MeDOC-KB: Knowledge base for unraveling the metabolic links between obesity-related cancers

Metabolic Dysregulation and Obesity Cancer Risk Consortium (MeDOC) is an NCI-sponsored program using team science and transdisciplinary approach to elucidate mechanisms linking obesity, metabolic dysregulation, and cancer risk. Both obesity and metabolic dysregulation contribute to a cascade of derangements in adipocyte function, growth factors, inflammation, gut microbiome, immune function, sex hormones, lipid and glucose metabolism which, in turn, can disrupt several downstream signaling pathways related to cancer initiation and progression. Given this complexity, integrating multi-omic, mouse models and epidemiologic data is critical. The MeDOC-Knowledge Base (MeDOC-KB) is a comprehensive atlas cataloging associations to link obesity, metabolic dysregulation, and cancer risk from consortium studies and external literature. A large language model-based agent harmonized biomarkers derived from metabolomics, proteomics, and lipidomics platforms such as Nightingale, Olink, and Metabolon, standardizing nomenclature and resolving cross-platform synonyms into a unified vocabulary. MeDOC-KB uses a Neo4j graph database architecture to enable efficient traversal of complex relationships among the biomarkers, publications, cohorts, and cancer sites. Literature data are extracted into four core tables (Citation, Cohort, Methods, and Association) and transformed into a graph structure where nodes represent publication, cohorts, biomarkers, and cancer sites while edges denote their relationships. MeDOC-KB is accessible through an interactive R Shiny web application. The current version contains 42,838 nodes and 189,709 relationships with 21,945 being biomarker-cancer associations spanning 1,645 biomarkers and 15 cancer outcomes, including 11 of the 13 known obesity related cancers. For example, MeDOC-KB reveals that insulin-like growth factor binding protein-1 (IGFBP-1) shows inverse associations with endometrial, colorectal, and pancreatic cancers across multiple cohorts, suggesting shared metabolic mechanisms. The platform enables researchers to identify biomarker patterns associated with obesity-induced metabolic dysregulation across cancer types, compare findings across cohorts, and discover understudied biomarker-cancer relationships. MeDOC-KB provides a critical resource for hypothesis generation regarding mechanistic pathways, biomarker validation across populations, and identification of promising targets for cancer prevention strategies in high-risk metabolic populations. The knowledge base is publicly accessible and will be continuously updated with consortium findings and literature.