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      Distinct roles and differential expression levels of Wnt5a mRNA isoforms in colorectal cancer cells

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          Abstract

          The canonical Wnt/β-catenin pathway is constitutively activated in more than 90% of colorectal cancer (CRC) cases in which β-catenin contributes to CRC cell growth and survival. In contrast to the Wnt/β-catenin pathway, the non-canonical Wnt pathway can antagonize functions of the canonical Wnt/β-catenin pathway. Wnt5a is a key factor in the non-canonical Wnt pathway, and it plays diverse roles in different types of cancers. It was shown that reintroducing Wnt5a into CRC cells resulted in inhibited cell proliferation and impaired cell motility. However, contradictory results were reported describing increased Wnt5a expression being associated with a poor prognosis of CRC patients. Recently, it was shown that the diverse roles of Wnt5a are due to two distinct roles of Wnt5a isoforms. However, the exact roles and functions of the Wnt5a isoforms in CRC remain largely unclear. The present study for the first time showed the ambiguous role of Wnt5a in CRC was due to the encoding of distinct roles of the various Wnt5a mRNA isoforms. A relatively high expression level of the Wnt5a-short (S) isoform transcript and a low expression level of the Wnt5a-long (L) isoform transcript were detected in CRC cell lines and specimens. In addition, high expression levels of the Wnt5a-S mRNA isoform and low expression levels of the Wnt5a-L mRNA isoform were significantly positively correlated with tumor depth of CRC patients. Furthermore, knockdown of the endogenous expression of the Wnt5a-S mRNA isoform in HCT116 cells drastically inhibited their growth ability by inducing apoptosis through induction of FASLG expression and reduction of TNFRSF11B expression. Moreover, reactivation of methylation inactivation of the Wnt5a-L mRNA isoform by treatment with 5-azacytidine (5-Aza) enhanced the siWnt5a-S isoform's ability to induce apoptosis. Finally, we showed that the simultaneous reactivation of Wnt5a-L mRNA isoform and knockdown of Wnt5a-S mRNA isoform expression enhanced siWnt5a-S isoform-induced apoptosis and siWnt5a-L isoform-regulated suppression of β-catenin expression in vitro. High expression levels of the Wnt5a-S mRNA isoform and low expression levels of the Wnt5a-L mRNA isoform were significantly positively correlated with high mRNA levels of β-catenin detection in vivo. Altogether, our study showed that, for the first time, different Wnt5a mRNA isoforms play distinct roles in CRC and can be used as novel prognostic markers for CRC in the future.

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          SurvExpress: An Online Biomarker Validation Tool and Database for Cancer Gene Expression Data Using Survival Analysis

          Validation of multi-gene biomarkers for clinical outcomes is one of the most important issues for cancer prognosis. An important source of information for virtual validation is the high number of available cancer datasets. Nevertheless, assessing the prognostic performance of a gene expression signature along datasets is a difficult task for Biologists and Physicians and also time-consuming for Statisticians and Bioinformaticians. Therefore, to facilitate performance comparisons and validations of survival biomarkers for cancer outcomes, we developed SurvExpress, a cancer-wide gene expression database with clinical outcomes and a web-based tool that provides survival analysis and risk assessment of cancer datasets. The main input of SurvExpress is only the biomarker gene list. We generated a cancer database collecting more than 20,000 samples and 130 datasets with censored clinical information covering tumors over 20 tissues. We implemented a web interface to perform biomarker validation and comparisons in this database, where a multivariate survival analysis can be accomplished in about one minute. We show the utility and simplicity of SurvExpress in two biomarker applications for breast and lung cancer. Compared to other tools, SurvExpress is the largest, most versatile, and quickest free tool available. SurvExpress web can be accessed in http://bioinformatica.mty.itesm.mx/SurvExpress (a tutorial is included). The website was implemented in JSP, JavaScript, MySQL, and R.
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            Modelling glandular epithelial cancers in three-dimensional cultures.

            Little is known about how the genotypic and molecular abnormalities associated with epithelial cancers actually contribute to the histological phenotypes observed in tumours in vivo. 3D epithelial culture systems are a valuable tool for modelling cancer genes and pathways in a structurally appropriate context. Here, we review the important features of epithelial structures grown in 3D basement membrane cultures, and how such models have been used to investigate the mechanisms associated with tumour initiation and progression.
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              Modeling Oncogenic Signaling in Colon Tumors by Multidirectional Analyses of Microarray Data Directed for Maximization of Analytical Reliability

              Background Clinical progression of colorectal cancers (CRC) may occur in parallel with distinctive signaling alterations. We designed multidirectional analyses integrating microarray-based data with biostatistics and bioinformatics to elucidate the signaling and metabolic alterations underlying CRC development in the adenoma-carcinoma sequence. Methodology/Principal Findings Studies were performed on normal mucosa, adenoma, and carcinoma samples obtained during surgery or colonoscopy. Collections of cryostat sections prepared from the tissue samples were evaluated by a pathologist to control the relative cell type content. The measurements were done using Affymetrix GeneChip HG-U133plus2, and probe set data was generated using two normalization algorithms: MAS5.0 and GCRMA with least-variant set (LVS). The data was evaluated using pair-wise comparisons and data decomposition into singular value decomposition (SVD) modes. The method selected for the functional analysis used the Kolmogorov-Smirnov test. Expressional profiles obtained in 105 samples of whole tissue sections were used to establish oncogenic signaling alterations in progression of CRC, while those representing 40 microdissected specimens were used to select differences in KEGG pathways between epithelium and mucosa. Based on a consensus of the results obtained by two normalization algorithms, and two probe set sorting criteria, we identified 14 and 17 KEGG signaling and metabolic pathways that are significantly altered between normal and tumor samples and between benign and malignant tumors, respectively. Several of them were also selected from the raw microarray data of 2 recently published studies (GSE4183 and GSE8671). Conclusion/Significance Although the proposed strategy is computationally complex and labor–intensive, it may reduce the number of false results.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysis
                Role: Data curationRole: Formal analysisRole: Methodology
                Role: Data curationRole: Formal analysisRole: Methodology
                Role: Formal analysisRole: Software
                Role: MethodologyRole: Resources
                Role: Resources
                Role: Resources
                Role: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Project administrationRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                31 August 2017
                2017
                : 12
                : 8
                : e0181034
                Affiliations
                [1 ] Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
                [2 ] Cellular Pathobiology Section, Intramural Research Program, National Institute on Drug Abuse, Rockville, Maryland, United States of America
                [3 ] Graduate Institute of Translational Medicine, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
                [4 ] Graduate Institute of Neural Regenerative Medicine, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
                [5 ] Institute of Bioinformatics and Biosignal Transduction, College of Bioscience and Biotechnology, National Cheng Kung University, Tainan, Taiwan
                [6 ] Cancer Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan
                National Cancer Center, JAPAN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-6354-3315
                Article
                PONE-D-17-00466
                10.1371/journal.pone.0181034
                5578641
                28859077
                7657ab70-219d-4515-b0f0-e840a07f1c37
                © 2017 Huang et al

                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.

                History
                : 4 January 2017
                : 26 June 2017
                Page count
                Figures: 7, Tables: 3, Pages: 19
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100004663, Ministry of Science and Technology, Taiwan;
                Award ID: MOST103-2320-B-038-051, MOST104-2320-B-038-006, and MOST 105-2320-B-038-005
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100004700, Taipei Medical University;
                Award ID: TMU103-AE2-I04-5, TMU104-AE2-I02-5, and TMU105-AE2-I03-5
                Award Recipient :
                Funded by: Research Team of Prevention and Therapy of Colorectal Cancer at Taipei Medical University
                Award ID: TMU-T104-01
                Award Recipient :
                Funded by: Health and Welfare Surcharge of Tobacco Products
                Award ID: MOHW105-TDU-B-212-134001, MOHW106-TDU-B-212-144001
                Funded by: funder-id http://dx.doi.org/10.13039/100008903, Ministry of Health and Welfare;
                Award ID: MOHW103-TD-B-111-01, MOHW103-TDU-212-114006, and MOHW103-TDU-B-212-113001
                The authors received no specific funding for this work.
                Categories
                Research Article
                Medicine and Health Sciences
                Oncology
                Cancers and Neoplasms
                Colorectal Cancer
                Biology and Life Sciences
                Genetics
                Gene Expression
                Biology and Life Sciences
                Cell Biology
                Cell Processes
                Cell Death
                Apoptosis
                Biology and life sciences
                Genetics
                Gene expression
                Gene regulation
                Small interfering RNAs
                Biology and life sciences
                Biochemistry
                Nucleic acids
                RNA
                Non-coding RNA
                Small interfering RNAs
                Biology and life sciences
                Biochemistry
                Nucleic acids
                RNA
                Messenger RNA
                Biology and Life Sciences
                Molecular Biology
                Molecular Biology Techniques
                Molecular Biology Assays and Analysis Techniques
                Gene Expression and Vector Techniques
                Protein Expression
                Research and Analysis Methods
                Molecular Biology Techniques
                Molecular Biology Assays and Analysis Techniques
                Gene Expression and Vector Techniques
                Protein Expression
                Biology and Life Sciences
                Molecular Biology
                Molecular Biology Techniques
                Transfection
                Research and Analysis Methods
                Molecular Biology Techniques
                Transfection
                Medicine and Health Sciences
                Oncology
                Cancer Treatment
                Custom metadata
                Some data are provided as Supporting Information. Additional data are available from Survexpress. Survexpress includes public microarray datasets with clinical annotation of gene expression and prognosis from Gene Expression Omnibus (GEO) and TCGA database ( http://bioinformatica.mty.itesm.mx:8080/Biomatec/SurvivaX.jsp). In the input page, interested researcher query FASLG and TNFRSF11B genes and select the colon metabase tissue dataset. The results are displayed in common and flexible publication-ready plots within the analysis page (FASLG and TNFRSF11B mRNA expressions by risk group of Fig 5C, and disease specific survival analysis for FASLG and TNFRSF11B genes of Fig 5D).

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