PROJECT SUMMARY From initial diagnosis through treatment and into survivorship, patients frequently report fatigue as a significant problem. Studies suggest that up to 90% of cancer patients experience moderate to severe fatigue during treatment and nearly 30% after treatment completion. Fatigue pathophysiology is thought to be multifactorial and complex, including host susceptibility, pro-inflammatory cytokine production, disruption in circadian rhythms of sleep/activity patterns, and neuroendocrine and metabolic dysregulation. However, to date most studies examining the biology of cancer-related fatigue have limited their focus to inflammation. We propose a new approach, the Predisposing, Precipitating, and Perpetuating (3P) model, to comprehensively examine cancer- related fatigue pathophysiology. The 3P model hypothesizes that: (1) genetic variants predispose patients to fatigue, (2) inflammation and metabolic dysregulation caused by cancer and its treatment are precipitating factors, and (3) behaviors such as poor diet, physical inactivity, and sleep disruption perpetuate the problem. In the current study, we will use a metabolomics approach, the study of small molecules, to examine the relative contributions of precipitating endogenous metabolism and cytokines as well as perpetuating behavioral factors to fatigue pathophysiology, and how these are modified by predisposing genetic variants and other factors. This approach offers an exciting opportunity to interrogate cancer-related fatigue at a multi-omics systems level. To our knowledge, cancer-related fatigue has never been studied in the context of the metabolome. We will leverage detailed clinical, epidemiological, and objective and subjective behavioral data as well as blood samples obtained at diagnosis/surgery and sequentially up to 2-years post-diagnosis from the ColoCare Study, a large, international, multi-site, prospective colorectal cancer (CRC) survivor cohort (n=2,379) to determine and validate predictors of fatigue. The ColoCare study is the only large cohort study that collects such comprehensive biological and behavioral data in the context of CRC. The study has three aims. In Aim 1, we will examine genomic variation and other baseline characteristics as predisposing factors for cancer-related fatigue. In Aim 2, we will examine the metabolome and inflammasome as precipitating factors for cancer-related fatigue. In Aim 3, we will conduct an integrative analysis to evaluate sleep, physical activity, diet, and their relationships with the genome, metabolome and inflammasome as perpetuating factors for cancer-related fatigue. This study is unique in using the 3P framework, detailed longitudinal evaluation of fatigue, and use of cutting-edge technologies to measure multi-omic and behavioral changes over time. Results will provide new avenues for risk prediction, prevention, and treatment of cancer-related fatigue.