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      UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses 1

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          Abstract

          Genomics data from The Cancer Genome Atlas (TCGA) project has led to the comprehensive molecular characterization of multiple cancer types. The large sample numbers in TCGA offer an excellent opportunity to address questions associated with tumo heterogeneity. Exploration of the data by cancer researchers and clinicians is imperative to unearth novel therapeutic/diagnostic biomarkers. Various computational tools have been developed to aid researchers in carrying out specific TCGA data analyses; however there is need for resources to facilitate the study of gene expression variations and survival associations across tumors. Here, we report UALCAN, an easy to use, interactive web-portal to perform to in-depth analyses of TCGA gene expression data. UALCAN uses TCGA level 3 RNA-seq and clinical data from 31 cancer types. The portal's user-friendly features allow to perform: 1) analyze relative expression of a query gene(s) across tumor and normal samples, as well as in various tumor sub-groups based on individual cancer stages, tumor grade, race, body weight or other clinicopathologic features, 2) estimate the effect of gene expression level and clinicopathologic features on patient survival; and 3) identify the top over- and under-expressed (up and down-regulated) genes in individual cancer types. This resource serves as a platform for in silico validation of target genes and for identifying tumor sub-group specific candidate biomarkers. Thus, UALCAN web-portal could be extremely helpful in accelerating cancer research. UALCAN is publicly available at http://ualcan.path.uab.edu.

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          Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

          The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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            Oncomine 3.0: genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles.

            DNA microarrays have been widely applied to cancer transcriptome analysis; however, the majority of such data are not easily accessible or comparable. Furthermore, several important analytic approaches have been applied to microarray analysis; however, their application is often limited. To overcome these limitations, we have developed Oncomine, a bioinformatics initiative aimed at collecting, standardizing, analyzing, and delivering cancer transcriptome data to the biomedical research community. Our analysis has identified the genes, pathways, and networks deregulated across 18,000 cancer gene expression microarrays, spanning the majority of cancer types and subtypes. Here, we provide an update on the initiative, describe the database and analysis modules, and highlight several notable observations. Results from this comprehensive analysis are available at http://www.oncomine.org.
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              High-throughput sequencing technologies.

              The human genome sequence has profoundly altered our understanding of biology, human diversity, and disease. The path from the first draft sequence to our nascent era of personal genomes and genomic medicine has been made possible only because of the extraordinary advancements in DNA sequencing technologies over the past 10 years. Here, we discuss commonly used high-throughput sequencing platforms, the growing array of sequencing assays developed around them, as well as the challenges facing current sequencing platforms and their clinical application. Copyright © 2015 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Neoplasia
                Neoplasia
                Neoplasia (New York, N.Y.)
                Neoplasia Press
                1522-8002
                1476-5586
                18 July 2017
                August 2017
                18 July 2017
                : 19
                : 8
                : 649-658
                Affiliations
                [* ]Molecular and Cellular Pathology, Department of Pathology, University of Alabama at Birmingham
                []Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL 35233, USA
                []Department of Medicine, Dan L. Duncan Comprehensive Cancer Center, and Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
                Author notes
                [* ]Address all correspondence to: Sooryanarayana Varambally, PhD, Molecular and Cellular Pathology, Department of Pathology, Wallace Tumor Institute, Room # 420B, University of Alabama at Birmingham, Birmingham, AL 35233, USA.Molecular and Cellular Pathology, Department of PathologyWallace Tumor InstituteUniversity of Alabama at BirminghamRoom # 420BBirminghamAL35233USA soorya@ 123456uab.edu
                Article
                S1476-5586(17)30179-3
                10.1016/j.neo.2017.05.002
                5516091
                28732212
                9cccb6bf-9b02-4c39-b5bd-3fdbf3fb6d3e
                © 2017 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 19 April 2017
                : 12 May 2017
                : 15 May 2017
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