Morilla Ian, Chan Philippe, Caffin Fanny, Svilar Ljubica, Selbonne Sonia, Ladaigue Ségolène, Buard Valérie, Tarlet Georges, Micheau Béatrice, Paget Vincent, François Agnès, Souidi Maâmar, Martin Jean-Charles, Vaudry David, Benadjaoud Mohamed-Amine, Milliat Fabien, Guipaud Olivier
IRSN, Radiobiology of Medical Exposure Laboratory (LRMed), Human Health Radiation Protection Unit, 92260 Fontenay-Aux-Roses, France.
Normandie Univ, UNIROUEN, PISSARO Proteomic Platform, 76821 Mont Saint-Aignan, France.
iScience. 2021 Dec 30;25(1):103685. doi: 10.1016/j.isci.2021.103685. eCollection 2022 Jan 21.
The vascular endothelium is a hot spot in the response to radiation therapy for both tumors and normal tissues. To improve patient outcomes, interpretable systemic hypotheses are needed to help radiobiologists and radiation oncologists propose endothelial targets that could protect normal tissues from the adverse effects of radiation therapy and/or enhance its antitumor potential. To this end, we captured the kinetics of multi-omics layers-i.e. miRNome, targeted transcriptome, proteome, and metabolome-in irradiated primary human endothelial cells cultured . We then designed a strategy of deep learning as in convolutional graph networks that facilitates unsupervised high-level feature extraction of important omics data to learn how ionizing radiation-induced endothelial dysfunction may evolve over time. Last, we present experimental data showing that some of the features identified using our approach are involved in the alteration of angiogenesis by ionizing radiation.
血管内皮是肿瘤和正常组织放射治疗反应中的一个热点。为了改善患者预后，需要可解释的系统性假设来帮助放射生物学家和放射肿瘤学家提出内皮靶点，这些靶点可以保护正常组织免受放射治疗的不良影响和/或增强其抗肿瘤潜力。为此，我们捕捉了培养的原代人内皮细胞在接受辐射后的多组学层面的动力学变化，即微小RNA组、靶向转录组、蛋白质组和代谢组。然后，我们设计了一种深度学习策略，如卷积图网络，以促进对重要组学数据进行无监督的高级特征提取，从而了解电离辐射诱导的内皮功能障碍是如何随时间演变的。最后，我们展示了实验数据，表明使用我们的方法识别出的一些特征参与了电离辐射引起的血管生成改变。
