Concepts of multi-level dynamical modelling: understanding mechanisms of squamous cell carcinoma development in Fanconi anemia.
Concepts of multi-level dynamical modelling: understanding mechanisms of squamous cell carcinoma development in Fanconi anemia.
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DOI：
10.3389/fgene.2023.1254966
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发表时间：
2023
影响因子：
3.7
通讯作者：
Carlberg, Carsten
中科院分区：
文献类型：
--
作者：
Velleuer, Eunike;Dominguez-Huettinger, Elisa;Rodriguez, Alfredo;Harris, Leonard A.;Carlberg, Carsten
关键词：
范可尼贫血（FA）是一种罕见的疾病（发病率为1:30万），主要基于FA/BRCA（乳腺癌）途径基因的致病变异遗传。这些变异最终降低了参与DNA链间交联和DNA双链断裂修复的不同蛋白质的功能。出生时，FA患者可能会出现典型的畸形，特别是桡骨轴和肾脏畸形，以及其他身体异常，如皮肤色素沉着异常。在生命的头十年，FA主要是由于造血干细胞和祖细胞的能力降低和丧失而导致骨髓衰竭。这通常使得造血干细胞移植成为必要，但这种治疗增加了成年早期发生鳞状细胞癌（SCC）的内在风险。由于FA的潜在遗传缺陷，传统的基于化疗的治疗方案不能应用。因此，在早期发现和治疗SCC的多步骤肿瘤发生过程，甚至是其祖细胞，是延长成年FA个体生命的最佳选择。然而，少数FA个体使得基于随机临床试验结果的经典循证医学方法不可能。作为一种替代方案，我们在这里引入了多层次动态建模的概念，使用大量纵向收集的基因组、蛋白质组和转录组数据集，这些数据集来自少数FA个体。这种机制建模方法是基于“FA中癌症的特征”，这是我们从750多名FA患者的独特临床病史数据库中得出的。来自FA个体健康和病变组织样本的多组学数据将用于训练多层次肿瘤发生模型的组成模型，然后将用于实验可测试的预测。通过这种方式，机制模型不仅有助于对FA中SCC的描述性理解，而且有助于对其功能性理解。这种方法将为检测早期SCCs及其前体的特征提供基础，从而可以有效地治疗甚至预防SCCs，从而为FA患者提供更好的预后和生活质量。
Fanconi anemia (FA) is a rare disease (incidence of 1:300,000) primarily based on the inheritance of pathogenic variants in genes of the FA/BRCA (breast cancer) pathway. These variants ultimately reduce the functionality of different proteins involved in the repair of DNA interstrand crosslinks and DNA double-strand breaks. At birth, individuals with FA might present with typical malformations, particularly radial axis and renal malformations, as well as other physical abnormalities like skin pigmentation anomalies. During the first decade of life, FA mostly causes bone marrow failure due to reduced capacity and loss of the hematopoietic stem and progenitor cells. This often makes hematopoietic stem cell transplantation necessary, but this therapy increases the already intrinsic risk of developing squamous cell carcinoma (SCC) in early adult age. Due to the underlying genetic defect in FA, classical chemo-radiation-based treatment protocols cannot be applied. Therefore, detecting and treating the multi-step tumorigenesis process of SCC in an early stage, or even its progenitors, is the best option for prolonging the life of adult FA individuals. However, the small number of FA individuals makes classical evidence-based medicine approaches based on results from randomized clinical trials impossible. As an alternative, we introduce here the concept of multi-level dynamical modelling using large, longitudinally collected genome, proteome- and transcriptome-wide data sets from a small number of FA individuals. This mechanistic modelling approach is based on the “hallmarks of cancer in FA”, which we derive from our unique database of the clinical history of over 750 FA individuals. Multi-omic data from healthy and diseased tissue samples of FA individuals are to be used for training constituent models of a multi-level tumorigenesis model, which will then be used to make experimentally testable predictions. In this way, mechanistic models facilitate not only a descriptive but also a functional understanding of SCC in FA. This approach will provide the basis for detecting signatures of SCCs at early stages and their precursors so they can be efficiently treated or even prevented, leading to a better prognosis and quality of life for the FA individual.
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DOI：
10.1182/asheducation-2017.1.96
发表时间：
2017-12-01
影响因子：
3
作者：
Calado, Rodrigo T.;Cle, Diego V.
通讯作者：
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DOI：
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期刊：
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