Pharmacogenomics of 17-Alpha Hydroxyprogesterone Caproate for Recurrent Preterm Birth Prevention Tracy A
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Supplemental Figure 1. Vimentin
Double mutant specific genes Transcript gene_assignment Gene Symbol RefSeq FDR Fold- FDR Fold- FDR Fold- ID (single vs. Change (double Change (double Change wt) (single vs. wt) (double vs. single) (double vs. wt) vs. wt) vs. single) 10485013 BC085239 // 1110051M20Rik // RIKEN cDNA 1110051M20 gene // 2 E1 // 228356 /// NM 1110051M20Ri BC085239 0.164013 -1.38517 0.0345128 -2.24228 0.154535 -1.61877 k 10358717 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 /// BC 1700025G04Rik NM_197990 0.142593 -1.37878 0.0212926 -3.13385 0.093068 -2.27291 10358713 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 1700025G04Rik NM_197990 0.0655213 -1.71563 0.0222468 -2.32498 0.166843 -1.35517 10481312 NM_027283 // 1700026L06Rik // RIKEN cDNA 1700026L06 gene // 2 A3 // 69987 /// EN 1700026L06Rik NM_027283 0.0503754 -1.46385 0.0140999 -2.19537 0.0825609 -1.49972 10351465 BC150846 // 1700084C01Rik // RIKEN cDNA 1700084C01 gene // 1 H3 // 78465 /// NM_ 1700084C01Rik BC150846 0.107391 -1.5916 0.0385418 -2.05801 0.295457 -1.29305 10569654 AK007416 // 1810010D01Rik // RIKEN cDNA 1810010D01 gene // 7 F5 // 381935 /// XR 1810010D01Rik AK007416 0.145576 1.69432 0.0476957 2.51662 0.288571 1.48533 10508883 NM_001083916 // 1810019J16Rik // RIKEN cDNA 1810019J16 gene // 4 D2.3 // 69073 / 1810019J16Rik NM_001083916 0.0533206 1.57139 0.0145433 2.56417 0.0836674 1.63179 10585282 ENSMUST00000050829 // 2010007H06Rik // RIKEN cDNA 2010007H06 gene // --- // 6984 2010007H06Rik ENSMUST00000050829 0.129914 -1.71998 0.0434862 -2.51672 -
Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino-Like Mouse Models: Tracking the Role of the Hairless Gene
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Doctoral Dissertations Graduate School 5-2006 Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino-like Mouse Models: Tracking the Role of the Hairless Gene Yutao Liu University of Tennessee - Knoxville Follow this and additional works at: https://trace.tennessee.edu/utk_graddiss Part of the Life Sciences Commons Recommended Citation Liu, Yutao, "Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino- like Mouse Models: Tracking the Role of the Hairless Gene. " PhD diss., University of Tennessee, 2006. https://trace.tennessee.edu/utk_graddiss/1824 This Dissertation is brought to you for free and open access by the Graduate School at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. To the Graduate Council: I am submitting herewith a dissertation written by Yutao Liu entitled "Molecular and Physiological Basis for Hair Loss in Near Naked Hairless and Oak Ridge Rhino-like Mouse Models: Tracking the Role of the Hairless Gene." I have examined the final electronic copy of this dissertation for form and content and recommend that it be accepted in partial fulfillment of the requirements for the degree of Doctor of Philosophy, with a major in Life Sciences. Brynn H. Voy, Major Professor We have read this dissertation and recommend its acceptance: Naima Moustaid-Moussa, Yisong Wang, Rogert Hettich Accepted for the Council: Carolyn R. -
SUPPLEMENTAL DATA Supplemental Materials And
SUPPLEMENTAL DATA Supplemental Materials and Methods Cells and Cell Culture Human breast carcinoma cell lines, MDA-MB-231 and MCF7, were purchased from American Type Tissue Culture Collection (ATCC). 231BoM-1833, 231BrM-2a, CN34, CN34-BoM2d, CN34-BrM2c and MCF7- BoM2d cell lines were kindly provided by Dr. Joan Massagué (Memorial Sloan-Kettering Cancer Center) (1-3). Luciferase-labeled cells were generated by infecting the lentivirus carrying the firefly luciferase gene. The immortalized mouse bone microvascular endothelial cell (mBMEC) was a generous gift from Dr. Isaiah J. Fidler (M.D. Anderson Cancer Center) (4). MCF10A and MCF10DCIS.com cells were purchased from ATCC and Asterand, respectively. MDA-MB-231, its variant cells, MCF7 and MCF-BoM2d cells were cultured in DMEM medium supplemented with 10% FBS and antibiotics. CN34 and its variant cells were cultured in Medium199 supplemented with 2.5% FBS, 10 µg/ml insulin, 0.5 µg/ml hydrocortisone, 20 ng/ml EGF, 100 ng/ml cholera toxin and antibiotics. MCF10DCIS.com cells were cultured in RPMI-1640 medium supplemented with 10% FBS and antibiotics. MCF10A cells were cultured in MEGM mammary epithelial cell growth medium (Lonza). mBMEC was maintained at 8% CO2 at 33 °C in DMEM with 10% FBS, 2 mM L-glutamine, 1 mM sodium pyruvate, 1% non-essential amino acids and 1% vitamin mixture. Bone marrow stromal fibroblast cell lines HS5 and HS27A, and osteoblast cell line, hFOB1.19, were purchased from ATCC. Bone marrow derived human mesenchymal stem cells, BM-hMSC, were isolated for enrichment of plastic adherent cells from unprocessed bone marrow (Lonza) which was depleted of red blood cells. -
Cellular and Molecular Signatures in the Disease Tissue of Early
Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of -
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 -
Appendix 2. Significantly Differentially Regulated Genes in Term Compared with Second Trimester Amniotic Fluid Supernatant
Appendix 2. Significantly Differentially Regulated Genes in Term Compared With Second Trimester Amniotic Fluid Supernatant Fold Change in term vs second trimester Amniotic Affymetrix Duplicate Fluid Probe ID probes Symbol Entrez Gene Name 1019.9 217059_at D MUC7 mucin 7, secreted 424.5 211735_x_at D SFTPC surfactant protein C 416.2 206835_at STATH statherin 363.4 214387_x_at D SFTPC surfactant protein C 295.5 205982_x_at D SFTPC surfactant protein C 288.7 1553454_at RPTN repetin solute carrier family 34 (sodium 251.3 204124_at SLC34A2 phosphate), member 2 238.9 206786_at HTN3 histatin 3 161.5 220191_at GKN1 gastrokine 1 152.7 223678_s_at D SFTPA2 surfactant protein A2 130.9 207430_s_at D MSMB microseminoprotein, beta- 99.0 214199_at SFTPD surfactant protein D major histocompatibility complex, class II, 96.5 210982_s_at D HLA-DRA DR alpha 96.5 221133_s_at D CLDN18 claudin 18 94.4 238222_at GKN2 gastrokine 2 93.7 1557961_s_at D LOC100127983 uncharacterized LOC100127983 93.1 229584_at LRRK2 leucine-rich repeat kinase 2 HOXD cluster antisense RNA 1 (non- 88.6 242042_s_at D HOXD-AS1 protein coding) 86.0 205569_at LAMP3 lysosomal-associated membrane protein 3 85.4 232698_at BPIFB2 BPI fold containing family B, member 2 84.4 205979_at SCGB2A1 secretoglobin, family 2A, member 1 84.3 230469_at RTKN2 rhotekin 2 82.2 204130_at HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2 81.9 222242_s_at KLK5 kallikrein-related peptidase 5 77.0 237281_at AKAP14 A kinase (PRKA) anchor protein 14 76.7 1553602_at MUCL1 mucin-like 1 76.3 216359_at D MUC7 mucin 7, -
Supplementary Methods
Supplementary methods Human lung tissues and tissue microarray (TMA) All human tissues were obtained from the Lung Cancer Specialized Program of Research Excellence (SPORE) Tissue Bank at the M.D. Anderson Cancer Center (Houston, TX). A collection of 26 lung adenocarcinomas and 24 non-tumoral paired tissues were snap-frozen and preserved in liquid nitrogen for total RNA extraction. For each tissue sample, the percentage of malignant tissue was calculated and the cellular composition of specimens was determined by histological examination (I.I.W.) following Hematoxylin-Eosin (H&E) staining. All malignant samples retained contained more than 50% tumor cells. Specimens resected from NSCLC stages I-IV patients who had no prior chemotherapy or radiotherapy were used for TMA analysis by immunohistochemistry. Patients who had smoked at least 100 cigarettes in their lifetime were defined as smokers. Samples were fixed in formalin, embedded in paraffin, stained with H&E, and reviewed by an experienced pathologist (I.I.W.). The 413 tissue specimens collected from 283 patients included 62 normal bronchial epithelia, 61 bronchial hyperplasias (Hyp), 15 squamous metaplasias (SqM), 9 squamous dysplasias (Dys), 26 carcinomas in situ (CIS), as well as 98 squamous cell carcinomas (SCC) and 141 adenocarcinomas. Normal bronchial epithelia, hyperplasia, squamous metaplasia, dysplasia, CIS, and SCC were considered to represent different steps in the development of SCCs. All tumors and lesions were classified according to the World Health Organization (WHO) 2004 criteria. The TMAs were prepared with a manual tissue arrayer (Advanced Tissue Arrayer ATA100, Chemicon International, Temecula, CA) using 1-mm-diameter cores in triplicate for tumors and 1.5 to 2-mm cores for normal epithelial and premalignant lesions. -
Supplementary Data
Supplementary Fig. 1 A B Responder_Xenograft_ Responder_Xenograft_ NON- NON- Lu7336, Vehicle vs Lu7466, Vehicle vs Responder_Xenograft_ Responder_Xenograft_ Sagopilone, Welch- Sagopilone, Welch- Lu7187, Vehicle vs Lu7406, Vehicle vs Test: 638 Test: 600 Sagopilone, Welch- Sagopilone, Welch- Test: 468 Test: 482 Responder_Xenograft_ NON- Lu7860, Vehicle vs Responder_Xenograft_ Sagopilone, Welch - Lu7558, Vehicle vs Test: 605 Sagopilone, Welch- Test: 333 Supplementary Fig. 2 Supplementary Fig. 3 Supplementary Figure S1. Venn diagrams comparing probe sets regulated by Sagopilone treatment (10mg/kg for 24h) between individual models (Welsh Test ellipse p-value<0.001 or 5-fold change). A Sagopilone responder models, B Sagopilone non-responder models. Supplementary Figure S2. Pathway analysis of genes regulated by Sagopilone treatment in responder xenograft models 24h after Sagopilone treatment by GeneGo Metacore; the most significant pathway map representing cell cycle/spindle assembly and chromosome separation is shown, genes upregulated by Sagopilone treatment are marked with red thermometers. Supplementary Figure S3. GeneGo Metacore pathway analysis of genes differentially expressed between Sagopilone Responder and Non-Responder models displaying –log(p-Values) of most significant pathway maps. Supplementary Tables Supplementary Table 1. Response and activity in 22 non-small-cell lung cancer (NSCLC) xenograft models after treatment with Sagopilone and other cytotoxic agents commonly used in the management of NSCLC Tumor Model Response type -
Plasma Fatty Acid Ratios Affect Blood Gene Expression Profiles - a Cross-Sectional Study of the Norwegian Women and Cancer Post-Genome Cohort
Plasma Fatty Acid Ratios Affect Blood Gene Expression Profiles - A Cross-Sectional Study of the Norwegian Women and Cancer Post-Genome Cohort Karina Standahl Olsen1*, Christopher Fenton2, Livar Frøyland3, Marit Waaseth4, Ruth H. Paulssen2, Eiliv Lund1 1 Department of Community Medicine, University of Tromsø, Tromsø, Norway, 2 Department of Clinical Medicine, University of Tromsø, Tromsø, Norway, 3 National Institute of Nutrition and Seafood Research (NIFES), Bergen, Norway, 4 Department of Pharmacy, University of Tromsø, Tromsø, Norway Abstract High blood concentrations of n-6 fatty acids (FAs) relative to n-3 FAs may lead to a ‘‘physiological switch’’ towards permanent low-grade inflammation, potentially influencing the onset of cardiovascular and inflammatory diseases, as well as cancer. To explore the potential effects of FA ratios prior to disease onset, we measured blood gene expression profiles and plasma FA ratios (linoleic acid/alpha-linolenic acid, LA/ALA; arachidonic acid/eicosapentaenoic acid, AA/EPA; and total n-6/n-3) in a cross-section of middle-aged Norwegian women (n = 227). After arranging samples from the highest values to the lowest for all three FA ratios (LA/ALA, AA/EPA and total n-6/n-3), the highest and lowest deciles of samples were compared. Differences in gene expression profiles were assessed by single-gene and pathway-level analyses. The LA/ALA ratio had the largest impact on gene expression profiles, with 135 differentially expressed genes, followed by the total n-6/ n-3 ratio (125 genes) and the AA/EPA ratio (72 genes). All FA ratios were associated with genes related to immune processes, with a tendency for increased pro-inflammatory signaling in the highest FA ratio deciles. -
Transcriptome Analysis Identifies an Attenuated Local Immune Response in Invasive Nonfunctioning Pituitary Adenomas
Original Endocrinol Metab 2019;34:314-322 https://doi.org/10.3803/EnM.2019.34.3.314 Article pISSN 2093-596X · eISSN 2093-5978 Transcriptome Analysis Identifies an Attenuated Local Immune Response in Invasive Nonfunctioning Pituitary Adenomas Yong Hwy Kim1,2, Jung Hee Kim2,3,4 1Department of Neurosurgery, 2Pituitary Center, 3Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine; 4Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University College of Medicine, Seoul, Korea Background: Invasive nonfunctioning pituitary adenomas (NFPAs) remain challenging due to their high complication rate and poor prognosis. We aimed to identify the distinctive molecular signatures of invasive NFPAs, compared with noninvasive NFPAs, using gene expression profiling by RNA sequencing. Methods: We obtained frozen fresh tissue samples from 14 patients with NFPAs who underwent primary transsphenoidal surgery. Three non-invasive and 11 invasive NFPAs were used for RNA sequencing. The bioinformatics analysis included differential gene expression, gene ontology analysis, and pathway analysis. Results: A total of 700 genes were differentially expressed (59 up-regulated and 641 down-regulated genes) between invasive and non-invasive NFPAs (false discovery rate <0.1, and |fold change| ≥2). Using the down-regulated genes in invasive NFPAs, gene ontology enrichment analyses and pathway analyses demonstrated that the local immune response was attenuated and that trans- forming growth factor-β (TGF-β) RII-initiated TGF-β signaling was down-regulated in invasive NFPAs. The overexpression of clau- din-9 (CLDN9) and the down-regulation of insulin-like growth factor-binding protein 5 (IGFBP5), death-associated protein kinase 1 (DAPK1), and tissue inhibitor of metalloproteinase-3 (TIMP3) may be related with invasiveness in NFPAs. -
Supplementary Information.Pdf
Supplementary Information Whole transcriptome profiling reveals major cell types in the cellular immune response against acute and chronic active Epstein‐Barr virus infection Huaqing Zhong1, Xinran Hu2, Andrew B. Janowski2, Gregory A. Storch2, Liyun Su1, Lingfeng Cao1, Jinsheng Yu3, and Jin Xu1 Department of Clinical Laboratory1, Children's Hospital of Fudan University, Minhang District, Shanghai 201102, China; Departments of Pediatrics2 and Genetics3, Washington University School of Medicine, Saint Louis, Missouri 63110, United States. Supplementary information includes the following: 1. Supplementary Figure S1: Fold‐change and correlation data for hyperactive and hypoactive genes. 2. Supplementary Table S1: Clinical data and EBV lab results for 110 study subjects. 3. Supplementary Table S2: Differentially expressed genes between AIM vs. Healthy controls. 4. Supplementary Table S3: Differentially expressed genes between CAEBV vs. Healthy controls. 5. Supplementary Table S4: Fold‐change data for 303 immune mediators. 6. Supplementary Table S5: Primers used in qPCR assays. Supplementary Figure S1. Fold‐change (a) and Pearson correlation data (b) for 10 cell markers and 61 hypoactive and hyperactive genes identified in subjects with acute EBV infection (AIM) in the primary cohort. Note: 23 up‐regulated hyperactive genes were highly correlated positively with cytotoxic T cell (Tc) marker CD8A and NK cell marker CD94 (KLRD1), and 38 down‐regulated hypoactive genes were highly correlated positively with B cell, conventional dendritic cell -
Discovery of a Molecular Glue That Enhances Uprmt to Restore
bioRxiv preprint doi: https://doi.org/10.1101/2021.02.17.431525; this version posted February 17, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Title: Discovery of a molecular glue that enhances UPRmt to restore proteostasis via TRKA-GRB2-EVI1-CRLS1 axis Authors: Li-Feng-Rong Qi1, 2 †, Cheng Qian1, †, Shuai Liu1, 2†, Chao Peng3, 4, Mu Zhang1, Peng Yang1, Ping Wu3, 4, Ping Li1 and Xiaojun Xu1, 2 * † These authors share joint first authorship Running title: Ginsenoside Rg3 reverses Parkinson’s disease model by enhancing mitochondrial UPR Affiliations: 1 State Key Laboratory of Natural Medicines, China Pharmaceutical University, 210009, Nanjing, Jiangsu, China. 2 Jiangsu Key Laboratory of Drug Discovery for Metabolic Diseases, China Pharmaceutical University, 210009, Nanjing, Jiangsu, China. 3. National Facility for Protein Science in Shanghai, Zhangjiang Lab, Shanghai Advanced Research Institute, Chinese Academy of Science, Shanghai 201210, China 4. Shanghai Science Research Center, Chinese Academy of Sciences, Shanghai, 201204, China. Corresponding author: Ping Li, State Key Laboratory of Natural Medicines, China Pharmaceutical University, 210009, Nanjing, Jiangsu, China. Email: [email protected], Xiaojun Xu, State Key Laboratory of Natural Medicines, Jiangsu Key Laboratory of Drug Discovery for Metabolic Diseases, China Pharmaceutical University, 210009, Nanjing, Jiangsu, China. Telephone number: +86-2583271203, E-mail: [email protected]. bioRxiv preprint doi: https://doi.org/10.1101/2021.02.17.431525; this version posted February 17, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.