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SUPPLEMENTARY DATA Cell-Cycle and DNA-Damage Response

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SUPPLEMENTARY DATA Cell-cycle and DNA-damage response pathway is involved in leptomeningeal metastasis of non-small cell lung cancer Yun Fan1†*, Xuehua Zhu2†, Yan Xu3†, Xuesong Lu4, Yanjun Xu1, Mengzhao Wang3, Haiyan Xu4, Jingyan Ding2, Xin Ye2, Luo Fang5, Zhiyu Huang5, Lei Gong5, Hongyang Lu1, Weimin Mao1, and Min Hu2* 1Key Laboratory Diagnosis and Treatment Technology on Thoracic Oncology, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China. 2IMED Asia, AstraZeneca, Shanghai, China. 3Department of Respiratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China. 4Research & Development Information, AstraZeneca, Shanghai, China. 5Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China. †These authors contributed equally to this work. *Corresponding Authors: Yun Fan, Zhejiang Cancer Hospital, No. 1 Banshan East Road, Hangzhou, Zhejiang 310022, China. Phone: (+86)0571-88122396; Fax: (+86)0571-88122396; Email: [email protected]. Min Hu, AstraZeneca, No. 199 Liangjing Road, Zhangjiang Hi-tech Park, Pudong New Area, Shanghai 201203, China. Phone: (+86)021-61097820; Fax: (+86)021-58387337; Email: min- [email protected]. 1 SUPPLEMENTARY FIGURES Supplementary Figure S1. 2100 Bioanalyzer spectra of total DNA extracted from CSF samples. Pellet DNA comprised the major proportion of total CSF DNA for most samples except in P6C there was a high fraction of cfDNA. The amount of DNA input used for library construction was indicated in each panel. 2 SUPPLEMENTARY TABLES Supplementary Table S1. Sample collection information. Patient P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 Primary tumor √ √ √ √ √ √ √ √ √ √ √ Tumor percentage 70% 60% 60% 85% 30% 90% 60% 30% 80% 60% 50% CSF √ √ √ √ √ √ √ √ √ √ √ Whole blood √ √ √ √ √ √ √ Adjacent normal √ 3 Supplementary Table S2. Genes/regions included in the LungPlasma panel. 44 genes (whole exons) AKT1 CDK6 FGFR2 MAP2K1 NTRK1 STK11 APC CDKN2A FGFR3 MDM2 NTRK2 TP53 ATM CTNNB1 FLT3 MET NTRK3 TSC1 AURKA DDR2 IGF1R MTOR PDGFRA TSC2 BIM EGFR JAK2 NF1 PIK3CA BRAF ERBB2 KDR NOTCH1 PTEN CCND1 ERBB4 KIT NRAS RB1 CDK4 FGFR1 KRAS NRG1 SMO 3 genes (whole exons and selected introns) ALK RET ROS1 121 genes (selected exons) ACER2 COL5A2 GKN2 NFE2L2 PTPRD TPTE ADAMTS12 CSMD1 GRIA3 NLRP4 PYHIN1 TRIM58 ADAMTS16 CSMD3 GUCY1A3 NRXN1 REG1B TRIML1 ADAMTS20 CTNNA2 HCN1 NTM RYR2 TRPC5 AK5 CYP2D6 HGF OBP2A SAGE1 TSHR AKR1B10 DHX9 HRAS OCA2 SCN7A U2AF1 AMOT DPP10 IL1RAPL1 ODZ3 SETD2 UGT1A1 ANKRD30A EIF3E INHBA OR2T4 SI UNC5D ASTN1 EPB41L4B ITM2A OR4A15 SLC26A3 VHL ATP10B EPHA3 KEAP1 OR4C6 SLC4A10 VPS13A BTRC EPHA5 KLHL1 OR5L2 SLC5A1 WISP3 CACNA1E EXOC5 KRTAP5-5 OR6F1 SLC6A5 WT1 CD5L EYA4 LRP1B PDE1C SNTG1 XPO1 CDH18 F9 LRRC2 PDE4DIP SORCS3 XRCC3 CNGB3 FAM135B LRRC7 POLDIP2 SPTA1 ZNF217 CNOT4 FAM5C LTBP1 POLR3B TBX15 ZNF703 CNTN5 FBN2 MDGA2 POM121L12 THSD7A CNTNAP5 FGFR4 MLL3 POTEG TIMD4 COASY GALNT13 MRPL1 PRSS1 TMEM132D COL19A1 GATA3 MYH2 PSG2 TNN COL25A1 GFRAL NAV3 PSG5 TNR 4 Supplementary Table S3. Genes included in the customized SeqCap EZ Choice Library. 394 genes (whole exons) ABCA6 CDKN1A FGF9 LRRK2 PAMR1 RNF43 ABCB1 CDKN1B FGFR1 LYRM5 PARP1 RPA1 ABL1 CDKN2A FGFR3 MALAT1 PAX6 RPA2 ACVR1B CDKN2B FGFR4 MAP2K1 PBRM1 RPA3 ACVR2A CDKN2C FHOD3 MAP2K2 PCBP1-AS1 RPL22 ACVRL1 CEBPA FIP1L1 MAP2K4 PDPK1 RPL5 ADAM28 CHD7 FKBP1A MAP3K1 PGM5 RPL6 AGTR2 CHEK1 FLT3 MAP3K13 PHF6 RPSAP58 AKT1 CHEK2 FOXA1 MAP3K8 PHLPP1 RUNX1 AKT1S1 CLVS1 FOXA2 MAPK1 PHLPP2 SBNO1 AKT2 CNTLN FOXC1 MAPK3 PIK3C2B SDK1 AKT3 COL6A3 FOXL2 MAPK8IP1 PIK3C2G SETBP1 AMER1 CR2 FRMD4A MAPKAP1 PIK3C3 SETD2 AOC3 CRIPAK FRS2 MBD6 PIK3CA SF3B1 APC CRKL GAS6 MCL1 PIK3CB SH3KBP1 AR CRYGD GATA3 MDC1 PIK3CD SIN3A ARAF CSNK2A1 GATA3-AS1 MDM2 PIK3CG SLC27A3 ARHGAP35 CTCF GLI1 MDM4 PIK3R1 SMAD2 ARID1A CTNNB1 GNA11 MECOM PIK3R2 SMAD4 ARID1B CYP2D6 GNA13 MED12 PIM1 SMC1A ARID2 DCUN1D1 GNAQ MEDAG PIM2 SMC3 ARID5B DDC GNAS MFRP PIM3 SMIM4 ASXL1 DDR1 GNG12 MGA PLEKHA6 SOX17 ATM DDR2 GSE1 MITF PMS1 SOX9-AS1 ATP2A1 DEPTOR GSTP1 MLH1 PMS2 SPOP ATP6V1B1 DIS3 H2AFX MLH3 POLD1 STAG2 ATR DNMT3A H3F3C MLST8 POLE STK11 ATRX DOCK2 HGF MPL POLM SVIL AXIN2 DSG3 HIST1H1C MRAS POLQ TAF1 B2M DYRK4 HIST1H2BD MRE11A PPOX TBL1XR1 ADGRB3 EDNRB HNF1A MSH3 PPP2R1A TBX3 BAP1 EGR3 HRAS MSH6 PPP2R2A TBX4 BARD1 EIF4A2 IDH1 MTHFR PRKAA1 TDP1 BCHE ELF3 IDH2 MTOR PRKAA2 TET2 BCL2L1 EP300 IGF1R MUC16 PRKAB1 TEX26-AS1 BCL2L11 EPCAM IL32 MUTYH PRKDC TFDP1 BCL9 EPHA3 IL6 MVK PRPF40B TGFBR2 BCORL1 EPHB6 INF2 MYC PRX TLR4 BMPR1A EPPK1 INPP4A MYCL PTCH1 TMEM132D BRAF ERAS INPP4B MYCN PTEN TP53 5 BRD2 ERBB2 IRAK4 MYH9 PTENP1 TP53BP1 BRD3 ERBB3 IRS4 MYOF PTPN11 TPTE BRD4 ERBB4 JAK1 NAV3 PTPN6 TRAM1L1 BRD9 ERCC1 JAK2 NBN RABGAP1 TSHZ2 BRIP1 ERCC2 JAK3 NCOR1 RAC1 TSHZ3 BUB1B ERRFI1 JARID2 NCOR2 RAD21 TTC19 BZRAP1 ESR1 KDM5C NDUFB11 RAD50 U2AF1 BZRAP1-AS1 EZH2 KDM6A NDUFB2 RAD51 USP9X C6orf89 FAM175A KDR NF1 RAD51AP2 UTP23 C7orf50 FANCI KEAP1 NF2 RAD51B VCAN C9orf131 FANCL KIF7 NFE2L2 RAD51C VEZF1 CBFB FAT4 KIT NFE2L3 RAD51D VHL RAD51L3- CBL FBXW7 KLC3 NKX2-1 WBP1 RFFL CCND1 FGF1 KLF3 NKX2-8 RAD52 WNT16 CCND2 FGF10 KLLN NLK RAD54L WT1 CCND3 FGF12 KMT2B NOTCH1 RAF1 XPC CCNE1 FGF14 KMT2C NPM1 RALGAPB XRCC1 CD4 FGF19 KMT2D NRAS RASA1 XRCC2 CDC14A FGF2 KRAS NRG1 RB1 XRCC4 CDH1 FGF23 KRTAP5-5 NSD1 RBM10 XRCC5 CDH10 FGF3 LAMP1 NTRK3 RELN XRCC6 CDK12 FGF4 LARP4B OR5M3 RHEB XYLT2 CDK4 FGF5 LIFR OTX2 RHOA ZBTB20 CDK6 FGF6 LIG1 PAFAH1B1 RICTOR ZNF43 CDK8 FGF7 LIG4 PAK1 RIT1 CDK9 FGF8 LMAN1 PALB2 RNF2 9 genes (whole exons and introns) ALK BRCA2 FGFR2 MSH2 RET ROS1 BRCA1 EGFR MET 6 Supplementary Table S4. List of hotspot mutations and structural rearrangements. Hotspot mutations Gene Accession No. CDS change AA change COSMIC ID AKT1 NM_005163 c.49G>A E17K COSM33765 BRAF NM_004333 c.1798_1799GT>AA V600K COSM473 BRAF NM_004333 c.1798_1799GT>AG V600R COSM474 BRAF NM_004333 c.1799T>A V600E COSM476 ERBB2 NM_004448 c.1963A>G I655V COSM4000121 ERBB2 NM_004448 c.2033G>A R678Q COSM436498 ERBB2 NM_004448 c.2264T>C L755S COSM14060 ERBB2 NM_004448 c.2524G>A V842I COSM14065 ERBB2 NM_004448 c.929C>T S310F COSM48358 KRAS NM_033360 c.182A>G Q61R COSM552 KRAS NM_033360 c.182A>T Q61L COSM553 KRAS NM_033360 c.183A>C Q61H COSM554 KRAS NM_033360 c.183A>T Q61H COSM555 KRAS NM_033360 c.34G>A G12S COSM517 KRAS NM_033360 c.34G>C G12R COSM518 KRAS NM_033360 c.34G>T G12C COSM516 KRAS NM_033360 c.35G>A G12D COSM521 KRAS NM_033360 c.35G>C G12A COSM522 KRAS NM_033360 c.35G>T G12V COSM520 KRAS NM_033360 c.37G>T G13C COSM527 KRAS NM_033360 c.38G>A G13D COSM532 MET NM_001127500 c.3029C>T T1010I COSM707 MET NM_001127500 c.3757T>G Y1253D COSM700 NRAS NM_002524 c.181C>A Q61K COSM580 NRAS NM_002524 c.182A>G Q61R COSM584 NRAS NM_002524 c.182A>T Q61L COSM583 NRAS NM_002524 c.183A>C Q61H COSM586 NRAS NM_002524 c.183A>T Q61H COSM585 NRAS NM_002524 c.34G>A G12S COSM563 NRAS NM_002524 c.34G>C G12R COSM561 NRAS NM_002524 c.34G>T G12C COSM562 NRAS NM_002524 c.35G>A G12D COSM564 NRAS NM_002524 c.35G>C G12A COSM565 7 NRAS NM_002524 c.35G>T G12V COSM566 NRAS NM_002524 c.37G>C G13R COSM569 NRAS NM_002524 c.37G>T G13C COSM570 NRAS NM_002524 c.38G>A G13D COSM573 NRAS NM_002524 c.38G>T G13V COSM574 PIK3CA NM_006218 c.1035T>A N345K COSM754 PIK3CA NM_006218 c.1258T>C C420R COSM757 PIK3CA NM_006218 c.1624G>A E542K COSM760 PIK3CA NM_006218 c.1633G>A E545K COSM763 PIK3CA NM_006218 c.2176G>A E726K COSM87306 PIK3CA NM_006218 c.3140A>G H1047R COSM775 PIK3CA NM_006218 c.3140A>T H1047L COSM776 PIK3CB NM_006219 c.3151G>A E1051K COSM317875 PTEN NM_000314 c.388C>G R130G COSM5219 PTEN NM_000314 c.388C>T R130* COSM5152 PTEN NM_000314 c.389G>A R130Q COSM5033 PTEN NM_000314 c.697C>T R233* COSM5154 Structural rearrangements EML4-ALK STRN-ALK KIAA1549-BRAF CCDC6-RET SLC34A2-ROS1 NPM1-ALK ATIC-ALK FAM131B-BRAF NCOA4-RET EZR-ROS1 CLTC-ALK KIF5B-ALK SND1-BRAF KIF5B-RET GOPC-ROS1 TPM3-ALK TPM4-ALK FGFR1-PLAG1 PRKAR1A-RET SDC4-ROS1 RANBP2-ALK TFG-ALK FGFR3-TACC3 CD74-ROS1 8 Supplementary Table S5. Co-existence of EGFR and PIK3CA mutations as reported in NSCLC patient datasets. Comparing with the current LM cohort, the co-existence of PIK3CA mutations was significantly lower in general EGFR mutation-positive NSCLC patient population (p-values: 1.65E-6 and 9.89E-06 by Fisher's exact test for Western and Asian datasets, respectively). *: datasets from cBioPortal (1,2); #: dataset from The Cancer Genome Atlas (TCGA) Research Network (http://cancergenome.nih.gov/). Co-existence Source Sample size EGFRm+ PIK3CAm+ Reported mutation sites (% EGFRm+) Lung adenocarcinoma EGFR exon 18-21; PIK3CA E542K, E545K, 182 21 4 1 (4.76%) (Broad, Cell 2012) * H1047L Lung adenocarcinoma 34 1 0 0 (0) EGFR exon 18-21 (MSKCC 2015) * Lung adenocarcinoma EGFR exon 18-21; PIK3CA E542K, E545K, 567 49 13 0 (0) (TCGA, Provisional) # E726K, H1047R Lung adenocarcinoma 163 20 0 0 (0) EGFR exon 18-21 (TSP, Nature 2008) * EGFR 19Del, G719A/D/C/S, L858R/M, T790M; PIK3CA K111E/N/R, E542K/Q, Sherwood JL, et al (3) 238 20 10 1 (5%) Western datasets Western E545A/G/D/K/Q, Q546H/R/P/L, H1047L/R/Q/Y EGFR exon 19-21; activating mutations in Chaft JE, et al (4) 1125 260 23 3 (1.15%) PIK3CA Total 2309 371 50 5 (1.35%) EGFR exons 18-21; PIK3CA exon 9 (T536I, Wang L, et al (5) 807 522 22 16 (3.07%) E542K, E545A/K/Q/G, Q546R) and exon 20 (G1007R, Y1021C, M1043L, H1047L/R) EGFR exons 18-21; PIK3CA E542K, Serizawa M, et al (6) 411 144 11 4 (2.78%) E545K/Q, H1047R atasets EGFR exons 18-21; PIK3CA E542K, Wu SG, et al (7) 760 485 14 12 (2.47%) E545K/Q, H1047R Asian d EGFR exons 18-21; PIK3CA exon 9 and exon Song Z, et al (8) 810 401 23 12 (2.99%) 20 Total 2788 1552 70 44 (2.84%) 9 Supplementary Table S6.
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  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus

    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.
  • Supplementary Table 1: Adhesion Genes Data Set

    Supplementary Table 1: Adhesion Genes Data Set

    Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like,
  • Functional Genomics Atlas of Synovial Fibroblasts Defining Rheumatoid Arthritis

    Functional Genomics Atlas of Synovial Fibroblasts Defining Rheumatoid Arthritis

    medRxiv preprint doi: https://doi.org/10.1101/2020.12.16.20248230; this version posted December 18, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Functional genomics atlas of synovial fibroblasts defining rheumatoid arthritis heritability Xiangyu Ge1*, Mojca Frank-Bertoncelj2*, Kerstin Klein2, Amanda Mcgovern1, Tadeja Kuret2,3, Miranda Houtman2, Blaž Burja2,3, Raphael Micheroli2, Miriam Marks4, Andrew Filer5,6, Christopher D. Buckley5,6,7, Gisela Orozco1, Oliver Distler2, Andrew P Morris1, Paul Martin1, Stephen Eyre1* & Caroline Ospelt2*,# 1Versus Arthritis Centre for Genetics and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK 2Department of Rheumatology, Center of Experimental Rheumatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland 3Department of Rheumatology, University Medical Centre, Ljubljana, Slovenia 4Schulthess Klinik, Zurich, Switzerland 5Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK 6NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, University of Birmingham, Birmingham, UK 7Kennedy Institute of Rheumatology, University of Oxford Roosevelt Drive Headington Oxford UK *These authors contributed equally #corresponding author: [email protected] NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. 1 medRxiv preprint doi: https://doi.org/10.1101/2020.12.16.20248230; this version posted December 18, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
  • Gene Symbol Category ACAN ECM ADAM10 ECM Remodeling-Related ADAM11 ECM Remodeling-Related ADAM12 ECM Remodeling-Related ADAM15 E

    Gene Symbol Category ACAN ECM ADAM10 ECM Remodeling-Related ADAM11 ECM Remodeling-Related ADAM12 ECM Remodeling-Related ADAM15 E

    Supplementary Material (ESI) for Integrative Biology This journal is (c) The Royal Society of Chemistry 2010 Gene symbol Category ACAN ECM ADAM10 ECM remodeling-related ADAM11 ECM remodeling-related ADAM12 ECM remodeling-related ADAM15 ECM remodeling-related ADAM17 ECM remodeling-related ADAM18 ECM remodeling-related ADAM19 ECM remodeling-related ADAM2 ECM remodeling-related ADAM20 ECM remodeling-related ADAM21 ECM remodeling-related ADAM22 ECM remodeling-related ADAM23 ECM remodeling-related ADAM28 ECM remodeling-related ADAM29 ECM remodeling-related ADAM3 ECM remodeling-related ADAM30 ECM remodeling-related ADAM5 ECM remodeling-related ADAM7 ECM remodeling-related ADAM8 ECM remodeling-related ADAM9 ECM remodeling-related ADAMTS1 ECM remodeling-related ADAMTS10 ECM remodeling-related ADAMTS12 ECM remodeling-related ADAMTS13 ECM remodeling-related ADAMTS14 ECM remodeling-related ADAMTS15 ECM remodeling-related ADAMTS16 ECM remodeling-related ADAMTS17 ECM remodeling-related ADAMTS18 ECM remodeling-related ADAMTS19 ECM remodeling-related ADAMTS2 ECM remodeling-related ADAMTS20 ECM remodeling-related ADAMTS3 ECM remodeling-related ADAMTS4 ECM remodeling-related ADAMTS5 ECM remodeling-related ADAMTS6 ECM remodeling-related ADAMTS7 ECM remodeling-related ADAMTS8 ECM remodeling-related ADAMTS9 ECM remodeling-related ADAMTSL1 ECM remodeling-related ADAMTSL2 ECM remodeling-related ADAMTSL3 ECM remodeling-related ADAMTSL4 ECM remodeling-related ADAMTSL5 ECM remodeling-related AGRIN ECM ALCAM Cell-cell adhesion ANGPT1 Soluble factors and receptors
  • Health-Relevant Phenotypes in the Offspring of Mice Given CAR Activators Prior to Pregnancy S

    Health-Relevant Phenotypes in the Offspring of Mice Given CAR Activators Prior to Pregnancy S

    Supplemental material to this article can be found at: http://dmd.aspetjournals.org/content/suppl/2018/08/28/dmd.118.082925.DC1 1521-009X/46/11/1827–1835$35.00 https://doi.org/10.1124/dmd.118.082925 DRUG METABOLISM AND DISPOSITION Drug Metab Dispos 46:1827–1835, November 2018 Copyright ª 2018 by The American Society for Pharmacology and Experimental Therapeutics Health-Relevant Phenotypes in the Offspring of Mice Given CAR Activators Prior to Pregnancy s Karin Dietrich, Jan Baumgart, Leonid Eshkind, Lea Reuter, Ute Gödtel-Armbrust, Elke Butt, Michael Musheev, Federico Marini, Piyush More, Tanja Grosser, Christof Niehrs, Leszek Wojnowski, and Marianne Mathäs Department of Pharmacology (K.D., L.R., U.G.-A., P.M., T.G., L.W., M.Ma.) and Institute of Medical Biostatistics, Epidemiology and Informatics (F.M.), University Medical Center Mainz, Mainz, Germany; Translational Animal Research Center (J.B., L.E.), University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany; Institute of Experimental Biomedicine II, University Hospital Würzburg, Würzburg, Germany (E.B.); Institute of Molecular Biology, Mainz, Germany (M.Mu., C.N.); and Division of Molecular Embryology, German Cancer Research Center (DKFZ-ZMBH Alliance), Heidelberg, Germany (C.N.) Received June 6, 2018; accepted August 22, 2018 Downloaded from ABSTRACT Hepatic induction in response to drugs and environmental chem- analyses. The important environmental pollutant PCB153 acti- icals affects drug therapies and energy metabolism. We investigated vated CAR in the F1 generation in a manner similar to TCPOBOP. whether the induction is transmitted to the offspring. We injected Our findings indicate that chemicals accumulating and persisting 3-day- and 6-week-old F0 female mice with TCPOBOP, an activator in adipose tissue may exert liver-mediated, health-relevant effects dmd.aspetjournals.org of the nuclear receptor constitutive androstane receptor (CAR, on F1 offspring simply via physical transmission in milk.