Computational Analysis of AP-2Γ Role in Bladder Cancer
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Macropinocytosis Requires Gal-3 in a Subset of Patient-Derived Glioblastoma Stem Cells
ARTICLE https://doi.org/10.1038/s42003-021-02258-z OPEN Macropinocytosis requires Gal-3 in a subset of patient-derived glioblastoma stem cells Laetitia Seguin1,8, Soline Odouard2,8, Francesca Corlazzoli 2,8, Sarah Al Haddad2, Laurine Moindrot2, Marta Calvo Tardón3, Mayra Yebra4, Alexey Koval5, Eliana Marinari2, Viviane Bes3, Alexandre Guérin 6, Mathilde Allard2, Sten Ilmjärv6, Vladimir L. Katanaev 5, Paul R. Walker3, Karl-Heinz Krause6, Valérie Dutoit2, ✉ Jann N. Sarkaria 7, Pierre-Yves Dietrich2 & Érika Cosset 2 Recently, we involved the carbohydrate-binding protein Galectin-3 (Gal-3) as a druggable target for KRAS-mutant-addicted lung and pancreatic cancers. Here, using glioblastoma patient-derived stem cells (GSCs), we identify and characterize a subset of Gal-3high glio- 1234567890():,; blastoma (GBM) tumors mainly within the mesenchymal subtype that are addicted to Gal-3- mediated macropinocytosis. Using both genetic and pharmacologic inhibition of Gal-3, we showed a significant decrease of GSC macropinocytosis activity, cell survival and invasion, in vitro and in vivo. Mechanistically, we demonstrate that Gal-3 binds to RAB10, a member of the RAS superfamily of small GTPases, and β1 integrin, which are both required for macro- pinocytosis activity and cell survival. Finally, by defining a Gal-3/macropinocytosis molecular signature, we could predict sensitivity to this dependency pathway and provide proof-of- principle for innovative therapeutic strategies to exploit this Achilles’ heel for a significant and unique subset of GBM patients. 1 University Côte d’Azur, CNRS UMR7284, INSERM U1081, Institute for Research on Cancer and Aging (IRCAN), Nice, France. 2 Laboratory of Tumor Immunology, Department of Oncology, Center for Translational Research in Onco-Hematology, Swiss Cancer Center Léman (SCCL), Geneva University Hospitals, University of Geneva, Geneva, Switzerland. -
WO 2014/135655 Al 12 September 2014 (12.09.2014) P O P C T
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date WO 2014/135655 Al 12 September 2014 (12.09.2014) P O P C T (51) International Patent Classification: (81) Designated States (unless otherwise indicated, for every C12Q 1/68 (2006.01) kind of national protection available): AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, (21) International Application Number: BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DK, DM, PCT/EP2014/054384 DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, (22) International Filing Date: HN, HR, HU, ID, IL, IN, IR, IS, JP, KE, KG, KN, KP, KR, 6 March 2014 (06.03.2014) KZ, LA, LC, LK, LR, LS, LT, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, (25) Filing Language: English OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (26) Publication Language: English SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, (30) Priority Data: ZW. 13305253.0 6 March 2013 (06.03.2013) EP (84) Designated States (unless otherwise indicated, for every (71) Applicants: INSTITUT CURIE [FR/FR]; 26 rue d'Ulm, kind of regional protection available): ARIPO (BW, GH, F-75248 Paris cedex 05 (FR). CENTRE NATIONAL DE GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, SZ, TZ, LA RECHERCHE SCIENTIFIQUE [FR/FR]; 3 rue UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, Michel Ange, F-75016 Paris (FR). -
Single Cell Derived Clonal Analysis of Human Glioblastoma Links
SUPPLEMENTARY INFORMATION: Single cell derived clonal analysis of human glioblastoma links functional and genomic heterogeneity ! Mona Meyer*, Jüri Reimand*, Xiaoyang Lan, Renee Head, Xueming Zhu, Michelle Kushida, Jane Bayani, Jessica C. Pressey, Anath Lionel, Ian D. Clarke, Michael Cusimano, Jeremy Squire, Stephen Scherer, Mark Bernstein, Melanie A. Woodin, Gary D. Bader**, and Peter B. Dirks**! ! * These authors contributed equally to this work.! ** Correspondence: [email protected] or [email protected]! ! Supplementary information - Meyer, Reimand et al. Supplementary methods" 4" Patient samples and fluorescence activated cell sorting (FACS)! 4! Differentiation! 4! Immunocytochemistry and EdU Imaging! 4! Proliferation! 5! Western blotting ! 5! Temozolomide treatment! 5! NCI drug library screen! 6! Orthotopic injections! 6! Immunohistochemistry on tumor sections! 6! Promoter methylation of MGMT! 6! Fluorescence in situ Hybridization (FISH)! 7! SNP6 microarray analysis and genome segmentation! 7! Calling copy number alterations! 8! Mapping altered genome segments to genes! 8! Recurrently altered genes with clonal variability! 9! Global analyses of copy number alterations! 9! Phylogenetic analysis of copy number alterations! 10! Microarray analysis! 10! Gene expression differences of TMZ resistant and sensitive clones of GBM-482! 10! Reverse transcription-PCR analyses! 11! Tumor subtype analysis of TMZ-sensitive and resistant clones! 11! Pathway analysis of gene expression in the TMZ-sensitive clone of GBM-482! 11! Supplementary figures and tables" 13" "2 Supplementary information - Meyer, Reimand et al. Table S1: Individual clones from all patient tumors are tumorigenic. ! 14! Fig. S1: clonal tumorigenicity.! 15! Fig. S2: clonal heterogeneity of EGFR and PTEN expression.! 20! Fig. S3: clonal heterogeneity of proliferation.! 21! Fig. -
Primary Tumor Site 137 Larynix
US 20190187143A1 ( 19) United States (12 ) Patent Application Publication ( 10) Pub . No. : US 2019 /0187143 A1 Wallweber ( 43 ) Pub . Date : Jun . 20 , 2019 ( 54 ) COMPOSITIONS AND METHODS TO Publication Classification DETECT HEAD AND NECK CANCER (51 ) Int. Cl. (71 ) Applicant : Laboratory Corporation of America GOIN 33 / 574 ( 2006 .01 ) GOIN 33 /52 (2006 . 01) Holdings , Burlington , NC (US ) (52 ) U . S . CI. (72 ) Inventor : Gerald J . Wallweber , Foster City , CA CPC .. GOIN 33 /57407 ( 2013 .01 ) ; GOIN 33 /5748 (US ) ( 2013 .01 ) ; GOIN 33 /52 ( 2013 .01 ) (57 ) ABSTRACT ( 21 ) Appl. No. : 16 /224 , 974 Disclosed are compositions and methods to detect proteins associated with Head and Neck Cancer, generally , or more ( 22 ) Filed : Dec . 19 , 2018 particularly , biomarkers of Head and Neck Squamous Cell Carcinoma (HNSCC ) . Such markers may be useful to allow Related U . S . Application Data individuals susceptible to HNSCC to manage their lifestyle (60 ) Provisional application No. 62/ 608 ,296 , filed on Dec . and /or medical treatment to avoid further progression of 20 , 2017 . disease . Primary Tumor Site primarytumor Site 137 Larynix Har Oralen cavityel . Gene Accuracy Kappa Sensitivity Specificity 1 CAB39L 0 . 9600 0 . 7745 0 .9831 0 .7818 2 ADAM12 0 . 9688 0 . 7506 0 . 9938 0 .6727 . 3 SH3BGRL2 0 .9596 0 .6972 0 . 9846 0 . 6636 4 NRG2 0 .9553 0 . 6710 0 .9808 0 .6545 5 COL13A11 0 . 9546 0 . 6376 0 . 9854 0 .5909 6 GRIN2D 1 0 . 9539 0 .6326 0 . 9862 0 .5727 7 LOXL2 0 . 9525 0 .5906 0 . 9915 0 .4909 8 HSD1786 0 . 9411 0 . -
Novel Gene Signatures for Stage Classification of the Squamous Cell
www.nature.com/scientificreports OPEN Novel gene signatures for stage classifcation of the squamous cell carcinoma of the lung Angel Juarez‑Flores, Gabriel S. Zamudio & Marco V. José* The squamous cell carcinoma of the lung (SCLC) is one of the most common types of lung cancer. As GLOBOCAN reported in 2018, lung cancer was the frst cause of death and new cases by cancer worldwide. Typically, diagnosis is made in the later stages of the disease with few treatment options available. The goal of this work was to fnd some key components underlying each stage of the disease, to help in the classifcation of tumor samples, and to increase the available options for experimental assays and molecular targets that could be used in treatment development. We employed two approaches. The frst was based in the classic method of diferential gene expression analysis, network analysis, and a novel concept known as network gatekeepers. The second approach was using machine learning algorithms. From our combined approach, we identifed two sets of genes that could function as a signature to identify each stage of the cancer pathology. We also arrived at a network of 55 nodes, which according to their biological functions, they can be regarded as drivers in this cancer. Although biological experiments are necessary for their validation, we proposed that all these genes could be used for cancer development treatments. As GLOBOCAN reported in 2018, lung cancer was the frst cause of deaths and new cases by cancer worldwide 1. Squamous cell carcinoma of the lung (SCC) is one type of lung cancer which comprises approximately 30% of all lung cancer cases. -
Case-Control Study for Colorectal Cancer Genetic Susceptibility in EPICOLON: Previously Identified Variants and Mucins
UC Davis UC Davis Previously Published Works Title Case-control study for colorectal cancer genetic susceptibility in EPICOLON: previously identified variants and mucins. Permalink https://escholarship.org/uc/item/48x6z4pq Journal BMC cancer, 11(1) ISSN 1471-2407 Authors Abulí, Anna Fernández-Rozadilla, Ceres Alonso-Espinaco, Virginia et al. Publication Date 2011-08-05 DOI 10.1186/1471-2407-11-339 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Abulí et al. BMC Cancer 2011, 11:339 http://www.biomedcentral.com/1471-2407/11/339 RESEARCHARTICLE Open Access Case-control study for colorectal cancer genetic susceptibility in EPICOLON: previously identified variants and mucins Anna Abulí1,2, Ceres Fernández-Rozadilla3, Virginia Alonso-Espinaco1, Jenifer Muñoz1, Victoria Gonzalo1, Xavier Bessa2, Dolors González4, Joan Clofent5, Joaquin Cubiella6, Juan D Morillas7, Joaquim Rigau8, Mercedes Latorre9, Fernando Fernández-Bañares10, Elena Peña11, Sabino Riestra12, Artemio Payá13, Rodrigo Jover13, Rosa M Xicola14, Xavier Llor14, Luis Carvajal-Carmona15, Cristina M Villanueva16, Victor Moreno17, Josep M Piqué1, Angel Carracedo3, Antoni Castells1, Montserrat Andreu2, Clara Ruiz-Ponte3 and Sergi Castellví-Bel1*, for for the Gastrointestinal Oncology Group of the Spanish Gastroenterological Association18 Abstract Background: Colorectal cancer (CRC) is the second leading cause of cancer death in developed countries. Familial aggregation in CRC is also important outside syndromic forms and, in this case, a polygenic model with several common low-penetrance alleles contributing to CRC genetic predisposition could be hypothesized. Mucins and GALNTs (N-acetylgalactosaminyltransferase) are interesting candidates for CRC genetic susceptibility and have not been previously evaluated. We present results for ten genetic variants linked to CRC risk in previous studies (previously identified category) and 18 selected variants from the mucin gene family in a case-control association study from the Spanish EPICOLON consortium. -
Whole-Genome Sequencing Identifies Genomic Heterogeneity at a Nucleotide and Chromosomal Level in Bladder Cancer
Whole-genome sequencing identifies genomic heterogeneity at a nucleotide and chromosomal level in bladder cancer Carl D. Morrisona,1,2, Pengyuan Liub,1, Anna Woloszynska-Readc, Jianmin Zhangd, Wei Luoc, Maochun Qine, Wiam Bsharaf, Jeffrey M. Conroya, Linda Sabatinif, Peter Vedellb, Donghai Xiongb, Song Liue, Jianmin Wange, He Shend, Yinwei Lid, Angela R. Omilianf, Annette Hillf, Karen Headf, Khurshid Gurug, Dimiter Kunnevh, Robert Leache, Kevin H. Enge, Christopher Darlaka, Christopher Hoeflicha, Srividya Veerankia, Sean Glennd, Ming Youb, Steven C. Pruitth, Candace S. Johnsonc, and Donald L. Trumpi aCenter for Personalized Medicine and Departments of cPharmacology and Therapeutics, dCancer Genetics, eBiostatistics and Bioinformatics, fPathology, gUrology, hMolecular and Cellular Biology, and iMedicine, Roswell Park Cancer Institute, Buffalo, NY 14263; and bDepartment of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226 Edited* by Carlo M. Croce, The Ohio State University, Columbus, OH, and approved January 2, 2014 (received for review July 22, 2013) Using complete genome analysis, we sequenced five bladder tumors earlier studies in melanoma (13) and medulloblastoma (14), ev- accrued from patients with muscle-invasive transitional cell carcinoma idence of the association of TP53 mutations with specific copy of the urinary bladder (TCC-UB) and identified a spectrum of genomic number alterations, referred to as chromothripsis, was noted. The aberrations. In three tumors, complex genotype changes were noted. study in medulloblastoma (14) was particularly intriguing in that All three had tumor protein p53 mutations and a relatively large identification of a molecular subclass with TP53 mutations was number of single-nucleotide variants (SNVs; average of 11.2 per associated with chromothripsis and a more aggressive clinical megabase), structural variants (SVs; average of 46), or both. -
Identi Cation of Novel Hub Genes Through Expression Pro Les
Identication of Novel Hub Genes Through Expression Proles Analysis in Adrenocortical Carcinoma Chenhe Yao Beijing Zhicheng Biomedical Technology Co,Ltd Xiaoling Zhao Beijing Zhicheng Biomedical Technology Co,Ltd Xuemeng Shang Beijing Zhicheng Biomedical Technology Co,Ltd Binghan Jia Beijing Zhicheng Biomedical Technology Co,Ltd Shuaijie Dou Beijing Zhicheng Biomedical Technology Co,Ltd Weiliang Ye Beijing Zhicheng Biomedical Technology Co,Ltd Yuemei Yang ( [email protected] ) Beijing Zhicheng Biomedical Technology,Co.,Ltd. Research Keywords: Adrenocortical carcinoma, biomarkers, gene expression proling, Co-expression, prognosis Posted Date: July 1st, 2020 DOI: https://doi.org/10.21203/rs.3.rs-38768/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/21 Abstract Background: Adrenocortical carcinoma (ACC) is a heterogeneous and rare malignant tumor associated with a poor prognosis. The molecular mechanisms of ACC remain elusive and more accurate biomarkers for the prediction of prognosis are needed. Methods: In this study, integrative proling analyses were performed to identify novel hub genes in ACC to provide promising targets for future investigation. Three gene expression proling datasets in the GEO database were used for the identication of overlapped differentially expressed genes (DEGs) following the criteria of adj.P.Value<0.05 and |log2 FC|>0.5 in ACC. Novel hub genes were screened out following a series of processes: the retrieval of DEGs with no known associations with ACC on Pubmed, then the cross-validation of expression values and signicant associations with overall survival in the GEPIA2 and starBase databases, and nally the prediction of gene-tumor association in the GeneCards database. -
Mitotic Checkpoints and Chromosome Instability Are Strong Predictors of Clinical Outcome in Gastrointestinal Stromal Tumors
MITOTIC CHECKPOINTS AND CHROMOSOME INSTABILITY ARE STRONG PREDICTORS OF CLINICAL OUTCOME IN GASTROINTESTINAL STROMAL TUMORS. Pauline Lagarde1,2, Gaëlle Pérot1, Audrey Kauffmann3, Céline Brulard1, Valérie Dapremont2, Isabelle Hostein2, Agnès Neuville1,2, Agnieszka Wozniak4, Raf Sciot5, Patrick Schöffski4, Alain Aurias1,6, Jean-Michel Coindre1,2,7 Maria Debiec-Rychter8, Frédéric Chibon1,2. Supplemental data NM cases deletion frequency. frequency. deletion NM cases Mand between difference the highest setswith of theprobe a view isdetailed panel Bottom frequently. sorted totheless deleted theprobe are frequently from more and thefrequency deletion represent Yaxes inblue. are cases (NM) metastatic for non- frequencies Corresponding inmetastatic (red). probe (M)cases sets figureSupplementary 1: 100 100 20 40 60 80 20 40 60 80 0 0 chr14 1 chr14 88 chr14 175 chr14 262 chr9 -MTAP 349 chr9 -MTAP 436 523 chr9-CDKN2A 610 Histogram presenting the 2000 more frequently deleted deleted frequently the 2000 more presenting Histogram chr9-CDKN2A 697 chr9-CDKN2A 784 chr9-CDKN2B 871 chr9-CDKN2B 958 chr9-CDKN2B 1045 chr22 1132 chr22 1219 chr22 1306 chr22 1393 1480 1567 M NM 1654 1741 1828 1915 M NM GIST14 GIST2 GIST16 GIST3 GIST19 GIST63 GIST9 GIST38 GIST61 GIST39 GIST56 GIST37 GIST47 GIST58 GIST28 GIST5 GIST17 GIST57 GIST47 GIST58 GIST28 GIST5 GIST17 GIST57 CDKN2A Supplementary figure 2: Chromosome 9 genomic profiles of the 18 metastatic GISTs (upper panel). Deletions and gains are indicated in green and red, respectively; and color intensity is proportional to copy number changes. A detailed view is given (bottom panel) for the 6 cases presenting a homozygous 9p21 deletion targeting CDKN2A locus (dark green). -
Mo25α/CAB39 (C49D8) Rabbit Mab A
Revision 1 C 0 2 - t MO25α/CAB39 (C49D8) Rabbit mAb a e r o t S Orders: 877-616-CELL (2355) [email protected] Support: 877-678-TECH (8324) 6 1 Web: [email protected] 7 www.cellsignal.com 2 # 3 Trask Lane Danvers Massachusetts 01923 USA For Research Use Only. Not For Use In Diagnostic Procedures. Applications: Reactivity: Sensitivity: MW (kDa): Source/Isotype: UniProt ID: Entrez-Gene Id: WB, IP H M R Mk Endogenous 39 Rabbit IgG Q9Y376 51719 Product Usage Information Application Dilution Western Blotting 1:1000 Immunoprecipitation 1:50 Storage Supplied in 10 mM sodium HEPES (pH 7.5), 150 mM NaCl, 100 µg/ml BSA, 50% glycerol and less than 0.02% sodium azide. Store at –20°C. Do not aliquot the antibody. Specificity / Sensitivity MO25α/CAB39 (C49D8) Rabbit mAb detects endogenous levels of total MO25α/CAB39 and MO25β/CAB39L proteins. Species Reactivity: Human, Mouse, Rat, Monkey Source / Purification Monoclonal antibody is produced by immunizing animals with a synthetic peptide corresponding to the sequence of human MO25α/CAB39. Background AMPK (AMP-activated protein kinase) is a key cellular component that regulates energy homeostasis (1,2). When the AMP/ATP ratio is increased due to energy depletion, AMPK is phosphorylated at its α1 and α2 catalytic subunits and activated (3). Studies showed that the tumor suppressor LKB1 phosphorylates and activates AMPK in mammals (4,5). MO25α (mouse protein 25α), also called CAB39 (calcium binding protein 39), is a component of the LKB1 complex in vivo (5,6). MO25α/CAB39 does not directly interact with LKB1; instead, it is physically associated with STRADα (6). -
Molecular Architecture of the Chick Vestibular Hair Bundle
RE so UR c E Molecular architecture of the chick vestibular hair bundle Jung-Bum Shin1,2,8, Jocelyn F Krey2,8, Ahmed Hassan3, Zoltan Metlagel3, Andrew N Tauscher3, James M Pagana1,2, Nicholas E Sherman4, Erin D Jeffery4, Kateri J Spinelli2, Hongyu Zhao2, Phillip A Wilmarth5, Dongseok Choi6, Larry L David5, Manfred Auer3 & Peter G Barr-Gillespie2,7 Hair bundles of the inner ear have a specialized structure and protein composition that underlies their sensitivity to mechanical stimulation. Using mass spectrometry, we identified and quantified >1,100 proteins, present from a few to 400,000 copies per stereocilium, from purified chick bundles; 336 of these were significantly enriched in bundles. Bundle proteins that we detected have been shown to regulate cytoskeleton structure and dynamics, energy metabolism, phospholipid synthesis and cell signaling. Three-dimensional imaging using electron tomography allowed us to count the number of actin-actin cross-linkers and actin- membrane connectors; these values compared well to those obtained from mass spectrometry. Network analysis revealed several hub proteins, including RDX (radixin) and SLC9A3R2 (NHERF2), which interact with many bundle proteins and may perform functions essential for bundle structure and function. The quantitative mass spectrometry of bundle proteins reported here establishes a framework for future characterization of dynamic processes that shape bundle structure and function. An outstanding example of a specialized organelle devoted to a single identified those proteins selectively targeted to bundles. Many bundle- purpose, the vertebrate hair bundle transduces mechanical signals enriched proteins are expressed from deafness-associated genes, for the inner ear, converting sound and head movement to electrical confirming their essential function in the inner ear. -
Table S1. 103 Ferroptosis-Related Genes Retrieved from the Genecards
Table S1. 103 ferroptosis-related genes retrieved from the GeneCards. Gene Symbol Description Category GPX4 Glutathione Peroxidase 4 Protein Coding AIFM2 Apoptosis Inducing Factor Mitochondria Associated 2 Protein Coding TP53 Tumor Protein P53 Protein Coding ACSL4 Acyl-CoA Synthetase Long Chain Family Member 4 Protein Coding SLC7A11 Solute Carrier Family 7 Member 11 Protein Coding VDAC2 Voltage Dependent Anion Channel 2 Protein Coding VDAC3 Voltage Dependent Anion Channel 3 Protein Coding ATG5 Autophagy Related 5 Protein Coding ATG7 Autophagy Related 7 Protein Coding NCOA4 Nuclear Receptor Coactivator 4 Protein Coding HMOX1 Heme Oxygenase 1 Protein Coding SLC3A2 Solute Carrier Family 3 Member 2 Protein Coding ALOX15 Arachidonate 15-Lipoxygenase Protein Coding BECN1 Beclin 1 Protein Coding PRKAA1 Protein Kinase AMP-Activated Catalytic Subunit Alpha 1 Protein Coding SAT1 Spermidine/Spermine N1-Acetyltransferase 1 Protein Coding NF2 Neurofibromin 2 Protein Coding YAP1 Yes1 Associated Transcriptional Regulator Protein Coding FTH1 Ferritin Heavy Chain 1 Protein Coding TF Transferrin Protein Coding TFRC Transferrin Receptor Protein Coding FTL Ferritin Light Chain Protein Coding CYBB Cytochrome B-245 Beta Chain Protein Coding GSS Glutathione Synthetase Protein Coding CP Ceruloplasmin Protein Coding PRNP Prion Protein Protein Coding SLC11A2 Solute Carrier Family 11 Member 2 Protein Coding SLC40A1 Solute Carrier Family 40 Member 1 Protein Coding STEAP3 STEAP3 Metalloreductase Protein Coding ACSL1 Acyl-CoA Synthetase Long Chain Family Member 1 Protein