Formally and intuitively, a system is a set of related objects such as molecules, cells, tissues, and organs. Key to a systems approach is the notion of a network: the behavior or (mal-) functioning of a system resulting from the interactions of its parts. A systems approach emphasizes interactions and thus processes. For instance, tumor development, progression and treatment are processes, as are the molecular and cellular interactions that underlie tissue and organ function. The challenges of a systems approach cannot be solved per se by the reductionist approaches that decomposes tumorigenesis into individual components (e.g., genes, RNAs, and proteins) and understands their functions and roles one by one. Therefore, the emergence of systems biology, which integrates experiments with artificial intelligence, network methods, and models of dynamical systems in interactive cycles, provides us with a promising way to investigate basic mechanisms and principles in cancer biology or conduct preclinical research related with cancer. In line with this, systems medicine appears and is the application of systems biology approaches to handle challenges related to human cancer. The aims of systems medicine in cancer research are multidimensional, ranging from the understanding of molecular mechanisms to accurate diagnosis and prognosis using accessible biopsies, tissues, and samples; from the identification of patient subgroups to the development of novel approaches in drug discovery and repurposing; and to more precise treatment based on individual patients’ measurements.