Cervical Cancer

Overview

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 (346)

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
IL10 1q32.1 CSIF, TGIF, GVHDS, IL-10, IL10A -Interleukin-10 and Cervical Cancer
75
EGFR 7p11.2 ERBB, HER1, mENA, ERBB1, PIG61, NISBD2 -EGFR and Cervical Cancer
58
FHIT 3p14.2 FRA3B, AP3Aase -FHIT and Cervical Cancer
56
HLA-DRB1 6p21.32 SS1, DRB1, HLA-DRB, HLA-DR1B -HLA-DRB1 and Cervical Cancer
50
TERC 3q26.2 TR, hTR, TRC3, DKCA1, PFBMFT2, SCARNA19 -TERC and Cervical Cancer
46
MTOR 1p36.22 SKS, FRAP, FRAP1, FRAP2, RAFT1, RAPT1 -MTOR and Cervical Cancer
44
MMP2 16q12.2 CLG4, MONA, CLG4A, MMP-2, TBE-1, MMP-II -MMP2 and Cervical Cancer
41
PTGS2 1q31.1 COX2, COX-2, PHS-2, PGG/HS, PGHS-2, hCox-2, GRIPGHS -PTGS2 (COX2) and Cervical Cancer
33
MDM2 12q15 HDMX, hdm2, ACTFS -MDM2 and Cervical Cancer
29
HIF1A 14q23.2 HIF1, MOP1, PASD8, HIF-1A, bHLHe78, HIF-1alpha, HIF1-ALPHA, HIF-1-alpha -HIF1A and Cervical Cancer
28
MMP9 20q13.12 GELB, CLG4B, MMP-9, MANDP2 -MMP9 and Cervical Cancer
26
CDH1 16q22.1 UVO, CDHE, ECAD, LCAM, Arc-1, CD324 -CDH1 and Cervical Cancer
25
HLA-A 6p22.1 HLAA -HLA-A and Cervical Cancer
23
SLC2A1 1p34.2 CSE, PED, DYT9, GLUT, DYT17, DYT18, EIG12, GLUT1, HTLVR, GLUT-1, SDCHCN, GLUT1DS -GLUT1 expression in Cervical Cancer
23
AKT1 14q32.33 AKT, PKB, RAC, CWS6, PRKBA, PKB-ALPHA, RAC-ALPHA -AKT1 and Cervical Cancer
22
DAPK2 15q22.31 DRP1, DRP-1 -DAPK2 and Cervical Cancer
22
CASP8 2q33-q34 CAP4, MACH, MCH5, FLICE, ALPS2B, Casp-8 -CASP8 and Cervical Cancer
22
MGMT 10q26.3 -MGMT and Cervical Cancer
21
DAPK1 9q21.33 DAPK -DAPK1 and Cervical Cancer
19
FAS 10q23.31 APT1, CD95, FAS1, APO-1, FASTM, ALPS1A, TNFRSF6 -FAS and Cervical Cancer
19
BCL2 18q21.33 Bcl-2, PPP1R50 -BCL2 and Cervical Cancer
19
CYP1A1 15q24.1 AHH, AHRR, CP11, CYP1, CYPIA1, P1-450, P450-C, P450DX -CYP1A1 and Cervical Cancer
18
MET 7q31.2 HGFR, AUTS9, RCCP2, c-Met, DFNB97 -C-MET and Cervical Cancer
17
TIMP1 Xp11.3 EPA, EPO, HCI, CLGI, TIMP, TIMP-1 -TIMP1 and Cervical Cancer
15
TIMP2 17q25.3 DDC8, CSC-21K -TIMP2 and Cervical Cancer
15
NME1 17q21.33 NB, AWD, NBS, GAAD, NDKA, NM23, NDPKA, NDPK-A, NM23-H1 -NME1 and Cervical Cancer
13
LIPA 10q23.31 LAL, CESD -LIPA and Cervical Cancer
12
CCNB1 5q13.2 CCNB -CCNB1 and Cervical Cancer
12
CXCL12 10q11.21 IRH, PBSF, SDF1, TLSF, TPAR1, SCYB12 -CXCL12 and Cervical Cancer
11
CCNA1 13q13.3 CT146 -CCNA1 and Cervical Cancer
11
GAPDH 12p13.31 G3PD, GAPD, HEL-S-162eP -GAPDH and Cervical Cancer
11
HLA-G 6p22.1 MHC-G -HLA-G and Cervical Cancer
10
EPB41L3 18p11.31 4.1B, DAL1, DAL-1 -EPB41L3 and Cervical Cancer
10
IFNG 12q15 IFG, IFI -IFNG and Cervical Cancer
10
SOX1 13q34 -SOX1 and Cervical Cancer
10
CD82 11p11.2 R2, 4F9, C33, IA4, ST6, GR15, KAI1, SAR2, TSPAN27 -CD82 and Cervical Cancer
10
TLR9 3p21.2 CD289 -TLR9 and Cervical Cancer
10
RARB 3p24.2 HAP, RRB2, NR1B2, MCOPS12, RARbeta1 -RARB and Cervical Cancer
10
BECN1 17q21.31 ATG6, VPS30, beclin1 -BECN1 and Cervical Cancer
9
CCR2 3p21.31 CKR2, CCR-2, CCR2A, CCR2B, CD192, CKR2A, CKR2B, CMKBR2, MCP-1-R, CC-CKR-2 -CCR2 and Cervical Cancer
8
FGF2 4q28.1 BFGF, FGFB, FGF-2, HBGF-2 -FGF2 and Cervical Cancer
8
CHEK1 11q24.2 CHK1 -CHEK1 and Cervical Cancer
8
MAPK1 22q11.22 ERK, p38, p40, p41, ERK2, ERT1, ERK-2, MAPK2, PRKM1, PRKM2, P42MAPK, p41mapk, p42-MAPK -MAPK1 and Cervical Cancer
8
H2AFX 11q23.3 H2AX, H2A.X, H2A/X -H2AFX and Cervical Cancer
8
ERCC1 19q13.32 UV20, COFS4, RAD10 -ERCC1 and Cervical Cancer
8
MIR126 9q34.3 MIRN126, mir-126, miRNA126 -MicroRNA mir-126 and Cervical Cancer
8
ESR1 6q25.1-q25.2 ER, ESR, Era, ESRA, ESTRR, NR3A1 -ESR1 and Cervical Cancer
8
EZH2 7q36.1 WVS, ENX1, EZH1, KMT6, WVS2, ENX-1, EZH2b, KMT6A -EZH2 and Cervical Cancer
7
FOXM1 12p13 MPP2, TGT3, HFH11, HNF-3, INS-1, MPP-2, PIG29, FKHL16, FOXM1B, HFH-11, TRIDENT, MPHOSPH2 -FOXM1 and Cervical Cancer
7
HLA-DPB1 6p21.32 DPB1, HLA-DP, HLA-DPB, HLA-DP1B -HLA-DPB1 and Cervical Cancer
7
CA9 9p13.3 MN, CAIX -CA9 and Cervical Cancer
7
ABCC1 16p13.11 MRP, ABCC, GS-X, MRP1, ABC29 -ABCC1 (MRP1) and Cervical Cancer
7
TGFA 2p13 TFGA -TGFA and Cervical Cancer
7
ARID1A 1p36.11 ELD, B120, CSS2, OSA1, P270, hELD, BM029, MRD14, hOSA1, BAF250, C1orf4, BAF250a, SMARCF1 -ARID1A and Cervical Cancer
7
XRCC6 22q13.2 ML8, KU70, TLAA, CTC75, CTCBF, G22P1 -XRCC6 and Cervical Cancer
7
HIC1 17p13.3 hic-1, ZBTB29, ZNF901 -HIC1 and Cervical Cancer
7
CCL2 17q12 HC11, MCAF, MCP1, MCP-1, SCYA2, GDCF-2, SMC-CF, HSMCR30 -CCL2 and Cervical Cancer
7
IL17C 16q24.2 CX2, IL-17C -IL17C and Cervical Cancer
7
MYB 6q23.3 efg, Cmyb, c-myb, c-myb_CDS -MYB and Cervical Cancer
7
HLA-C 6p21.33 MHC, HLAC, HLC-C, D6S204, PSORS1, HLA-JY3 -HLA-C and Cervical Cancer
7
IL1RN 2q14.2 DIRA, IRAP, IL1F3, IL1RA, MVCD4, IL-1RN, IL-1ra, IL-1ra3, ICIL-1RA -IL1RN and Cervical Cancer
6
SMAD4 18q21.2 JIP, DPC4, MADH4, MYHRS -SMAD4 and Cervical Cancer
6
RECK 9p13.3 ST15 -RECK and Cervical Cancer
6
FBXW7 4q31.3 AGO, CDC4, FBW6, FBW7, hAgo, FBX30, FBXW6, SEL10, hCdc4, FBXO30, SEL-10 -FBXW7 mutations in Cervical Cancer
6
CDC6 17q21.2 CDC18L, HsCDC6, MGORS5, HsCDC18 -CDC6 and Cervical Cancer
6
FGFR3 4p16.3 ACH, CEK2, JTK4, CD333, HSFGFR3EX -FGFR3 and Cervical Cancer
6
CASP7 10q25.3 MCH3, CMH-1, LICE2, CASP-7, ICE-LAP3 -CASP7 and Cervical Cancer
6
TLR3 4q35.1 CD283, IIAE2 -TLR3 and Cervical Cancer
6
MCM5 22q12.3 CDC46, MGORS8, P1-CDC46 -MCM5 and Cervical Cancer
6
JUNB 19p13.13 AP-1 -JUNB and Cervical Cancer
6
ERCC2 19q13.32 EM9, TTD, XPD, TTD1, COFS2, TFIIH -ERCC2 and Cervical Cancer
5
ETS1 11q24.3 p54, ETS-1, EWSR2, c-ets-1 -ETS1 and Cervical Cancer
5
TFPI2 7q21.3 PP5, REF1, TFPI-2 -TFPI2 and Cervical Cancer
5
SIX1 14q23.1 BOS3, TIP39, DFNA23 -SIX1 and Cervical Cancer
5
HDAC1 1p35.2-p35.1 HD1, RPD3, KDAC1, GON-10, RPD3L1 -HDAC1 and Cervical Cancer
5
MMP14 14q11.2 MMP-14, MMP-X1, MT-MMP, MT1MMP, MTMMP1, WNCHRS, MT1-MMP, MT-MMP 1 -MMP14 and Cervical Cancer
5
MTDH 8q22.1 3D3, AEG1, AEG-1, LYRIC, LYRIC/3D3 -MTDH and Cervical Cancer
5
PAPPA 9q33.1 PAPA, DIPLA1, PAPP-A, PAPPA1, ASBABP2, IGFBP-4ase -PAPPA and Cervical Cancer
5
CLU 8p21.1 CLI, AAG4, APOJ, CLU1, CLU2, KUB1, SGP2, APO-J, SGP-2, SP-40, TRPM2, TRPM-2, NA1/NA2 -Clusterin and Cervical Cancer
5
S100P 4p16.1 MIG9 -S100P and Cervical Cancer
5
IL12B 5q33.3 CLMF, NKSF, CLMF2, IMD28, IMD29, NKSF2, IL-12B -IL12B and Cervical Cancer
4
THRB 3p24.2 GRTH, PRTH, THR1, ERBA2, NR1A2, THRB1, THRB2, C-ERBA-2, C-ERBA-BETA -THRB and Cervical Cancer
4
BARD1 2q35 -BARD1 and Cervical Cancer
4
CDK2 12q13 CDKN2, p33(CDK2) -CDK2 and Cervical Cancer
4
CA12 15q22.2 CAXII, CA-XII, T18816, HsT18816 -CA12 and Cervical Cancer
4
TLR7 Xp22.2 TLR7-like -TLR7 and Cervical Cancer
4
H19 11p15.5 ASM, BWS, WT2, ASM1, D11S813E, LINC00008, NCRNA00008 -H19 and Cervical Cancer
4
CD55 1q32.2 CR, TC, DAF, CROM, CHAPLE -CD55 and Cervical Cancer
4
CASP9 1p36.21 MCH6, APAF3, APAF-3, PPP1R56, ICE-LAP6 -CASP9 and Cervical Cancer
4
SCRIB 8q24.3 CRIB1, SCRB1, SCRIB1, Vartul -SCRIB and Cervical Cancer
4
SFRP1 8p11.21 FRP, FRP1, FrzA, FRP-1, SARP2 -SFRP1 and Cervical Cancer
4
LTA 6p21.33 LT, TNFB, TNFSF1, TNLG1E -LTA and Cervical Cancer
4
CYP27B1 12q14.1 VDR, CP2B, CYP1, PDDR, VDD1, VDDR, VDDRI, CYP27B, P450c1, CYP1alpha -CYP27B1 and Cervical Cancer
4
ICOS 2q33 AILIM, CD278, CVID1 -ICOS and Cervical Cancer
4
PPP2R1B 11q23.1 PR65B, PP2A-Abeta -PPP2R1B and Cervical Cancer
4
PDGFRA 4q12 CD140A, PDGFR2, PDGFR-2 -PDGFRA and Cervical Cancer
4
MACC1 7p21.1 7A5, SH3BP4L -MACC1 and Cervical Cancer
4
HMGA1 6p21.31 HMG-R, HMGIY, HMGA1A -HMGA1 and Cervical Cancer
4
CAV1 7q31.2 CGL3, PPH3, BSCL3, LCCNS, VIP21, MSTP085 -CAV1 and Cervical Cancer
4
HLA-DRA 6p21.32 HLA-DRA1 -HLA-DRA and Cervical Cancer
4
IL12A 3q25.33 P35, CLMF, NFSK, NKSF1, IL-12A -IL12A and Cervical Cancer
4
CLDN3 7q11.23 RVP1, HRVP1, C7orf1, CPE-R2, CPETR2 -CLDN3 and Cervical Cancer
4
MIR10A 17q21.32 MIRN10A, mir-10a, miRNA10A, hsa-mir-10a -miR-10a and Cervical Cancer
4
ABCB1 7q21.12 CLCS, MDR1, P-GP, PGY1, ABC20, CD243, GP170 -ABCB1 and Cervical Cancer
4
LAMB3 1q32.2 AI1A, LAM5, LAMNB1, BM600-125KDA -LAMB3 and Cervical Cancer
4
MMP7 11q22.2 MMP-7, MPSL1, PUMP-1 -MMP7 and Cervical Cancer
3
PCDH10 4q28.3 PCDH19, OL-PCDH -PCDH10 and Cervical Cancer
3
RBP1 3q23 CRBP, RBPC, CRBP1, CRBPI, CRABP-I -RBP1 and Cervical Cancer
3
POU2F1 1q24.2 OCT1, OTF1, oct-1B -POU2F1 and Cervical Cancer
3
SMARCA4 19p13.2 BRG1, CSS4, SNF2, SWI2, MRD16, RTPS2, BAF190, SNF2L4, SNF2LB, hSNF2b, BAF190A -SMARCA4 and Cervical Cancer
3
RECQL4 8q24.3 RECQ4 -RECQL4 and Cervical Cancer
3
IL1B 2q14 IL-1, IL1F2, IL1-BETA -IL1B and Cervical Cancer
3
RASSF2 20p13 CENP-34, RASFADIN -RASSF2 and Cervical Cancer
3
CTSB 8p23.1 APPS, CPSB -CTSB and Cervical Cancer
3
DIABLO 12q24.31 SMAC, DFNA64 -DIABLO and Cervical Cancer
3
HOTAIR 12q13.13 HOXAS, HOXC-AS4, HOXC11-AS1, NCRNA00072 -HOTAIR and Cervical Cancer
3
EGR1 5q31.2 TIS8, AT225, G0S30, NGFI-A, ZNF225, KROX-24, ZIF-268 -EGR1 and Cervical Cancer
3
MCM7 7q22.1 MCM2, CDC47, P85MCM, P1CDC47, PNAS146, PPP1R104, P1.1-MCM3 -MCM7 and Cervical Cancer
3
CTDSPL 3p22.2 PSR1, SCP3, HYA22, RBSP3, C3orf8 -CTDSPL and Cervical Cancer
3
HPRT1 Xq26.2-q26.3 HPRT, HGPRT -HPRT1 and Cervical Cancer
3
NDRG1 8q24.22 GC4, RTP, DRG1, NDR1, NMSL, TDD5, CAP43, CMT4D, DRG-1, HMSNL, RIT42, TARG1, PROXY1 -NDRG1 and Cervical Cancer
3
IL1A 2q14 IL1, IL-1A, IL1F1, IL1-ALPHA -IL1A and Cervical Cancer
3
LAMC2 1q25.3 B2T, CSF, EBR2, BM600, EBR2A, LAMB2T, LAMNB2 -LAMC2 and Cervical Cancer
3
TFPI 2q32 EPI, TFI, LACI, TFPI1 -TFPI and Cervical Cancer
3
ROBO1 3p12 SAX3, DUTT1 -ROBO1 and Cervical Cancer
3
CCN1 1p22.3 GIG1, CYR61, IGFBP10 -CYR61 and Cervical Cancer
3
IL17A 6p12.2 IL17, CTLA8, IL-17, CTLA-8, IL-17A -IL17A and Cervical Cancer
3
UBE2C 20q13.12 UBCH10, dJ447F3.2 -UBE2C and Cervical Cancer
3
TMC8 17q25.3 EV2, EVER2, EVIN2 -TMC8 and Cervical Cancer
3
EPOR 19p13.2 EPO-R -EPOR and Cervical Cancer
3
MIB1 18q11.2 MIB, DIP1, ZZZ6, DIP-1, LVNC7, ZZANK2 -MIB1 and Cervical Cancer
3
POLI 18q21.2 RAD30B, RAD3OB -POLI and Cervical Cancer
3
MEG3 14q32.2 GTL2, FP504, prebp1, PRO0518, PRO2160, LINC00023, NCRNA00023, onco-lncRNA-83 -MEG3 and Cervical Cancer
3
APEX1 14q11.2 APE, APX, APE1, APEN, APEX, HAP1, REF1 -APEX1 and Cervical Cancer
3
TMC6 17q25.3 EV1, EVER1, EVIN1, LAK-4P -TMC6 and Cervical Cancer
3
TOP1 20q12 TOPI -TOP1 and Cervical Cancer
3
CYP19A1 15q21.2 ARO, ARO1, CPV1, CYAR, CYP19, CYPXIX, P-450AROM -CYP19A1 and Cervical Cancer
3
CD83 6p23 BL11, HB15 -CD83 and Cervical Cancer
3
CHI3L1 1q32.1 GP39, ASRT7, GP-39, YK-40, YKL40, CGP-39, YKL-40, YYL-40, HC-gp39, HCGP-3P, hCGP-39 -CHI3L1 and Cervical Cancer
2
FTCDNL1 2q33.1 FONG -FONG and Cervical Cancer
2
CCR6 6q27 BN-1, DCR2, DRY6, CCR-6, CD196, CKRL3, GPR29, CKR-L3, CMKBR6, GPRCY4, STRL22, CC-CKR-6, C-C CKR-6 -CCR6 and Cervical Cancer
2
CYBA 16q24.2 p22-PHOX -CYBA and Cervical Cancer
2
BIRC2 11q22.2 API1, MIHB, HIAP2, RNF48, cIAP1, Hiap-2, c-IAP1 -BIRC2 and Cervical Cancer
2
CLPTM1L 5p15.33 CRR9 -CLPTM1L and Cervical Cancer
2
TACC3 4p16.3 ERIC1, ERIC-1 -TACC3 and Cervical Cancer
2
CD46 1q32.2 MCP, TLX, AHUS2, MIC10, TRA2.10 -CD46 and Cervical Cancer
2
PTCH1 9q22.32 PTC, BCNS, HPE7, PTC1, PTCH, NBCCS, PTCH11 -PTCH1 and Cervical Cancer
2
XRCC4 5q14.2 SSMED -XRCC4 and Cervical Cancer
2
KIAA1524 3q13.13 p90, CIP2A -KIAA1524 and Cervical Cancer
2
CDC25B 20p13 -CDC25B and Cervical Cancer
2
S100A9 1q21.3 MIF, NIF, P14, CAGB, CFAG, CGLB, L1AG, LIAG, MRP14, 60B8AG, MAC387 -S100A9 and Cervical Cancer
2
LGALS3 14q22.3 L31, GAL3, MAC2, CBP35, GALBP, GALIG, LGALS2 -LGALS3 and Cervical Cancer
2
PDCD6 5p15.33 ALG2, ALG-2, PEF1B -PDCD6 and Cervical Cancer
2
EGLN1 1q42.2 HPH2, PHD2, SM20, ECYT3, HALAH, HPH-2, HIFPH2, ZMYND6, C1orf12, HIF-PH2 -EGLN1 and Cervical Cancer
2
HLTF 3q25.1-q26.1 ZBU1, HLTF1, RNF80, HIP116, SNF2L3, HIP116A, SMARCA3 -HLTF and Cervical Cancer
2
RBL1 20q11.23 PRB1, p107, CP107 -RBL1 and Cervical Cancer
2
MIR127 14q32.2 MIRN127, mir-127, miRNA127 -MicroRNA miR-127 and Cervical Cancer
2
IL27 16p12.1-p11.2 p28, IL30, IL-27, IL27A, IL-27A, IL27p28 -IL27 and Cervical Cancer
2
HOXA11 7p15.2 HOX1, HOX1I, RUSAT1 -HOXA11 and Cervical Cancer
2
SERPINA1 14q32.13 PI, A1A, AAT, PI1, A1AT, PRO2275, alpha1AT -SERPINA1 and Cervical Cancer
2
CASP1 11q22.3 ICE, P45, IL1BC -CASP1 and Cervical Cancer
2
CDX2 13q12.2 CDX3, CDX-3, CDX2/AS -CDX2 and Cervical Cancer
2
IRF3 19q13.33 IIAE7 -IRF3 and Cervical Cancer
2
RRM2 2p25-p24 R2, RR2, RR2M -RRM2 and Cervical Cancer
2
PPP1R13L 19q13.32 RAI, RAI4, IASPP, NKIP1 -PPP1R13L and Cervical Cancer
2
DHFR 5q14.1 DYR, DHFRP1 -DHFR and Cervical Cancer
2
MIR124-1 8p23.1 MIR124A, MIR124A1, MIRN124-1, MIRN124A1, mir-124-1 -microRNA 124-1 and Cervical Cancer
2
EXO1 1q43 HEX1, hExoI -EXO1 and Cervical Cancer
2
MAML1 5q35.3 Mam1, Mam-1 -MAML1 and Cervical Cancer
2
NAV1 1q32.1 POMFIL3, UNC53H1, STEERIN1 -NAV1 and Cervical Cancer
2
DLX4 17q21.33 BP1, DLX7, DLX8, DLX9, OFC15 -DLX4 and Cervical Cancer
2
PINX1 8p23.1 LPTL, LPTS -PINX1 and Cervical Cancer
2
MYBL2 20q13.12 BMYB, B-MYB -MYBL2 and Cervical Cancer
2
PDCD1 2q37.3 PD1, PD-1, CD279, SLEB2, hPD-1, hPD-l, hSLE1 -PDCD1 and Cervical Cancer
2
KRT7 12q13.13 K7, CK7, SCL, K2C7 -KRT7 and Cervical Cancer
2
MCM4 8q11.21 NKCD, CDC21, CDC54, NKGCD, hCdc21, P1-CDC21 -MCM4 and Cervical Cancer
2
NR3C2 4q31.23 MR, MCR, MLR, NR3C2VIT -NR3C2 and Cervical Cancer
2
IGFBP5 2q35 IBP5 -IGFBP5 and Cervical Cancer
2
DGCR8 22q11.21 Gy1, pasha, DGCRK6, C22orf12 -DGCR8 and Cervical Cancer
2
SHBG 17p13.1 ABP, SBP, TEBG -SHBG and Cervical Cancer
2
MSLN 16p13.3 MPF, SMRP -MSLN and Cervical Cancer
2
HOXB4 17q21.32 HOX2, HOX2F, HOX-2.6 -HOXB4 and Cervical Cancer
2
CKS2 9q22.2 CKSHS2 -CKS2 and Cervical Cancer
2
LIG4 13q33.3 LIG4S -LIG4 and Cervical Cancer
2
IMP3 15q24.2 BRMS2, MRPS4, C15orf12 -IMP3 and Cervical Cancer
2
MTRR 5p15.31 MSR, cblE -MTRR and Cervical Cancer
2
SLPI 20q13.12 ALP, MPI, ALK1, BLPI, HUSI, WAP4, WFDC4, HUSI-I -SLPI and Cervical Cancer
2
PRKCD 3p21.1 MAY1, PKCD, ALPS3, CVID9, nPKC-delta -PRKCD and Cervical Cancer
2
POLB 8p11.21 -POLB and Cervical Cancer
2
ETS2 21q22.2 ETS2IT1 -ETS2 and Cervical Cancer
2
SOD1 21q22.11 ALS, SOD, ALS1, IPOA, hSod1, HEL-S-44, homodimer -SOD1 and Cervical Cancer
2
DKK3 11p15.3 RIG, REIC -DKK3 and Cervical Cancer
2
RALGDS 9q34.13-q34.2 RGF, RGDS, RalGEF -RALGDS and Cervical Cancer
2
ZNF350 19q13.41 ZFQR, ZBRK1 -ZNF350 and Cervical Cancer
2
TLR1 4p14 TIL, CD281, rsc786, TIL. LPRS5 -TLR1 and Cervical Cancer
2
MMP10 11q22.2 SL-2, STMY2 -MMP10 and Cervical Cancer
2
MIR106A Xq26.2 mir-106, MIRN106A, mir-106a -MIR106A and Cervical Cancer
2
MBL2 10q21.1 MBL, MBP, MBP1, MBPD, MBL2D, MBP-C, COLEC1, HSMBPC -MBL2 and Cervical Cancer
2
PYCARD 16p11.2 ASC, TMS, TMS1, CARD5, TMS-1 -PYCARD and Cervical Cancer
2
CTSL 9q21.33 MEP, CATL, CTSL1 -CTSL and Cervical Cancer
2
FYN 6q21 SLK, SYN, p59-FYN -FYN and Cervical Cancer
2
TWIST2 2q37.3 FFDD3, DERMO1, SETLSS, bHLHa39 -TWIST2 and Cervical Cancer
2
DUSP1 5q35.1 HVH1, MKP1, CL100, MKP-1, PTPN10 -DUSP1 and Cervical Cancer
2
SLC9A1 1p36.11 APNH, NHE1, LIKNS, NHE-1, PPP1R143 -SLC9A1 and Cervical Cancer
2
CCR5 3p21.31 CKR5, CCR-5, CD195, CKR-5, CCCKR5, CMKBR5, IDDM22, CC-CKR-5 -CCR5 and Cervical Cancer
2
AQP3 9p13.3 GIL, AQP-3 -AQP3 and Cervical Cancer
2
PBX1 1q23.3 CAKUHED -PBX1 and Cervical Cancer
2
MTA1 14q32.33 -MTA1 and Cervical Cancer
2
LAPTM4B 8q22.1 LC27, LAPTM4beta -LAPTM4B and Cervical Cancer
2
DLG1 3q29 hdlg, DLGH1, SAP97, SAP-97, dJ1061C18.1.1 -DLG1 and Cervical Cancer
2
CDK9 9q34.11 TAK, C-2k, CTK1, CDC2L4, PITALRE -CDK9 and Cervical Cancer
1
REV1 2q11.1-q11.2 REV1L -REV1 and Cervical Cancer
1
HOXA7 7p15.2 ANTP, HOX1, HOX1A, HOX1.1 -HOXA7 and Cervical Cancer
1
MUC5AC 11p15.5 TBM, leB, MUC5, mucin -MUC5AC and Cervical Cancer
1
CFTR 7q31.2 CF, MRP7, ABC35, ABCC7, CFTR/MRP, TNR-CFTR, dJ760C5.1 -CFTR and Cervical Cancer
1
TSC22D1 13q14.11 Ptg-2, TSC22, TGFB1I4 -TSC22D1 and Cervical Cancer
1
TBK1 12q14.1 NAK, T2K -TBK1 and Cervical Cancer
1
NR4A1 12q13 HMR, N10, TR3, NP10, GFRP1, NAK-1, NGFIB, NUR77 -NR4A1 and Cervical Cancer
1
CASP4 11q22.3 TX, Mih1, ICH-2, Mih1/TX, ICEREL-II, ICE(rel)II -CASP4 and Cervical Cancer
1
KLRK1 12p13.2-p12.3 KLR, CD314, NKG2D, NKG2-D, D12S2489E -KLRK1 and Cervical Cancer
1
KRT14 17q21.2 K14, NFJ, CK14, EBS3, EBS4 -KRT14 and Cervical Cancer
1
NUMB 14q24.2-q24.3 S171, C14orf41, c14_5527 -NUMB and Cervical Cancer
1
CHAT 10q11.23 CMS6, CMS1A, CMS1A2, CHOACTASE -CHAT and Cervical Cancer
1
NDRG2 14q11.2 SYLD -NDRG2 and Cervical Cancer
1
CMBL 5p15.2 JS-1 -CMBL and Cervical Cancer
1
MIR1290 1p36.13 MIRN1290, hsa-mir-1290 -miR-1290 and Cervical Cancer
1
HFE 6p22.2 HH, HFE1, HLA-H, MVCD7, TFQTL2 -HFE and Cervical Cancer
1
PECAM1 17q23.3 CD31, PECA1, GPIIA', PECAM-1, endoCAM, CD31/EndoCAM -PECAM1 and Cervical Cancer
1
HOXC11 12q13.13 HOX3H -HOXC11 and Cervical Cancer
1
AURKB 17p13.1 AIK2, AIM1, ARK2, AurB, IPL1, STK5, AIM-1, STK12, PPP1R48, aurkb-sv1, aurkb-sv2 -AURKB and Cervical Cancer
1
PIK3CD 1p36.22 APDS, PI3K, IMD14, p110D, P110DELTA -PIK3CD and Cervical Cancer
1
ZBTB7A 19p13.3 LRF, FBI1, FBI-1, TIP21, ZBTB7, ZNF857A, pokemon -ZBTB7A and Cervical Cancer
1
KDM5A 12p13.33 RBP2, RBBP2, RBBP-2 -KDM5A and Cervical Cancer
1
IFITM1 11p15.5 9-27, CD225, IFI17, LEU13, DSPA2a -IFITM1 and Cervical Cancer
1
FCGR3A 1q23.3 CD16, FCG3, CD16A, FCGR3, IGFR3, IMD20, FCR-10, FCRIII, FCGRIII, FCRIIIA -FCGR3A and Cervical Cancer
1
CCNC 6q21 CycC -CCNC and Cervical Cancer
1
TPR 1q31.1 -TPR and Cervical Cancer
1
EPHB4 7q22.1 HTK, MYK1, HFASD, TYRO11 -EPHB4 and Cervical Cancer
1
YWHAZ 8q22.3 HEL4, YWHAD, KCIP-1, HEL-S-3, HEL-S-93, 14-3-3-zeta -YWHAZ and Cervical Cancer
1
ALDH3A1 17p11.2 ALDH3, ALDHIII -ALDH3A1 and Cervical Cancer
1
SIPA1 11q13.1 SPA1 -SIPA1 and Cervical Cancer
1
IFNA17 9p21.3 IFNA, INFA, LEIF2C1, IFN-alphaI -IFNA17 and Cervical Cancer
1
ISG15 1p36.33 G1P2, IP17, UCRP, IFI15, IMD38, hUCRP -ISG15 and Cervical Cancer
1
PTCH2 1p34.1 PTC2 -PTCH2 and Cervical Cancer
1
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 Cervical Cancer
1
FOXG1 14q12 BF1, BF2, QIN, FKH2, HBF2, HFK1, HFK2, HFK3, KHL2, FHKL3, FKHL1, FKHL2, FKHL3, FKHL4, HBF-1, HBF-2, HBF-3, FOXG1A, FOXG1B, FOXG1C, HBF-G2 -FOXG1 and Cervical Cancer
1
STIM1 11p15.4 GOK, TAM, TAM1, IMD10, STRMK, D11S4896E -STIM1 and Cervical Cancer
1
MAPK3 16p11.2 ERK1, ERT2, ERK-1, PRKM3, P44ERK1, P44MAPK, HS44KDAP, HUMKER1A, p44-ERK1, p44-MAPK -MAPK3 and Cervical Cancer
1
GNL3 3p21.1 NS, E2IG3, NNP47, C77032 -GNL3 and Cervical Cancer
1
BDNF 11p14.1 ANON2, BULN2 -BDNF and Cervical Cancer
1
OPCML 11q25 OPCM, OBCAM, IGLON1 -OPCML and Cervical Cancer
1
IL16 15q25.1 LCF, NIL16, PRIL16, prIL-16 -IL16 and Cervical Cancer
1
SRSF2 17q25.1 SC35, PR264, SC-35, SFRS2, SFRS2A, SRp30b -SRSF2 and Cervical Cancer
1
HOXA13 7p15.2 HOX1, HOX1J -HOXA13 and Cervical Cancer
1
LAMP1 13q34 LAMPA, CD107a, LGP120 -LAMP1 and Cervical Cancer
1
CCNG1 5q34 CCNG -CCNG1 and Cervical Cancer
1
UCHL1 4p13 NDGOA, PARK5, PGP95, SPG79, PGP9.5, Uch-L1, HEL-117, PGP 9.5, HEL-S-53 -UCHL1 and Cervical Cancer
1
NOP53 19q13.33 PICT1, PICT-1, GLTSCR2 -GLTSCR2 and Cervical Cancer
1
CXCL11 4q21.1 IP9, H174, IP-9, b-R1, I-TAC, SCYB11, SCYB9B -CXCL11 and Cervical Cancer
1
VIPR1 3p22.1 II, HVR1, RDC1, V1RG, VIPR, VIRG, VAPC1, VPAC1, VPAC1R, VIP-R-1, VPCAP1R, PACAP-R2, PACAP-R-2 -VIPR1 and Cervical Cancer
1
NR4A2 2q22-q23 NOT, RNR1, HZF-3, NURR1, TINUR -NR4A2 and Cervical Cancer
1
TEP1 14q11.2 TP1, TLP1, p240, TROVE1, VAULT2 -TEP1 and Cervical Cancer
1
CDH2 18q12.1 CDHN, NCAD, CD325, CDw325 -CDH2 and Cervical Cancer
1
CRP 1q23.2 PTX1 -CRP and Cervical Cancer
1
PLAGL1 6q24.2 ZAC, LOT1, ZAC1 -PLAGL1 and Cervical Cancer
1
MEST 7q32.2 PEG1 -MEST and Cervical Cancer
1
TLR6 4p14 CD286 -TLR6 and Cervical Cancer
1
CEBPB 20q13.13 TCF5, IL6DBP, NF-IL6, C/EBP-beta -CEBPB and Cervical Cancer
1
LTB 6p21.33 p33, TNFC, TNFSF3, TNLG1C -LTB and Cervical Cancer
1
KRT1 12q13.13 K1, CK1, EHK, EHK1, EPPK, KRT1A, NEPPK -KRT1 and Cervical Cancer
1
TNFSF13 17p13.1 APRIL, CD256, TALL2, ZTNF2, TALL-2, TNLG7B, TRDL-1, UNQ383/PRO715 -TNFSF13 and Cervical Cancer
1
TRIM27 6p22.1 RFP, RNF76 -TRIM27 and Cervical Cancer
1
LRRC3B 3p24.1 LRP15 -LRRC3B and Cervical Cancer
1
NBN 8q21.3 ATV, NBS, P95, NBS1, AT-V1, AT-V2 -NBN and Cervical Cancer
1
PTHLH 12p11.22 HHM, PLP, BDE2, PTHR, PTHRP -PTHLH and Cervical Cancer
1
TFRC 3q29 T9, TR, TFR, p90, CD71, TFR1, TRFR, IMD46 -TFRC and Cervical Cancer
1
SOX11 2p25 MRD27 -SOX11 and Cervical Cancer
1
SPINT2 19q13.2 PB, Kop, HAI2, DIAR3, HAI-2 -SPINT2 and Cervical Cancer
1
NR4A3 9q31.1 CHN, TEC, CSMF, NOR1, MINOR -NR4A3 and Cervical Cancer
1
HTRA2 2p12 OMI, PARK13, PRSS25 -HTRA2 and Cervical Cancer
1
DPYD 1p21.3 DHP, DPD, DHPDHASE -DPYD and Cervical Cancer
1
PPIA 7p13 CYPA, CYPH, HEL-S-69p -PPIA and Cervical Cancer
1
PRIM1 12q13 p49 -PRIM1 and Cervical Cancer
1
SMO 7q32.1 Gx, CRJS, SMOH, FZD11 -SMO and Cervical Cancer
1
HSPA8 11q24.1 LAP1, HSC54, HSC70, HSC71, HSP71, HSP73, LAP-1, NIP71, HEL-33, HSPA10, HEL-S-72p -HSPA8 and Cervical Cancer
1
MRTFA 22q13.1-q13.2 MAL, MKL, BSAC, MKL1, MRTF-A -MKL1 and Cervical Cancer
1
GZMB 14q12 C11, HLP, CCPI, CGL1, CSPB, SECT, CGL-1, CSP-B, CTLA1, CTSGL1 -GZMB and Cervical Cancer
1
CRTC1 19p13.11 MECT1, TORC1, TORC-1, WAMTP1 -CRTC1 and Cervical Cancer
1
NTRK2 9q21.33 TRKB, trk-B, GP145-TrkB -NTRK2 and Cervical Cancer
1
WWTR1 3q25.1 TAZ -WWTR1 and Cervical Cancer
1
ADAR 1q21.3 DSH, AGS6, G1P1, IFI4, P136, ADAR1, DRADA, DSRAD, IFI-4, K88DSRBP -ADAR and Cervical Cancer
1
MTHFD1 14q23.3 MTHFC, MTHFD -MTHFD1 and Cervical Cancer
1
HTRA1 10q26.13 L56, HtrA, ARMD7, ORF480, PRSS11, CARASIL, CADASIL2 -HTRA1 and Cervical Cancer
1
EPHX1 1q42.12 MEH, EPHX, EPOX, HYL1 -EPHX1 and Cervical Cancer
1
TFAP2B 6p12.3 PDA2, AP-2B, AP2-B -TFAP2B and Cervical Cancer
1
TLE1 9q21.32 ESG, ESG1, GRG1 -TLE1 and Cervical Cancer
1
CAMTA1 1p36.31-p36.23 CANPMR -CAMTA1 and Cervical Cancer
1
CXCR3 Xq13.1 GPR9, MigR, CD182, CD183, Mig-R, CKR-L2, CMKAR3, IP10-R -CXCR3 and Cervical Cancer
1
CREB3L1 11p11.2 OASIS -CREB3L1 and Cervical Cancer
1
KRT18 12q13.13 K18, CK-18, CYK18 -KRT18 and Cervical Cancer
1
TP53BP2 1q41 BBP, 53BP2, ASPP2, P53BP2, PPP1R13A -TP53BP2 and Cervical Cancer
1
CST6 11q13.1 -CST6 and Cervical Cancer
1
INHA 2q35 -INHA and Cervical Cancer
1
DDR2 1q23.3 TKT, WRCN, MIG20a, NTRKR3, TYRO10 -DDR2 and Cervical Cancer
1
GJA1 6q22.31 HSS, CMDR, CX43, EKVP, GJAL, ODDD, AVSD3, HLHS1 -GJA1 and Cervical Cancer
1
MICB 6p21.33 PERB11.2 -MICB and Cervical Cancer
1
MYCL 1p34.2 LMYC, L-Myc, MYCL1, bHLHe38 -MYCL and Cervical Cancer
1
IDO1 8p11.21 IDO, INDO, IDO-1 -IDO1 and Cervical Cancer
1
ANXA8 10q11.22 ANX8, CH17-360D5.2 -ANXA8 and Cervical Cancer
1
APOD 3q29 -APOD and Cervical Cancer
1
ELF4 Xq26.1 MEF, ELFR -ELF4 and Cervical Cancer
1
IL6R 1q21.3 IL6Q, gp80, CD126, IL6RA, IL6RQ, IL-6RA, IL-6R-1 -IL6R and Cervical Cancer
1
RFC1 4p14 A1, RFC, PO-GA, RECC1, MHCBFB, RFC140 -RFC1 and Cervical Cancer
1
FOXC2 16q24.1 LD, MFH1, MFH-1, FKHL14 -FOXC2 and Cervical Cancer
1
IBSP 4q22.1 BSP, BNSP, SP-II, BSP-II -IBSP and Cervical Cancer
1
IRAK2 3p25.3 IRAK-2 -IRAK2 and Cervical Cancer
1
TP53INP1 8q22.1 SIP, Teap, p53DINP1, TP53DINP1, TP53INP1A, TP53INP1B -TP53INP1 and Cervical Cancer
1
PTP4A3 8q24.3 PRL3, PRL-3, PRL-R -PTP4A3 and Cervical Cancer
1
RRM2B 8q22.3 P53R2, MTDPS8A, MTDPS8B -RRM2B and Cervical Cancer
1
SLC45A3 1q32.1 PRST, IPCA6, IPCA-2, IPCA-6, IPCA-8, PCANAP2, PCANAP6, PCANAP8 -SLC45A3 and Cervical Cancer
1
SRSF3 6p21.31-p21.2 SFRS3, SRp20 -SRSF3 and Cervical Cancer
1
GALE 1p36.11 SDR1E1 -GALE and Cervical Cancer
1
RASSF5 1q32.1 RAPL, Maxp1, NORE1, NORE1A, NORE1B, RASSF3 -RASSF5 and Cervical Cancer
1
S100A2 1q21.3 CAN19, S100L -S100A2 and Cervical Cancer
1
EPHA2 1p36.13 ECK, CTPA, ARCC2, CTPP1, CTRCT6 -EPHA2 and Cervical Cancer
1
TGFB3 14q24.3 ARVD, LDS5, RNHF, ARVD1, TGF-beta3 -TGFB3 and Cervical Cancer
1
ADAMTS9 3p14.1 -ADAMTS9 and Cervical Cancer
1
WWOX 16q23.1-q23.2 FOR, WOX1, EIEE28, FRA16D, SCAR12, HHCMA56, PRO0128, SDR41C1, D16S432E -WWOX and Cervical Cancer
1
LRIG3 12q14.1 LIG3 -LRIG3 and Cervical Cancer
1
GUSB 7q11.21 BG, MPS7 -GUSB and Cervical Cancer
1
MAML2 11q21 MAM2, MAM3, MAM-3, MLL-MAML2 -MAML2 and Cervical Cancer
1
RARRES3 11q12.3 RIG1, TIG3, HRSL4, HRASLS4, PLA1/2-3 -RARRES3 and Cervical Cancer
1
SMARCB1 22q11.23 RDT, CSS3, INI1, SNF5, Snr1, BAF47, MRD15, RTPS1, Sfh1p, hSNFS, SNF5L1, SWNTS1, PPP1R144 -SMARCB1 and Cervical Cancer
1
CLMP 11q24.1 ACAM, ASAM, CSBM, CSBS -CLMP and Cervical Cancer
1
USP7 16p13.2 TEF1, HAUSP -USP7 and Cervical Cancer
1
CASP6 4q25 MCH2 -CASP6 and Cervical Cancer
1
ETV5 3q27.2 ERM -ETV5 and Cervical Cancer
1
PER1 17p13.1 PER, hPER, RIGUI -PER1 and Cervical Cancer
1
SMARCA2 9p24.3 BRM, SNF2, SWI2, hBRM, NCBRS, Sth1p, BAF190, SNF2L2, SNF2LA, hSNF2a -SMARCA2 and Cervical Cancer
1
S100A8 1q21.3 P8, MIF, NIF, CAGA, CFAG, CGLA, L1Ag, MRP8, CP-10, MA387, 60B8AG -S100A8 and Cervical Cancer
PPP2CB 8p12 PP2CB, PP2Abeta -PPP2CB and Cervical Cancer
POLL 10q24.32 BETAN, POLKAPPA -POLL and Cervical Cancer
PPP2CA 5q31.1 RP-C, PP2Ac, PP2CA, PP2Calpha -PPP2CA and Cervical Cancer
PTPRC 1q31.3-q32.1 LCA, LY5, B220, CD45, L-CA, T200, CD45R, GP180 -PTPRC and Cervical Cancer
FOLR1 11q13.4 FBP, FOLR -FOLR1 and Cervical Cancer
TNFRSF10B 8p21.3 DR5, CD262, KILLER, TRICK2, TRICKB, ZTNFR9, TRAILR2, TRICK2A, TRICK2B, TRAIL-R2, KILLER/DR5 -TNFRSF10B and Cervical 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

Lan C, Huan DW, Nie XC, et al.
Association of C8orf4 expression with its methylation status, aberrant β-catenin expression, and the development of cervical squamous cell carcinoma.
Medicine (Baltimore). 2019; 98(31):e16715 [PubMed] Related Publications
Chromosome 8 open reading frame 4 (C8orf4) is an activator of Wnt signaling pathway, and participates in the tumorigenesis and progression of many tumors. The expression levels of C8orf4 and β-catenin were assessed via immunohistochemical staining in 100 cervical squamous cell carcinoma (CSCC) tissues, 50 high-grade squamous intraepithelial lesions (HSILs), 50 low-grade squamous intraepithelial lesions (LSILs), and 50 normal cervical tissues. Bisulfite sequencing polymerase chain reaction analysis was used to examine the methylation status of the C8orf4 locus in CSCC and normal cervical tissues. The expression rates of C8orf4 and β-catenin were significantly higher in CSCCs or HSILs than in LSILs or normal cervical tissues (P < .05). C8orf4 expression was positively correlated with the poor differentiation of CSCCs (P = .009), and with aberrant expression of β-catenin in CSCCs (P = .002) and squamous intraepithelial lesions (P < .001). The methylation rate of C8orf4 in CSCCs was significantly lower than that in normal cervical tissues (P = .001). The Cancer Genome Atlas genomics data also confirmed that the mRNA expression of C8orf4 was positively associated with the copy number alteration of C8orf4 (correlation coefficient = 0.213, P < .001), and negatively correlated with the methylation level of C8orf4 (correlation coefficient = -0.408, P < .001). In conclusion, the expressions of C8orf4 and β-catenin were synergistically increased in CSCCs and HSILs and higher than those in LSILs and normal cervical tissues. The methylation level of C8orf4 is decreased in CSCCs and is responsible for the increased expression of C8orf4.

Banerjee S, Karunagaran D
An integrated approach for mining precise RNA-based cervical cancer staging biomarkers.
Gene. 2019; 712:143961 [PubMed] Related Publications
Since international federation of gynecology and obstetrics (FIGO) staging is mainly based on clinical assessment, an integrated approach for mining RNA based biomarkers for understanding the molecular deregulation of signaling pathways and RNAs in cervical cancer was proposed in this study. Publicly available data were mined for identifying significant RNAs after patient staging. Significant miRNA families were identified from mRNA-miRNA and lncRNA-miRNA interaction network analyses followed by stage specific mRNA-miRNA-lncRNA association network generation. Integrated bioinformatic analyses of selected mRNAs and lncRNAs were performed. Results suggest that HBA1, HBA2, HBB, SLC2A1, CXCL10 (stage I), PKIA (stage III) and S100A7 (stage IV) were important. miRNA family enrichment of interacting miRNA partners of selected RNAs indicated the enrichment of let-7 family. Assembly of collagen fibrils and other multimeric structures_Homosapiens_R-HSA-2022090 in pathway analysis and progesterone_CTD_00006624 in DSigDB analysis were the most significant and SLC2A1, hsa-miR-188-3p, hsa-miR-378a-3p and hsa-miR-150-5p were selected as survival markers.

Lin CH, Peng SF, Chueh FS, et al.
The Ethanol Crude Extraction of
Anticancer Res. 2019; 39(7):3697-3709 [PubMed] Related Publications
BACKGROUND/AIM: Cervical cancer is considered poorly chemo-sensitive in women and its treatment remains unsatisfactory. Cyperus rotundus is used in Chinese medicine as a therapeutic agent for women's disease. The effects and molecular mechanisms of the ethanol extraction of C. rotundus (CRE) on cervical cancer remain unclear. We aimed to explore the mechanisms and genetic influence of CRE on cervical cancer.
MATERIALS AND METHODS: HeLa, human cervical cancer cells were treated with various doses of CRE and changes in cell morphology and cell viability were assessed using microscopy and flow cytometry. Finally, we performed a microarray analysis to scan related genes.
RESULTS: The treatment of CRE on HeLa cells caused morphological changes and induced chromatin condensation. DNA microarray analysis showed that CRE led to up-regulation of 449 genes and down-regulation of 484 genes, which were classified in several interaction pathways.
CONCLUSION: CRE changed HeLa cell morphology and induced gene expression which associated with apoptosis and cell-cycle arrest. These results provide important information at the transcription level for targeting treatments of human cervical cancer.

Liu F, Zou Y, Wang F, et al.
Genet Test Mol Biomarkers. 2019; 23(6):409-417 [PubMed] Related Publications

Guo Y, Ma D, Jia SF, et al.
[Proliferation of MicroRNA-365 and E74-like Factor 4 in Cervical Cancer Cells and Its Clinical Significance].
Zhongguo Yi Xue Ke Xue Yuan Xue Bao. 2019; 41(2):220-227 [PubMed] Related Publications
Objective To investigate the expressions,roles,and clinical significance of microRNA-365(miR-365)and E74-like factor 4(ELF4)in cervical cancer. Methods The expressions of miR-365 in normal cervical tissues(n=34),cervical intraepithelial neoplasia 1(CIN 1)(n=31),cervical intraepithelial neoplasia2-3(CIN 2-3)(n=37),squamous cell carcinoma of the cervix(SCC)(n=33),and three cervical cancer cell lines(C33A cells,Hela cells,and SiHa cells)were detected by real-time quantitative polymerase chain reaction(qPCR).Bioinformatic prediction and luciferase reporter gene assay were performed to verify whether ELF4 was a direct target of miR-365.Western blot and immunohistochemistry were used to detect ELF4 expression in cervical cancer cells and in different pathological cervix tissues.CCK8 assay was used to detect the effect of overexpression or inhibition of miR-365 on the proliferation of cervical cancer cells at different time points.The relationships among the miR-365 expression,ELF4 expression,and clinicopathological parameters of cervical cancer were analyzed by correlation analysis. Results qPCR results showed that compared with the normal cervical cell HcerEpic,the expressions of miR-365 in CIN1,CIN2-3,and cervical cancer tissues gradually decreased with the increased pathologic grade,and its expressions also decreased in different cervical cancer cell lines.The luciferase reporter gene assay confirmed that ELF4 was the direct target of miR-365.Western blot showed that the expression of ELF4 increased in all three cervical cancer cell lines compared with normal cervical epidermal cell(P=0.013,P=0.002,P=0.004).Immunohistochemistry showed that ELF4 expression was up-regulated in CIN and cervical cancer tissues.CCK8 assay showed that overexpression of miR-365 inhibited cell proliferation,while inhibition of miR-365 promoted the proliferation of three cervical cancer cells(P<0.05).Further analysis confirmed that there was a negative correlation between the expression levels of miR-365 and ELF4 in CIN2-3 and SCC(r=-0.351,P=0.045;r=-0.349,P=0.035).Clinical analysis showed that the expressions of both miR-365 and ELF4 were correlated with tumor size,pathological grade,and clinical stage in SCC(all P < 0.05).Conclusion The decreased expression of miR-365 in human cervical cancer cells relieves its inhibitory effect on ELF4,which promotes the proliferation of cervical cancer cells and the formation of tumor.

Ding L, Zhang H
Circ-ATP8A2 promotes cell proliferation and invasion as a ceRNA to target EGFR by sponging miR-433 in cervical cancer.
Gene. 2019; 705:103-108 [PubMed] Related Publications
Cervical cancer (CC), a common gynecological carcinoma, is a serious threat to women's health. The dysregulation of circular RNAs (circRNAs) is associated with the pathogenesis of cervical cancer. Therefore, we explored the role of circ-ATP8A2 in CC cell development and progression. Circ-ATP8A2 profiles in CC specimens and cells were detected using real-time PCR. In addition, cell counting kit-8 (CCK-8), acridine orange/ethidium bromide (AO/EB), flow cytometric, and Transwell experiments were carried out on HeLa and SW756 cells to determine cell proliferation, apoptosis, migration and invasion. Furthermore, the mechanism of circ-ATP8A2 was explored by dual-luciferase reporter system. Circ-ATP8A2 was significantly enhanced in CC specimens and cells. Knockdown of circ-ATP8A2 inhibited cell proliferation, migratory and invasive capacities and increased apoptotic cells. Ectopically expressed circ-ATP8A2 induced the opposite effects. For the mechanism exploration, circ-ATP8A2 sponges miR-433 to release its suppression on epidermal growth factor receptor (EGFR) expression at post-transcriptional level. What's more, circ-ATP8A2 could promote cell progression by miR-433/EGFR axis in CC cells. Collectively, this work might offer a potential treatment target for CC. ABBREVIATIONS.

Chen H, Wang H, Liu J, et al.
Association of the MUTYH Gln324His (CAG/CAC) variant with cervical carcinoma and HR-HPV infection in a Chinese population.
Medicine (Baltimore). 2019; 98(17):e15359 [PubMed] Related Publications
This study was performed to investigate the relationship between the MUTYH Gln324His (CAG/CAC) genotype and risk of cervical squamous cell carcinoma (CSCC) in a case-control setting. Mismatch amplification-polymerase chain reaction (MA-PCR) was applied to detect the polymorphism in 400 CSCC, 400 CIN III and 1200 control participants. The homozygous His324His (CAC/CAC) genotype of MUTYH was associated with significantly increased risk of CIN III (OR = 1.94) and CSCC (OR = 3.83). Increased risk of CIN III (OR = 1.34) and CSCC (OR = 1.97) was additionally observed with the heterozygous CAG/CAC genotype. Overall, individuals in both CAC/CAC and CAG/CAC genotype groups were at higher risk of cervical carcinoma (CINIII (OR = 1.46) and CSCC (OR = 2.34)). Within the HR-HPV infection-positive group, CAC/CAC and CAG/CAC genotypes were significantly enriched in relation to CIN III and CSCC. Moreover, we observed a positive correlation between the proportion of homozygous CAC/CAC MUTYH genotype and malignant prognostic factors of CSCC, such as cell differentiation grade and lymph node metastasis. These findings clearly highlight associations between the MUTYH Gln324His (CAG/CAC) polymorphism and susceptibility to CSCC, HR-HPV infection and specific prognostic factors, supporting the utility of this variant as an early indicator for patients at high risk of cervical carcinoma.

Xie Z, Wei Y, Xu J, et al.
Alkaloids from Piper nigrum Synergistically Enhanced the Effect of Paclitaxel against Paclitaxel-Resistant Cervical Cancer Cells through the Downregulation of Mcl-1.
J Agric Food Chem. 2019; 67(18):5159-5168 [PubMed] Related Publications
In the current study, nine amide alkaloids, including two new dimeric amides and a new natural product, were identified from Piper nigrum. Among them, seven compounds sensitized paclitaxel-resistant cervical cancer cells HeLa/PTX to paclitaxel. Piperine was a major component obtained from Piper nigrum, and its sensitization mechanism was investigated. Combination treatment enhanced cell apoptosis, which was mediated by downregulation of phospho-Akt and Mcl-1. Piperine (50 μM) combined with paclitaxel (200 nM) downregulated Mcl-1 protein expression with a decrease of 35.9 ± 9.5% ( P < 0.05). Moreover, overexpression of Mcl-1 attenuated the inhibitory effect of this combination. Furthermore, combination treatments of six dimeric amide alkaloids and paclitaxel all downregulated Mcl-1 protein expression with a decrease ranging from 23.5 ± 9.7% to 41.7 ± 7.2% ( P < 0.05). We reveal, for the first time, that dimeric amide alkaloids from plants possess a remarkable sensitization effect on cancer cells to paclitaxel.

Fu W, Hou G, Huang D
[Long non-coding RNA and cervical cancer].
Sheng Wu Gong Cheng Xue Bao. 2019; 35(4):598-606 [PubMed] Related Publications
Long non-coding RNAs (lncRNAs) are members of RNA that are structurally similar to mRNA. They cannot encode proteins because they do not have a conserved open reading frame. LncRNAs were once regarded as abnormalities or noises or without any biological function after gene transcription. With the further development of research, it has been found that it can participate in normal or abnormal biological processes as an important regulator. LncRNAs are closely related to the development of nervous system function, metabolic disorders and tumors. LncRNAs abnormally expressed in cervical cancer participate in the regulation of various biological processes of cervical cancer by inhibiting or promoting tumors. This article reviews the recent reports on the abnormal regulation, molecular regulation mechanism and potential clinical application of lncRNAs in cervical cancer.

Chen W, Chen X, Wang Y, et al.
Construction and Analysis of lncRNA-Mediated ceRNA Network in Cervical Squamous Cell Carcinoma by Weighted Gene Co-Expression Network Analysis.
Med Sci Monit. 2019; 25:2609-2622 [PubMed] Free Access to Full Article Related Publications
BACKGROUND More and more recent studies have clearly shown that long non-coding RNA (lncRNA) should be considered as a fundamental part of the ceRNA network, mainly because lncRNA can act as miRNA sponges to regulate the protein-coding gene expression. Nevertheless, it is still not clear how lncRNA-mediated ceRNAs function in cervical squamous cell carcinoma (CESC). Moreover, information about the ceRNA regulatory mechanism is also remarkably limited; thus, prediction of CESC prognosis using ceRNA-related information remains challenging. MATERIAL AND METHODS We collected 306 RNA (lncRNA, miRNA, and mRNA) expression profile datasets obtained from cervical squamous cancer tissues plus 3 more from adjacent cervical tissues via the TCGA database. Subsequently, we constructed a lncRNAs-miRNAs-mRNAs CESC ceRNA network, and Gene Ontology (GO) analysis was carried out. RESULTS We identified a total of 30 DElncRNAs, 70 DEmiRNAs, and 1089 DEmRNAs in CESC. Subsequently, to reveal the expression patterns of dysregulated genes, weighted gene co-expression network analysis was carried out, resulting in 3 co-expression modules with significantly related clinical properties. The constructed aberrant lncRNAs-miRNAs-mRNAs CESC ceRNA network was composed of 17 DEmiRNAs, 5 DElncRNAs, and 7 DEmRNAs. Moreover, the survival analysis was performed for DElncRNAs, DEmiRNAs, and DEmRNAs. CONCLUSIONS The present study shows the involvement of the lncRNA-related ceRNA network in the pathogenesis of CESC. We believe the newly generated ceRNA network will provide more insights into the lncRNA-mediated ceRNA regulatory mechanisms.

Xiang H, Zhou J, Peng H, et al.
[Association of EGFR gene G719S and T790M mutations with cervical cancer].
Zhonghua Yi Xue Yi Chuan Xue Za Zhi. 2019; 36(4):376-379 [PubMed] Related Publications
OBJECTIVE: To establish a rapid and accurate "on/off" switch technique consisted of 3'-phosphorothioate-modified allele-specific primers and exo+ polymerase to screen the G719S and T790M mutations of epidermal growth factor receptor (EGFR) gene. The switch was used to identify cervical cancer patients who are sensitive to tyrosine kinase inhibitor (TKI).
METHODS: Allele-specific primers targeting recombinant wild-type and mutation-type templates were designed with 3' terminal phosphorothioate modification. Two-directional primer extension was carried out using Pfu polymerase. The G719S and T790M mutations were detected by the technique among cervical cancer tissues. The results were verified by Sanger sequencing.
RESULTS: No mutation was detected among the 80 cervical cancer cases, and the results were consistent with that of Sanger sequencing. No significant difference was found between the frequencies of the G719S and T790M mutations between the patient and the control groups (P> 0.05).
CONCLUSION: A sensitive "on/off" switch technique for detecting the two EGFR mutations was established. The G719S and T790M mutations are not associated with cervical cancer.

Sun JJ, Li HL, Guo SJ, et al.
The Increased PTK7 Expression Is a Malignant Factor in Cervical Cancer.
Dis Markers. 2019; 2019:5380197 [PubMed] Free Access to Full Article Related Publications
Cervical cancer is one of the most common malignant neoplasms in gynecology. Protein tyrosine kinase 7 (PTK7) with an inactive kinase domain is an important regulator of multiple Wnt pathways under normal and various pathological conditions and overexpressed in various tumors; however, the clinical and biological significance of PTK7 in cervical cancer is still unknown. In the present study, the protein expression level of PTK7 was detected in clinical cervical cancer patient samples, and the relationship between PTK7 expression and clinicopathological features was analyzed. In addition, the Kaplan-Meier method was performed to estimate the overall survival (OS) and progression-free survival (PFS) of patients to investigate the clinicopathological significance of PTK7 expression. Functional assays demonstrated that knocking down PTK7 might inhibit the ability of cancer cells to proliferate and invade or migrate, both in vivo and in vitro. Thus, PTK7 might serve as a potential target for cervical cancer.

Shi C, Yang Y, Zhang L, et al.
Optimal subset of signature miRNAs consisting of 7 miRNAs that can serve as a novel diagnostic and prognostic predictor for the progression of cervical cancer.
Oncol Rep. 2019; 41(6):3167-3178 [PubMed] Free Access to Full Article Related Publications
Cervical cancer is the second most commonly diagnosed cancer in women. Novel prognostic biomarkers are required to predict the progression of cervical cancer. Cervical cancer expression data were obtained from The Cancer Genome Atlas (TCGA) database. MicroRNAs (miRNAs) significantly differentially expressed between early‑ and advanced‑stage samples were identified by expression analysis. An optimal subset of signature miRNAs for pathologic stage prediction was delineated using the random forest algorithm and was used for the construction of a cervical cancer‑specific support vector machine (SVM) classifier. The roles of signature miRNAs in cervical cancer were analyzed by functional annotation. In total, 44 significantly differentially expressed miRNAs were identified. An optimal subset of 7 signature miRNAs was identified, including hsa‑miR‑144, hsa‑miR‑147b, hsa‑miR‑218‑2, hsa‑miR‑425, hsa‑miR‑451, hsa‑miR‑483 and hsa‑miR‑486. The signature miRNAs were used to construct an SVM classifier and exhibited a good performance in predicting pathologic stages of samples. SVM classification was found to be an independent prognostic factor. Functional enrichment analysis indicated that these signature miRNAs are involved in tumorigenesis. In conclusion, the subset of signature miRNAs could potentially serve as a novel diagnostic and prognostic predictor for cervical cancer.

Mao Y, Zhang L, Li Y
circEIF4G2 modulates the malignant features of cervical cancer via the miR‑218/HOXA1 pathway.
Mol Med Rep. 2019; 19(5):3714-3722 [PubMed] Free Access to Full Article Related Publications
Circular RNAs (circRNAs) serve important roles in tumorigenesis and may be used as novel molecular biomarkers for clinical diagnosis. However, the role and molecular mechanisms of circRNAs in cervical cancer (CC) remain unknown. In the present study, circRNA isoform of eukaryotic translation initiation factor 4γ2 (circEIF4G2) was revealed to be significantly upregulated in CC tissues and cell lines. Furthermore, increased expression of circEIF4G2 was associated with poor prognosis in patients with CC. circEIF4G2 knockdown suppressed the malignant features of CC cells, including cell proliferation, colony formation, migration and invasion. Additionally, circEIF4G2 was identified to serve as a sponge for microRNA‑218 (miR‑218), which targeted homeobox A1 (HOXA1). Furthermore, circEIF4G2 may increase the expression levels of HOXA1 by sponging miR‑218. Rescue experiments suggested that transfection with a miR‑218 inhibitor attenuated the inhibitory effects of circEIF4G2 knockdown on cell proliferation, migration and invasion. Furthermore, silencing HOXA1 reversed the effects of the miR‑218 inhibitor on CC cells. Collectively, the present findings suggested that circEIF4G2 promoted cell proliferation and migration via the miR‑218/HOXA1 pathway.

Hernández-Juárez J, Vargas-Sierra O, Herrera LA, et al.
Sodium-coupled monocarboxylate transporter is a target of epigenetic repression in cervical cancer.
Int J Oncol. 2019; 54(5):1613-1624 [PubMed] Free Access to Full Article Related Publications
The SLC5A8 gene encodes Na monocarboxylate transporter 1, which is epigenetically inactivated in various tumour types. This has been attributed to the fact that it prevents the entry of histone deacetylase (HDAC) inhibitors and favours the metabolic reprogramming of neoplastic cells. Nevertheless, its expression and regulation in cervical cancer (CC) have not been elucidated to date. The aim of the present study was to investigate whether SLC5A8 expression is silenced in CC and if epigenetic mechanisms are involved in its regulation. Using RNA and DNA from human CC cell lines and tumour tissues from patients with CC, the expression of SLC5A8 was analysed by reverse transcription polymerase chain reaction and the methylation status of its CpG island (CGI) by bisulphite‑modified sequencing. Additionally, SLC5A8 reactivation was examined in the CC cell lines following treatment with DNA methylation (5‑aza‑2'‑deoxycytidine) and HDAC inhibitors (trichostatin A and pyruvate). All the CC cell lines and a range of tumour tissues (65.5%) exhibited complete or partial loss of SLC5A8 transcription. The bisulphite‑sequencing revealed that hypermethylation of the CGI within SLC5A8 first exon was associated with its downregulation in the majority of cases. The transporter expression was restored in the CC cell lines following exposure to 5‑aza‑2'‑deoxycytidine alone, or in combination with trichostatin A or pyruvate, suggesting that DNA methylation and histone deacetylation contribute to its inhibition in a cell line‑dependent manner. Together, the results of the present study demonstrate the key role of DNA hypermethylation in the repression of SLC5A8 in CC, as well as the involvement of histone deacetylation, at least partially. This allows for research focused on the potential function of SLC5A8 as a tumour suppressor in CC, and as a biomarker or therapeutic target in this malignancy.

Xiang X, Luo L, Nodzyński M, et al.
LION: a simple and rapid method to achieve CRISPR gene editing.
Cell Mol Life Sci. 2019; 76(13):2633-2645 [PubMed] Related Publications
The RNA-guided CRISPR-Cas9 technology has paved the way for rapid and cost-effective gene editing. However, there is still a great need for effective methods for rapid generation and validation of CRISPR/Cas9 gRNAs. Previously, we have demonstrated that highly efficient generation of multiplexed CRISPR guide RNA (gRNA) expression array can be achieved with Golden Gate Assembly (GGA). Here, we present an optimized and rapid method for generation and validation in less than 1 day of CRISPR gene targeting vectors. The method (LION) is based on ligation of double-stranded gRNA oligos into CRISPR vectors with GGA followed by nucleic acid purification. Using a dual-fluorescent reporter vector (C-Check), T7E1 assay, TIDE assay and a traffic light reporter assay, we proved that the LION-based generation of CRISPR vectors are functionally active, and equivalent to CRISPR plasmids generated by traditional methods. We also tested the activity of LION CRISPR vectors in different human cell types. The LION method presented here advances the rapid functional validation and application of CRISPR system for gene editing and simplified the CRISPR gene-editing procedures.

Cao XM
Role of miR-337-3p and its target Rap1A in modulating proliferation, invasion, migration and apoptosis of cervical cancer cells.
Cancer Biomark. 2019; 24(3):257-267 [PubMed] Related Publications
OBJECTIVE: To investigate the role of miR-337-3p targeting Rap1A in modulating proliferation, invasion, migration and apoptosis of cervical cancer cells.
METHODS: The expression levels of miR-337-3p and Rap1A in cervical cancer tissues and normal tissues were evaluated through quantitative Real-time PCR (qRT-PCR) and Western blotting; and correlations of miR-337-3p with clinicopathological characteristics and prognosis of patients were also analyzed. Besides, human cervical cancer cell line HeLa cells were randomly divided into five groups (Mock, NC, miR-337-3p mimic, Rap1A, and miR-337-3p mimic + Rap1A groups). CCK-8 assay was utilized to measure cell proliferation, flow cytometry to evaluate cell apoptosis, and wound-healing and Transwell assays to detect cell migration and invasion.
RESULTS: Cervical cancer tissues presented a significant decrease in miR-337-3p and a remarkable increase in Rap1A protein. Besides, the expression levels of miR-337-3p and Rap1A were closely related to the major clinicopathological characteristics of cervical cancer; and patients with high-miR-337-3p-expression had the higher 5-year survival rate (all p< 0.05). When compared to Mock group, cells in miR-337-3p mimic group were suppressed in proliferation, migration, and invasion, but significantly promoted in apoptosis; meanwhile, cells in the Rap1A group showed changes in a completely opposite trend (all p< 0.05). Moreover, Rap1A can reverse the effect of miR-337-3p mimic on cell proliferation, invasion, migration and apoptosis (all p< 0.05).
CONCLUSION: MiR-337-3p was discovered to be decreased in cervical cancer, and miR-337-3p up-regulation may inhibit the proliferation, migration and invasion and promote the apoptosis of cervical cancer cells via down-regulating Rap1A.

Li T, Li M, Xu C, et al.
miR‑146a regulates the function of Th17 cell differentiation to modulate cervical cancer cell growth and apoptosis through NF‑κB signaling by targeting TRAF6.
Oncol Rep. 2019; 41(5):2897-2908 [PubMed] Related Publications
The aim of the present study was to investigate whether miRNA‑146a regulated the function of Th17 cell differentiation to modulate cervical cancer cell growth and apoptosis. miR‑146a expression was increased in human cervical cancer. Both overall survival (OS) and disease‑free survival (DFS) of low miR‑146a expression were higher than those of high miR‑146a expression. Additionally, IL‑17a expression was lower in patients with high miR‑146a expression compared to that of patients with lower miR‑146a expression. In a co‑culture of cervical cancer and CD4+ T cells, downregulation of miR‑146a inhibited cell growth and induced apoptosis of cervical cancer cells, while overexpression of miR‑146a promoted cell growth and reduced apoptosis of cervical cancer cells. Downregulation of miR‑146a induced TRAF6 and NF‑κB protein expression, increased IL‑6, IL‑17A and IL‑21 levels, and enhanced p‑STAT3 protein expression. The inhibition of TRAF6 attenuated the effects of anti‑miR‑146a on the function of Th17 cell differentiation to modulate cervical cancer cell growth and apoptosis. Collectively, miR‑146a regulated the function of Th17 cell differentiation to modulate cervical cancer cell growth and apoptosis through NF‑κB signaling by targeting TRAF6. miR‑146a may function as an oncogene in cervical cancer via Th17 cell differentiation by targeting TRAF6.

Gao F, Feng J, Yao H, et al.
LncRNA SBF2-AS1 promotes the progression of cervical cancer by regulating miR-361-5p/FOXM1 axis.
Artif Cells Nanomed Biotechnol. 2019; 47(1):776-782 [PubMed] Related Publications
Long non-coding RNAs (lncRNAs) have been identified as critical players in tumorigenesis. Previous studies revealed that lncRNA SBF2-AS1 was involved in tumor progression. However, the role and underlying mechanism of SBF2-AS1 in cervical cancer (CC) remain unknown. In the present study, our data showed that SBF2-AS1 expression was significantly increased in CC. High SBF2-AS1 expression was associated with advanced FIGO stage and lymph node metastasis of CC patients. Function assays showed that SBF2-AS1 inhibition significantly reduced CC cells proliferation both in vitro and in vivo. Mechanistically, we showed that SBF2-AS1 upregulation restrained the activity of miR-361-5p and led to overexpression of FOXM1 in CC cells. Furthermore, we found that miR-361-5p inhibitors could rescue the effects of SBF2-AS1 inhibition on CC cells proliferation. Taken together, we demonstrated that the SBF2-AS1/miR-361-5p/FOXM1 axis might play an important role in CC progression. SBF2-AS1 might serve as a potential therapeutic target for CC treatment.

Bhattacharjee S, Jaiswal RK, Yadava PK
Measles virus phosphoprotein inhibits apoptosis and enhances clonogenic and migratory properties in HeLa cells.
J Biosci. 2019; 44(1) [PubMed] Related Publications
Measles virus is the causative agent of measles, a major cause of child mortality in developing countries. Two major proteins, coded by the viral genome, are nucleocapsid protein (N) and phosphoprotein (P). The N protein protects the viral genomic RNA and forms ribonucleoprotein complex (RNP) together with P protein. MeV-P protein recruits the large protein (L), i.e. viral RNA-depended RNA polymerase (RdRp), to ensure viral replication in host cell. Apoptogenic properties of N protein of Edmonston vaccine strain have been established in our lab previously. We investigated the role of MeV-P protein of Edmonston vaccine strain as modulator of apoptosis in cervical cancer cell line (HeLa) and found that MeV-P protein is anti-apoptotic and enhances cell proliferation. Measles virus is considered to be innately oncotropic virus. However, the anti-apoptotic property of MeV-P protein raises important concerns while adopting this virus as an anti-cancer therapeutic tool.

Zhang X, Zhi Y, Li Y, et al.
Study on the relationship between methylation status of HPV 16 E2 binding sites and cervical lesions.
Clin Chim Acta. 2019; 493:98-103 [PubMed] Related Publications
BACKGROUND: The aim of this study was to investigate the methylation status of E2BSs in the HPV 16 long control region (LCR) in clinical cervical samples.
METHODS: Methylation status of the four E2BSs in 43 clinical cervical samples with HPV 16 infection was quantitatively detected using pyrosequencing. Meanwhile, Quantivirus® HPV E6/E7 RNA 3.0 assay (bDNA) was used to detect E6/E7 mRNA levels in the corresponding specimens.
RESULTS: Our results showed that methylation status of E2BS1, 2 and 4 sites in high-grade squamous intraepithelial lesions (HSIL) and cervical cancer were significantly higher than that of asymptomatic HPV 16 infection and low-grade squamous intraepithelial lesions (LSIL) (all P < .05). Furthermore, methylation status of HPV 16 E2BS1 and 2 was positively correlated with E6/E7 mRNA levels (r
CONCLUSIONS: The methylation status of E2BS1 and 2 may have utility as diagnostic markers for the severity of cervical lesions in the future.

Zhang L, Liu SK, Song L, Yao HR
SP1-induced up-regulation of lncRNA LUCAT1 promotes proliferation, migration and invasion of cervical cancer by sponging miR-181a.
Artif Cells Nanomed Biotechnol. 2019; 47(1):556-564 [PubMed] Related Publications
Long noncoding RNA lung cancer associated transcript 1 (LUCAT1) has been shown to be a lncRNA that facilitates the development and progression of several tumours. However, the evidence of LUCAT1 modulating the growth and metastasis of cervical cancer (CC) were still lacking. The present study aimed to explore the expression pattern, biological function and potential mechanism of LUCAT1 in CC. In this study, we, first, confirmed that LUCAT1 acted as an up-regulated lncRNA by analyzing the data from GCTA dataset and RT-PCR in both CC tissues and cell lines. We also showed that TINCR overexpression is induced by nuclear transcription factor SP1. Then, clinical assays showed that LUCAT1 was associated with advanced clinical progression and poor prognosis of CC patients. Importantly, multivariate Cox model confirmed that LUCAT1 expression was an independent prognostic factor for both 5-year overall survival in CC. Then, lost-function assays revealed that knockdown of LUCAT1 significantly suppressed CC cells proliferation, colony formation, migration, invasion and EMT by a series of cells experiments. Mechanistically, Bioinformatic tools predicted that miR-181a may target LUCAT1, which was confirmed using luciferase reporter assay and RNA immunoprecipitation (RIP) assays. Overall, our findings showed that SP1-activated LUCAT1 exerts an oncogenic function in CC by binding to miR-181a, suggesting that miR-181a may be a ponderable and promising therapeutic target for CC.

Aierken K, Dong Z, Abulimiti T, et al.
CDK6 3'UTR polymorphisms alter the susceptibility to cervical cancer among Uyghur females.
Mol Genet Genomic Med. 2019; 7(5):e626 [PubMed] Free Access to Full Article Related Publications
AIMS: Cyclin dependent kinase 6 (CDK6) plays a crucial role in malignant tumor whereas less is reported in cervical cancer development. The aim of this study was to evaluate the effects of CDK6 3' untranslated region (3'UTR) polymorphisms on cervical cancer susceptibility among Uyghur females.
METHODS: The genotypes of the six CDK6 variants (rs8179, rs42032, rs42033, rs42034, rs42035, and rs42038) were identified among 306 cervical cancer cases and 310 healthy controls with the Agena MassARRAY platform. The associations of the candidate single nucleotide polymorphisms (SNPs) with the cervical cancer risk were evaluated under genetic models using conditional logistic regression analysis. Bioinformatics analysis was performed for SNP function prediction with the online databases. The expression differences between tumor tissues and normal cervix samples were also examined by Real-time PCR.
RESULTS: CDK6 rs8179 and rs42033 were correlated to the decreased risk of cervical cancer in Uyghurs under the allele model (rs8179 and rs42033: OR = 0.60, 95% CI: 0.37-0.99, p = 0.043) and log-additive model (rs8179 and rs42033: OR = 0.62, 95% CI: 0.38-1.00, p = 0.047). Rs8179, rs42032, and rs42033 were associated with susceptibility to high-grade cervical cancer in different genetic models as well (p < 0.05). Dataset-based analysis also uncovered the potential effects of these significant SNPs. In addition, aberrant expression of CDK6 were detected in cervical tumors.
CONCLUSIONS: Our results suggested the relationships between CDK6 3'UTR polymorphisms and cervical cancer pathogenesis, and the involvement of CDK6 in cervical cancer development among Uyghur females.

Bo H, Fan L, Gong Z, et al.
Upregulation and hypomethylation of lncRNA AFAP1‑AS1 predicts a poor prognosis and promotes the migration and invasion of cervical cancer.
Oncol Rep. 2019; 41(4):2431-2439 [PubMed] Related Publications
Although lncRNA AFAP1 antisense RNA1 (AFAP1‑AS1) is considered an oncogenic lncRNA, little is known about the role of AFAP1‑AS1 in cervical cancer. In the present study, we found that AFAP1‑AS1 was elevated and hypomethylated in cervical cancer and was associated with a poor prognosis of patients with cervical cancer by analyzing the Cancer RNA‑Seq Nexus (CRN), MethCH and UCSC XENA databases. Subsequently, we knocked AFAP1‑AS1 expression down using siRNAs in cervical cancer cells. Wound healing experiments and matrigel invasion experiments revealed that the downregulation of AFAP1‑AS1 suppressed the migration and invasion of cervical cancer cells. Furthermore, western blot analysis demonstrated that the antitumor effects induced by the silencing of AFAP1‑AS1 were mainly mediated through the regulation of the Rho/Rac signaling pathway and epithelial‑mesenchymal transition (EMT)‑related genes. Taken together, the findings of the present study indicate that the expression level of AFAP1‑AS1 may be involved in the development of cervical cancer. Thus, AFAP1‑AS1 may be a novel prognostic biomarker and a potential therapeutic target for patients with cervical cancer.

Yi Y, Liu Y, Wu W, et al.
Reconstruction and analysis of circRNA‑miRNA‑mRNA network in the pathology of cervical cancer.
Oncol Rep. 2019; 41(4):2209-2225 [PubMed] Free Access to Full Article Related Publications
The present study was performed with the aim of understanding the mechanisms of pathogenesis and providing novel biomarkers for cervical cancer by constructing a regulatory circular (circ)RNA‑micro (mi)RNA‑mRNA network. Using an adjusted P-value of <0.05 and an absolute log value of fold-change >1, 16 and 156 miRNAs from GSE30656 and The Cancer Genome Atlas (TCGA), 5,321 mRNAs from GSE63514, 4,076 mRNAs from cervical squamous cell carcinoma and endocervical adenocarcinoma (from TCGA) and 75 circRNAs from GSE102686 were obtained. Using RNAhybrid, Venn and UpSetR plot, 12 circRNA‑miRNA pairs and 266 miRNA‑mRNA pairs were obtained. Once these pairs were combined, a circRNA‑miRNA‑mRNA network with 11 circRNA nodes, 4 miRNA nodes, 153 mRNA nodes and 203 edges was constructed. By constructing the protein‑protein interaction network using Molecular Complex Detection scores >5 and >5 nodes, 7 hubgenes (RRM2, CEP55, CHEK1, KIF23, RACGAP1, ATAD2 and KIF11) were identified. By mapping the 7 hubgenes into the preliminary circRNA‑miRNA‑mRNA network, a circRNA‑miRNA‑hubgenes network consisting of 5 circRNAs (hsa_circRNA_000596, hsa_circRNA_104315, hsa_circRNA_400068, hsa_circRNA_101958 and hsa_circRNA_103519), 2 mRNAs (hsa‑miR‑15b and hsa‑miR‑106b) and 7 mRNAs (RRM2, CEP55, CHEK1, KIF23, RACGAP1, ATAD2 and KIF11) was constructed. There were 22 circRNA‑miRNA‑mRNA regulatory axes identified in the subnetwork. By analyzing the overall survival for the 7 hubgenes using the Gene Expression Profiling Interactive Analysis tool, higher expression of RRM2 was demonstrated to be associated with a significantly poorer overall survival. PharmGkb analysis identified single nucleotide polymorphisms (SNPs) of rs5030743 and rs1130609 of RRM2, which can be treated with cladribine and cytarabine. RRM2 was also indicated to be involved in the gemcitabine pathway. The 5 circRNAs (hsa_circRNA_000596, hsa_circRNA_104315, hsa_circRNA_400068, hsa_circRNA_101958 and hsa_circRNA_103519) may function as competing endogenous RNAs and serve critical roles in cervical cancer. In addition, cytarabine may produce similar effects to gemcitabine and may be an optional chemotherapeutic drug for treating cervical cancer by targeting rs5030743 and rs1130609 or other similar SNPs. However, the specific mechanism of action should be confirmed by further study.

Xu Y, Zhou W, Zhang C, et al.
Long non-coding RNA RP11-552M11.4 favors tumorigenesis and development of cervical cancer via modulating miR-3941/ATF1 signaling.
Int J Biol Macromol. 2019; 130:24-33 [PubMed] Related Publications
As one of the most aggressive malignancies, cervical cancer (CC) which mainly affects females has high risks of relapse and death. Long non-coding RNA (lncRNA) RP11-552M11.4 is verified to promote the progression of ovarian cancer; nevertheless, its role and the probable molecular mechanisms in CC remain unclear until the present study. Herein, we unveiled that the expression of lncRNA RP11-552M11.4 tested by qRT-PCR was enhanced in tumor tissues compared with the para-carcinoma tissues and related to FIGO Stage, lymph node metastasis, vascular invasion and distant metastasis in CC. Additionally, CC patients with high lncRNA RP11-552M11.4 level suffered from poor clinical outcomes. Moreover, silenced lncRNA RP11-552M11.4 restrained cell proliferation, migration and invasion in CC cells. Subsequently, the mechanistic studies revealed that lncRNA RP11-552M11.4 functioned as a ceRNA of ATF1 in CC by acting as the endogenous sponge for miR-3941, which was identified as a tumor suppressor in CC. Moreover, both miR-3941 inhibition and ATF1 overexpression restored the impacts of inhibited lncRNA RP11-552M11.4 on cellular processes in CC cells. Our observations elucidated the carcinogenic role of lncRNA RP11-552M11.4 in CC was mediated through miR-3941/ATF1 axis, giving a new insight into the effective target for the treatment and prognosis of cervical cancer.

Paaso A, Jaakola A, Syrjänen S, Louvanto K
From HPV Infection to Lesion Progression: The Role of HLA Alleles and Host Immunity.
Acta Cytol. 2019; 63(2):148-158 [PubMed] Related Publications
Persistent high-risk human papillomavirus (HPV) infection has been associated with increased risk for cervical precancerous lesions and cancer. The host's genetic variability is known to play a role in the development of cervical cancer. The human leukocyte antigen (HLA) genes are highly polymorphic and have shown to be important risk determinants of HPV infection persistence and disease progression. HLA class I and II cell surface molecules regulate the host's immune system by presenting HPV-derived peptides to T-cells. The activation of T-cell response may vary depending on the HLA allele polymorphism. The engagement of the T-cell receptor with the HPV peptide-HLA complex to create an active costimulatory signal is essential for the activation of the T-cell response. Functional peptide presentation by both HLA class I and II molecules is needed to activate efficient helper and effector T-cell responses in HPV infection recognition and clearance. Some of these HLA risk alleles could also be used as preventive tools in the detection of HPV-induced cervical lesions and cancer. These HLA alleles, together with HPV vaccines, could potentially offer possible solutions for reducing HPV-induced cervical cancer as well as other HPV-related cancers.

Chen Y, Hou Y, Yang Y, et al.
Gene expression changes in cervical squamous cancers following neoadjuvant interventional chemoembolization.
Clin Chim Acta. 2019; 493:79-86 [PubMed] Related Publications
BACKGROUND: The efficacy of therapy for cervical cancer is related to the alteration of multiple molecular events and signaling networks during treatment. The aim of this study was to evaluate gene expression alterations in advanced cervical cancers before- and after-trans-uterine arterial chemoembolization- (TUACE).
METHODS: Gene expression patterns in three squamous cell cervical cancers before- and after-TUACE were determined using microarray technique. Changes in AKAP12 and CA9 genes following TUACE were validated by quantitative real-time PCR.
RESULTS: Unsupervised cluster analysis revealed that the after-TUACE samples clustered together, which were separated from the before-TUACE samples. Using a 2-fold threshold, we identified 1131 differentially expressed genes that clearly discriminate after-TUACE tumors from before-TUACE tumors, including 209 up-regulated genes and 922 down-regulated genes. Pathway analysis suggests these genes represent diverse functional categories. Results from real-time PCR confirmed the expression changes detected by microarray.
CONCLUSIONS: Gene expression signature significantly changes during TUACE therapy of cervical cancer. Theses alterations provide useful information for the development of novel treatment strategies for cervical cancers on the molecular level.

Yu J, Zhang J, Zhou L, et al.
The Octamer-Binding Transcription Factor 4 (OCT4) Pseudogene, POU Domain Class 5 Transcription Factor 1B (POU5F1B), is Upregulated in Cervical Cancer and Down-Regulation Inhibits Cell Proliferation and Migration and Induces Apoptosis in Cervical Cancer Cell Lines.
Med Sci Monit. 2019; 25:1204-1213 [PubMed] Free Access to Full Article Related Publications
BACKGROUND The POU domain class 5 transcription factor 1B (POU5F1B), is a pseudogene that is homologous to octamer-binding transcription factor 4 (OCT4), and is located adjacent to the MYC gene on human chromosome 8q24. POU5F1B has been reported to be transcribed in several types of cancer, but its role in cervical cancer remains unclear. This study aimed to investigate the expression and function of POU5F1B in tissue samples of human cervical cancer and in cervical cancer cell lines in vitro. MATERIAL AND METHODS Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to quantify POU5F1B expression in cervical cancer tissues and in SiHa, HeLa, CaSki, and C33A human cervical cancer cell lines. Functional in vitro studies included analysis of the effects of POU5F1B expression on cervical cancer cell proliferation, migration, and apoptosis using a Cell Counting Kit-8 (CCK-8) assay, cell migration assays, and flow cytometry. Luciferase activity assays, qRT-PCR, and Western blot were performed to confirm the expression of POU5F1B. RESULTS POU5F1B was significantly upregulated in cervical cancer tissues and cell lines. Interference with the expression of POU5F1B significantly inhibited cell proliferation, apoptosis, migration and invasion, and induced apoptosis in vitro. Western blot demonstrated that POU5F1B could modulate the expression of the OCT4 protein. CONCLUSIONS POU5F1B was upregulated in cervical cancer and down-regulation inhibited cell proliferation and migration and induced apoptosis in cervical cancer cell lines by modulating OCT4. Further studies are required to determine whether POU5F1B might be a diagnostic or prognostic biomarker or therapeutic target in cervical cancer.

Abedin S, Paul SK, Haque N, et al.
Distribution of HPV-16 and HPV-18 from the Patients Attending At Mymensingh Medical College Hospital by Newly Developed Oncoprotein Detection Assay.
Mymensingh Med J. 2019; 28(1):31-36 [PubMed] Related Publications
Cervical cancer is one of cause of death in women in many developing countries. Persistent infection with Human Papilloma Virus (HPV), primarily high risk types 16 and 18, is recognized as a causal and essential factor for the development of cervical cancer. The objective of this cross sectional observational study is to detect the distribution of HPV-16 and HPV-18 among Onco E6 positive cases. Following universal safety precautions a total of 180 endocervical swabs were collected from Colposcopy clinic of Obstetrics and Gynaecology Department of Mymensingh Medical College Hospital (MMCH), Mymensingh, Bangladesh from January 2016 to December 2016. Laboratory work was done in the department of Microbiology, Mymensingh Medical College. E6 strip test is an immunochromatographic test based on the detection of HPV-E6 oncoprotein in cervical swab samples. Onco E6 cervical test was done on 180cases. Among them 60% were VIA positive and 120% were VIA negative. From this VIA positive cases 12(16.25%) were On E6 cervical test positive and from VIA negative cases 3(2.5%) were positive by this On E6 cervical test. From this 12 Onco E6 cervical test positive cases 10(%) were HPV-16 and 2(%) were HPV-18 and from VIA negative cases 3 were only HPV-16 by this test. Histopathological test done on 35 suspected cases and out of 08 cervical carcinoma cases 07 were positive by this Onco E6 cervical test which was also HPV-16 type. It may be concluded that HPV-16 is most prevalent type to cause cervical cancer and by this newly developed protein detection assay will be helpful to reduce over treatment and save many lives.

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Cite this page: Cotterill SJ. Cervical Cancer, Cancer Genetics Web: http://www.cancer-genetics.org/X1002.htm Accessed:

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