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.