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一种用于评估膀胱癌诊断和预后基因表达生物标志物的在线工具。

An online tool for evaluating diagnostic and prognostic gene expression biomarkers in bladder cancer.

作者信息

Dancik Garrett M

机构信息

Mathematics and Computer Science Department, Eastern Connecticut State University, Science Building, Rm. 257, Willimantic, CT, 06226, USA.

出版信息

BMC Urol. 2015 Jul 1;15:59. doi: 10.1186/s12894-015-0056-z.

Abstract

BACKGROUND

In the past ~15 years, the identification of diagnostic and prognostic biomarkers from gene expression data has increased our understanding of cancer biology and has led to advances in the personalized treatment of many cancers. A diagnostic biomarker is indicative of tumor status such as tumor stage, while a prognostic biomarker is indicative of disease outcome. Despite these advances, however, there are no clinically approved biomarkers for the treatment of bladder cancer, which is the fourth most common cancer in males in the United States and one of the most expensive cancers to treat. Although gene expression profiles of bladder cancer patients are publicly available, biomarker identification requires bioinformatics expertise that is not available to many research laboratories.

DESCRIPTION

We collected gene expression data from 13 publicly available patient cohorts (N = 1454) and developed BC-BET, an online Bladder Cancer Biomarker Evaluation Tool for evaluating candidate diagnostic and prognostic gene expression biomarkers in bladder cancer. A user simply selects a gene, and BC-BET evaluates the utility of that gene's expression as a diagnostic and prognostic biomarker. Specifically, BC-BET calculates how strongly a gene's expression is associated with tumor presence (distinguishing tumor from normal samples), tumor grade (distinguishing low- from high-grade tumors), tumor stage (distinguishing non-muscle invasive from muscle invasive samples), and patient outcome (e.g., disease-specific survival) across all patients in each cohort. Patients with low-grade, non-muscle invasive tumors and patients with high-grade, muscle invasive tumors are also analyzed separately in order to evaluate whether the biomarker of interest has prognostic value independent of grade and stage.

CONCLUSION

Although bladder cancer gene expression datasets are publicly available, their analysis is computationally intensive and requires bioinformatics expertise. BC-BET is an easy-to-use tool for rapidly evaluating bladder cancer gene expression biomarkers across multiple patient cohorts.

摘要

背景

在过去约15年中,从基因表达数据中识别诊断和预后生物标志物增进了我们对癌症生物学的理解,并推动了多种癌症个性化治疗的进展。诊断生物标志物可指示肿瘤状态,如肿瘤分期,而预后生物标志物则可指示疾病转归。然而,尽管有这些进展,但目前尚无经临床批准用于膀胱癌治疗的生物标志物。膀胱癌是美国男性中第四大常见癌症,也是治疗费用最高的癌症之一。虽然膀胱癌患者的基因表达谱是公开可用的,但生物标志物的识别需要生物信息学专业知识,而许多研究实验室并不具备。

描述

我们从13个公开可用的患者队列(N = 1454)中收集了基因表达数据,并开发了BC - BET,这是一种用于评估膀胱癌候选诊断和预后基因表达生物标志物的在线膀胱癌生物标志物评估工具。用户只需选择一个基因,BC - BET就会评估该基因表达作为诊断和预后生物标志物的效用。具体而言,BC - BET计算一个基因的表达与肿瘤存在(区分肿瘤与正常样本)、肿瘤分级(区分低级别与高级别肿瘤)、肿瘤分期(区分非肌层浸润性与肌层浸润性样本)以及每个队列中所有患者的疾病转归(如疾病特异性生存)之间的关联强度。还分别对低级别、非肌层浸润性肿瘤患者和高级别、肌层浸润性肿瘤患者进行分析,以评估感兴趣的生物标志物是否具有独立于分级和分期的预后价值。

结论

虽然膀胱癌基因表达数据集是公开可用的,但其分析计算量很大,需要生物信息学专业知识。BC - BET是一种易于使用的工具,可快速评估多个患者队列中的膀胱癌基因表达生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae46/4487975/531b4d0e2f56/12894_2015_56_Fig1_HTML.jpg

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