Effects of protein restriction on insulin-like growth factor (IGF)-1 in men with prostate cancer: results from a randomized clinical trial

Abstract

Background: Insulin-like growth factor (IGF)-1 and its binding proteins are important in cancer growth, especially in prostate cancer. Observational studies suggest that protein restriction can lower IGF-1 levels. However, it is unclear whether an isocaloric protein-restricted diet affects IGF-1 and IGFBPs in men with prostate cancer.

Methods: In this academic, single-center, parallel-group, prospective, randomized, open-label, blinded end-point trial, 38 consenting overweight (BMI 30.5 ± 5.5 kg/m²) men with localized prostate cancer, aged 43-72 years, were randomized (1:1) with permuted blocks to 4-6 weeks of customized isocaloric PR diets (0.8 g protein/kg lean body mass) or their usual diet. Biomarkers influencing cancer biology, including serum IGF-1 and its binding proteins were measured longitudinally.

Results: Contrary to our hypothesis, feeding individuals an isocaloric protein-restricted diet did not result in a significant reduction in serum IGF-1. Moreover, there was no observed increase in serum IGFBP-1 or IGFBP-3 concentration.

Conclusion: These findings demonstrate that protein restriction without calorie restriction does not reduce serum IGF-1 concentration or increase IGFBP-1 and IGFBP-3 in men with localized prostate cancer. Further research is needed to identify dietary interventions for safely and effectively reducing IGF-1 in this patient group.

Fig. 1

A protein restricted diet without calorie restriction does not affect the IGF-1 axis. A Schematic representation of the study. The average macronutrient composition (% of energy) was calculated from provided customized meals (intervention = PR diet) and food diary assessments (control = usual diet). B-E Fasting blood measurements of IGF-1, IGFBP-1, IGFBP-3 (absolute) and IGF-1:IGFBP-3 ratio (relative) at baseline and at 4–6 weeks follow up. Each dot represents an individual (n = 19 per group). Violin plots represent the distribution of the variables. Statistical significance is indicated by p-values calculated using 2-way ANOVA for repeated measurements (baseline and follow-up) and multiple comparisons

Fig. 2

Individual variations in IGF-1 levels are not explained by changes in glucose, insulin, or IGF-binding proteins. A-D Linear regression analysis between changes in IGF-1 (Δ IGF-1) and Δ IGFBP-1, Δ IGFBP-3, Δ glucose, and Δ insulin for the intervention (yellow) and control (blue) arms. Delta (Δ) represents the value at follow up minus the value at baseline. Each dot represents an individual (n = 19 per group). The shaded areas show the 95% confidence bands for the best-fit line. R2 values quantify the strength of the correlation, with R2 < 0.2 suggesting a lack of association