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放射组学预测食管癌患者血清中 microRNA-1246 的表达。

Radiogenomics predicts the expression of microRNA-1246 in the serum of esophageal cancer patients.

机构信息

Division of Gastroenterological Surgery, Chiba Cancer Center, Chiba, Japan.

Department of Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, Chiba, Japan.

出版信息

Sci Rep. 2020 Feb 13;10(1):2532. doi: 10.1038/s41598-020-59500-7.

Abstract

Radiogenomics is a new field that provides clinically useful prognostic predictions by linking molecular characteristics such as the genetic aberrations of malignant tumors with medical images. The abnormal expression of serum microRNA-1246 (miR-1246) has been reported as a prognostic factor of esophageal squamous cell carcinoma (ESCC). To evaluate the power of the miR-1246 level predicted with radiogenomics techniques as a predictor of the prognosis of ESCC patients. The real miR-1246 expression (miR-1246) was measured in 92 ESCC patients. Forty-five image features (IFs) were extracted from tumor regions on contrast-enhanced computed tomography. A prediction model for miR-1246 was constructed using linear regression with selected features identified in a correlation analysis of miR-1246 and each IF. A threshold to divide the patients into two groups was defined according to a receiver operating characteristic analysis for miR-1246. Survival analyses were performed between two groups. Six IFs were correlated with miR-1246 and were included in the prediction model. The survival curves of high and low groups of miR-1246 and miR-1246 showed significant differences (p = 0.001 and 0.016). Both miR-1246 and miR-1246 were independent predictors of overall survival (p = 0.030 and 0.035). miR-1246 produced by radiogenomics had similar power to miR-1246 for predicting the prognosis of ESCC.

摘要

放射组学是一个新领域,通过将恶性肿瘤的分子特征(如基因突变)与医学图像联系起来,为临床提供有用的预后预测。血清 microRNA-1246(miR-1246)的异常表达已被报道为食管鳞状细胞癌(ESCC)的预后因素。为了评估基于放射组学技术预测 miR-1246 水平作为 ESCC 患者预后预测因子的能力。对 92 名 ESCC 患者的真实 miR-1246 表达(miR-1246)进行了测量。从增强 CT 肿瘤区域提取了 45 个图像特征(IFs)。使用线性回归分析了 miR-1246 与每个 IF 的相关性分析中选择的特征,构建了 miR-1246 的预测模型。根据 miR-1246 的受试者工作特征分析,为 miR-1246 定义了一个阈值,将患者分为两组。对两组患者进行生存分析。有 6 个 IF 与 miR-1246 相关,被纳入预测模型。miR-1246 高和低组的生存曲线有显著差异(p=0.001 和 0.016)。miR-1246 和 miR-1246 均为总生存的独立预测因子(p=0.030 和 0.035)。放射组学产生的 miR-1246 对预测 ESCC 患者的预后与 miR-1246 具有相似的能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1854/7018689/6183f0bf2fde/41598_2020_59500_Fig1_HTML.jpg

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