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基于放射组学的结直肠癌预后分析。

Radiogenomics-based cancer prognosis in colorectal cancer.

机构信息

INSERM, UMR 1101, LaTIM, 22 rue Camille Desmoulins, 29238, Brest, France.

INSERM, UMR 1078, 22, avenue Camille Desmoulins, 29238, Brest, France.

出版信息

Sci Rep. 2019 Jul 5;9(1):9743. doi: 10.1038/s41598-019-46286-6.

Abstract

Radiogenomics aims at investigating the relationship between imaging radiomic features and gene expression alterations. This study addressed the potential prognostic complementary value of contrast enhanced computed tomography (CE-CT) radiomic features and gene expression data in primary colorectal cancers (CRC). Sixty-four patients underwent CT scans and radiomic features were extracted from the delineated tumor volume. Gene expression analysis of a small set of genes, previously identified as relevant for CRC, was conducted on surgical samples from the same tumors. The relationships between radiomic and gene expression data was assessed using the Kruskal-Wallis test. Multiple testing was not performed, as this was a pilot study. Cox regression was used to identify variables related to overall survival (OS) and progression free survival (PFS). ABCC2 gene expression was correlated with N (p = 0.016) and M stages (p = 0.022). Expression changes of ABCC2, CD166, CDKNV1 and INHBB genes exhibited significant correlations with some radiomic features. OS was associated with Ratio 3D Surface/volume (p = 0.022) and ALDH1A1 expression (p = 0.042), whereas clinical stage (p = 0.004), ABCC2 expression (p = 0.035), and Entropy (p = 0.0031), were prognostic factors for PFS. Combining CE-CT radiomics with gene expression analysis and histopathological examination of primary CRC could provide higher prognostic stratification power, leading to improved patient management.

摘要

放射组学旨在研究影像学放射组学特征与基因表达改变之间的关系。本研究旨在探讨原发性结直肠癌(CRC)中增强 CT(CE-CT)放射组学特征和基因表达数据的潜在预后互补价值。64 名患者接受了 CT 扫描,并从勾画的肿瘤体积中提取放射组学特征。对来自同一肿瘤的手术样本进行了一组先前确定与 CRC 相关的基因的基因表达分析。使用 Kruskal-Wallis 检验评估放射组学和基因表达数据之间的关系。未进行多重检验,因为这是一项初步研究。Cox 回归用于识别与总生存期(OS)和无进展生存期(PFS)相关的变量。ABCC2 基因表达与 N(p=0.016)和 M 分期(p=0.022)相关。ABCC2、CD166、CDKNV1 和 INHBB 基因的表达变化与一些放射组学特征呈显著相关。OS 与 3D 表面积/体积比(p=0.022)和 ALDH1A1 表达(p=0.042)相关,而临床分期(p=0.004)、ABCC2 表达(p=0.035)和熵(p=0.0031)是 PFS 的预后因素。将 CE-CT 放射组学与基因表达分析以及原发性 CRC 的组织病理学检查相结合,可能提供更高的预后分层能力,从而改善患者管理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c260/6611779/c9d6791669a3/41598_2019_46286_Fig1_HTML.jpg

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