It is becoming evident that holistic perspectives toward cancer are crucial in deciphering the overwhelming complexity of tumors. Single-layer analysis of genome-wide data has greatly contributed to our understanding of cellular systems and their perturbations. However, fundamental gaps in our knowledge persist and hamper the design of effective interventions. It is becoming more apparent than ever, that cancer should not only be viewed as a disease of the genome but as a disease of the cellular system. Integrative multilayer approaches are emerging as vigorous assets in our endeavors to achieve systemic views on cancer biology. Herein, we provide a comprehensive review of the approaches, methods and technologies that can serve to achieve systemic perspectives of cancer. We start with genome-wide single-layer approaches of omics analyses of cellular systems and move on to multilayer integrative approaches in which in-depth descriptions of proteogenomics and network-based data analysis are provided. Proteogenomics is a remarkable example of how the integration of multiple levels of information can reduce our blind spots and increase the accuracy and reliability of our interpretations and network-based data analysis is a major approach for data interpretation and a robust scaffold for data integration and modeling. Overall, this review aims to increase cross-field awareness of the approaches and challenges regarding the omics-based study of cancer and to facilitate the necessary shift toward holistic approaches.

中文翻译：

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癌症系统医学的前景与挑战：从基因到疾病网络

越来越明显的是，对癌症的整体观点对于破译肿瘤的压倒性复杂性至关重要。全基因组数据的单层分析极大地促进了我们对细胞系统及其扰动的理解。然而，我们知识上的根本差距仍然存在，并阻碍了有效干预措施的设计。比以往任何时候都更加明显的是，癌症不仅应被视为基因组疾病，而且应被视为细胞系统疾病。综合多层方法正在成为我们努力实现癌症生物学系统观点的有力资产。在此，我们全面回顾了可用于实现癌症系统性观点的方法、方法和技术。我们从细胞系统组学分析的全基因组单层方法开始，然后转向多层整合方法，其中提供了对蛋白质组学和基于网络的数据分析的深入描述。蛋白质组学是一个显着的例子，说明多层次信息的整合如何减少我们的盲点并提高我们解释的准确性和可靠性，基于网络的数据分析是数据解释的主要方法，也是数据集成和建模的强大支架. 总体而言，本综述旨在提高跨领域对基于组学的癌症研究方法和挑战的认识，并促进向整体方法的必要转变。