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UALCAN:一个促进肿瘤亚组基因表达和生存分析的平台。

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

作者信息

Chandrashekar Darshan S, Bashel Bhuwan, Balasubramanya Sai Akshaya Hodigere, Creighton Chad J, Ponce-Rodriguez Israel, Chakravarthi Balabhadrapatruni V S K, Varambally Sooryanarayana

机构信息

Molecular and Cellular Pathology, Department of Pathology, University of Alabama at Birmingham; Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL 35233, USA.

Molecular and Cellular Pathology, Department of Pathology, University of Alabama at Birmingham.

出版信息

Neoplasia. 2017 Aug;19(8):649-658. doi: 10.1016/j.neo.2017.05.002. Epub 2017 Jul 18.

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.

摘要

来自癌症基因组图谱(TCGA)项目的基因组学数据已实现对多种癌症类型的全面分子特征描述。TCGA中的大量样本为解决与肿瘤异质性相关的问题提供了绝佳机会。癌症研究人员和临床医生对这些数据进行探索,对于挖掘新的治疗/诊断生物标志物至关重要。已经开发了各种计算工具来帮助研究人员进行特定的TCGA数据分析;然而,需要有资源来促进对肿瘤间基因表达变异和生存关联的研究。在此,我们报告了UALCAN,这是一个易于使用的交互式网络门户,用于对TCGA基因表达数据进行深入分析。UALCAN使用来自31种癌症类型的TCGA 3级RNA测序和临床数据。该门户的用户友好功能允许进行:1)分析查询基因在肿瘤和正常样本中的相对表达,以及在基于个体癌症阶段、肿瘤分级、种族、体重或其他临床病理特征的各种肿瘤亚组中的相对表达;2)评估基因表达水平和临床病理特征对患者生存的影响;3)识别个别癌症类型中表达最高和最低(上调和下调)的基因。该资源可作为一个平台,用于在计算机上验证靶基因并识别肿瘤亚组特异性候选生物标志物。因此,UALCAN网络门户在加速癌症研究方面可能会非常有帮助。UALCAN可在http://ualcan.path.uab.edu上公开获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ebd8/5516091/3f4f5c6095da/gr3.jpg

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