PROJECT SUMMARY Cancer survivors with overweight or obesity (ow/ob) display increased morbidity and mortality even after amelioration of disease. Improvements in dietary and physical activity patterns can mitigate this risk and can be supported through comprehensive, multiple health behavior change (MHBC) interventions. Yet, translation of MHBC interventions to clinical practice is limited, in part because traditional “treatment package” approaches are not optimized for real-world implementation. Integration of multi-omic data can capture lifestyle exposures and biological responses, providing the potential to strengthen conclusions and overcome limitations of existing assessment methods. This approach could elucidate the biological underpinnings of how changes in modifiable behaviors influence individual phenotype during survivorship. Such knowledge would help to identify and tailor interventions for incorporation into survivorship care. Yet, this has not been conducted, posing a critical research gap. My goal is to create a sustainable and scalable MHBC program combining diet and exercise to support survivors with ow/ob and improve health in survivorship. Thus, the overall objectives for this NCI early K99/R00 award are to: (1) develop a survivorship nutrition intervention, BfedBwell, for implementation within an existing clinical exercise oncology program; and (2) determine the impact of the intervention on diet and health through the integration of multi-omic approaches. In the K99 phase, I will utilize the Multiphase Optimization Strategy (MOST) framework, an engineering-based approach to efficiently and systematically develop, optimize, and evaluate behavioral interventions, to test three social cognitive theory-based components: (1) 1:1 counseling with a registered dietitian, (2) behavioral skills development, and (3) group support for delivery alongside a core nutrition education curriculum within a clinical exercise oncology program. Post-treatment survivors (n=80) with ow/ob will complete a 12-week cluster-randomized 2^3 factorial trial to test candidate intervention components for feasibility and acceptability and to identify a set of components that demonstrates patterns of efficacy for increased adherence to lifestyle recommendations, weight loss, and improvements in cardiometabolic health. In the R00 phase, I will utilize targeted metabolomics to measure changes in biomarkers of dietary exposure through analysis of participant biospecimens collected before and after the intervention. I will then perform integrated network analysis using multi-omics (metabolome, proteome, microbiome) to examine the effects of the intervention on cardiometabolic health. My K99 mentorship and training plan will provide skills in behavioral weight loss trials, MOST study design, and multi-omics integration in survivorship. The R00 phase will advance my foundational knowledge as I become an expert in identifying and interpreting multi-omic findings and integrating them into behavioral interventions to predict and evaluate individual response. Completion of these aims will lay the groundwork for an R01-level optimization trial, leading to advances in care while spanning behavioral and biological domains to develop precision oncology nutrition strategies for improved survivorship.

PROJECT NARRATIVE The public health significance of this study lies in its potential to develop an improved understanding of the components of lifestyle interventions that are necessary to help adult cancer survivors with overweight and obesity improve dietary patterns to reduce weight and improve cardiometabolic health. Results will lead to optimized interventions that balance effectiveness with affordability, scalability, and efficiency to improve clinical implementation. These findings, coupled with integration and interpretation of multi-omic assessments to predict and evaluate response, will address a growing need for translational science that can result in more effective nutrition interventions for this population, and ultimately, advance survivorship care and move the field toward precision health.