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Abstract 3628: Obesity, metabolic dysfunction, and cancer risk: Uncovering the metabolic landscape
Abstract   Peer reviewed

Abstract 3628: Obesity, metabolic dysfunction, and cancer risk: Uncovering the metabolic landscape

Liza Makowski, Mary Playdon, Bing Li, Sonia L. Sugg, Scott A. Summers, Cornelia M. Ulrich, Deirdre Tobias, Edward L. Giovannucci, Xuehong Zhang, James R. Hébert, …
Cancer research (Chicago, Ill.), Vol.86(7_Supplement), pp.3628-3628
04/03/2026
DOI: 10.1158/1538-7445.AM2026-3628

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Abstract

As smoking rates decline, obesity has emerged as the leading modifiable risk factor for cancer in the United States. With obesity rates rising, especially in younger populations, its association with increased cancer risk is becoming more evident. There is an urgent need to understand the mechanisms underlying the relationship between obesity related metabolic dysregulation and cancer risk. This session highlights transdisciplinary research from the NCI-sponsored Metabolic Dysregulation and Obesity Cancer Risk (MeDOC) Consortium, which applies integrative methods across basic science, translational models, and clinical research. The MeDOC Consortium aims to discover mechanisms linking obesity and cancer to define markers that will enhance cancer risk prediction and identify targets for intervention. Metabolic alterations include immune dysfunction, metabolite signaling, hormonal imbalance, gut microbiome and adipocyte metabolism which can disrupt several downstream signaling pathways related to cancer initiation and progression. In our novel triangulation approach, we synthesize evidence from randomized controlled trials, mechanistic animal studies, and large-scale secondary data analyses establishing population-level patterns with clinical relevance to build a comprehensive metabolic atlas of cancer risk factors. Our research topics include the gut microbiome, lipid signaling, circulating metabolites, and local and systemic immune landscape, with a focus on how these processes influence the development of colorectal, breast, and liver cancers. We will highlight complementary research projects that bridge animal studies, human cohorts, and data science across diet, inflammation, microbiome, immunity, and obesity and weight loss. We will review current evidence and describe novel applications of systems biology with big data analytics featured as tools to integrate mechanistic insights and population-level patterns to establish robust causal frameworks. Early-career investigators will participate in an open discussion on emerging challenges and opportunities in obesity and cancer research. Specifically, we will report on the role of fatty acid binding protein, ceramides, bile acids, hormones, inflammation, and gut microbiome metabolites in cancers of the colon, breast, and liver, Through a translational lens, the session will emphasize how combining data science, bench studies, and interventional trials can accelerate the discovery of biomarkers, risk stratification tools, and actionable targets for cancer prevention or interception.

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