Suppr超能文献

基于分子特征的肾肿瘤分类

Classification of renal neoplasms based on molecular signatures.

作者信息

Yang Ximing J, Sugimura Jun, Schafernak Kristian T, Tretiakova Maria S, Han Misop, Vogelzang Nicholas J, Furge Kyle, Teh Bin Tean

机构信息

Department of Pathology, Northwestern University, Feinberg School of Medicine, Chicago, Illinois, USA.

出版信息

J Urol. 2006 Jun;175(6):2302-6. doi: 10.1016/S0022-5347(06)00255-2.

Abstract

PURPOSE

Gene expression microarray studies have demonstrated distinct molecular signatures for different types of renal neoplasms based on overall gene expression patterns. However, in most of these studies the investigators used renal tumors with defined histology. We analyzed a test set of renal tumors in double-blind fashion using recently established molecular profiles of renal tumors as benchmarks.

MATERIALS AND METHODS

A total of 16 consecutive nephrectomies performed for neoplasms at a single urological service were subjected to gene expression profiling using cDNA chips containing 21,632 genes. Analysis was clustered with our previously established molecular profiles of 91 histologically defined kidney neoplasms and comparative genomic microarray analysis while blinded to tumor histology and clinical information.

RESULTS

With molecular analysis 9, 4, 2 and 1 tumors were classified as clear cell, papillary RCC, chromophobe RCC, and renal oncocytoma, respectively. Histopathological evaluation was concordant in 14 tumors. One of the 2 tumors with a discrepancy between molecular and pathological diagnoses was composed of oncocytoma and high grade clear cell RCC, and the other was chromophobe RCC that histologically mimicked papillary RCC.

CONCLUSIONS

We report the feasibility of the molecular diagnosis and classification of unknown renal neoplasms. Molecular diagnosis appears to be reliable and comparable to the standard of urological pathology. This molecular method may be a potentially useful test for establishing an accurate diagnosis that can impact clinical management.

摘要

目的

基因表达微阵列研究已基于整体基因表达模式证明不同类型肾肿瘤具有独特的分子特征。然而,在大多数此类研究中,研究者使用的是具有明确组织学特征的肾肿瘤。我们以双盲方式分析了一组肾肿瘤测试样本,使用最近建立的肾肿瘤分子图谱作为基准。

材料与方法

在单一泌尿外科服务机构,对总共16例因肿瘤而连续进行的肾切除术标本,使用包含21,632个基因的cDNA芯片进行基因表达谱分析。分析与我们之前建立的91例组织学明确的肾肿瘤分子图谱以及比较基因组微阵列分析进行聚类,同时对肿瘤组织学和临床信息保持盲态。

结果

通过分子分析,分别有9例、4例、2例和1例肿瘤被分类为透明细胞癌、乳头状肾细胞癌、嫌色性肾细胞癌和肾嗜酸细胞瘤。14例肿瘤的组织病理学评估结果一致。分子诊断与病理诊断存在差异的2例肿瘤中,1例由嗜酸细胞瘤和高级别透明细胞癌组成,另1例是组织学上类似乳头状肾细胞癌的嫌色性肾细胞癌。

结论

我们报告了对未知肾肿瘤进行分子诊断和分类的可行性。分子诊断似乎可靠且与泌尿外科病理学标准相当。这种分子方法可能是一种对确立准确诊断有潜在帮助的检测手段,可影响临床管理。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验