OCT4 Induces Embryonic Pluripotency Via STAT3 Signaling and Metabolic Mechanisms
Total Page:16
File Type:pdf, Size:1020Kb

Load more
Recommended publications
-
Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis. -
Anti-Rab11 Antibody (ARG41900)
Product datasheet [email protected] ARG41900 Package: 100 μg anti-Rab11 antibody Store at: -20°C Summary Product Description Goat Polyclonal antibody recognizes Rab11 Tested Reactivity Hu, Ms, Rat, Dog, Mk Tested Application IHC-Fr, IHC-P, WB Host Goat Clonality Polyclonal Isotype IgG Target Name Rab11 Antigen Species Mouse Immunogen Purified recombinant peptides within aa. 110 to the C-terminus of Mouse Rab11a, Rab11b and Rab11c (Rab25). Conjugation Un-conjugated Alternate Names RAB11A: Rab-11; Ras-related protein Rab-11A; YL8 RAB11B: GTP-binding protein YPT3; H-YPT3; Ras-related protein Rab-11B RAB25: RAB11C; CATX-8; Ras-related protein Rab-25 Application Instructions Application table Application Dilution IHC-Fr 1:100 - 1:400 IHC-P 1:100 - 1:400 WB 1:250 - 1:2000 Application Note IHC-P: Antigen Retrieval: Heat mediation was recommended. * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Positive Control Hepa cell lysate Calculated Mw 24 kDa Observed Size ~ 26 kDa Properties Form Liquid Purification Affinity purification with immunogen. Buffer PBS, 0.05% Sodium azide and 20% Glycerol. Preservative 0.05% Sodium azide www.arigobio.com 1/3 Stabilizer 20% Glycerol Concentration 3 mg/ml Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. For long-term storage, aliquot and store at -20°C. Storage in frost free freezers is not recommended. Avoid repeated freeze/thaw cycles. Suggest spin the vial prior to opening. The antibody solution should be gently mixed before use. Note For laboratory research only, not for drug, diagnostic or other use. -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Annexina7 and CAP1 Are Associated with Regulating Tumor Cell Adhesion Molecule Expression and Biological Behavior
AnnexinA7 and CAP1 are associated with regulating tumor cell adhesion molecule expression and biological behavior Type Research paper Keywords hepatocellular carcinoma, adhesion molecule, AnnexinA7, CAP1, Biological behaviors Abstract Introduction To find out the correlations between the effects of down-regulating AnnexinA7 and CAP1 gene on cell adhesion factors and the biological behavior of Hca-p cells cells, and finally infer the relationship between the two genes. Material and methods Western blot ,qRT-PCR,immunocytochemistry, CCK8 cell proliferation, flow cytometry, lymph node adhesion and transwell chamber assay testing . Results AnnexinA7 and CAP1 were consistent with the regulation of the expression of the adhesion molecules such as FAK, Src, Paxillin and E-cadherin. At the mRNA and protein levels, the expression of FAK, Src and Paxillin were increased with down-regulated AnnexinA7 and CAP1 genes, while E-cadherin was down-regulated in the change of these two genes. And the low expression of AnnexinA7 could affect the expression of CAP1 in mRNA and protein levels. otherwise, the localization of AnnexinA7 and CAP1 in hepatocellular carcinoma cells was also the same. After down-regulating the expression of CAP1, the functions of proliferation, lymph node adhesion and invasion were increased and earlyPreprint apoptotic ability was decreased in Hca-P cells. Conclusions AnnexinA7 and CAP1 could control the expression of these adhesion molecules in the same trend. We speculated they may be co-localization. And AnnexinA7 gene may be related to the molecular mechanism of CAP1 gene, which is likely to have a consistent effect on cell adhesion molecules and be closely related to the biological behaviors of Hca-P cells.AnnexinA7 and CAP1 may play an inhibitory role in lymph node metastasis to provide a reliable basis for the early identification of lymphatic metastasis in hepatocellular carcinoma. -
The N-Cadherin Interactome in Primary Cardiomyocytes As Defined Using Quantitative Proximity Proteomics Yang Li1,*, Chelsea D
© 2019. Published by The Company of Biologists Ltd | Journal of Cell Science (2019) 132, jcs221606. doi:10.1242/jcs.221606 TOOLS AND RESOURCES The N-cadherin interactome in primary cardiomyocytes as defined using quantitative proximity proteomics Yang Li1,*, Chelsea D. Merkel1,*, Xuemei Zeng2, Jonathon A. Heier1, Pamela S. Cantrell2, Mai Sun2, Donna B. Stolz1, Simon C. Watkins1, Nathan A. Yates1,2,3 and Adam V. Kwiatkowski1,‡ ABSTRACT requires multiple adhesion, cytoskeletal and signaling proteins, The junctional complexes that couple cardiomyocytes must transmit and mutations in these proteins can cause cardiomyopathies (Ehler, the mechanical forces of contraction while maintaining adhesive 2018). However, the molecular composition of ICD junctional homeostasis. The adherens junction (AJ) connects the actomyosin complexes remains poorly defined. – networks of neighboring cardiomyocytes and is required for proper The core of the AJ is the cadherin catenin complex (Halbleib and heart function. Yet little is known about the molecular composition of the Nelson, 2006; Ratheesh and Yap, 2012). Classical cadherins are cardiomyocyte AJ or how it is organized to function under mechanical single-pass transmembrane proteins with an extracellular domain that load. Here, we define the architecture, dynamics and proteome of mediates calcium-dependent homotypic interactions. The adhesive the cardiomyocyte AJ. Mouse neonatal cardiomyocytes assemble properties of classical cadherins are driven by the recruitment of stable AJs along intercellular contacts with organizational and cytosolic catenin proteins to the cadherin tail, with p120-catenin β structural hallmarks similar to mature contacts. We combine (CTNND1) binding to the juxta-membrane domain and -catenin β quantitative mass spectrometry with proximity labeling to identify the (CTNNB1) binding to the distal part of the tail. -
Function of Deptor and Its Roles in Hematological Malignancies
www.aging-us.com AGING 2021, Vol. 13, No. 1 Review Function of Deptor and its roles in hematological malignancies Mario Morales-Martinez1, Alan Lichtenstein2, Mario I. Vega1,2 1Molecular Signal Pathway in Cancer Laboratory, UIMEO, Oncology Hospital, Siglo XXI National Medical Center, IMSS, México, México 2Department of Medicine, Hematology-Oncology Division, Greater Los Angeles VA Healthcare Center, UCLA Medical Center, Jonsson Comprehensive Cancer Center, Los Angeles, CA 90024, USA Correspondence to: Mario I. Vega; email: [email protected] Keywords: Deptor, Multiple Myeloma, leukemia, Non-Hodgkin Lymphoma, hematological malignances Received: November 6, 2020 Accepted: December 10, 2020 Published: January 7, 2020 Copyright: © 2020 Morales-Martinez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Deptor is a protein that interacts with mTOR and that belongs to the mTORC1 and mTORC2 complexes. Deptor is capable of inhibiting the kinase activity of mTOR. It is well known that the mTOR pathway is involved in various signaling pathways that are involved with various biological processes such as cell growth, apoptosis, autophagy, and the ER stress response. Therefore, Deptor, being a natural inhibitor of mTOR, has become very important in its study. Because of this, it is important to research its role regarding the development and progression of human malignancies, especially in hematologic malignancies. Due to its variation in expression in cancer, it has been suggested that Deptor can act as an oncogene or tumor suppressor depending on the cellular or tissue context. -
Trop2 and Its Overexpression in Cancers: Regulation and Clinical/ Therapeutic Implications
www.impactjournals.com/Genes&Cancer Genes & Cancer, Vol. 6 (3-4), March 2015 Trop2 and its overexpression in cancers: regulation and clinical/ therapeutic implications Anna Shvartsur1 and Benjamin Bonavida1 1 Department of Microbiology, Immunology and Molecular Genetics, Jonsson Comprehensive Cancer Center and David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, USA Correspondence to: Benjamin Bonavida, email: [email protected] Keywords: cancer, prognosis, resistance, signaling, Trop2 Received: September 29, 2014 Accepted: October 19, 2014 Published: October 19, 2014 This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Trop2 is a transmembrane glycoprotein encoded by the Tacstd2 gene. It is an intracellular calcium signal transducer that is differentially expressed in many cancers. It signals cells for self-renewal, proliferation, invasion, and survival. It has stem cell-like qualities. Trop2 is expressed in many normal tissues, though in contrast, it is overexpressed in many cancers and the overexpression of Trop2 is of prognostic significance. Several ligands have been proposed that interact with Trop2. Trop2 signals the cells via different pathways and it is transcriptionally regulated by a complex network of several transcription factors. Trop2 expression in cancer cells has been correlated with drug resistance. Several strategies target Trop2 on cancer cells that include antibodies, antibody fusion proteins, chemical inhibitors, nanoparticles, etc. The in vitro studies and pre-clinical studies, using these various therapeutic treatments, have resulted in significant inhibition of tumor cell growth both in vitro and in vivo in mice. -
Original Article Mining Expression and Prognosis of TACSTD2 and SPP1 in Thyroid Carcinoma by Using Oncomine and Kaplan-Meier Plotter Databases
Int J Clin Exp Med 2019;12(9):11231-11240 www.ijcem.com /ISSN:1940-5901/IJCEM0094709 Original Article Mining expression and prognosis of TACSTD2 and SPP1 in thyroid carcinoma by using Oncomine and Kaplan-Meier plotter databases Qing Chang1, Mingda You1, Cui Li2 1Department of Head and Neck Surgery, Tangshan Worker Hospital of Hebei Province, Tangshan 063000, Hebei Province, PR China; 2Department of Neurosurgery, Yanghe People’s Hospital, Suqian 223800, Jiangsu Province, PR China Received April 1, 2019; Accepted June 11, 2019; Epub September 15, 2019; Published September 30, 2019 Abstract: Objective: To further investigate TACSTD2 and SPP1 gene mRNA expression in thyroid carcinoma and their association with patients’ prognosis and clinical pathological characteristics by data mining of the Oncomine and Kaplan-Meier plotter databases. Methods: TACSTD2 and SPP1 mRNA expression data from thyroid carcinoma were retrieved from the Oncomine database and further analyzed by comparing tumor tissue with corresponding normal tissue. The prognostic significance of TACSTD2 and SPP1 mRNA in thyroid carcinoma were evaluated by the online survival analysis tool “Kaplan-Meier Plotter” (KM plotter) database. Fifty-one patients with thyroid carcinoma who received surgery were retrospectively analyzed. The TACSTD2 and SPP1 protein expression in cancer tissue and nor- mal thyroid tissue were examined by immunohistochemical assay. The correlation between TACSTD2, SPP1 protein expression and patients’ clinicopathological characteristics were also evaluated. Results: Four analyses compared the TACSTD2 gene expression between thyroid cancer and normal tissue were included in the present work. The pooled results showed that TACSTD2 mRNA expression levels in thyroid carcinoma tissue was significantly higher than that of normal thyroid tissue (p=0.003). -
CRAVAT 4: Cancer-Related Analysis of Variants Toolkit David L
Cancer Focus on Computer Resources Research CRAVAT 4: Cancer-Related Analysis of Variants Toolkit David L. Masica1,2, Christopher Douville1,2, Collin Tokheim1,2, Rohit Bhattacharya2,3, RyangGuk Kim4, Kyle Moad4, Michael C. Ryan4, and Rachel Karchin1,2,5 Abstract Cancer sequencing studies are increasingly comprehensive and level interpretation, including joint prioritization of all nonsilent well powered, returning long lists of somatic mutations that can be mutation consequence types, and structural and mechanistic visu- difficult to sort and interpret. Diligent analysis and quality control alization. Results from CRAVAT submissions are explored in an can require multiple computational tools of distinct utility and interactive, user-friendly web environment with dynamic filtering producing disparate output, creating additional challenges for the and sorting designed to highlight the most informative mutations, investigator. The Cancer-Related Analysis of Variants Toolkit (CRA- even in the context of very large studies. CRAVAT can be run on a VAT) is an evolving suite of informatics tools for mutation inter- public web portal, in the cloud, or downloaded for local use, and is pretation that includes mutation mapping and quality control, easily integrated with other methods for cancer omics analysis. impact prediction and extensive annotation, gene- and mutation- Cancer Res; 77(21); e35–38. Ó2017 AACR. Background quickly returning mutation interpretations in an interactive and user-friendly web environment for sorting, visualizing, and An investigator's work is far from over when results are returned inferring mechanism. CRAVAT (see Supplementary Video) is from the sequencing center. Depending on the service, genetic suitable for large studies (e.g., full-exome and large cohorts) mutation calls can require additional mapping to include all and small studies (e.g., gene panel or single patient), performs relevant RNA transcripts or correct protein sequences. -
S41467-020-18249-3.Pdf
ARTICLE https://doi.org/10.1038/s41467-020-18249-3 OPEN Pharmacologically reversible zonation-dependent endothelial cell transcriptomic changes with neurodegenerative disease associations in the aged brain Lei Zhao1,2,17, Zhongqi Li 1,2,17, Joaquim S. L. Vong2,3,17, Xinyi Chen1,2, Hei-Ming Lai1,2,4,5,6, Leo Y. C. Yan1,2, Junzhe Huang1,2, Samuel K. H. Sy1,2,7, Xiaoyu Tian 8, Yu Huang 8, Ho Yin Edwin Chan5,9, Hon-Cheong So6,8, ✉ ✉ Wai-Lung Ng 10, Yamei Tang11, Wei-Jye Lin12,13, Vincent C. T. Mok1,5,6,14,15 &HoKo 1,2,4,5,6,8,14,16 1234567890():,; The molecular signatures of cells in the brain have been revealed in unprecedented detail, yet the ageing-associated genome-wide expression changes that may contribute to neurovas- cular dysfunction in neurodegenerative diseases remain elusive. Here, we report zonation- dependent transcriptomic changes in aged mouse brain endothelial cells (ECs), which pro- minently implicate altered immune/cytokine signaling in ECs of all vascular segments, and functional changes impacting the blood–brain barrier (BBB) and glucose/energy metabolism especially in capillary ECs (capECs). An overrepresentation of Alzheimer disease (AD) GWAS genes is evident among the human orthologs of the differentially expressed genes of aged capECs, while comparative analysis revealed a subset of concordantly downregulated, functionally important genes in human AD brains. Treatment with exenatide, a glucagon-like peptide-1 receptor agonist, strongly reverses aged mouse brain EC transcriptomic changes and BBB leakage, with associated attenuation of microglial priming. We thus revealed tran- scriptomic alterations underlying brain EC ageing that are complex yet pharmacologically reversible. -
Oxidative Stress Activates SIRT2 to Deacetylate and Stimulate Phosphoglycerate Mutase
Published OnlineFirst May 1, 2014; DOI: 10.1158/0008-5472.CAN-13-3615 Cancer Tumor and Stem Cell Biology Research Oxidative Stress Activates SIRT2 to Deacetylate and Stimulate Phosphoglycerate Mutase Yanping Xu2,3, Fulong Li2,3, Lei Lv1,2, Tingting Li2,3, Xin Zhou2,3, Chu-Xia Deng4, Kun-Liang Guan1,2,5, Qun-Ying Lei1,2, and Yue Xiong1,2,6 Abstract Glycolytic enzyme phosphoglycerate mutase (PGAM) plays an important role in coordinating energy production with generation of reducing power and the biosynthesis of nucleotide precursors and amino acids. Inhibition of PGAM by small RNAi or small molecule attenuates cell proliferation and tumor growth. PGAM activity is commonly upregulated in tumor cells, but how PGAM activity is regulated in vivo remains poorly understood. Here we report that PGAM is acetylated at lysine 100 (K100), an active site residue that is invariably conserved from bacteria, to yeast, plant, and mammals. K100 acetylation is detected in fly, mouse, and human cells and in multiple tissues and decreases PGAM2 activity. The cytosolic protein deacetylase sirtuin 2 (SIRT2) deacetylates and activates PGAM2. Increased levels of reactive oxygen species stimulate PGAM2 deacetylation and activity by promoting its interaction with SIRT2. Substitution of endogenous PGAM2 with an acetylation mimetic mutant K100Q reduces cellular NADPH production and inhibits cell proliferation and tumor growth. These results reveal a mechanism of PGAM2 regulation and NADPH homeostasis in response to oxidative stress that impacts cell proliferation and tumor growth. Cancer Res; 74(13); 1–13. Ó2014 AACR. Introduction contains two PGAM genes, PGAM1 (also known as PGAM-B), Enhanced glycolysis, commonly referred to as the "Warburg which is expressed in brain and most other tissues, and PGAM2 effect" (1), is a distinctive and prominent feature of cancer cells. -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig.