Table 1.

Summary of key area-specific priorities for cancer research and proposed actions

Area-specific priorities for cancer researchActions
Nutrition and cancer epidemiology
Expand research across the life course, improve diet measurements, and utilize biological samples.
  • Investigate the impact of diet across the life course, especially gaps in early life.

  • Investigate long latencies between exposure and diagnosis of cancer.

  • Investigate dose-response relationships with better categorization of dietary components.

  • Study molecular effects of different dietary components/patterns.

  • Integrate genomics, microbiomics, metabolomics, and epigenomics with nutrition.

  • Leverage emerging technologies and integrate objective measures such as metabolomics for identification of dietary biomarkers and patterns.

  • Strengthen the development and application of intake biomarkers from body fluids, particularly blood and urine.

  • Link to infrastructural resources of health care settings to investigate diet and cancer prognosis and related outcomes.

  • Expand studies outside the industrialized world to capture current demographic transition.

  • Utilize short-term feeding studies for biomarker assessment for use in cohorts.

Physical activity and cancer epidemiology
Expand research on PA and sedentary behaviors across the life course, improve measurements, and utilize biological samples.
  • Expand research across the cancer spectrum to cover cancer sites and subtypes that have not adequately been studied.

  • Study effect modification by adiposity, diet, age, race/ethnicity, comorbidities, etc.

  • Expand research on PA in older adults.

  • Study PA type, frequency, intensity, dose, and timing in life.

  • Improve measures with applicable emerging technologies.

  • Focus on biologic mechanisms of action of PA-cancer relationships.

Obesity and cancer epidemiology
Expand research on the impact of weight gain across the life course and measures of adiposity.
  • Evaluate whether “obesity paradox” observed for certain cancer sites is due to methodological limitations.

  • Expand investigations of the impact of obesity and/or weight gain across the life course, including earlier in life.

  • Improve approaches to modeling of weight gain across the life course and cancer.

  • Confirm validity of adiposity measurements by age, race/ethnicity.

  • Investigate whether more precise measurement of fat compartments and body fat distribution have advantages beyond simple BMI.

  • Investigate obesity and/or weight trajectory on cancer survivors, including pediatric cancer survivors, and study the impact of obesity on second primary cancers and cancer recurrence.

  • Study whether obesity phenotypes are important for metabolic health.

  • Investigate transgenerational impact of obesity on cancer.

  • Investigate and identify mechanistic targets and intervention strategies to offset effects of obesity on chemotherapeutic drugs among cancer survivors.

  • Evaluate whether intentional weight loss following chronic obesity reverses the carcinogenic effects of obesity.

  • Evaluate effective methods to translate evidence-based methods to reducing obesity (i.e., healthy diet, PA) at both the individual and societal levels.

Gut microbiome
Expand prospective studies of the microbiome and cancer, and improve current methodological limitations.
  • Incorporate additional tools and resource development.

  • Expand and incorporate nonbacterial components of the microbiome.

  • Standardize sample and data collection protocols.

  • Utilize large databases and repositories for increasing volume of complex data.

  • Increase human resources and training for bioinformatics and computational biology.

Metabolomics and biomarkers of dietary exposures
Expand prospective studies of the metabolome and cancer, and improve current methodological limitations.
  • Utilize validation studies because many biomarkers proposed are not necessarily informative in community dwelling populations.

  • Utilize standard reference materials for different types of biological samples (e.g., plasma, serum, and urine).

  • Expand studies to include other types of biospecimens (e.g., teeth, hair, and other tissues).

  • Incorporate biomarker panels.

  • Evaluate impact of long-term storage and subsequent sample processing of biospecimens.

  • Consolidate open-source tools and databases.

  • Conduct studies to identify metabolomics-based dietary intake biomarkers.

Emerging technologies for measuring diet
Expand studies on emerging technologies to improve accuracy and precision of assessment of dietary intake.
  • Evaluate the utility and validity of dietary assessment apps in mobile devices, wearable sensors, and other emerging technologies.

  • Improve methods and measures to capture dietary intake and context of eating in diverse groups.

  • Incorporate biomarkers as part of validation/calibration testing for emerging technologies.

  • Expand studies to include usability and cross-disciplinary teams to pursue automation of food identification and volume estimation.

Emerging technologies for measuring PA and sedentary behavior
Expand studies on emerging technologies to improve accuracy and precision of assessment of PA and sedentary behaviors.
  • Evaluate usability, feasibility, and acceptability of mobile devices, wearable sensors, and other emerging technologies that measure PA and sedentary behavior.

  • Evaluate technologies in participants of large, prospective cohort studies.

  • Evaluate impact of behavioral variability on use of specific technologies.

  • Improve systems and scalability for implementation of accelerometer-based measures.

Hormones and cancer
Expand pooling projects to test homone cancer relationships.
  • Pool hormone biomarkers from prospective cohort studies to understand cancer risk by ethnicity and other population subgroups.

  • Standardize methods for hormone measurements.

  • Expand human studies to investigate whether dietary factors and PA are associated with patterns of hormonal profiles.

Gene–environment Interactions
Interpret the impact of GWAS-identified SNPs located in noncoding regions of the genome.
  • There is a need to understand the functional significance of GWAS identified SNPs in the noncoding regions of the genome.

  • More precise and accurate ways to measure environmental exposures are needed because exposure assessment errors contribute to inabilities to consistently detect GxE interactions.

SNPs associated with cancer risk in noncoding regions of genes or their promoters that do not produce functional proteins may have importance in epigenomics.
  • There is a need to understand the difference between epigenetic drift and epigenetic alterations due to modifiable environmental risk factors such as diet.

  • For impact of environmental factors on the epigenome, there is a need to understand which of the three classes of epigenetic molecules, DNA methylation, modifications of histone or other chromosomal proteins and noncoding RNAs, would be ideal candidate biomarkers in cancer risk assessment.

Implementation of what we already now
Implement evidence based knowledge such as national guidelines on food, nutrition, PA, and cancer prevention.
  • Expand implementation science efforts to ensure that knowledge already generated benefits the most people possible.

Abbreviations: PA, physical activity; BMI, body mass index; GWAS, genome-wide association studies.