Personalizing endometrial cancer prevention through diet and lifestyle

This review synthesizes emerging evidence on modifiable risk factors for endometrial cancer (EC)-the sixth most common female malignancy globally-with rising incidence despite diagnostic advances. Obesity drives ~60% of preventable cases, positioning diet and lifestyle as critical prevention targets. This work evaluates current evidence, unresolved controversies, and pathways toward personalized prevention frameworks.

Introduction

EC incidence increased 1.5% annually post-2010, notably among premenopausal women in developed nations. Obesity underlies 40–60% of preventable cases, establishing diet and physical activity as pivotal modifiable factors. The review maps evidence from 2014–2024 to clarify EC prevention mechanisms and address population-specific variability.

Dietary patterns: Evidence and controversies

• Mediterranean diet: Associated with 13% EC risk reduction (high fruit/vegetable/whole grain intake; anti-inflammatory effects), but efficacy varies by BMI, ethnicity, and socioeconomic status.

• Ketogenic diet (KD): Improves insulin sensitivity and weight management (key for EC prevention) but risks nutritional imbalance and hepatic/renal toxicity.

• Diabetes Risk Reduction Diet (DRRD): High-fiber, low-sugar patterns reduce EC risk, though less effective in older, obese, or non-white subgroups.

• Soy isoflavones: Show dual effects-protective in Asian populations with high dietary intake but potentially harmful in hormone-sensitive subgroups or cancer survivors.
  
  Key debate: Whether diet impacts EC directly or indirectly via BMI mediation (e.g., BMI explains 84–93% of diet-EC associations in cohort studies). Regional variations (e.g., Asia vs. West) necessitate population-specific guidelines.

Lifestyle factors beyond diet

• Physical activity: 7.5–15 MET-hours/week reduces EC risk by improving insulin sensitivity and reducing inflammation. Sedentary behavior increases risk by 28–30%.

• Smoking: Paradoxically lowers EC risk (anti-estrogenic effects) but elevates all-cause mortality.

• Alcohol: Low intake may lower risk in obese/insulin-resistant women; higher intake shows neutral effects.

• Psychological stress: Depression/anxiety correlate with poor prognosis, mediated by immune-endocrine disruption.

Hereditary (Lynch Syndrome [LS]) vs. Sporadic EC

Nutrient debate: Reductionist vs. holistic approaches

• Reductionist view: Focuses on single nutrients:

  
  

  • Omega-3 fatty acids show conflicting results (15–23% risk reduction vs. 9% increase with docosahexaenoic acid).

  • Selenium/vitamin C exhibit pro-/anti-tumor effects contingent on dose and context.

• Holistic view: Emphasizes dietary patterns (e.g., Mediterranean/plant-based diets outperform isolated nutrients). Challenges include marketing influences and cultural dietary preferences.
  
  Consensus: Hybrid approach-prioritize whole-diet patterns, then refine with nutrient-specific insights.

The “dose-effect” paradox in interventions

• Low-intensity interventions (e.g., walking) often outperform high-intensity regimens due to better adherence and metabolic sustainability.

• Obese women require higher exercise intensity (≥15 MET-hours/week) for significant EC risk reduction.

• Self-reporting bias overestimates compliance; wearable devices improve data accuracy.

Toward personalized prevention

• Metabolic phenotyping: Targeting insulin resistance/inflammation. Example: Omega-3 benefits are pronounced in overweight women.

• Genetic stratification: LS patients need distinct strategies (e.g., aspirin prophylaxis over OCs).

  
  

• Barriers:

  
  

  • Limited multi-omics cohorts (genomics/metabolomics).

  • Lack of validated biomarkers (e.g., inflammatory markers like IL-6).

  • Cost-effective screening tools for high-risk subgroups.

• Clinical Integration: Digital health tools, culturally tailored interventions, and multidisciplinary teams (dietitians/oncologists) enable feasible, sustained prevention.

Limitations and future directions

• Evidence gaps: Heterogeneous methodologies, BMI confounding, self-reporting biases, and understudied populations (racial/age/genetic subgroups).

• Priorities:

  
  

  • Large cohorts integrating genomics/lifestyle data.

  • Culturally adapted interventions and digital health integration (apps/wearables).

  • Policy support for public education and inter-disciplinary collaboration.

Conclusions

Diet (Mediterranean/plant-based patterns) and lifestyle (activity/sedentary reduction) significantly lower EC risk, but efficacy is modulated by BMI, genetics, and sociocultural factors. Personalized prevention-stratified by metabolic phenotype, genetic risk (e.g., LS), and cultural context-is essential. Future work must bridge research-practice gaps through multi-omics, digital monitoring, and tailored public health strategies.