Non-Small Cell Lung Cancer Radiogenomics Map Identifies Relationships between Molecular and Imaging Phenotypes with Prognostic Implications.

Non-Small Cell Lung Cancer Radiogenomics Map Identifies Relationships between Molecular and Imaging Phenotypes with Prognostic Implications.
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DOI:
10.1148/radiol.2017161845
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发表时间:
2018-01
期刊:
影响因子:
19.7
通讯作者:
Gevaert O
Gevaert O
中科院分区:
医学1区
文献类型:
--
作者:
Zhou M;Leung A;Echegaray S;Gentles A;Shrager JB;Jensen KC;Berry GJ;Plevritis SK;Rubin DL;Napel S;Gevaert O

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我们的研究提出了一个非小细胞肺癌的放射基因组学图谱,该图谱将图像表型与由多基因捕获的核糖核酸特征联系起来,并显示了它们与分子途径的关联。创建一个放射基因组图谱,将计算机断层扫描(CT)图像特征与非小细胞肺癌(NSCLC)患者RNA测序生成的基因表达谱联系起来。对2008年4月至2014年9月期间诊断为NSCLC的113例患者进行了队列研究,这些患者具有术前CT数据和肿瘤组织。对于每个肿瘤,胸部放射科医生记录了87个语义图像特征,选择这些特征以反映结节形状、边缘、纹理、肿瘤环境和整体肺部特征的放射学特征。然后,从组织中提取总RNA并用RNA测序技术分析。10个高度共表达的基因簇,称为多基因,被确定,在公开的基因表达队列中验证,并与预后相关。接下来,通过使用t统计量和具有多重检验校正的斯皮尔曼相关性度量,构建了将语义图像特征与元基因联系起来的放射基因组学图谱。RNA测序分析产生了10个捕获各种分子途径的多基因,包括表皮生长因子(EGF)途径。放射基因组图谱创建32语义图像特征和元基因之间的统计学显着的相关性。例如,结节变薄和边缘与晚期细胞周期基因相关,代表EGF途径的多基因与毛玻璃样阴影和不规则结节或边缘不清的结节的存在显著相关。NSCLC放射基因组学分析显示语义图像特征与代表典型分子通路的多基因之间存在多重关联,可以无创性地识别NSCLC的分子特性。在线补充材料可用于本文。
Our study presented a radiogenomics map of non–small cell lung cancer that linked image phenotypes with ribonucleic acid signatures captured by metagenes and showed their association with molecular pathways. To create a radiogenomic map linking computed tomographic (CT) image features and gene expression profiles generated by RNA sequencing for patients with non–small cell lung cancer (NSCLC). A cohort of 113 patients with NSCLC diagnosed between April 2008 and September 2014 who had preoperative CT data and tumor tissue available was studied. For each tumor, a thoracic radiologist recorded 87 semantic image features, selected to reflect radiologic characteristics of nodule shape, margin, texture, tumor environment, and overall lung characteristics. Next, total RNA was extracted from the tissue and analyzed with RNA sequencing technology. Ten highly coexpressed gene clusters, termed metagenes, were identified, validated in publicly available gene-expression cohorts, and correlated with prognosis. Next, a radiogenomics map was built that linked semantic image features to metagenes by using the t statistic and the Spearman correlation metric with multiple testing correction. RNA sequencing analysis resulted in 10 metagenes that capture a variety of molecular pathways, including the epidermal growth factor (EGF) pathway. A radiogenomic map was created with 32 statistically significant correlations between semantic image features and metagenes. For example, nodule attenuation and margins are associated with the late cell-cycle genes, and a metagene that represents the EGF pathway was significantly correlated with the presence of ground-glass opacity and irregular nodules or nodules with poorly defined margins. Radiogenomic analysis of NSCLC showed multiple associations between semantic image features and metagenes that represented canonical molecular pathways, and it can result in noninvasive identification of molecular properties of NSCLC. Online supplemental material is available for this article.
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