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      An Integrated Bioinformatics Analysis Repurposes an Antihelminthic Drug Niclosamide for Treating HMGA2-Overexpressing Human Colorectal Cancer

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          Abstract

          Aberrant overexpression of high mobility group AT-hook 2 (HMGA2) is frequently found in cancers and HMGA2 has been considered an anticancer therapeutic target. In this study, a pan-cancer genomics survey based on Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Atlas (TCGA) data indicated that HMGA2 was mainly overexpressed in gastrointestinal cancers including colorectal cancer. Intriguingly, HMGA2 overexpression had no prognostic impacts on cancer patients’ overall and disease-free survivals. In addition, HMGA2-overexpressing colorectal cancer cell lines did not display higher susceptibility to a previously identified HMGA2 inhibitor (netroposin). By microarray profiling of HMGA2-driven gene signature and subsequent Connectivity Map (CMap) database mining, we identified that S100 calcium-binding protein A4 (S100A4) may be a druggable vulnerability for HMGA2-overexpressing colorectal cancer. A repurposing S100A4 inhibitor, niclosamide, was found to reverse the HMGA2-driven gene signature both in colorectal cancer cell lines and patients’ tissues. In vitro and in vivo experiments validated that HMGA2-overexpressing colorectal cancer cells were more sensitive to niclosamide. However, inhibition of S100A4 by siRNAs and other inhibitors was not sufficient to exert effects like niclosamide. Further RNA sequencing analysis identified that niclosamide inhibited more cell-cycle-related gene expression in HMGA2-overexpressing colorectal cancer cells, which may explain its selective anticancer effect. Together, our study repurposes an anthelminthic drug niclosamide for treating HMGA2-overexpression colorectal cancer.

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          BioGPS: building your own mash-up of gene annotations and expression profiles

          BioGPS (http://biogps.org) is a centralized gene-annotation portal that enables researchers to access distributed gene annotation resources. This article focuses on the updates to BioGPS since our last paper (2013 database issue). The unique features of BioGPS, compared to those of other gene portals, are its community extensibility and user customizability. Users contribute the gene-specific resources accessible from BioGPS (‘plugins’), which helps ensure that the resource collection is always up-to-date and that it will continue expanding over time (since the 2013 paper, 162 resources have been added, for a 34% increase in the number of resources available). BioGPS users can create their own collections of relevant plugins and save them as customized gene-report pages or ‘layouts’ (since the 2013 paper, 488 user-created layouts have been added, for a 22% increase in the number of layouts). In addition, we recently updated the most popular plugin, the ‘Gene expression/activity chart’, to include ∼6000 datasets (from ∼2000 datasets) and we enhanced user interactivity. We also added a new ‘gene list’ feature that allows users to save query results for future reference.
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            Sequencing technology does not eliminate biological variability

            RNA sequencing has generated much excitement for the advantages offered over microarrays. This excitement has led to a barrage of publications discounting the importance of biological variability; as microarray publications did in the 1990s. By comparing microarray and sequencing data, we demonstrate that expression measurements exhibit biological variability across individuals irrespective of measurement technology. Our analysis suggests RNA-sequencing experiments designed to estimate biological variability are more likely to produce reproducible results.
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              Overexpression of HMGA2 promotes metastasis and impacts survival of colorectal cancers.

              This study aims to address the hypothesis that the high-mobility group A2 (HMGA2), an oncofetal protein, relates to survivability and serves as a prognostic biomarker for colorectal cancer (CRC). This is a retroprospective multiple center study. The HMGA2 expression level was determined by performing immunohistochemistry on surgical tissue samples of 89 CRCs from a training set and 191 CRCs from a validation set. The Kaplan-Meier analysis and COX proportional hazard model were employed to analyze the survivability. Multivariate logistic analysis indicated that the expression of HMGA2 significantly correlates with distant metastasis in training set (odds ratio, OR = 3.53, 95% CI: 1.37-9.70) and validation set (OR = 6.38, 95% CI: 1.47-43.95). Survival analysis revealed that the overexpression of HMGA2 is significantly associated with poor survival of CRC patients (P < 0.05). The adjusted HRs for overall survival were 2.38 (95% CI: 1.30-4.34) and 2.14 (95% CI: 1.21-3.79) in training and validation sets, respectively. Further investigation revealed that HMGA2 delays the clearance of γ-H2AX in HCT-116 and SW480 cells post γ-irradiation, which supports our finding that CRC patients with HMAG2-positive staining in primary tumors had augmented the efficacy of adjuvant radiotherapy (HR = 0.18, 95% CI: 0.04-0.63). Overexpression of HMGA2 is associated with metastasis and unequivocally occurred in parallel with reduced survival rates of patients with CRC. Therefore, HMGA2 may potentially serve as a biomarker for predicting aggressive CRC with poor survivability and as an indicator for better response of radiotherapy. ©2011 AACR.
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                Author and article information

                Journal
                Cancers (Basel)
                Cancers (Basel)
                cancers
                Cancers
                MDPI
                2072-6694
                02 October 2019
                October 2019
                : 11
                : 10
                : 1482
                Affiliations
                [1 ]Department of Radiation Oncology, Yuan’s General Hospital, Kaohsiung 80249, Taiwan; lwan@ 123456ms36.hinet.net
                [2 ]Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan; coll78418@ 123456yahoo.com.tw (C.-J.C.); tsuichin@ 123456tmu.edu.tw (T.-C.H.)
                [3 ]PhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
                [4 ]TMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei 11031, Taiwan
                [5 ]Cancer Center, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan
                Author notes
                [* ]Correspondence: yangpm@ 123456tmu.edu.tw ; Tel.: +886-2-2697-2035 (ext.143)
                Author information
                https://orcid.org/0000-0001-7873-132X
                https://orcid.org/0000-0002-4004-2518
                Article
                cancers-11-01482
                10.3390/cancers11101482
                6826424
                31581665
                c1d6223f-eddc-4978-82df-213132afb9b3
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 30 August 2019
                : 30 September 2019
                Categories
                Article

                bioinformatics,connectivity map,colorectal cancer,drug repurposing,hmga2,s100a4

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