Jansen Robin W, van Amstel Paul, Martens Roland M, Kooi Irsan E, Wesseling Pieter, de Langen Adrianus J, Menke-Van der Houven van Oordt Catharina W, Jansen Bernard H E, Moll Annette C, Dorsman Josephine C, Castelijns Jonas A, de Graaf Pim, de Jong Marcus C
Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands.
Department of Clinical Genetics, VU University Medical Center, Amsterdam, The Netherlands.
Oncotarget. 2018 Apr 13;9(28):20134-20155. doi: 10.18632/oncotarget.24893.
With targeted treatments playing an increasing role in oncology, the need arises for fast non-invasive genotyping in clinical practice. Radiogenomics is a rapidly evolving field of research aimed at identifying imaging biomarkers useful for non-invasive genotyping. Radiogenomic genotyping has the advantage that it can capture tumor heterogeneity, can be performed repeatedly for treatment monitoring, and can be performed in malignancies for which biopsy is not available. In this systematic review of 187 included articles, we compiled a database of radiogenomic associations and unraveled networks of imaging groups and gene pathways oncology-wide. Results indicated that ill-defined tumor margins and tumor heterogeneity can potentially be used as imaging biomarkers for 1p/19q codeletion in glioma, relevant for prognosis and disease profiling. In non-small cell lung cancer, FDG-PET uptake and CT-ground-glass-opacity features were associated with treatment-informing traits including -mutations and -rearrangements. Oncology-wide gene pathway analysis revealed an association between contrast enhancement (imaging) and the targetable VEGF-signalling pathway. Although the need of independent validation remains a concern, radiogenomic biomarkers showed potential for prognosis prediction and targeted treatment selection. Quantitative imaging enhanced the potential of multiparametric radiogenomic models. A wealth of data has been compiled for guiding future research towards robust non-invasive genomic profiling.
随着靶向治疗在肿瘤学中发挥越来越重要的作用，临床实践中对快速非侵入性基因分型的需求应运而生。放射基因组学是一个快速发展的研究领域，旨在识别有助于非侵入性基因分型的影像生物标志物。放射基因组基因分型具有以下优势：它能够捕捉肿瘤异质性，可重复进行以监测治疗情况，并且可在无法进行活检的恶性肿瘤中开展。在对187篇纳入文章的这项系统评价中，我们编制了一个放射基因组关联数据库，并梳理了全肿瘤范围内影像组与基因通路的网络。结果表明，边界不清的肿瘤边缘和肿瘤异质性可能用作胶质瘤中1p/19q共缺失的影像生物标志物，这与预后和疾病特征分析相关。在非小细胞肺癌中，氟代脱氧葡萄糖正电子发射断层扫描（FDG-PET）摄取和CT磨玻璃密度特征与包括-突变和-重排在内的指导治疗的特征相关。全肿瘤范围的基因通路分析揭示了对比增强（影像表现）与可靶向的血管内皮生长因子（VEGF）信号通路之间的关联。尽管独立验证的必要性仍然是一个问题，但放射基因组生物标志物显示出预后预测和靶向治疗选择的潜力。定量成像增强了多参数放射基因组模型的潜力。已汇集了大量数据以指导未来开展稳健的非侵入性基因组分析研究。
