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B and IFNG Transcripts (Bottom Row) in the Top and Bottom 20% of EPHA2 Expression, in Human TCGA PDA Dataset

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A B mRNA CD8A C 8 R2=0.03705 6 p = 0.0098 4 2 mRNA IFNG -2 2468 -2 EPHA2 mRNA 2500 ** 800 2000 600 * 1500 400 mRNA 1000 200 IFNG 500 0 0 EPHA2 high low EPHA2 high low D gMDSCs 80 *** 60 40 % CD45+ 20 0 T cell low high Figure S1. Expression of EPHA2 correlates with the abundance of CD8+ T cells in PDA (Related to Figure 1). (A) Top pathways from Metascape analysis of genes negatively correlated with CD8A in human TCGA PDA dataset. (B) Correlation of transcript abundance for CD8A and EPHA2 (left) and abundance of CD8A mRNA in the top and bottom 20% of EPHA2 expression (right) in human PDA samples (QCMG_Nature_2016 dataset, cbioportal). (C) Correlation of transcript abundance (top row) and abundance of CD3E, PRF1, GZMB and IFNG transcripts (bottom row) in the top and bottom 20% of EPHA2 expression, in human TCGA PDA dataset. (D) Flow cytometric analysis of immune cell populations in subcutaneously implanted T cell low and T cell high tumors derived from indicated clones (n=10/group). In (B-D), data presented as boxplots with horizontal lines and error bars indicating mean and range, respectively. Statistical analysis by Students’ unpaired t-test (B, C, D) with significance indicated (*, p<0.05; **, p<0.01; ***, p<0.001; ****, p<0.0001; ns, not significant in this and all subsequent figures, unless otherwise indicated). A EPHA2 staining B 6419c5 6694c2 Ctrl WT % YFP+ Epha2-WT KO1 KO2 Epha2-KO C CD8+/myeloid cells CD8+/gMDSC D Macs cDC CD103+ cDC 40 30 20 10 CD103+ (% CD45+) CD8+/CD11b+MHCII- 0 6419c5 6694c2 E CD8+/myeloid cells CD8+/gMDSCF Macs cDC CD103+ 2.5 2.0 1.5 *** 1.0 0.5 CD103+ (% CD45+) CD103+ (% CD8+/CD11b+MHCII- 0.0 6419c5 6694c2 G Arginase 1+ IDO1+ iNOS+ H Arginase 1+ IDO1+ iNOS+ CD206+ 25 100 40 ** *** *** 20 80 30 15 60 20 10 40 10 5 % F480+ Macs Macs F480+ % 20 0 0 0 6419c5 6419c5 6419c5 6419c5 6419c5 6419c5 6419c5 IKJL 1000 *** 800 600 400 *** 200 0 6419c5 6694c2 Figure S2. Tumor cell-intrinsic Epha2 regulates T cell infiltration (Related to Figure 2). (A-B) Representative histogram (A) and quantification (B) of EPHA2 protein expression in subcutaneous Epha2-WT and Epha2-KO tumors from indicated clones (n=5/group). (C-F) Flow cytometric analysis of immune cell populations in subcutaneous (C-D, n=12-25/group) and orthotopic (E-F, n=5-10/group) tumors from Epha2-WT and Epha2-KO tumors from indicated clones. (G-H) Flow cytometric analysis of gMDSCs and Macs in subcutaneous Epha2-WT and Epha2-KO tumors from indicated clone (n=10/group). (I) Quantification of SMA and PDGFR stainings in subcutaneous Epha2-WT and Epha2-KO tumors from indicated clones (n=4- 10/group). (J) Proportions of Ki67+ tumor cells among cultured Epha2-WT and Epha2-KO tumor cells, by flow cytometry (n=3-6/group). (K-L) Weights of implanted subcutaneous (K, n=12-25/group) and orthotopic (L,n=5- 10/group) Epha2-WT and Epha2-KO tumors from indicated clones, 21 days post implantation. Statistical difference between groups calculated using Student’s unpaired t-test (B-L). Epha2 WT FDR Epha2 KO A FDR Translational initiation 0.010 DNA conformation change 0.006 Response to Type I Interferon 0.000 Cytoplasmic translation 0.009 Interferon gamma mediated signaling 0.000 0.000 Epithelial to mesenchymal transition 0.009 Response to Interferon gamma 0.000 Cell cycle phase transition 0.008 Cellular Response to Interferon gamma Defense response to virus 0.000 Multi organism metabolic process 0.008 Innate immune response 0.000 Sister chromatid cohesion 0.008 Negative regulation of Type I interferon 0.003 Transcription elongation from POI II 0.011 Cytokine mediated signaling 0.003 Establishment of protein to ER 0.011 Response to virus 0.005 RNA secondary structure unwinding 0.013 Response to interferon beta 0.005 Protein DNA complex organization 0.012 Negative regulation of viral process 0.009 DNA packaging 0.013 Regulation of translation initiation 0.015 0123 Normalized Enrichment Score 0.0 0.5 1.0 1.5 2.0 2.5 Normalized Enrichment Score B C D E 6419c5 80000 6419c5-Epha2-WT 6694c2-Epha2-WT 60000 40000 DAPI 20000 8000 6000 4000 STAT1 DESeq2 Scaled count Scaled DESeq2 2000 % YFP+ 0 1 0 1 4 44 l9 t3 x i c l1 fi35 Ifit1 as3 Ifi 1 1 p If c I Ifi44 M d27 k b Stat Cx O Isg15Isg20 D p Cx C Oas1a B2m Tap1 Tap2 2- 2- 6419c5-Epha2-KO 6694c2-Epha2-KO H H Ta 5000 6694c2 4000 80000 3000 6694c2 2000 60000 1000 40000 300 Epha2-WT 20000 200 8000 Epha2-KO 100 6000 4000 0 2000 1 l9 t1 3 1 4 5 0 a i44 c l10 i35 fi i44 fit 1 at If x c If I If I Mx 27 g1 g2 0 St C x Oas3 d Is Is as C C O 2 p k1 2m a - B Tap1 T 2 apbp F G H H2-D1T 6694c2 20000 **** WT PTGS2 padj value=0.0092 **** EPHA2-KO1 MACC1 padj value=0.0001 15000 **** EPHA2-KO2 CCK padj value=0.0000 **** 10000 5000 0 Ctrl IFN-g IFN-b H I J K EPHA2 MFI -2 -1 0 1 2 6694c2 6419c5 6499c4 EPHA2 MFI 2838c3 V 2 V 1 trl O E ctrl TGF E C -KO1 KO KO 3 3-KO 4-K d d3- d d a a ad3- ad4-KO1 a a Sm Sm Sm Smad3-KO2Sm Smad4-KO2 Sm Sm Figure S3. TGF-SMAD3, 4-PTGS2 axis as potential tumor cell-intrinsic regulator of TME (Related to Figure 4). (A) Gene set enrichment analysis of differentially expressed genes in Epha2-WT or Epha2-KO tumor cells using the GO biological processes gene sets (n=3-8/group). (B) Interferon responsive genes in tumor cells from implanted tumors (n=3-8/group). (C) Representative IF images of STAT1 staining (red) in tumors (n=3 /group). (D) Antigen presentation genes on implanted tumor cells (n=3-8/group). (E) Proportions of MHC I+ YFP+ tumor cells in implanted tumors (n=5/group). (F) MHC I protein expression on YFP+ tumor cells in vitro after 24 hours with either no treatment (ctrl) or IFN,orIFN treatments (n=3/group). (G) Differentially expressed genes identified in human T cell high (red) and T cell low (blue) PDA tumors (top and bottom 20% of CD8A expression). Genes with padj<0.05 and log2foldChange>2 shown. (H) Relative expression of Smad3 and Smad4 in control (EV) and KO tumor cell clones generated from 6419c5. Data from n=4 independent experiments. (I) EPHA2 protein expression in PDA tumor cell clones treated with either PBS orTGF for72hours.Datafrom n=3 independent experiments. Color key represents the normalized Z score.(J) EPHA2 protein expression on Smad3 and Smad4 KO cell lines in vitro (n=3/group). (K) EPHA2 protein expression in YFP+ cells from control and Smad3 and Smad4 KO tumors (n=5-9/group). In (E, H, K) data presented as boxplots with horizontal lines and error bars indicating mean and range, respectively. In (B, D, F and J), data presented as mean with error bars indicating SEM. Statistical difference between two groups calculated by Students’ unpaired t-test (E), between multiple groups determined by one-way ANOVA with Tukey’s HSD post-test (F, H, J, K). A IgG anti-CD4/CD8 BC 160 ** 120 80 40 0 ctrl Ptgs2-KO D Day 1 Day 4 E ctrl Ptgs2-KO Ctrl -KO Ptgs2 Ki67 F 1200 900 600 * 300 0 0 10203040 Days post injection Figure S4. Effect of Ptgs2 deletion on PDA cells in vitro and in vivo (Related to Figure 5). (A) T cell depletion check by flow cytometry on day 35 post tumor implantation. (B-C) Relative Ptgs2 mRNA expression (B) and extracellular PGE2 levels (C) measured in control (ctrl, Cas9, no gRNA, transduced) and Ptgs2-KO (Cas9/ Ptges2 gRNA transduced) KPC cell line conditioned media (n=3/group). (D) Control (ctrl) and Ptgs2-KO KPC cells plated 50000 cells/well on 6 well plates. Phase contrast 4X images taken on day 1 and day 4 in culture (representative image of 3/group). (E) Ki67+ control (ctrl) and Ptgs2-KO cells, shown as percent of live cells; flow cytometry performed on day 3 in culture. (F) Control (ctrl) and Ptgs2-KO KPC cell lines injected in WT and global Ptgs2 knockout (Ptgs2-gKO) mice (n=5-10/group); tumor free survival (left) and tumor growth (right). In (B-C) data presented as mean with error bars indicating SEM. Statistical differences calculated using Students’ unpaired t-test (B-C) and linear mixed-effects model with Tukey’s HSD post-test using the lme4 and survival package in R (F). A B PD-L1+ 25 Control **** Ptgs2-KO 20 15 10 MHC I MHC MFI % live cells live % 5 0 ctrl KO C CD73 MFI CD73 DE KPCY KPCYPtgs2 s2 g Pt CD3 YFP DAPI Figure S5. Effect of Ptgs2 deletion on tumor cells and TME in vitro and in vivo (Related to Figure 6). (A-C) Flow cytometric analysis of control (ctrl) and Ptgs2-KO tumor cells after 48 hours in culture (representative experiment of 2, n=3/group). (D-E) Representative 20X images (D) and quantification (E) of CD3+ cells (red) in autochthonous tumors from KPCY and KPCYPtgs2 mice (n=20- 25 fields/group). YFP+ cells and nuclei stained in green and blue, respectively.
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  • Smart and Green Mobility in Istanbul

    Smart and Green Mobility in Istanbul

    Smart and Green Mobility in Istanbul Commissioned by the Netherlands Enterprise Agency Smart and Green Mobility in Istanbul About This report has been commissioned by the Netherlands Consulate General in Istanbul as a part of the Public Private Partnership programme of the Netherlands Enterprise Agency, RVO. This Fact-Finding Study Pre-PPS was coordinated by Eda Beyazit Ince (Istanbul Technical University – IstanbulON Urban Mobility Lab) and Kenan Aksular (Clearwater Innovations B.V.). Citation Netherlands Enterprise Agency (RVO) Fact-Finding Study Pre-PPS: Smart and Green Mobility in Istanbul, 2020 Authors Eda Beyazit Ince Kenan Aksular Mazdak Sadeghpour İpek Yargıç With special thanks to Rory Nuijens Head of Netherlands Innovation Network Turkey [email protected] Ceren ErtenSenior Commercial Officer [email protected] Ece Ömür Advisor for Innovation, Technology & Science [email protected] Kenneth Heijns Managing Director AMSInstitute www.ams-institute.org Dr. ir. Stephan van Dijk Director of Innovation AMS Institute Tom Kuipers Program Developer Smart Urban Mobility AMS Institute Unless stated otherwise, all photos of Istanbul are courtesy of © Haluk Gercek Layout Duygu Kalkanlı Cover photo: emiratiproductions.ae © Netherlands Enterprise Agency | October 2020 Table of Contents Foreword 01 Executive Summary 02 Introduction 03 The Way Forward: Green and Smart Mobility 05 Methodology 08 Mobility in Istanbul: Green and Smart? 09 An Evaluation of Existing Plans & Projects 10 Project Potentials Under EIT 26 A Summary of Challanges