DOCSLIB.ORG

Supplemental Table 1 and Supplemental Figures 1-3 (PDF

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Supplemental Table 1 and Supplemental Figures 1-3 (PDF A 25000 * * * 20000 15000 * 10000 ns 5000 Nb CD38hi cells /ml cells Nb CD38hi 0 none 0.05 0.5 5 50 500 IL-2 (U/ml) B D0 D1 D2 D3 D4 CD25 CD122 CD132 C IL2RA IL2RB IL2RG / Day Day 0 / mRNA expression mRNA D ** Relative number Relative cells of CD38hi Supplemental Figure 1: IL-2 cytokine and receptor analysis A) Dose-response assay of IL-2 cytokine and generation of absolute number of CD38hi plasmablasts per mL. (*; p<0.05). B) Specific IL-2 receptor chain expression onto NBCs get in our differentiation model at different time points; one representative experiment among 3 distinct. Grey histogram, isotype Ig; red histogram, without IL-2; blue histogram, with IL-2. C) mRNA expression of IL2 receptor chains on B cells cultured with (bold line) or without (dotted line) IL2. D) IL-4 and IL-2 effect during the differentiation phase (step 2) on plasmablast generation (N=4). Supplemental Table 1 Genelist GL2: Genelist GL3 (see also footnotes): 112 single genes (113 probes) differentially 86 single genes differentially expressed with expressed with a FC>= 1.2, at D0+22h a FC>= 1.2, at D4 between CSFElo IL2+ & CSFElo IL2- cells between IL2+ & IL2- FC: D0+22h,CFSElo, IL2+ / FC: D4-CFSElo, IL2+ / D0+22h,CFSElo, IL2- Column ID TargetID p-value eanFC (Day0+22h IL2+/Day0+22h IL Probe ID TargetID p-value CSFEloD4-CFSElo, IL2+/D4 IL2- 4480288 0.0294072 ISG20L1 1.49017 2370010 GZMH 0.0204272 5.98886 1440564 0.0475587 RUNX3 1.43492 1570348 0.0468738 4.43831 4730181 FTHL12 0.0308831 1.40699 CCND2 450468 MRPL44 0.0243757 1.40195 130021 IL2RA 0.0226678 3.3176 2970431 FTHL7 0.0252716 1.38331 1440440 MAPKAPK3 0.0202046 3.25386 4040360 ZNF483 0.0342887 1.3385 6770673 SOCS2 0.0356731 3.23171 5820681 0.0183986 PBX2 1.334 7320288 0.0279072 3.12019 4200450 G6PD 0.00534329 1.33282 CXCR4 2850433 SPSB3 0.0259232 1.33237 4850301 PTRF 0.00639325 3.11387 4760538 ZC3H3 0.0334508 1.32721 5220093 HAVCR2 0.0216012 2.91303 990358 LIMS1 0.0492346 1.32021 1030743 LTA 0.0126373 2.78672 6940202 R3HCC1 0.00288754 1.3199 270152 SLC7A5 0.048731 2.63811 2350209 YY1AP1 0.0125286 1.3135 4540328 RNF220 0.0025394 1.31002 1570484 ATF5 0.0101804 2.39129 5080482 TNPO1 0.0199022 1.30242 2490537 TNFRSF1B 0.0335157 2.20538 840544 RBM4 0.0151596 1.29834 830735 CENTA1 0.0202725 2.14856 1850047 FAM189B 0.00259803 1.289 240086 PHGDH 0.000875239 2.08106 4730739 RPS6KA1 0.0202923 1.28839 540681 S100A10 0.0179661 1.28722 1780273 ALOX5 0.0133416 1.85219 2320356 VASP 0.00140197 1.28672 2480326 HSP90B1 0.0499817 1.81744 770524 EEF1D 0.0164436 1.28622 2350538 RPS6KB2 0.00566355 1.80156 430669 0.04192 SPTLC1 1.28544 6660382 CDKN1A 0.0256676 1.7336 5890528 PPIAL4A 0.00544786 1.28255 2690561 RPLP1 0.0393095 1.2822 2230288 TST 0.0356684 1.59279 1980594 FTHL8 0.0378127 1.28027 610148 GSDMD 0.00314109 1.58116 4640435 CHD4 0.0230079 1.27476 4590494 YIF1A 0.0453352 1.57629 2810669 0.00929455 LCMT1 1.27365 5670180 TUBG1 0.0416095 1.55224 6270037 RAPGEF1 0.0130052 1.27149 6180465 0.0350301 1.53675 3800487 ZNFX1 0.00547642 1.27073 SLC2A6 3180273 PDXP 0.0315421 1.26625 1770717 HIRIP3 0.0351694 1.52434 840358 EXOSC10 0.0481548 1.26238 5130577 SLC37A4 0.0251123 1.51691 6110609 0.036946 FAM39DP 1.26222 1230187 CSNK1E 0.0109496 1.50001 5670037 MUTYH 0.0113059 1.26067 6220070 0.0179373 1.49735 3370300 CCBE1 0.0419224 1.26066 NT5C 6980156 CIAO1 0.042332 1.25733 6380370 CCND3 0.0130323 1.49312 840551 CEP27 0.0370393 1.25726 6110605 KRTCAP2 0.0277168 1.49269 60148 0.0102241 BOLA2 1.25643 2630433 CDT1 0.0187117 1.48358 3390092 0.0131578 PLEKHM2 1.2556 3890681 0.040688 1.47306 2630102 CCDC28B 0.0298375 1.25383 SLC41A3 730647 ANAPC1 0.022605 1.25373 6660270 MRPL17 0.00927692 1.4673 5310768 PAF1 0.0284634 1.2529 1500010 CDC20 0.00629866 1.46224 6380128 0.0332148 CLTA 1.25235 1990630 TRIB3 0.0410713 1.45917 3310463 0.0414889 ARHGAP15 1.25121 270736 0.040309 1.45886 2970563 RPRC1 0.00529062 1.25098 TRABD 2490730 SF4 0.0294099 1.24975 5560131 ATOX1 0.0285416 1.44303 360445 ITPA 0.0108141 1.24959 1570523 ASCC2 0.0202116 1.44225 1980301 FKTN 0.0281427 1.2488 7570711 PRR14 0.0177223 1.43536 1820722 0.0199047 APBB1IP 1.2485 1010364 0.0343938 1.42862 2470259 FBXO18 0.0246597 1.24829 DGCR6 830047 GSTP1 0.017282 1.24804 7650315 JMJD8 0.0219739 1.40776 6110035 DDX42 0.00630556 1.24799 290603 AARS 0.0227463 1.39028 6940255 PLSCR3 0.0358544 1.24544 150692 SLC26A6 0.0302638 1.38309 2100576 0.0107691 ARAF 1.24488 1850047 0.0141194 1.37806 4290196 SCRIB 0.00135044 1.24423 FAM189B 4860224 WARS 0.0129734 1.24315 4150670 CDC37 0.0256873 1.37475 3830273 NIT2 0.0243849 1.24278 6280360 SPG7 0.0110889 1.36593 6960037 EDC4 0.0469187 1.24245 6770343 ETFB 0.023446 1.36212 7210634 ZBED5 0.0405135 1.24222 60437 PLOD1 0.00983202 1.35372 4670487 SIVA 0.036272 1.24114 3990215 RPL3 0.0307856 1.24095 2030148 WDR54 0.0458358 1.35356 4290014 FLAD1 0.0237271 1.24047 2470367 INPPL1 0.0201836 1.35167 4220180 WDR68 0.0457381 1.24013 7400554 WDR18 0.0101739 1.34564 6590201 ATP6AP1 0.00889757 1.23976 1110072 PEX16 0.0262879 1.3348 3360681 TNFAIP3 0.0223769 1.23917 1300315 MRPL21 0.0299255 1.23773 3190274 LLPH 0.0125215 1.33399 380369 TRRAP 0.00784854 1.23392 5220347 BCKDK 0.0426319 1.32986 7200452 BCL2L13 0.0420196 1.23372 2350504 ECGF1 0.0462949 1.32689 3830538 0.013753 CCDC130 1.23144 3130349 CPSF1 0.0294645 1.32429 1090646 FAM119A 0.0378484 1.23114 4250372 KLHDC3 0.0426002 1.23006 2100576 ARAF 0.0225422 1.32083 6420180 TJAP1 0.0381346 1.22969 3140438 GRAMD1A 0.0390934 1.31935 360747 COASY 0.030792 1.22909 6370068 GNL1 0.0482471 1.31229 5090068 0.0331492 STX5 1.22901 2070170 UBE2L6 0.00609296 1.31117 1340689 RPN1 0.0158027 1.22896 5910128 0.015784 1.31064 650564 CCDC125 0.011742 1.22828 VAMP8 6620356 ARPP19 0.00216779 1.22806 5690228 CDK5RAP2 0.00900298 1.31049 2940451 RAB9A 0.0344138 1.2275 6860131 HNRNPUL2 0.0386839 1.30206 4540475 0.0223216 FABP5L2 1.22713 1230747 SF3A3 0.0423418 1.30188 3370274 ANKRD11 0.0339847 1.22594 1470315 0.0446092 1.28611 2650477 TRAF4 0.0189341 1.2247 PIAS4 2900594 PGD 0.0075781 1.22379 1340047 PHRF1 0.0384334 1.27307 4480162 SND1 0.0231838 1.22371 6380431 RXRB 0.0221392 1.26538 4560110 0.0137226 ARMET 1.22359 4900079 UIMC1 0.0209351 1.26418 4250753 0.00742646 TSPAN33 1.22327 3190288 0.0243864 1.26004 1170164 RPL35 0.00694207 1.22259 LYL1 20491 UBE2F 0.016096 1.22146 6110477 NUDC 0.0464155 1.25128 1300491 POLE3 0.00963564 1.21955 2510411 SLC44A4 0.0326771 1.24338 2140630 0.0236988 GLE1 1.21828 6040609 PNPT1 0.017573 1.24304 6100768 0.0221077 CYFIP2 1.21639 4730086 0.014989 1.23727 2680100 TNIP1 0.00318681 1.21623 SHCBP1 1570523 ASCC2 0.0132371 1.21608 5870452 TMEM14C 0.0260779 1.23318 6110392 GNS 0.0137419 1.21593 6900424 TYK2 0.0283992 1.23263 1410079 CDC26 0.0128702 1.21591 2450093 VCP 0.0230563 1.22859 3890300 0.0206457 PRR13 1.21453 6590661 0.025803 1.22613 5310068 NUP93 0.0318226 1.21434 MED22 4150142 SUCLG1 0.0209793 1.21322 510079 HLA-DRB4 0.0197213 -1.20783 6770242 MARCKSL1 0.00461462 1.21131 2260349 MIR1974 0.025226 -1.25214 5860162 ATP5J 0.0267964 1.21046 3710647 MXD4 0.045236 -1.26273 6660382 0.0233915 CDKN1A 1.20948 5050577 0.0255899 -1.39602 1440440 MAPKAPK3 0.0297581 1.20836 PNPLA7 4390288 TH1L 0.0327688 1.20821 5820768 DEF8 0.0499232 -1.48543 6250280 PRDX1 0.0229894 1.208 4200546 CD72 0.0410273 -1.60731 6270241 TPD52L2 0.0332761 1.20753 1820681 DPEP2 0.0271145 -1.69384 620240 ABR 0.00251076 1.20708 6620026 CD83 0.029319 -1.80214 7210224 DYNLRB1 0.0490815 1.20593 2030730 UBE2I 0.0295814 1.2054 7210192 ADA 0.0411682 -1.82966 1240593 CFLAR 0.0226573 1.20537 6180228 FCRL3 0.0477405 -1.84431 620376 PPP1R11 0.0299983 1.20421 2060082 MRPS10 0.00843868 1.20364 3850053 ANP32B 0.0203647 1.20231 6250017 TH1L 0.0134835 1.20132 5420592 SRC 0.0236376 1.20127 4570136 NHP2 0.0393187 1.20083 Supplemental Table 1 (Footnotes Right Panel) Upregulated genes by IL-2: GZMH 1, MAPKAPK3 2, SOCS2 3, TYK2 4, ATF5 5 ,IL-2RA and LTA, plus TNFRSF1B regulated by both, IL-2 & LTA 3,6 1. Boyman O, Purton JF, Surh CD, Sprent J. Cytokines and T-cell homeostasis. Curr Opin Immunol. 2007;19:320-326. 2. Kovanen PE, Rosenwald A, Fu J, et al. Analysis of gamma c-family cytokine target genes. Identification of dual-specificity phosphatase 5 (DUSP5) as a regulator of mitogen-activated protein kinase activity in interleukin-2 signaling. J Biol Chem. 2003;278:5205-5213. 3. Marzec M, Halasa K, Kasprzycka M, et al. Differential effects of interleukin-2 and interleukin-15 versus interleukin-21 on CD4+ cutaneous T-cell lymphoma cells. Cancer Res. 2008;68:1083-1091. 4. Eckenberg R, Rose T, Moreau JL, et al. The first alpha helix of interleukin (IL)-2 folds as a homotetramer, acts as an agonist of the IL-2 receptor beta chain, and induces lymphokine- activated killer cells.
Load more

Recommended publications
  • 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]
  • Receptor-Mediated Mitophagy Accepted21march2016
    King’s Research Portal DOI: 10.1016/j.yjmcc.2016.03.010 Document Version Peer reviewed version Link to publication record in King's Research Portal Citation for published version (APA): Yamaguchi, O., Murakawa, T., Nishida, K., & Otsu, K. (2016). Receptor-mediated mitophagy. Journal of Molecular and Cellular Cardiology, 95, 50-56. [95]. https://doi.org/10.1016/j.yjmcc.2016.03.010 Citing this paper Please note that where the full-text provided on King's Research Portal is the Author Accepted Manuscript or Post-Print version this may differ from the final Published version. If citing, it is advised that you check and use the publisher's definitive version for pagination, volume/issue, and date of publication details. And where the final published version is provided on the Research Portal, if citing you are again advised to check the publisher's website for any subsequent corrections. General rights Copyright and moral rights for the publications made accessible in the Research Portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognize and abide by the legal requirements associated with these rights. •Users may download and print one copy of any publication from the Research Portal for the purpose of private study or research. •You may not further distribute the material or use it for any profit-making activity or commercial gain •You may freely distribute the URL identifying the publication in the Research Portal Take down policy If you believe that this document breaches copyright please contact [email protected] providing details, and we will remove access to the work immediately and investigate your claim.
    [Show full text]
  • Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
    Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase
    [Show full text]
  • Supplementary Material DNA Methylation in Inflammatory Pathways Modifies the Association Between BMI and Adult-Onset Non- Atopic
    Supplementary Material DNA Methylation in Inflammatory Pathways Modifies the Association between BMI and Adult-Onset Non- Atopic Asthma Ayoung Jeong 1,2, Medea Imboden 1,2, Akram Ghantous 3, Alexei Novoloaca 3, Anne-Elie Carsin 4,5,6, Manolis Kogevinas 4,5,6, Christian Schindler 1,2, Gianfranco Lovison 7, Zdenko Herceg 3, Cyrille Cuenin 3, Roel Vermeulen 8, Deborah Jarvis 9, André F. S. Amaral 9, Florian Kronenberg 10, Paolo Vineis 11,12 and Nicole Probst-Hensch 1,2,* 1 Swiss Tropical and Public Health Institute, 4051 Basel, Switzerland; [email protected] (A.J.); [email protected] (M.I.); [email protected] (C.S.) 2 Department of Public Health, University of Basel, 4001 Basel, Switzerland 3 International Agency for Research on Cancer, 69372 Lyon, France; [email protected] (A.G.); [email protected] (A.N.); [email protected] (Z.H.); [email protected] (C.C.) 4 ISGlobal, Barcelona Institute for Global Health, 08003 Barcelona, Spain; [email protected] (A.-E.C.); [email protected] (M.K.) 5 Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain 6 CIBER Epidemiología y Salud Pública (CIBERESP), 08005 Barcelona, Spain 7 Department of Economics, Business and Statistics, University of Palermo, 90128 Palermo, Italy; [email protected] 8 Environmental Epidemiology Division, Utrecht University, Institute for Risk Assessment Sciences, 3584CM Utrecht, Netherlands; [email protected] 9 Population Health and Occupational Disease, National Heart and Lung Institute, Imperial College, SW3 6LR London, UK; [email protected] (D.J.); [email protected] (A.F.S.A.) 10 Division of Genetic Epidemiology, Medical University of Innsbruck, 6020 Innsbruck, Austria; [email protected] 11 MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, W2 1PG London, UK; [email protected] 12 Italian Institute for Genomic Medicine (IIGM), 10126 Turin, Italy * Correspondence: [email protected]; Tel.: +41-61-284-8378 Int.
    [Show full text]
  • Supplementary Material and Methods
    Supplementary material and methods Generation of cultured human epidermal sheets Normal human epidermal keratinocytes were isolated from human breast skin. Keratinocytes were grown on a feeder layer of irradiated human fibroblasts pre-seeded at 4000 cells /cm² in keratinocyte culture medium (KCM) containing a mix of 3:1 DMEM and HAM’s F12 (Invitrogen, Carlsbad, USA), supplemented with 10% FCS, 10ng/ml epidermal growth factor (EGF; R&D systems, Minneapolis, MN, USA), 0.12 IU/ml insulin (Lilly, Saint- Cloud, France), 0.4 mg/ml hydrocortisone (UpJohn, St Quentin en Yvelelines, France) , 5 mg/ml triiodo-L- thyronine (Sigma, St Quentin Fallavier, France), 24.3 mg/ml adenine (Sigma), isoproterenol (Isuprel, Hospira France, Meudon, France) and antibiotics (20 mg/ml gentamicin (Phanpharma, Fougères, France), 100 IU/ml penicillin (Phanpharma), and 1 mg/ml amphotericin B (Phanpharma)). The medium was changed every two days. NHEK were then cultured over a period of 13 days according to the protocol currently used at the Bank of Tissues and Cells for the generation of clinical grade epidermal sheets used for the treatment of severe extended burns (Ref). When needed, cells were harvested with trypsin-EDTA 0.05% (Thermo Fisher Scientific, Waltham, MA, USA) and collected for analysis. Clonogenic assay Keratinocytes were seeded on a feeder layer of irradiated fibroblasts, at a clonal density of 10-20 cells/cm² and cultivated for 10 to 14 days. Three flasks per tested condition were fixed and colored in a single 30 mns step using rhodamine B (Sigma) diluted at 0.01 g/ml in 4% paraformaldehyde. In each tested condition, cells from 3 other flasks were numerated after detachment by trypsin treatment.
    [Show full text]
  • Alterations of the Interactome of Bcl-2 Proteins in Breast Cancer at the Transcriptional, Mutational and Structural Level
    RESEARCH ARTICLE Alterations of the interactome of Bcl-2 proteins in breast cancer at the transcriptional, mutational and structural level Simon Mathis Kønig1, Vendela Rissler1, Thilde Terkelsen1, Matteo Lambrughi1, 1,2 Elena PapaleoID * 1 Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark, a1111111111 2 Translational Disease Systems Biology, Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Protein Research University of Copenhagen, Copenhagen, Denmark a1111111111 a1111111111 * [email protected] a1111111111 a1111111111 Abstract Apoptosis is an essential defensive mechanism against tumorigenesis. Proteins of the B- OPEN ACCESS cell lymphoma-2 (Bcl-2) family regulate programmed cell death by the mitochondrial apopto- sis pathway. In response to intracellular stress, the apoptotic balance is governed by inter- Citation: Kønig SM, Rissler V, Terkelsen T, Lambrughi M, Papaleo E (2019) Alterations of the actions of three distinct subgroups of proteins; the activator/sensitizer BH3 (Bcl-2 homology interactome of Bcl-2 proteins in breast cancer at 3)-only proteins, the pro-survival, and the pro-apoptotic executioner proteins. Changes in the transcriptional, mutational and structural level. expression levels, stability, and functional impairment of pro-survival proteins can lead to an PLoS Comput Biol 15(12): e1007485. https://doi. imbalance in tissue homeostasis. Their overexpression or hyperactivation can result in org/10.1371/journal.pcbi.1007485 oncogenic effects. Pro-survival Bcl-2 family members carry out their function by binding the Editor: Igor N. Berezovsky, A�STAR Singapore, BH3 short linear motif of pro-apoptotic proteins in a modular way, creating a complex net- SINGAPORE work of protein-protein interactions. Their dysfunction enables cancer cells to evade cell Received: July 8, 2019 death.
    [Show full text]
  • Engineered Type 1 Regulatory T Cells Designed for Clinical Use Kill Primary
    ARTICLE Acute Myeloid Leukemia Engineered type 1 regulatory T cells designed Ferrata Storti Foundation for clinical use kill primary pediatric acute myeloid leukemia cells Brandon Cieniewicz,1* Molly Javier Uyeda,1,2* Ping (Pauline) Chen,1 Ece Canan Sayitoglu,1 Jeffrey Mao-Hwa Liu,1 Grazia Andolfi,3 Katharine Greenthal,1 Alice Bertaina,1,4 Silvia Gregori,3 Rosa Bacchetta,1,4 Norman James Lacayo,1 Alma-Martina Cepika1,4# and Maria Grazia Roncarolo1,2,4# Haematologica 2021 Volume 106(10):2588-2597 1Department of Pediatrics, Division of Stem Cell Transplantation and Regenerative Medicine, Stanford School of Medicine, Stanford, CA, USA; 2Stanford Institute for Stem Cell Biology and Regenerative Medicine, Stanford School of Medicine, Stanford, CA, USA; 3San Raffaele Telethon Institute for Gene Therapy, Milan, Italy and 4Center for Definitive and Curative Medicine, Stanford School of Medicine, Stanford, CA, USA *BC and MJU contributed equally as co-first authors #AMC and MGR contributed equally as co-senior authors ABSTRACT ype 1 regulatory (Tr1) T cells induced by enforced expression of interleukin-10 (LV-10) are being developed as a novel treatment for Tchemotherapy-resistant myeloid leukemias. In vivo, LV-10 cells do not cause graft-versus-host disease while mediating graft-versus-leukemia effect against adult acute myeloid leukemia (AML). Since pediatric AML (pAML) and adult AML are different on a genetic and epigenetic level, we investigate herein whether LV-10 cells also efficiently kill pAML cells. We show that the majority of primary pAML are killed by LV-10 cells, with different levels of sensitivity to killing. Transcriptionally, pAML sensitive to LV-10 killing expressed a myeloid maturation signature.
    [Show full text]
  • Proteomic Signatures of Brain Regions Affected by Tau Pathology in Early and Late Stages of Alzheimer's Disease
    Neurobiology of Disease 130 (2019) 104509 Contents lists available at ScienceDirect Neurobiology of Disease journal homepage: www.elsevier.com/locate/ynbdi Proteomic signatures of brain regions affected by tau pathology in early and T late stages of Alzheimer's disease Clarissa Ferolla Mendonçaa,b, Magdalena Kurasc, Fábio César Sousa Nogueiraa,d, Indira Plác, Tibor Hortobágyie,f,g, László Csibae,h, Miklós Palkovitsi, Éva Renneri, Péter Dömej,k, ⁎ ⁎ György Marko-Vargac, Gilberto B. Domonta, , Melinda Rezelic, a Proteomics Unit, Department of Biochemistry, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil b Gladstone Institute of Neurological Disease, San Francisco, USA c Division of Clinical Protein Science & Imaging, Department of Clinical Sciences (Lund) and Department of Biomedical Engineering, Lund University, Lund, Sweden d Laboratory of Proteomics, LADETEC, Institute of Chemistry, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil e MTA-DE Cerebrovascular and Neurodegenerative Research Group, University of Debrecen, Debrecen, Hungary f Institute of Pathology, Faculty of Medicine, University of Szeged, Szeged, Hungary g Centre for Age-Related Medicine, SESAM, Stavanger University Hospital, Stavanger, Norway h Department of Neurology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary i SE-NAP – Human Brain Tissue Bank Microdissection Laboratory, Semmelweis University, Budapest, Hungary j Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary k National Institute of Psychiatry and Addictions, Nyírő Gyula Hospital, Budapest, Hungary ARTICLE INFO ABSTRACT Keywords: Background: Alzheimer's disease (AD) is the most common neurodegenerative disorder. Depositions of amyloid β Alzheimer's disease peptide (Aβ) and tau protein are among the major pathological hallmarks of AD. Aβ and tau burden follows Proteomics predictable spatial patterns during the progression of AD.
    [Show full text]
  • Database and Bioinformatic Analysis of BCL-2 Family Proteins and BH3-Only Proteins Abdel Aouacheria, Vincent Navratil, Christophe Combet
    Database and Bioinformatic Analysis of BCL-2 Family Proteins and BH3-Only Proteins Abdel Aouacheria, Vincent Navratil, Christophe Combet To cite this version: Abdel Aouacheria, Vincent Navratil, Christophe Combet. Database and Bioinformatic Analysis of BCL-2 Family Proteins and BH3-Only Proteins. Gavathiotis E. BCL-2 Family Proteins. Methods in Molecular Biology, 1877, Springer Nature, pp.23-43, 2019, Methods in Molecular Biology, 978-1-4939- 8860-0. 10.1007/978-1-4939-8861-7_2. hal-02347884 HAL Id: hal-02347884 https://hal.archives-ouvertes.fr/hal-02347884 Submitted on 5 Nov 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Copyright Database and bioinformatic analysis of BCL-2 family proteins and BH3-only proteins Abdel Aouacheria 1,*, Vincent Navratil 2 and Christophe Combet 3 1 ISEM, Institut des Sciences de l’Evolution de Montpellier, Université de Montpellier, UMR 5554, CNRS, IRD, EPHE, Place Eugène Bataillon, 34095 Montpellier, France 2 PRABI, Rhône Alpes Bioinformatics Center, UCBL, Lyon1, Université de Lyon, Lyon, France. 3 Centre de Recherche en Cancérologie de Lyon, UMR Inserm U1052, CNRS 5286, Université Claude Bernard Lyon 1, Centre Léon Bérard, Lyon, France.
    [Show full text]
  • Anti-VEGF Drugs Influence Epigenetic Regulation and AMD-Specific
    cells Article Anti-VEGF Drugs Influence Epigenetic Regulation and AMD-Specific Molecular Markers in ARPE-19 Cells Mohamed A. Hamid 1,2,† , M. Tarek Moustafa 1,2,† , Sonali Nashine 1, Rodrigo Donato Costa 1,3 , Kevin Schneider 1, Shari R. Atilano 1 , Baruch D. Kuppermann 1,4 and M. Cristina Kenney 1,5,* 1 Gavin Herbert Eye Institute, University of California Irvine, Irvine, CA 92697, USA; [email protected] (M.A.H.); [email protected] (M.T.M.); [email protected] (S.N.); [email protected] (R.D.C.); [email protected] (K.S.); [email protected] (S.R.A.); [email protected] (B.D.K.) 2 Ophthalmology Department, Faculty of Medicine, Minia University, Minia 61111, Egypt 3 Instituto Donato Oftalmologia, PoVos de Caldas, MG 37701-528, Brazil 4 Department of Biomedical Engineering, University of California Irvine, Irvine, CA 92697, USA 5 Department of Pathology and Laboratory Medicine, University of California Irvine, Irvine, CA 92697, USA * Correspondence: [email protected]; Tel.: +1-949-824-7603 † Both authors contributed equally. Abstract: Our study assesses the effects of anti-VEGF (Vascular Endothelial Growth Factor) drugs and Trichostatin A (TSA), an inhibitor of histone deacetylase (HDAC) activity, on cultured ARPE-19 (Adult Retinal Pigment Epithelial-19) cells that are immortalized human retinal pigment epithelial cells. ARPE-19 cells were treated with the following anti-VEGF drugs: aflibercept, ranibizumab, or bevacizumab at 1× and 2× concentrations of the clinical intravitreal dose (12.5 µL/mL and 25 µL/mL, Citation: Hamid, M.A.; Moustafa, respectively) and analyzed for transcription profiles of genes associated with the pathogenesis M.T.; Nashine, S.; Costa, R.D.; age-related macular degeneration (AMD).
    [Show full text]
  • Alterations of the Pro-Survival Bcl-2 Protein Interactome in Breast Cancer
    bioRxiv preprint doi: https://doi.org/10.1101/695379; this version posted July 12, 2019. 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-NC-ND 4.0 International license. 1 Alterations of the pro-survival Bcl-2 protein interactome in 2 breast cancer at the transcriptional, mutational and 3 structural level 4 5 Simon Mathis Kønig1, Vendela Rissler1, Thilde Terkelsen1, Matteo Lambrughi1, Elena 6 Papaleo1,2 * 7 1Computational Biology Laboratory, Danish Cancer Society Research Center, 8 Strandboulevarden 49, 2100, Copenhagen 9 10 2Translational Disease Systems Biology, Faculty of Health and Medical Sciences, Novo 11 Nordisk Foundation Center for Protein Research University of Copenhagen, Copenhagen, 12 Denmark 13 14 Abstract 15 16 Apoptosis is an essential defensive mechanism against tumorigenesis. Proteins of the B-cell 17 lymphoma-2 (Bcl-2) family regulates programmed cell death by the mitochondrial apoptosis 18 pathway. In response to intracellular stresses, the apoptotic balance is governed by interactions 19 of three distinct subgroups of proteins; the activator/sensitizer BH3 (Bcl-2 homology 3)-only 20 proteins, the pro-survival, and the pro-apoptotic executioner proteins. Changes in expression 21 levels, stability, and functional impairment of pro-survival proteins can lead to an imbalance 22 in tissue homeostasis. Their overexpression or hyperactivation can result in oncogenic effects. 23 Pro-survival Bcl-2 family members carry out their function by binding the BH3 short linear 24 motif of pro-apoptotic proteins in a modular way, creating a complex network of protein- 25 protein interactions.
    [Show full text]
  • Asparaginase Therapy in Pediatric Acute Lymphoblastic Leukemia: a Focus on the Mode of Drug Resistance Shih-Hsiang Chen
    Pediatrics and Neonatology (2015) 56, 287e293 Available online at www.sciencedirect.com ScienceDirect journal homepage: http://www.pediatr-neonatol.com REVIEW ARTICLE Asparaginase Therapy in Pediatric Acute Lymphoblastic Leukemia: A Focus on the Mode of Drug Resistance Shih-Hsiang Chen Division of Hematology/Oncology, Department of Pediatrics, Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, 5 Fu-Shin Street, Kwei-Shan 333, Taoyuan, Taiwan Received Apr 24, 2014; received in revised form Aug 28, 2014; accepted Oct 6, 2014 Available online 23 December 2014 Key Words Asparaginase is one of the most important chemotherapeutic agents against pediatric acute acute lymphoblastic lymphoblastic leukemia (ALL), the most common form of childhood cancer. The therapeutic leukemia; efficacy (e.g., chemoresistance) and adverse effects of asparaginase (e.g., hypersensivity asparaginase; and pancreatitis) have been investigated over the past four decades. It was suggested early chemotherapy; on that leukemic cells are resistant to asparaginase because of their increased asparagine syn- children; thetase activity. Afterward, other mechanisms associated with asparaginase resistance were resistance reported. Not only leukemic cells but also patients themselves may play a role in causing as- paraginase resistance, which has been associated with unfavorable outcome in children with ALL. This article will briefly review asparaginase therapy in children with ALL and comprehen- sively analyze recent reports on the potential mechanisms of asparaginase resistance. Copyright ª 2015, Taiwan Pediatric Association. Published by Elsevier Taiwan LLC. All rights reserved. 1. Introduction Taiwan Childhood Cancer Foundation, there are about 130e140 newly diagnosed ALL children (younger than Acute lymphoblastic leukemia (ALL) is the most common 18 years), accounting for 25% of all childhood cancers in cancer in children.
    [Show full text]