Network Physiology of Cancer

Cancer is one of the most complex and heterogeneous diseases known to medicine. It is not confined to a single organ or molecular pathway but instead emerges from a web of interdependent physiological, molecular, cellular, and systemic networks. In this sense, cancer is fundamentally a network disease, and understanding its origin, progression, and treatment requires a paradigm that integrates all research approaches and potentially link them to the language and methods of Network Physiology.

This Research Topic on “Cancer in Network Physiology” aims to bring together cutting-edge research at the intersection of cancer biology, clinical aspects of cancer, and cancer data analysis. We welcome contributions that apply all possible concepts to explore how cancer arises, evolves, and interacts with multi-level physiological systems—from genomic and proteomic networks to immune, metabolic, neural, and social systems. Our goal is to illuminate how cancer disrupts physiological coordination and communication, and how network-based insights can lead to better diagnostics, prognostics, and therapeutic strategies.

Cancer is tightly linked to alterations in physiological omic networks, including genomic, transcriptomic, proteomic, methylation, and protein–protein interaction networks. Through these multi-omic lenses, researchers can uncover dynamic patterns, nonlinear interactions, and emergent properties that drive oncogenesis and tumor heterogeneity. Network analysis of omic data holds immense potential for the discovery of network oncomarkers—biomarkers defined not by isolated molecular signals, but by patterns across multiple network layers. Immune networks also play a pivotal role in the landscape of cancer. Cancer can evade immune surveillance, suppress immune responses, and even co-opt immune cells for its own progression. Moreover, cancer is a dynamic process. Tumor growth, metastasis, and resistance to treatment are inherently temporal phenomena involving feedback loops, bifurcations, and phase transitions in physiological states. Finally, the broader context in which cancer occurs—social, epidemiological, and economic—can also be fruitfully studied through data analysis and network approaches. Social determinants of health, disparities in care, and risk stratification are all embedded in complex societal networks that influence the incidence and outcomes of cancer.

We invite original research articles, reviews, and theoretical perspectives addressing (but not limited to) the following topics:

• Omics, EHR and various Data analysis in cancer (e.g., genomics, transcriptomics, proteomics, methylation)
• Discovery and validation of network oncomarkers
• Cancer as a dynamic, multi-scale phenomenon
• Immune-cancer interaction and immune network reprogramming
• Multiorgan physiological coordination and disruption in cancer
• Applications of network physiology to cancer diagnostics and treatment
• Temporal network analysis of tumor evolution and treatment response
• Multi-patient and population-level network models of cancer
• Social and epidemiological networks in cancer risk and prevention
• Economic and systemic factors in cancer treatment networks

Topic Editor Aleksandra Gentry-Maharaj reports personal consulting fees from Mercy BioAnalytics Ltd and research support grants paid to the institution from Intelligent Lab on Fiber, RNA Guardian and MercyBio Analytics for early detection of cancer. Topic Editor Ranjit Manchanda receives research grant funding through QMUL from GSK and receives income for lecturing with EGL, GSK, Astrazeneca, MSD. The other Topic Editors declare no competing interests with regard to the Research Topic subject.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: Cancer, Oncomarkers, Network Physiology, Data Analysis, Screening, EHR, Genomics, Proteomics, Transcriptomics, Methylation

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.