Table SI. Targets of Berberine. Gene Symbol Gene Name ABL1 ABO

Total Page:16

File Type:pdf, Size:1020Kb

Table SI. Targets of Berberine. Gene Symbol Gene Name ABL1 ABO Table SI. Targets of berberine. Table SI. Continued. Gene symbol Gene name Gene symbol Gene name ABL1 CHEK1 ABO CMA1 ACADM CRABP2 ACHE CTNNA1 ADAM17 CTSB ADAM33 CTSK ADH1C CTSS ADH5 CYP19A1 ADK CYP2C9 ADRB2 DAPK1 AKR1B1 DCK AKR1C1 DCPS AKR1C2 DHFR AKR1C3 DHODH AKT1 DPEP1 ALB DPP4 AMD1 DTYMK AMY2A DUSP6 ANXA5 DUT APAF1 EGFR APOA2 EIF4E APRT ELANE AR EPHB4 AURKA EPHX2 BACE1 ERBB4 BCAT2 ESR1 BCHE ESR2 BCL2L1 ESRRG BHMT F10 BIRC7 F2 BMP2 FABP3 BRAF FABP6 CA2 FABP7 CALM FDPS CASP1 FECH CASP3 FGFR1 CASP7 FGFR2 CCL5 FGG CCNA2 FKBP1A CDK2 FKBP1B CDK6 FKBP3 CES1 GC CFD GMPR Table SI. Continued. Table SI. Continued. Gene symbol Gene name Gene symbol Gene name GMPR2 MAPK14 GPI MAPKAPK2 GSK3B MET GSR METAP2 GSTA1 MME GSTA3 MMP12 GSTM1 MMP13 GSTM2 MMP2 GSTP1 MMP3 HADH MMP8 HCK MMP9 HDAC8 MTAP HINT1 MTHFD1 HMGCR NCOA2 HNF4G NGAL HNMT NMNAT1 HPGDS NOS2 HPRT1 NOS3 HRAS NQO1 HSD11B1 NQO2 HSD17B1 NR1A1 HSP90AA1 NR1B2 HSP90AB1 NR1H2 HSPA8 NR1H3 IGF1 NR1H4 IGF1R NR1I2 IGLV2-8 NR3C1 IL2 NR3C2 INSR OAT ITK OTC JAK2 PAH JAK3 PAPSS1 KAT2B PCK1 KCNH2 PDE10A KDR PDE3B KIF11 PDE4B KIT PDE4D LCK PDE5A LSS PDK2 LTA4H PDPK1 MAOB PGF MAP2K1 PGR MAPK10 Pim1 Table SI. Continued. Table SI. Continued. Gene symbol Gene name Gene symbol Gene name PKLR SULT2A1 PLA2G2A TAP1 PNMT TEK PPARA TGFB2 PPARD TGFBR1 PPARG TGM3 PPIA THRB PPP1CC TPSB2 PPP5C TRAPPC3 PRKACA TTPA PRKCQ TTR PROCR TYMS PRSS1 VDR PTGS1 XIAP PTGS2 ZAP70 PTK2 PTPN1 PTPN11 PYGL RAP2A RARA RARG RBP4 REN RFK RORA RXRA RXRB S100A9 SCN5A SDS SEC14L2 SERPINA1 SETD7 SHBG SIRT5 SORD SPR Src STAT1 STS SULT1A1 SULT1E1 Table SII. Genes differentially expressed in liver cancer. Table SII. Continued. Gene-OncoDB. Gene symbol- Common targets Gene-OncoDB. Gene symbol- Common targets HCC (n=611) liverome (n=6,927) (n=167) HCC (n=611) liverome (n=6,927) (n=167) TP73 ECHS1 ABL1 MUC1 AOX1 DAPK1 ENO1 ADH1B ABO SCAMP3 APOA1 DCK MASP2 GPC3 ACADM FDPS ARG1 DCPS ALDH4A1 ALB ADAM17 YY1AP1 CCT3 DHFR PLA2G2A BHMT ADH1C CCT3 CTSB DHODH ALPL PLG ADH5 HDGF CYP2C8 DPP4 RUNX3 VIM ADK CD5L FAH DTYMK STMN1 RGN ADRB2 APCS FGA DUSP6 SFN TF AKR1B1 CRP FGL1 DUT FCN3 FABP1 AKR1C1 COPA FTCD EGFR FAM76A HPD AKR1C2 NCSTN GHR EIF4E KHDRBS1 ACADSB AKR1C3 ITLN1 HSPB1 EPHB4 EIF3S2 CAT AKT1 ATF6 IGF2 EPHX2 FNDC5 MTHFD1 ALB RGS5 KRT8 ERBB4 PHC2 RPSA AMD1 GLUL NDRG1 ESR1 DNALI1 SLC22A1 ANXA5 PTGS2 S100A10 ESR2 YBX1 TDO2 APAF1 RGS1 SCP2 ESRRG CDC20 ADH4 APOA2 CFHR3 SELENBP1 F10 PRDX1 CP APRT UBE2T SULT2A1 F2 CDKN2C CYP2E1 AR CHI3L1 UBD FDPS SCP2 PCK1 AURKA KISS1 ACAA1 FGFR1 C8A SPARC BCAT2 CD34 ACAA2 FGFR2 CACHD1 ACSL1 BCHE PPP2R5A AFP FGG LEPR ALDH1L1 BCL2L1 PARP1 ALDH2 FKBP1A IL12RB2 ALDH4A1 BHMT MTR ANXA2 FKBP3 BCL10 ALDOB BMP2 ADAM17 BUB1 GC CYR61 CPS1 BRAF RRM2 CLIC1 GMPR GNAI3 CYB5A CA2 RHOB COL1A2 GMPR2 RHOC CYP2C9 CASP1 DNMT3A COMT GPI SYCP1 FGB CASP3 KHK CYP2B6 GSR HAO2 FGG CASP7 EHD3 DCXR GSTA1 HMGCS2 GAPDH CCL5 HAAO DNASE1L3 GSTA3 FAM72B HRSP12 CCNA2 TACSTD1 FEN1 GSTM1 ECM1 HSD17B10 CDK2 GPR75 FN1 GSTM2 MCL1 HSPA5 CDK6 RTN4 GLUL GSTP1 PSMD4 IGFBP3 CES1 XPO1 HMMR HADH SNX27 PCK2 CHEK1 UGP2 HNRNPA2B1 HINT1 S100A9 PDIA3 CRABP2 TGFA HSP90B1 HMGCR ILF2 SERPINA1 CTNNA1 REG1A ITIH4 HNF4G JTB TTR CTSB REG3A KHK HNMT SHC1 AGXT CTSS MAT2A MT2A HPRT1 EFNA1 AKR1B10 CYP2C9 FABP1 NNMT HSD11B1 Table SII. Continued. Table SII. Continued. Gene-OncoDB. Gene symbol- Common targets Gene-OncoDB. Gene symbol- Common targets HCC (n=611) liverome (n=6,927) (n=167) HCC (n=611) liverome (n=6,927) (n=167) IL18RAP NPM1 HSD17B1 PDGFRA HAAO PKLR STEAP3 PCSK6 HSP90AA1 UGT2B4 HDGF PLA2G2A RND3 PGK1 HSP90AB1 IGJ HGD PNMT CD302 PPIB IGF1 DCK HMGCS2 PPARA ITGA6 PRDX6 IGF1R SLC4A4 HSD17B4 PPARD HSPD1 RFC4 IL2 ALB HSPA1B PPARG CPS1 SLC2A2 INSR AFP HSPA8 PPIA ERBB4 SNRPE JAK2 AFM IGKC PPP1CC FN1 STMN1 KAT2B CXCL2 ISG15 PRKACA TUBA1 TOP2A KDR PLAC8 KNG1 PROCR SPP2 A2M KIF11 HPSE LAMP2 PRSS1 AGXT ACAT1 KIT PTPN13 MAT1A PTGS2 RAF1 ACY1 LCK SPARCL1 MCM2 PTK2 XPC ALDH1A1 MAOB SPP1 MMP9 PTPN1 TGFBR2 APOC3 MAP2K1 ABCG2 NME1 PTPN11 ACAA1 ARID3A MAPK14 ADH4 PCNA PYGL RPSAP15 ASS1 MET BDH2 PEMT RAP2A CTNNB1 C6 MME EGF PGRMC1 RBP4 VIPR1 C9 MMP12 MAD2L1 PKM2 REN CDC25A CA2 MMP13 ANXA5 PON3 RORA COL7A1 CAP2 MMP2 CCNA2 QDPR RXRA SEMA3B CCT5 MMP3 IL2 RBP1 RXRB RASSF1 CD14 MMP9 FGF2 RDBP SDS ZMYND10 CD24 MTAP EDNRA SCAMP3 SEC14L2 ACY1 CDK4 MTHFD1 FGB SERPING1 SERPINA1 DNASE1L3 CDKN1A NCOA2 FGA SOD1 SHBG FHIT CES1 NMNAT1 FGG TST SIRT5 ROBO1 CES2 NOS2 TDO2 TUBB SORD TMEM45A CLU NQO1 ANXA10 VTN SPR MUC13 COL1A1 NQO2 MFAP3L ACADVL Src ALDH1L1 CPB2 NR1H4 GPM6A ACTB STAT1 TF CTGF NR1I2 VEGFC ADH1C SULT1A1 MME CYP27A1 NR3C1 CASP3 ADH6 SULT1E1 SMC4 CYP2J2 OAT ACSL1 AKR1C2 SULT2A1 TNFSF10 CYP3A4 OTC KLKB1 ALAS1 TAP1 PIK3CA EFNA1 PAH VPS53 ALDH1B1 TGFB2 TFRC EPHX1 PAPSS1 NP_001001870.1 ALDH3A2 THRB FGFR3 ETS2 PCK1 SERPINF2 ALDOA TTPA HGFAC FABP5 PDK2 DERL2 B2M TTR S100P FH PDPK1 CENTB1 BNIP3 TYMS GPR78 GC PGF SHBG C1R XIAP LAP3 GNMT Pim1 TP53 C5orf13 Table SII. Continued. Table SII. Continued. Gene-OncoDB. Gene symbol- Common targets Gene-OncoDB. Gene symbol- Common targets HCC (n=611) liverome (n=6,927) (n=167) HCC (n=611) liverome (n=6,927) (n=167) NP_001004313.1 C8A GPC3 PC SHMT1 CAPG F9 PEG10 MFAP4 CBX1 SPANXC PGM1 NOS2A CFH MAGEC2 PRDX1 VTN CRHBP MAGEA11 PROZ CCL2 CSTB MAGEA8 PTTG1 CCL3 CTH FATE1 PUF60 ERBB2 CXCL12 MAGEA4 PYGB RARA CYP1A2 GABRE RBP4 P11388-3 CYP2A6 MAGEA10 RCAN1 KRT19 CYP2A7 MAGEA2B RHOA ACLY CYR61 MAGEA2 RHOB ETV4 DDR1 MAGEA3 RND3 GRN DLGAP5 MAGEA1 RPLP0 CBX1 ENO1 BCAP31 RPS5 NGFR FCGRT CTAG1A S100A6 NME1 FCN3 TSPY1_HUMAN SAA2 DYNLL2 GLUD1 RBMY1B SERPINC1 AXIN2 GRHPR TERT SERPINF2 SSTR2 GYS2 CCT5 SGK1 SLC9A3R1 HAMP NP_001030022.1 SLC16A2 GALK1 HAO1 GHR SLC7A2 PRPSAP1 HGFAC CRHBP SOD2 BIRC5 HMGA1 BHMT SPARCL1 SOCS3 HNRNPC APC SRGN NOTUM HPX AP3S1 STAT1 CD99 HSD17B6 SLC27A6 TGM2 SRPX IFI27 IRF1 THBS1 DDX3X IFIT1 HSPA4 TIMP1 RGN IGF2R FBXL21 TMED2 SSX5 ILF2 EGR1 TPM2 SSX1 ITIH2 HSPA9 UGT2B7 SSX4_HUMAN ITPR2 NRG2 ABAT RBM3 KIF23 HBEGF ACADM GAGE8 LPGAT1 FGF1 ACADS GAGD2_HUMAN LYZ SPARC ACLY SSX2_HUMAN MAD2L1 PTTG2 ACO1 AR MCM6 HMMR ACOX1 EFNB1 MDK NPM1 AKR1C3 GJB1 MT1F DUSP1 AKR1C4 PSMD10 NAMPT STC2 ANXA1 LUZP4 NFKBIA MUTED ANXA4 Table SII. Continued. Table SII. Continued. Gene-OncoDB. Gene symbol- Common targets Gene-OncoDB. Gene symbol- Common targets HCC (n=611) liverome (n=6,927) (n=167) HCC (n=611) liverome (n=6,927) (n=167) EDN1 APOC1 SERPINE1 GMNN CAP2 APOC4 NP_114111.2 GOT2 DEK APOH SYPL1 GPX2 GMNN ARHGDIB DOCK4 GSN SLC17A3 ARNT MET GSTA2 HFE ASGR1 LEP H1F0 UBD_HUMAN ASGR2 SMO H2AFZ CLIC1_HUMAN BLVRB AKR1B10 HAGH HSPA1B C5 ZYX HIST1H4C HMGA1 C8B EZH2 HLA-DRA DEF6 CANX SHH HMGCL CDKN1A CCNB1 KBTBD11 HP PGC CCT4 ANGPT2 HRG GNMT CD74 CTSB HSPA4 VEGFA CDKN3 DLC1 HSPA9 MUT CEP55 VPS37A HSPD1 PNRC1 CETP MTUS1 ICAM1 ARG1 CFB FGL1 IFITM1 CTGF CRYL1 NAT2 IGF1 ALDH8A1 CSE1L STC1 IGFALS ESR1 CTSC NRG1 KCNJ8 ACAT2 CYP3A5 PRKDC KIAA0101 IGF2R CYP4A11 SNAI2 KIAA0196 SLC22A1 DAB2 ASPH LBR PLG DAO COPS5 LCN2 PARK2 DBI STMN2 LGALS3 ACTB DCN FABP5 LGALS3BP HOXA13 DDX5 CA1 LGALS8 PPIA_HUMAN DUSP1 CA3 MCM3 ADCY1 DUSP9 CA2 MME IGFBP1 ECH1 CDH17 MMP14 IGFBP3 EHHADH LAPTM4B MPST EGFR EHMT2 PABPC1 MT1E CLDN4 EIF6 ANGPT1 NAP1L1 HSPB1 ENPP1 EIF3S6 NAT2 GNAI1 F11 EBAG9 NEK2 HGF FAS EIF3S3 NME2 ABCB1 FBP1 ENPP2 OTC SGCE FLNB HAS2 PEBP1 PEG10 FOS ZHX2 PLIN2 AZGP1 GAMT ATAD2 PON1 MCM7 GBP1 MTSS1 POR Table SII. Continued. Table SII. Continued. Gene-OncoDB. Gene symbol- Common targets Gene-OncoDB. Gene symbol- Common targets HCC (n=611) liverome (n=6,927) (n=167) HCC (n=611) liverome (n=6,927) (n=167) MYC PPAP2B MT1B AEBP1 PTK2 PPIA MT1F AGL LY6E PPP1CC MT1G AGRN GPAA1 PRDX3 MT1X AHCY RLN1 PSMC5 CETP AK3 MTAP RGS2 CDH1 AKR1D1 CDKN2A RGS5 HP ALDH9A1 CDKN2B RPL6 WWOX ALDOC TEK SEPP1 COMT AMACR AQP7 SERPINE1 UBE2L3 AMBP AQP3 SF3B4 MAPK1 ANG ALDH1A1 SHBG IGLV4-3 ANXA5 HNRPK SHC1 IGLL1 APOC2 GADD45G SHMT1 MIF AQP3 FBP1 SLC10A1 MMP11 AR PTCH1 SLC29A1 UPB1 ARHGDIA BAAT SLC38A3 TST ASAP1 ALDOB SLC39A14 SSTR3 ATP1A1 NEK6 SMC4 FAM10A6 ATP6AP1 HSPA5 SNRPB MLC1 AZGP1 ENG SORL1 ECGF1 BAAT LCN2 SPP1 SNRPB BCAP31 ASS1 SQLE CDC25B BCHE AXIN1 SYPL1 PCNA BLOC1S1 SSTR5 TPX2 ID1 C1orf9 NME3 TRIP13 DNMT3B C1S GFER TSPAN8 MAPRE1 C6orf97 SOCS1 TUBA1B E2F1 C7 SMG1_HUMAN TUBA4A SRC CALR NP_060358.2 UBAP2L MYBL2 CAPZA1 ACSM3 WARS UBE2C CCL14 PLK1 XPO1 MMP9 CCL2 TAOK2 YWHAZ CD40 CCL20 MAPK3 ACOX2 SNAI1 CCL3 ZNF689 ACSL5 AURKA CCND1 PRSS8 ACSL6 PCK1 CCT6A PYDC1 ACSS3 GNAS CD302 SIAH1 ADAMTS1 TPTE CD46 RBL2 ADAR BAGE5 CD81 MMP2 ADH1A TIAM1 CDC14B MT3 ADH5 SOD1 CDC20 MT1JP ADM ETS2 CDC25B Table SII. Continued. Table SII. Continued. Gene-OncoDB. Gene symbol- Common targets Gene-OncoDB. Gene symbol- Common targets HCC (n=611) liverome (n=6,927) (n=167) HCC (n=611) liverome (n=6,927) (n=167) TFF3 CDH1 CYP2E1 GCKR CBS CDK1 IFITM1 GCLM FTCD CENPF H19 GCN1L1 USP14 CKLF IGF2 GGH TNFSF5IP1 CLDN1 Q8N2L8_HUMAN GJB1 AQP4 CMBL CD81 GLA TTR COL4A2 CDKN1C GLYAT ATP5A1 COL6A3 SLC22A18 GNPAT SMAD2 COLEC10 RRM1 GOT1 SMAD4 CPD XLKD1 GPAA1 DCC CRP BBOX1 GPD1 SERPINB2 CTSA CAT GPNMB CYB5A CTSS CD44 GRN KLF6 CXCR4 CD82 GSTM1 AKR1C3 CYBA MDK GSTO1 TRDMT1 CYP8B1 SERPING1 GSTP1 VIM DCI GLYAT GSTZ1 SVIL DECR1 FEN1 GUSB ITGB1 DEK FADS2 H3F3A RET DPP4 BAD HABP2 CXCL12 DPYSL2 PYGM HADH DKK1 DUSP5 CDCA5 HADHB MAWBP_HUMAN DUSP6 GSTP1 HBA1 SUPV3L1 EDNRB CCND1 HDAC2 PLAU EGFR FADD HIPK2 MAT1A EIF2S1 FUT4 HK2 NRG3 EIF3E MMP7 HLA-A SNCG EIF4A1 MMP3 HLA-B C10orf116 EIF4EBP2 MMP12 HLA-DQA1 PTENP1 EPCAM CASP1 HLF FAS EPHA1 NNMT HLTF RBP4 EPHX2 APOA1 HNRNPU CYP2C9 ETFA HSPA8 HSDL2 CYP2C8 FBN1 NP_689935.1 HSP90AA1 SCD FDPS NP_001032647.1 ID2 TCF7L2 FETUB FKBP4 IDH1 HABP2 FGFR2 CD9 IFI16 ACADSB FMO3 727728 IGHA1 OAT FYN CD163 IL6R MKI67 GATA6 A2M IL8 MGMT GATM CLEC1B INSIG1 ECHS1 GCH1 CSDA IQGAP1 Table SII.
Recommended publications
  • PARSANA-DISSERTATION-2020.Pdf
    DECIPHERING TRANSCRIPTIONAL PATTERNS OF GENE REGULATION: A COMPUTATIONAL APPROACH by Princy Parsana A dissertation submitted to The Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland July, 2020 © 2020 Princy Parsana All rights reserved Abstract With rapid advancements in sequencing technology, we now have the ability to sequence the entire human genome, and to quantify expression of tens of thousands of genes from hundreds of individuals. This provides an extraordinary opportunity to learn phenotype relevant genomic patterns that can improve our understanding of molecular and cellular processes underlying a trait. The high dimensional nature of genomic data presents a range of computational and statistical challenges. This dissertation presents a compilation of projects that were driven by the motivation to efficiently capture gene regulatory patterns in the human transcriptome, while addressing statistical and computational challenges that accompany this data. We attempt to address two major difficulties in this domain: a) artifacts and noise in transcriptomic data, andb) limited statistical power. First, we present our work on investigating the effect of artifactual variation in gene expression data and its impact on trans-eQTL discovery. Here we performed an in-depth analysis of diverse pre-recorded covariates and latent confounders to understand their contribution to heterogeneity in gene expression measurements. Next, we discovered 673 trans-eQTLs across 16 human tissues using v6 data from the Genotype Tissue Expression (GTEx) project. Finally, we characterized two trait-associated trans-eQTLs; one in Skeletal Muscle and another in Thyroid. Second, we present a principal component based residualization method to correct gene expression measurements prior to reconstruction of co-expression networks.
    [Show full text]
  • Small Cell Ovarian Carcinoma: Genomic Stability and Responsiveness to Therapeutics
    Gamwell et al. Orphanet Journal of Rare Diseases 2013, 8:33 http://www.ojrd.com/content/8/1/33 RESEARCH Open Access Small cell ovarian carcinoma: genomic stability and responsiveness to therapeutics Lisa F Gamwell1,2, Karen Gambaro3, Maria Merziotis2, Colleen Crane2, Suzanna L Arcand4, Valerie Bourada1,2, Christopher Davis2, Jeremy A Squire6, David G Huntsman7,8, Patricia N Tonin3,4,5 and Barbara C Vanderhyden1,2* Abstract Background: The biology of small cell ovarian carcinoma of the hypercalcemic type (SCCOHT), which is a rare and aggressive form of ovarian cancer, is poorly understood. Tumourigenicity, in vitro growth characteristics, genetic and genomic anomalies, and sensitivity to standard and novel chemotherapeutic treatments were investigated in the unique SCCOHT cell line, BIN-67, to provide further insight in the biology of this rare type of ovarian cancer. Method: The tumourigenic potential of BIN-67 cells was determined and the tumours formed in a xenograft model was compared to human SCCOHT. DNA sequencing, spectral karyotyping and high density SNP array analysis was performed. The sensitivity of the BIN-67 cells to standard chemotherapeutic agents and to vesicular stomatitis virus (VSV) and the JX-594 vaccinia virus was tested. Results: BIN-67 cells were capable of forming spheroids in hanging drop cultures. When xenografted into immunodeficient mice, BIN-67 cells developed into tumours that reflected the hypercalcemia and histology of human SCCOHT, notably intense expression of WT-1 and vimentin, and lack of expression of inhibin. Somatic mutations in TP53 and the most common activating mutations in KRAS and BRAF were not found in BIN-67 cells by DNA sequencing.
    [Show full text]
  • Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse
    Welcome to More Choice CD Marker Handbook For more information, please visit: Human bdbiosciences.com/eu/go/humancdmarkers Mouse bdbiosciences.com/eu/go/mousecdmarkers Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse CD3 CD3 CD (cluster of differentiation) molecules are cell surface markers T Cell CD4 CD4 useful for the identification and characterization of leukocytes. The CD CD8 CD8 nomenclature was developed and is maintained through the HLDA (Human Leukocyte Differentiation Antigens) workshop started in 1982. CD45R/B220 CD19 CD19 The goal is to provide standardization of monoclonal antibodies to B Cell CD20 CD22 (B cell activation marker) human antigens across laboratories. To characterize or “workshop” the antibodies, multiple laboratories carry out blind analyses of antibodies. These results independently validate antibody specificity. CD11c CD11c Dendritic Cell CD123 CD123 While the CD nomenclature has been developed for use with human antigens, it is applied to corresponding mouse antigens as well as antigens from other species. However, the mouse and other species NK Cell CD56 CD335 (NKp46) antibodies are not tested by HLDA. Human CD markers were reviewed by the HLDA. New CD markers Stem Cell/ CD34 CD34 were established at the HLDA9 meeting held in Barcelona in 2010. For Precursor hematopoetic stem cell only hematopoetic stem cell only additional information and CD markers please visit www.hcdm.org. Macrophage/ CD14 CD11b/ Mac-1 Monocyte CD33 Ly-71 (F4/80) CD66b Granulocyte CD66b Gr-1/Ly6G Ly6C CD41 CD41 CD61 (Integrin b3) CD61 Platelet CD9 CD62 CD62P (activated platelets) CD235a CD235a Erythrocyte Ter-119 CD146 MECA-32 CD106 CD146 Endothelial Cell CD31 CD62E (activated endothelial cells) Epithelial Cell CD236 CD326 (EPCAM1) For Research Use Only.
    [Show full text]
  • Viewed Under 23 (B) Or 203 (C) fi M M Male Cko Mice, and Largely Unaffected Magni Cation; Scale Bars, 500 M (B) and 50 M (C)
    BRIEF COMMUNICATION www.jasn.org Renal Fanconi Syndrome and Hypophosphatemic Rickets in the Absence of Xenotropic and Polytropic Retroviral Receptor in the Nephron Camille Ansermet,* Matthias B. Moor,* Gabriel Centeno,* Muriel Auberson,* † † ‡ Dorothy Zhang Hu, Roland Baron, Svetlana Nikolaeva,* Barbara Haenzi,* | Natalya Katanaeva,* Ivan Gautschi,* Vladimir Katanaev,*§ Samuel Rotman, Robert Koesters,¶ †† Laurent Schild,* Sylvain Pradervand,** Olivier Bonny,* and Dmitri Firsov* BRIEF COMMUNICATION *Department of Pharmacology and Toxicology and **Genomic Technologies Facility, University of Lausanne, Lausanne, Switzerland; †Department of Oral Medicine, Infection, and Immunity, Harvard School of Dental Medicine, Boston, Massachusetts; ‡Institute of Evolutionary Physiology and Biochemistry, St. Petersburg, Russia; §School of Biomedicine, Far Eastern Federal University, Vladivostok, Russia; |Services of Pathology and ††Nephrology, Department of Medicine, University Hospital of Lausanne, Lausanne, Switzerland; and ¶Université Pierre et Marie Curie, Paris, France ABSTRACT Tight control of extracellular and intracellular inorganic phosphate (Pi) levels is crit- leaves.4 Most recently, Legati et al. have ical to most biochemical and physiologic processes. Urinary Pi is freely filtered at the shown an association between genetic kidney glomerulus and is reabsorbed in the renal tubule by the action of the apical polymorphisms in Xpr1 and primary fa- sodium-dependent phosphate transporters, NaPi-IIa/NaPi-IIc/Pit2. However, the milial brain calcification disorder.5 How- molecular identity of the protein(s) participating in the basolateral Pi efflux remains ever, the role of XPR1 in the maintenance unknown. Evidence has suggested that xenotropic and polytropic retroviral recep- of Pi homeostasis remains unknown. Here, tor 1 (XPR1) might be involved in this process. Here, we show that conditional in- we addressed this issue in mice deficient for activation of Xpr1 in the renal tubule in mice resulted in impaired renal Pi Xpr1 in the nephron.
    [Show full text]
  • Differential Physiological Role of BIN1 Isoforms in Skeletal Muscle Development, Function and Regeneration
    bioRxiv preprint doi: https://doi.org/10.1101/477950; this version posted December 11, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Differential physiological role of BIN1 isoforms in skeletal muscle development, function and regeneration Ivana Prokic1,2,3,4, Belinda Cowling1,2,3,4, Candice Kutchukian5, Christine Kretz1,2,3,4, Hichem Tasfaout1,2,3,4, Josiane Hergueux1,2,3,4, Olivia Wendling1,2,3,4, Arnaud Ferry10, Anne Toussaint1,2,3,4, Christos Gavriilidis1,2,3,4, Vasugi Nattarayan1,2,3,4, Catherine Koch1,2,3,4, Jeanne Lainné6,7, Roy Combe2,3,4,8, Laurent Tiret9, Vincent Jacquemond5, Fanny Pilot-Storck9, Jocelyn Laporte1,2,3,4 1Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Illkirch, France 2Centre National de la Recherche Scientifique (CNRS), UMR7104, Illkirch, France 3Institut National de la Santé et de la Recherche Médicale (INSERM), U1258, Illkirch, France 4Université de Strasbourg, Illkirch, France 5Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR-5310, INSERM U-1217, Institut NeuroMyoGène, 8 avenue Rockefeller, 69373 Lyon, France 6Sorbonne Université, INSERM, Institute of Myology, Centre of Research in Myology, UMRS 974, F- 75013, Paris, France 7Sorbonne Université, Department of Physiology, UPMC Univ Paris 06, Pitié-Salpêtrière Hospital, F- 75013, Paris, France 8CELPHEDIA-PHENOMIN, Institut Clinique de la Souris (ICS), Illkirch, France 9U955 – IMRB, Team 10 - Biology of the neuromuscular system, Inserm, UPEC, Ecole nationale vétérinaire d’Alfort, Maisons-Alfort, 94700, France 10Sorbonne Université, INSERM, Institute of Myology, Centre of Research in Myology, UMRS 794, F- 75013, Paris, France Correspondence to: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/477950; this version posted December 11, 2018.
    [Show full text]
  • Roles of the CSE1L-Mediated Nuclear Import Pathway in Epigenetic
    Roles of the CSE1L-mediated nuclear import pathway PNAS PLUS in epigenetic silencing Qiang Donga,b,c, Xiang Lia,b,c, Cheng-Zhi Wangb, Shaohua Xuc, Gang Yuanc, Wei Shaoc, Baodong Liud, Yong Zhengb, Hailin Wangd, Xiaoguang Leic,e,f, Zhuqiang Zhangb,1, and Bing Zhua,b,g,1 aGraduate Program, Peking Union Medical College and Chinese Academy of Medical Sciences, 100730 Beijing, China; bNational Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101 Beijing, China; cNational Institute of Biological Sciences, 102206 Beijing, China; dThe State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, 100085 Beijing, China; eBeijing National Laboratory for Molecular Sciences, Department of Chemical Biology, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China; fPeking-Tsinghua Center for Life Sciences, Peking University, 100871 Beijing, China; and gCollege of Life Sciences, University of Chinese Academy of Sciences, 100049 Beijing, China Edited by Arthur D. Riggs, Beckman Research Institute of City of Hope, Duarte, CA, and approved March 21, 2018 (received for review January 17, 2018) Epigenetic silencing can be mediated by various mechanisms, CSE1L, a key player in the nuclear import pathway, as an es- and many regulators remain to be identified. Here, we report a sential factor for maintaining the repression of many methyl- genome-wide siRNA screening to identify regulators essential for ated genes. Mechanistically, CSE1L functions by facilitating maintaining gene repression of a CMV promoter silenced by DNA the nuclear import of certain cargo proteins that are essential methylation.
    [Show full text]
  • Datasheet PB1029 Anti-AEBP2 Antibody
    Product datasheet Anti-AEBP2 Antibody Catalog Number: PB1029 BOSTER BIOLOGICAL TECHNOLOGY Special NO.1, International Enterprise Center, 2nd Guanshan Road, Wuhan, China Web: www.boster.com.cn Phone: +86 27 67845390 Fax: +86 27 67845390 Email: [email protected] Basic Information Product Name Anti-AEBP2 Antibody Gene Name AEBP2 Source Rabbit IgG Species Reactivity human,mouse,rat Tested Application WB,IHC-P,ICC/IF,FCM Contents 500ug/ml antibody with PBS ,0.02% NaN3 , 1mg BSA and 50% glycerol. Immunogen E.coli-derived human AEBP2 recombinant protein (Position: K424-Q517). Human AEBP2 shares 98.8% amino acid (aa) sequence identity with mouse AEBP2. Purification Immunogen affinity purified. Observed MW 54KD Dilution Ratios Western blot: 1:500-2000 Immunohistochemistry(Paraffin-embedded Section): 1:50-400 Immunocytochemistry/Immunofluorescence (ICC/IF): 1:50-400 Flow cytometry (FCM): 1-3μg/1x106 cells Storage 12 months from date of receipt,-20℃ as supplied.6 months 2 to 8℃ after reconstitution. Avoid repeated freezing and thawing Background Information Adipocyte Enhancer-Binding Protein is a zinc finger protein that in humans is encoded by the evolutionarily well-conserved gene AEBP2. This gene is mapped to 12p12.3. AEBP2 is a DNA-binding transcriptional repressor. It may regulate the migration and development of the neural crest cells through the PRC2-mediated epigenetic mechanism and is most likely a targeting protein for the mammalian PRC2 complex. Reference Anti-AEBP2 Antibody被引用在0文献中。 暂无引用 FOR RESEARCH USE ONLY. NOT FOR DIAGNOSTIC AND CLINICAL USE. 1 Product datasheet Anti-AEBP2 Antibody Catalog Number: PB1029 BOSTER BIOLOGICAL TECHNOLOGY Special NO.1, International Enterprise Center, 2nd Guanshan Road, Wuhan, China Web: www.boster.com.cn Phone: +86 27 67845390 Fax: +86 27 67845390 Email: [email protected] Selected Validation Data Figure 1.
    [Show full text]
  • Nucleotide Sequence and Analysis of the 58.3 to 65.5-Kb Early Region of Bacteriophage T4
    Volume 14 Number 21 1986 Nucleic Acids Research Nucleotide sequence and analysis of the 58.3 to 65.5-kb early region of bacteriophage T4 Kristoffer Valerie 13.4, John Stevens', Mark Lynch'5, Earl E.Henderson12 and Jon K.de Riel1 'Fels Research Institute, and 2Department of Microbiology and Immunology, Temple University School of Medicine, Philadelphia, PA 19140, USA and 3Department of Biochemistry and Biotechnology, Royal Institute of Technology, S-100 44 Stockholm, Sweden Received 21 July 1986; Revised and Accepted 30 September 1986 ABSTRACT The complete 7.2-kb nucleotide sequence from the 58.3 to 65.5-kb early region of bacteriophage T4 has been determined by Maxam and Gilbert sequencing. Computer analysis revealed at least 20 open reading frames (ORFs) within this sequence. All major ORFs are transcribed from the left strand, suggesting that they are expressed early during infection. Among the ORFs, we have identified the pIIII, II, denV and tk genes. The ORFs are very tightly spaced, even over Lapping in some instances, and when ORF interspacing occurs, promoter-like sequences can be implicated. Several of the sequences preceding the ORFs, in particular those at ipIII, ipII, denV, and orf6l.9, can potentially form stable stem-loop structures. INTRODUCTION Recently, considerable progress has been made studying the bacteriophage T4 genome at the molecular level due to the development of T4 strains with unmod- ified DNA suitable for digestion with restriction endonucleases (1). Many T4 genes have since been cloned, sequenced, and their gene products overproduced in Escherichia coli (for review see ref. 2). A majority of the T4 genes studied so far have been essential and non-essential genes with well-characterized pheno- types.
    [Show full text]
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
    [Show full text]
  • Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
    Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7
    [Show full text]
  • Murine Megakaryopoiesis Is Critical for P21 SCL-Mediated Regulation Of
    From bloodjournal.hematologylibrary.org at UNIVERSITY OF BIRMINGHAM on March 1, 2012. For personal use only. 2011 118: 723-735 Prepublished online May 19, 2011; doi:10.1182/blood-2011-01-328765 SCL-mediated regulation of the cell-cycle regulator p21 is critical for murine megakaryopoiesis Hedia Chagraoui, Mira Kassouf, Sreemoti Banerjee, Nicolas Goardon, Kevin Clark, Ann Atzberger, Andrew C. Pearce, Radek C. Skoda, David J. P. Ferguson, Steve P. Watson, Paresh Vyas and Catherine Porcher Updated information and services can be found at: http://bloodjournal.hematologylibrary.org/content/118/3/723.full.html Articles on similar topics can be found in the following Blood collections Platelets and Thrombopoiesis (260 articles) Information about reproducing this article in parts or in its entirety may be found online at: http://bloodjournal.hematologylibrary.org/site/misc/rights.xhtml#repub_requests Information about ordering reprints may be found online at: http://bloodjournal.hematologylibrary.org/site/misc/rights.xhtml#reprints Information about subscriptions and ASH membership may be found online at: http://bloodjournal.hematologylibrary.org/site/subscriptions/index.xhtml Blood (print ISSN 0006-4971, online ISSN 1528-0020), is published weekly by the American Society of Hematology, 2021 L St, NW, Suite 900, Washington DC 20036. Copyright 2011 by The American Society of Hematology; all rights reserved. From bloodjournal.hematologylibrary.org at UNIVERSITY OF BIRMINGHAM on March 1, 2012. For personal use only. PLATELETS AND THROMBOPOIESIS SCL-mediated regulation of the cell-cycle regulator p21 is critical for murine megakaryopoiesis Hedia Chagraoui,1 *Mira Kassouf,1 *Sreemoti Banerjee,1 Nicolas Goardon,1 Kevin Clark,1 Ann Atzberger,1 Andrew C.
    [Show full text]
  • Genomic Aberrations Associated with Erlotinib Resistance in Non-Small Cell Lung Cancer Cells
    ANTICANCER RESEARCH 33: 5223-5234 (2013) Genomic Aberrations Associated with Erlotinib Resistance in Non-small Cell Lung Cancer Cells MASAKUNI SERIZAWA1, TOSHIAKI TAKAHASHI2, NOBUYUKI YAMAMOTO2,3 and YASUHIRO KOH1 1Drug Discovery and Development Division, Shizuoka Cancer Center Research Institute, Sunto-gun, Shizuoka, Japan; 2Division of Thoracic Oncology, Shizuoka Cancer Center Hospital, Sunto-gun, Shizuoka, Japan; 3Third Department of Internal Medicine, Wakayama Medical University, Kimiidera, Wakayama, Japan Abstract. Background/Aim: Mechanisms of resistance to mutations develop resistance, usually within one year of epidermal growth factor receptor (EGFR)-tyrosine kinase treatment. Therefore, there is an urgent need to elucidate the inhibitors (TKIs) in non-small cell lung cancer (NSCLC) underlying mechanisms of resistance in such tumors to are not fully-understood. In this study we aimed to overcome this obstacle (11-14, 17, 24). Recent studies elucidate remaining unknown mechanisms using erlotinib- suggest that mechanisms of acquired resistance to EGFR- resistant NSCLC cells. Materials and Methods: We TKIs can be categorized into three groups: occurrence of performed array comparative genomic hybridization genetic alterations, activation of downstream pathways via (aCGH) to identify genomic aberrations associated with bypass signaling, and phenotypic transformation (15, 16, 21); EGFR-TKI resistance in erlotinib-resistant PC-9ER cells. therapeutic strategies to overcome these resistance Real-time polymerase chain reaction (PCR) and mechanisms are under development. However, although the immunoblot analyses were performed to confirm the results causes of acquired resistance to EGFR-TKIs have been of aCGH. Results: Among the five regions with copy investigated, in more than 30% of patients with acquired number gain detected in PC-9ER cells, we focused on resistance to EGFR-TKI treatment, the mechanisms remain 22q11.2-q12.1 including v-crk avian sarcoma virus CT10 unknown (15).
    [Show full text]