of samples. Among PDACs without mutations in KRAS, we found alterations in genes whose products are in the mitogen-activated protein kinase signaling pathway and are candidate drug targets (actionable targets, n = 132; 4%), as well as gene fusions (n = 51), gene amplifications (n = 35), genes with missense mutations (n = 30), and genes that contain deletions (n = 16). Many of these encode proteins in receptor tyrosine kinase, RAS, or mitogen-activated protein kinase signaling pathways. Aside from TP53, alterations in genes encoding DNA damage repair proteins (BRCA and FANC) were detected in 14% of PDACs. Among PDACs evaluated for MSI (n = 2563) and TMB (n = 1021), MSI-high and/or TMB-high phenotypes were detected in 0.5% of samples. Alterations in FGF23, CCND2, PIK3CA, and FGF6 were more commonly detected in intraductal papillary mucinous neoplasm-associated PDACs.
CONCLUSIONS: In targeted genomic profile analyses of 3594 PDACs, we found 17% to contain genomic alterations that might make the tumor cells susceptible to currently used anticancer agents. We identified mutations in genes that could contribute to progression of intraductal papillary mucinous neoplasms into malignancies. These alterations might be used as biomarkers for early detection.

Liang J, Liu Y, Zhang L, et al.
Overexpression of microRNA-519d-3p suppressed the growth of pancreatic cancer cells by inhibiting ribosomal protein S15A-mediated Wnt/β-catenin signaling.
Chem Biol Interact. 2019; 304:1-9 [PubMed] Related Publications
Ribosomal protein S15A (RPS15A) has emerged as a novel oncogene of various human cancers. However, whether RPS15A is involved in pancreatic cancer remains unclear. In this study, we aimed to investigate the potential relevance of RPS15A in pancreatic cancer and elucidate the underlying regulatory mechanism. We found that RPS15A expression was significantly up-regulated in pancreatic cancer cell lines. RPS15A knockdown resulted in a decrease of cell proliferation and colony formation, and induced cell cycle arrest in G0/G1 phases of pancreatic cancer cells in vitro. In addition, RPS15A knockdown down-regulated β-catenin expression and blocked the activation of Wnt signaling. Notably, RPS15A was identified as a target gene of microRNA-519d-3p (miR-519d-3p), a tumor suppressive miRNA. Further data showed that miR-519d-3p negatively regulated RPS15A expression in pancreatic cancer cells. Moreover, miR-591d-3p expression was significantly decreased in pancreatic cancer cell lines and tissues and was inversely correlated with RPS15A expression. The overexpression of miR-519d-3p significantly inhibited the proliferation and Wnt/β-catenin signaling in pancreatic cancer cells, mimicking the similar effect of RPS15A knockdown. However, restoration of RPS15A expression partially reversed the antitumor effect of miR-519d-3p. Taken together, our results demonstrate that RPS15A knockdown or RPS15A inhibition by miR-519d-3p suppresses the growth of pancreatic cancer cells associated with the inhibition of Wnt/β-catenin signaling. Our study suggests that the miR-519d-3p/RPS15A/Wnt/β-catenin regulation axis plays an important role in the progression of pancreatic cancer and may serve as potential targets for treatment of pancreatic cancer.

Wang J, Gerrard G, Poskitt B, et al.
Targeted next generation sequencing of pancreatic solid pseudopapillary neoplasms show mutations in Wnt signaling pathway genes.
Pathol Int. 2019; 69(4):193-201 [PubMed] Related Publications
Solid pseudopapillary neoplasms of the pancreas are rare neoplasms that have been shown to harbor recurrent somatic pathogenic variants in the beta-catenin gene, CTNNB1. Here, we used targeted next generation sequencing to analyze these tumors for other associated mutations. Six cases of solid pseudopapillary neoplasms were studied. DNA extracted from formalin-fixed paraffin embedded tissue blocks was analyzed using the Ion Torrent platform, with the 50-gene Ampliseq Cancer Hotspot Panel v2 (CHPv2), with further variant validation performed by Sanger sequencing. Four tumors (67%) were confirmed to harbor mutations within CTNNB1, two with c.109T > G p.(Ser37Ala) and two with c.94G > A p.(Asp32Asn). One case showed a frameshift deletion in the Adenomatous Polyposis Coli gene, APC c.3964delG p.(Glu1322Lysfs*93) with a variant allele frequency of 42.6%. Sanger sequencing on non-tumoral tissue confirmed the variant was somatic. The patient with the APC mutation developed metastasis and died. In addition to the four cases harboring CTNNB1 variants, we found a case characterized by poor outcome, showing a rare frameshift deletion in the APC gene. Since the APC product interacts with beta-catenin, APC variants may, in addition to CTNNB1, contribute to the pathogenesis of solid pseudopapillary neoplasms via the Wnt signaling pathway.

Huang R, Nie W, Yao K, Chou J
Depletion of the lncRNA RP11-567G11.1 inhibits pancreatic cancer progression.
Biomed Pharmacother. 2019; 112:108685 [PubMed] Related Publications
BACKGROUND: Pancreatic cancer is one of the most lethal malignancies, as demonstrated by its 5-year survival rate of less than 10%. The poor response of pancreatic cancer to conventional therapeutics, especially against cancer stem cells (CSCs), is the primary obstacle to improving patient survival. Emerging evidence indicates that the long non-coding RNA (lncRNA) RP11-567G11.1 is up-regulated in pancreatic cancer tissues and that its expression is associated with poor prognosis. This study aimed to elucidate the mechanism by which RP11-567G11.1 influences survival in pancreatic cancer.
METHODS: We evaluated the expression of RP11-567G11.1 in pancreatic cancer tissues via in situ hybridization. We also constructed RP11-567G11.1 knockdown cell models and used CCK8 and flow cytometry to detect the function of this lncRNA. Western blotting and qPCR were used to detect the expression levels of factors related to RP11-567G11.1.
RESULTS: The results illustrated that RP11-567G11.1 was significantly up-regulated in poorly differentiated pancreatic cancer tissues as compared to its expression in non-tumor tissues. Additionally, depletion of RP11-567G11.1 in pancreatic cancer cells inhibited proliferation and cell cycle progression, induced apoptosis, suppressed the stem cell-like phenotype, and increased sensitivity to gemcitabine. Also depletion of RP11-567G11.1 in pancreatic cancer cells inhibited factors downstream of the NOTCH signaling pathway.
CONCLUSION: RP11-567G11.1 plays a crucial role in pancreatic cancer. Importantly, depletion of RP11-567G11.1 boosts the sensitivity of pancreatic cancer cells to gemcitabine, suggesting that this lncRNA is a promising target for pancreatic cancer treatment.

Tang D, Wu Q, Yuan Z, et al.
Identification of key pathways and gene changes in primary pancreatic stellate cells after cross-talk with pancreatic cancer cells (BXPC-3) using bioinformatics analysis.
Neoplasma. 2019; 2019(3):446-458 [PubMed] Related Publications
It is well known that as the king of cancer, pancreatic ductal adenocarcinoma (PDAC) has relatively malignant biological behavior and poor prognosis. The interaction between pancreatic stellate cells and PDAC cells promotes the development of PDAC. The aim of this study was to describe gene characteristics in pancreatic stellate cell (PSCs) after cross-talked with BXPC-3 and unravel their underlying mechanisms. The expression profiling analysis of genes in PSCs was completed after co-cultured with primary BXPC-3 for 48h. The Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis and gene ontology (GO) analysis were performed, and the differentially expressed genes (DEGs) were identified by Agilent GeneSpring GX program. In total, 1804 DEGs were filtered out in PSCs, including 958 up-regulated genes and 846 downregulated genes. GO analysis showed that the up-regulated DEGs were significantly enriched in biological processes (BP) such as defense response, immune system process and immune response; the down-regulated DEGs were significantly enriched in biological regulation and cytoskeleton organization. KEGG pathway analysis showed that 28 pathways were upregulated and 5 were downregulated. By constructing PPI network, we selected out 10 key genes (IL6,IL8, IL1B, BCL2, CCL2, CSF2, KIT, ICAM1, PTPRC and IGF1) and significant enriched pathways. In conclusion, the current study suggests that the filtered DEGs contribute to our understanding of the molecular mechanisms underlying the interaction between PSCs and pancreatic cancer cells, and might be used as molecular targets to further the study the role of tumor microenvironment in the progression of PDAC.

Yang Y, Ishak Gabra MB, Hanse EA, et al.
MiR-135 suppresses glycolysis and promotes pancreatic cancer cell adaptation to metabolic stress by targeting phosphofructokinase-1.
Nat Commun. 2019; 10(1):809 [PubMed] Article available free on PMC after 20/09/2019 Related Publications
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal human cancers. It thrives in a nutrient-poor environment; however, the mechanisms by which PDAC cells undergo metabolic reprogramming to adapt to metabolic stress are still poorly understood. Here, we show that microRNA-135 is significantly increased in PDAC patient samples compared to adjacent normal tissue. Mechanistically, miR-135 accumulates specifically in response to glutamine deprivation and requires ROS-dependent activation of mutant p53, which directly promotes miR-135 expression. Functionally, we found miR-135 targets phosphofructokinase-1 (PFK1) and inhibits aerobic glycolysis, thereby promoting the utilization of glucose to support the tricarboxylic acid (TCA) cycle. Consistently, miR-135 silencing sensitizes PDAC cells to glutamine deprivation and represses tumor growth in vivo. Together, these results identify a mechanism used by PDAC cells to survive the nutrient-poor tumor microenvironment, and also provide insight regarding the role of mutant p53 and miRNA in pancreatic cancer cell adaptation to metabolic stresses.

Liu Y, Zhu D, Xing H, et al.
A 6‑gene risk score system constructed for predicting the clinical prognosis of pancreatic adenocarcinoma patients.
Oncol Rep. 2019; 41(3):1521-1530 [PubMed] Article available free on PMC after 20/09/2019 Related Publications
Pancreatic adenocarcinoma (PAC) is the most common type of pancreatic cancer, which commonly has an unfavorable prognosis. The present study aimed to develop a novel prognostic prediction strategy for PAC patients. mRNA sequencing data of PAC (the training dataset) were extracted from The Cancer Genome Atlas database, and the validation datasets (GSE62452 and GSE79668) were acquired from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) between good and poor prognosis groups were analyzed by limma package, and then prognosis‑associated genes were screened using Cox regression analysis. Subsequently, the risk score system was constructed and confirmed using Kaplan‑Meier (KM) survival analysis. After the survival associated‑clinical factors were screened using Cox regression analysis, they were performed with stratified analysis. Using DAVID tool, the DEGs correlated with risk scores were conducted with enrichment analysis. The results revealed that there were a total of 242 DEGs between the poor and good prognosis groups. Afterwards, a risk score system was constructed based on 6 prognosis‑associated genes (CXCL11, FSTL4, SEZ6L, SPRR1B, SSTR2 and TINAG), which was confirmed in both the training and validation datasets. Cox regression analysis showed that risk score, targeted molecular therapy, and new tumor (the new tumor event days after the initial treatment according to the TCGA database) were significantly related to clinical prognosis. Under the same clinical condition, 6 clinical factors (age, history of chronic pancreatitis, alcohol consumption, radiation therapy, targeted molecular therapy and new tumor (event days) had significant associations with clinical prognosis. Under the same risk condition, only targeted molecular therapy was significantly correlated with clinical prognosis. In conclusion, the 6‑gene risk score system may be a promising strategy for predicting the outcome of PAC patients.

Drake TM, Søreide K
Cancer epigenetics in solid organ tumours: A primer for surgical oncologists.
Eur J Surg Oncol. 2019; 45(5):736-746 [PubMed] Related Publications
Cancer is initiated through both genetic and epigenetic alterations. The end-effect of such changes to the DNA machinery is a set of uncontrolled mechanisms of cell division, invasion and, eventually, metastasis. Epigenetic changes are now increasingly appreciated as an essential driver to the cancer phenotype. The epigenetic regulation of cancer is complex and not yet fully understood, but application of epigenetics to clinical practice and in cancer research has the potential to improve cancer care. Epigenetics changes do not cause changes in the DNA base-pairs (and, hence, does not alter the genetic code per se) but rather occur through methylation of DNA, by histone modifications, and, through changes to chromatin structure to alter genetic expression. Epigenetic regulators are characterized as writers, readers or erasers by their mechanisms of action. The human epigenome is influenced from cradle to grave, with internal and external life-time exposure influencing the epigenetic marks that may act as modifiers or drivers of carcinogenesis. Preventive and public health strategies may follow from better understanding of the life-time influence of the epigenome. Epigenetics may be used to define risk, to investigate mechanisms of carcinogenesis, to identify biomarkers, and to identify novel therapeutic options. Epigenetic alterations are found across many solid cancers and are increasingly making clinical impact to cancer management. Novel epigenetic drugs may be used for a more tailored and specific response to treatment of cancers. We present a primer on epigenetics for surgical oncologists with examples from colorectal cancer, breast cancer, pancreatic cancer and hepatocellular carcinoma.

Sakai Y, Honda M, Matsui S, et al.
Development of novel diagnostic system for pancreatic cancer, including early stages, measuring mRNA of whole blood cells.
Cancer Sci. 2019; 110(4):1364-1388 [PubMed] Article available free on PMC after 20/09/2019 Related Publications
Pancreatic ductal adenocarcinoma (PDAC) is the most life-threating disease among all digestive system malignancies. We developed a blood mRNA PDAC screening system using real-time detection PCR to detect the expression of 56 genes, to discriminate PDAC from noncancer subjects. We undertook a clinical study to assess the performance of the developed system. We collected whole blood RNA from 53 PDAC patients, 102 noncancer subjects, 22 patients with chronic pancreatitis, and 23 patients with intraductal papillary mucinous neoplasms in a per protocol analysis. The sensitivity of the system for PDAC diagnosis was 73.6% (95% confidence interval, 59.7%-84.7%). The specificity for noncancer volunteers, chronic pancreatitis, and patients with intraductal papillary mucinous neoplasms was 64.7% (54.6%-73.9%), 63.6% (40.7%-82.8%), and 47.8% (26.8%-69.4%), respectively. Importantly, the sensitivity of this system for both stage I and stage II PDAC was 78.6% (57.1%-100%), suggesting that detection of PDAC by the system is not dependent on the stage of PDAC. These results indicated that the screening system, relying on assessment of changes in mRNA expression in blood cells, is a viable alternative screening strategy for PDAC.

Wu J, Liu J, Wei X, et al.
A feature-based analysis identifies COL1A2 as a regulator in pancreatic cancer.
J Enzyme Inhib Med Chem. 2019; 34(1):420-428 [PubMed] Article available free on PMC after 20/09/2019 Related Publications
This study aimed to identify genetic biomarkers in pancreatic cancer (PC) and explore its function in PC via a feature-base analysis of bioinformatics. OMIM and DisGeNET databases discovered 209 PC connected genes and then 516 connected genes were identified. We selected 29 genes according to optimal features and chose COL1A2, which had the highest expression, for the following experiment. The expression of COL1A2 was determined by qRT-PCR; cell proliferation was determined by MTT assay; migration and invasion after COL1A2 and miR-25-3p transfection was evaluated by Transwell assay. COL1A2 presented the highest expression in PC tissues, which was validated in functional experiments. MiR-25-3p suppressed the expression of COL1A2 in cell lines and inhibited migration, invasion and proliferation of PC cells. MiR-25-3p could suppress the expression of COL1A2 and inhibit the proliferation, migration and invasion of PC cells which provided a new idea for the detection and treatment of PC.

Fu J, Shrivastava A, Shrivastava SK, et al.
Triacetyl resveratrol upregulates miRNA‑200 and suppresses the Shh pathway in pancreatic cancer: A potential therapeutic agent.
Int J Oncol. 2019; 54(4):1306-1316 [PubMed] Related Publications
Trans‑3,4',5‑trihydroxystilbene (resveratrol) is a naturally occurring polyphenolic phytoalexin with marked anticancer activities, and is mainly found in grapes, berries and peanuts. However, due to a low bioavailability, it has not progressed to clinical practice for cancer treatment. Therefore, the aims of the present study were to examine the anticancer activities of the resveratrol derivative, triacetyl resveratrol (TCRV), in pancreatic cancer cells. Apoptosis was measured by fluorescence‑activated cell sorting and terminal deoxynucleotidyl transferase (TdT)‑mediated dUTP nick‑end labeling assays. Gene expression was measured by reverse transcription‑quantitative polymerase chain reaction. TCRV inhibited colony formation and induced apoptosis through caspase‑3 activation in human pancreatic cancer AsPC‑1 and PANC‑1 cells, whereas it exerted no effect on human pancreatic normal ductal epithelial cells (HPNE). TCRV inhibited epithelial‑mesenchymal transition (EMT) by upregulating the expression of E‑cadherin and suppressing the expression of N‑cadherin and the transcription factors, Snail, Slug and Zeb1. TCRV inhibited Zeb1 3'UTR‑luciferase activity through the upregulation of microRNA (miR)‑200 family members. The inhibitory effects of TCRV on pancreatic cancer cell migration and invasion were counteracted by anti‑miR‑200 family members. The inhibitory effects of TCRV on EMT and the induction of apoptosis were exerted through the suppression of the sonic hedgehog (Shh) pathway, and through the modulation of cyclin D1 and Bcl‑2 expression. The hyperactivation of the Shh pathway by either Shh protein or Gli1 overexpression abrogated the biological effects of TCRV. Taken together, the results of this study demonstrate that TCRV inhibits pancreatic cancer growth and EMT by targeting the Shh pathway and its downstream signaling mediators. TCRV inhibited EMT through the upregulation of miR‑200 family members. Since TCRV effectively inhibited the growth of human pancreatic cancer cells by modulating the Shh pathway, without affecting the growth of HPNE cells, our findings suggest the possible use of TCRV as a promising candidate for the treatment and/or prevention of pancreatic cancer.

Skaro M, Nanda N, Gauthier C, et al.
Prevalence of Germline Mutations Associated With Cancer Risk in Patients With Intraductal Papillary Mucinous Neoplasms.
Gastroenterology. 2019; 156(6):1905-1913 [PubMed] Article available free on PMC after 01/05/2020 Related Publications
BACKGROUND & AIMS: Many patients with pancreatic adenocarcinoma carry germline mutations associated with increased risk of cancer. It is not clear whether patients with intraductal papillary mucinous neoplasms (IPMNs), which are precursors to some pancreatic cancers, also carry these mutations. We assessed the prevalence of germline mutations associated with cancer risk in patients with histologically confirmed IPMN.
METHODS: We obtained nontumor tissue samples from 315 patients with surgically resected IPMNs from 1997 through 2017, and we sequenced 94 genes with variants associated with cancer risk. Mutations associated with increased risk of cancer were identified and compared with individuals from the Exome Aggregation Consortium.
RESULTS: We identified 23 patients with a germline mutation associated with cancer risk (7.3%; 95% confidence interval, 4.9-10.8). Nine patients had a germline mutation associated with pancreatic cancer susceptibility (2.9%; 95% confidence interval, 1.4-5.4). More patients with IPMNs carried germline mutations in ATM (P < .0001), PTCH1 (P < .0001), and SUFU (P < .0001) compared with controls. Patients with IPMNs and germline mutations associated with pancreatic cancer were more like to have concurrent invasive pancreatic carcinoma compared with patients with IPMNs without these mutations (P < .0320).
CONCLUSIONS: In sequence analyses of 315 patients with surgically resected IPMNs, we found that almost 3% to carry mutations associated with pancreatic cancer risk. More patients with IPMNs and germline mutations associated with pancreatic cancer had concurrent invasive pancreatic carcinoma compared with patients with IPMNs without these mutations. Genetic analysis of patients with IPMNs might identify those at greatest risk for cancer.

Gurbuz N, Ozpolat B
MicroRNA-based Targeted Therapeutics in Pancreatic Cancer.
Anticancer Res. 2019; 39(2):529-532 [PubMed] Related Publications
The discovery during the last decade of microRNAs (miRs, miRNA) and their role in regulating normal physiological processes as well as in the pathogenesis of human tumors has been a revolutionary development in molecular oncology. miRNAs activating or inhibiting oncogenic molecular pathways that are involved in tumorigenesis, cell progression, invasion, angiogenesis and metastasis are now considered of major impact in many cancer types. miRNA-based therapeutics that inhibit the levels of oncogenic miRNAs (oncomiRs) or elevate tumor suppressor miRs have enormous potential as molecular therapeutic targets. Thus, the development of new targeted cancer therapies based on miRNAs promise to revolutionize cancer treatment due to their increased efficacy compared to conventional chemoradiation-based therapies and hopefully to lower levels of adverse effects.

Patzak MS, Kari V, Patil S, et al.
Cytosolic 5'-nucleotidase 1A is overexpressed in pancreatic cancer and mediates gemcitabine resistance by reducing intracellular gemcitabine metabolites.
EBioMedicine. 2019; 40:394-405 [PubMed] Article available free on PMC after 01/05/2020 Related Publications
BACKGROUND: Cytosolic 5'-nucleotidase 1A (NT5C1A) dephosphorylates non-cyclic nucleoside monophosphates to produce nucleosides and inorganic phosphates. Here, we investigate NT5C1A expression in pancreatic ductal adenocarcinoma (PDAC) and its impact on gemcitabine metabolism and therapeutic efficacy.
METHODS: NT5C1A expression was determined by semiquantitative immunohistochemistry using tissue microarrays. Gemcitabine metabolites and response were assessed in several human and murine PDAC cell lines using crystal violet assays, Western blot, viability assays, and liquid chromatography tandem mass-spectrometry (LC-MS/MS).
FINDINGS: NT5C1A was strongly expressed in tumor cells of a large subgroup of resected PDAC patients in two independent patient cohorts (44-56% score 2 and 8-26% score 3, n = 414). In contrast, NT5C1A was expressed at very low levels in the tumor stroma, and neither stromal nor tumoral expression was a prognostic marker for postoperative survival. In vitro, NT5C1A overexpression increased gemcitabine resistance by reducing apoptosis levels and significantly decreased intracellular amounts of cytotoxic dFdCTP in +NT5C1A tumor cells. Co-culture experiments with conditioned media from +NT5C1A PSCs improved gemcitabine efficacy in tumor cells. In vivo, therapeutic efficacy of gemcitabine was significantly decreased and serum levels of the inactive gemcitabine metabolite dFdU significantly increased in mice bearing NT5C1A overexpressing tumors.
INTERPRETATION: NT5C1A is robustly expressed in tumor cells of resected PDAC patients. Moreover, NT5C1A mediates gemcitabine resistance by decreasing the amount of intracellular dFdCTP, leading to reduced tumor cell apoptosis and larger pancreatic tumors in mice. Further studies should clarify the role of NT5C1A as novel predictor for gemcitabine treatment response in patients with PDAC.

Abiatari I, Midelashvili T, Motsikulashvili M, et al.
OVEREXPRESSED PROGENITOR GENE CSF1R IN PANCREATIC CANCER TISSUES AND NERVE INVASIVE PANCREATIC CANCER CELLS.
Georgian Med News. 2018; (285):96-100 [PubMed] Related Publications
Aim- pancreatic ductal adenocarcinoma is one of the most aggressive oncological disease with early metastasis and high mortality rate. CSF1R is a gene with progenitor activity, which is also associated with different malignant diseases. In this study our objective was to analyze expression of CSF1R in pancreatic cancer tissues and nerve invasive cancer cells. Quantitative real time polymerase chain reaction (QRT-PCR) was used to analyze the expression of CSF1R mRNA in nine cultured pancreatic cancer cell lines and pancreatic bulk tissues of the normal pancreas, chronic pancreatitis (n=20/20) and pancreatic ductal adenocarcinoma (n=58). Nerve invasive clones of two pancreatic cancer cell lines was also used. QRT-PCR analysis revealed a significant up-regulation of CSF1R mRNA expression in pancreatic adenocarcinoma tissues compared to normal tissues and low expression of this gene indicated a tendency for better survival of pancreatic cancer patients. Expression of CSF1R mRNA was present in all tested pancreatic cancer cell lines with comparably low to moderate expression levels. The CSF1R was significantly overexpressed in nerve invasive pancreatic cancer cells. Increased expression of CSF1R in pancreatic cancer might be related to perineural invasion and poor prognosis. CSF1R might be an important factor during the development and malignant transformation of tissues.

Ohmoto A, Yachida S, Morizane C
Genomic Features and Clinical Management of Patients with Hereditary Pancreatic Cancer Syndromes and Familial Pancreatic Cancer.
Int J Mol Sci. 2019; 20(3) [PubMed] Article available free on PMC after 01/05/2020 Related Publications
Pancreatic cancer (PC) is one of the most devastating malignancies; it has a 5-year survival rate of only 9%, and novel treatment strategies are urgently needed. While most PC cases occur sporadically, PC associated with hereditary syndromes or familial PC (FPC; defined as an individual having two or more first-degree relatives diagnosed with PC) accounts for about 10% of cases. Hereditary cancer syndromes associated with increased risk for PC include Peutz-Jeghers syndrome, hereditary pancreatitis, familial atypical multiple mole melanoma, familial adenomatous polyposis, Lynch syndrome and hereditary breast and ovarian cancer syndrome. Next-generation sequencing of FPC patients has uncovered new susceptibility genes such as

Malsy M, Graf B, Almstedt K
The active role of the transcription factor Sp1 in NFATc2-mediated gene regulation in pancreatic cancer.
BMC Biochem. 2019; 20(1):2 [PubMed] Article available free on PMC after 01/05/2020 Related Publications
BACKGROUND: Adenocarcinoma of the pancreas is one of the most aggressive tumor diseases affecting the human body. The oncogenic potential of pancreatic cancer is mainly characterized by extremely rapid growth triggered by the activation of oncogenic signaling cascades, which suggests a change in the regulation of important transcription factors. Amongst others, NFAT transcription factors are assumed to play a central role in the carcinogenesis of pancreatic cancer. Recent research has shown the importance of the transcription factor Sp1 in the transcriptional activity of NFATc2 in pancreatic cancer. However, the role of the interaction between these two binding partners remains unclear. The current study investigated the role of Sp1 proteins in the expression of NFATc2 target genes and identified new target genes and their function in cells. A further objective was the domain of the Sp1 protein that mediates interaction with NFATc2. The involvement of Sp1 proteins in NFATc2 target genes was shown by means of a gene expression profile analysis, and the results were confirmed by quantitative RT-PCR. The functional impact of this interaction was shown in a thymidine incorporation assay. A second objective was the physical interaction between NFATc2 and different Sp1 deletion mutants that was investigated by means of immunoprecipitation.
RESULTS: In pancreatic cancer, the proto-oncogene c-Fos, the tumor necrosis factor TNF-alpha, and the adhesion molecule integrin beta-3 are target genes of the interaction between Sp1 and NFATc2. Loss of just one transcription factor inhibits oncogenic complex formation and expression of cell cycle-regulating genes, thus verifiably decreasing the carcinogenic effect. The current study also showed the interaction between the transcription factor NFATc2 and the N-terminal domain of Sp1 in pancreatic cancer cells. Sp1 increases the activity of NFATc2 in the NFAT-responsive promoter.
CONCLUSIONS: The regulation of gene promotors during transcription is a rather complex process because of the involvement of many proteins that - as transcription factors or co-factors - regulate promotor activity as required and control cell function. NFATc2 and Sp1 seem to play a key role in the progression of pancreatic cancer.

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