 Developments in systems and synthetic biology have encouraged philosophers to revisit traditional conceptions of disease as dysfunctional states (Holm 2013, 2014), or broken mechanisms (Gross 2011). Rather than focusing on the function or dysfunction of specific genes or molecular mechanisms, network approaches to disease may suggest a more dynamic approach to disease that accounts for an increasing number of integrated processes (Del Sol et al. 2010; Huang et al. 2009). Cancer research is a major priority of systems biology research, and exemplifies a field where data-intensive approaches may be needed to address biological complexity (Plutynski 2021). Developments in cancer genomics have revealed an astonishing diversity of tumor types, suggesting that finer-grained disease-categories and more targeted treatments may be needed. This line of research has opened new research venues, such as the development of multi-action remedies targeting numerous disease-related pathways identified via genomic analysis. The discovered diversity of mutations identified in sequenced tumors has, however, also led to heated debates on whether the behavior and identity of cancer cells can fully be understood at the molecular level. Some have stressed the need to move beyond gene-centric or cell-centric approaches and to consider cancer as a problem of tissue-organization (Soto &amp; Sonnenschein 2011). Although some systems biological explanations of cancer illustrate the possibility of integrating “top-down” and “bottom-up” approaches (Bertolaso 2016; Plutynski and Bertolaso 2018), systems biology research also displays a variety and sometimes conflicting approaches to cancer. These debates not only have philosophical implications for discussions about reductionism but also practical implications for how cancer should be approached experimentally and treated in clinical practice (Bertolaso 2011; Soto et al. 2008).