1 Integrin to Regulate Cell Proliferation and Adhesion in Colorectal Cancer Cells Causing Liver Metastasis
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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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. -
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, -
Learning from Cadherin Structures and Sequences: Affinity Determinants and Protein Architecture
Learning from cadherin structures and sequences: affinity determinants and protein architecture Klára Fels ıvályi Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2014 Klara Felsovalyi All rights reserved ABSTRACT Learning from cadherin structures and sequences: affinity determinants and protein architecture Klara Felsovalyi Cadherins are a family of cell-surface proteins mediating adhesion that are important in development and maintenance of tissues. The family is defined by the repeating cadherin domain (EC) in their extracellular region, but they are diverse in terms of protein size, architecture and cellular function. The best-understood subfamily is the type I classical cadherins, which are found in vertebrates and have five EC domains. Among the five different type I classical cadherins, the binding interactions are highly specific in their homo- and heterophilic binding affinities, though their sequences are very similar. As previously shown, E- and N-cadherins, two prototypic members of the subfamily, differ in their homophilic K D by about an order of magnitude, while their heterophilic affinity is intermediate. To examine the source of the binding affinity differences among type I cadherins, we used crystal structures, analytical ultracentrifugation (AUC), surface plasmon resonance (SPR), and electron paramagnetic resonance (EPR) studies. Phylogenetic analysis and binding affinity behavior show that the type I cadherins can be further divided into two subgroups, with E- and N-cadherin representing each. In addition to the affinity differences in their wild-type binding through the strand-swapped interface, a second interface also shows an affinity difference between E- and N-cadherin. -
Pan-Cancer Genomic Amplifications Underlie a WNT Hyperactivation Phenotype Associated with Stem Cell-Like Features Leading to Po
1 Pan-cancer genomic amplifications underlie a WNT hyperactivation phenotype 2 associated with stem cell-like features leading to poor prognosis 3 4 5 6 Running title: Prognosis of a 16-gene signature of WNT hyperactivation in six cancers 7 8 Wai Hoong Chang and Alvina G. Lai 9 10 11 Nuffield Department of Medicine, University of Oxford, 12 Old Road Campus, OX3 7FZ, United Kingdom 13 14 For correspondence: [email protected] 15 List of Abbreviations 16 TCGA The Cancer Genome Atlas KEGG Kyoto Encyclopedia of Genes and Genomes GO Gene Ontology ROC Receiver operating characteristic AUC Area under the curve HR Hazard ratio TNM Tumor, node and metastasis HIF Hypoxia inducible factor TF Transcription factor EMT Epithelial-to-mesenchymal transition 17 18 Abstract 19 20 Cancer stem cells pose significant obstacles to curative treatment contributing to tumor 21 relapse and poor prognosis. They share many signaling pathways with normal stem cells that 22 control cell proliferation, self-renewal and cell fate determination. One of these pathways 23 known as Wnt is frequently implicated in carcinogenesis where Wnt hyperactivation is seen in 24 cancer stem cells. Yet, the role of conserved genomic alterations in Wnt genes driving tumor 25 progression across multiple cancer types remains to be elucidated. In an integrated pan-cancer 26 study involving 21 cancers and 18,484 patients, we identified a core Wnt signature of 16 genes 27 that showed high frequency of somatic amplifications linked to increased transcript 28 expression. The signature successfully predicted overall survival rates in six cancer cohorts 29 (n=3,050): bladder (P=0.011), colon (P=0.013), head and neck (P=0.026), pan-kidney 30 (P<0.0001), clear cell renal cell (P<0.0001) and stomach (P=0.032). -
Molecular Characteristics of Circulating Tumor Cells Resemble the Liver Metastasis More Closely Than the Primary Tumor in Metastatic Colorectal Cancer
www.impactjournals.com/oncotarget/ Oncotarget, Vol. 7, No. 37 Research Paper Molecular characteristics of circulating tumor cells resemble the liver metastasis more closely than the primary tumor in metastatic colorectal cancer Wendy Onstenk1, Anieta M. Sieuwerts1, Bianca Mostert1, Zarina Lalmahomed2, Joan B. Bolt-de Vries1, Anne van Galen1, Marcel Smid1, Jaco Kraan1, Mai Van1, Vanja de Weerd1, Raquel Ramírez-Moreno1, Katharina Biermann3, Cornelis Verhoef2, Dirk J. Grünhagen2, Jan N.M. IJzermans2, Jan W. Gratama1, John W.M. Martens1, John A. Foekens1, Stefan Sleijfer1 1Erasmus MC Cancer Institute, Department of Medical Oncology and Cancer Genomics Netherlands, Rotterdam, The Netherlands 2Department of Surgery, Erasmus University Medical Center, Rotterdam, The Netherlands 3Department of Pathology, Erasmus University Medical Center, Rotterdam, The Netherlands Correspondence to: Wendy Onstenk, email: [email protected] Keywords: circulating tumor cells, CTCs, CellSearch, colorectal cancer, gene expression profiling Received: April 06, 2016 Accepted: May 29, 2016 Published: June 20, 2016 ABSTRACT Background: CTCs are a promising alternative for metastatic tissue biopsies for use in precision medicine approaches. We investigated to what extent the molecular characteristics of circulating tumor cells (CTCs) resemble the liver metastasis and/ or the primary tumor from patients with metastatic colorectal cancer (mCRC). Results: The CTC profiles were concordant with the liver metastasis in 17/23 patients (74%) and with the primary tumor in 13 patients (57%). The CTCs better resembled the liver metastasis in 13 patients (57%), and the primary tumor in five patients (22%). The strength of the correlations was not associated with clinical parameters. Nine genes (CDH1, CDH17, CDX1, CEACAM5, FABP1, FCGBP, IGFBP3, IGFBP4, and MAPT) displayed significant differential expressions, all of which were downregulated, in CTCs compared to the tissues in the 23 patients. -