J Clin Endocrinol Metab. 2021 Jul 13:dgab516. doi: 10.1210/clinem/dgab516. Online ahead of print.
ABSTRACT
CONTEXT: Recent studies emphasize the importance of considering the metabolic status to develop personalized medicine approaches. This is especially relevant in prostate cancer (PCa), wherein the diagnostic capability of PSA dramatically drops when considering patients with PSA levels ranging 3-10 ng/mL, the so-called “grey-zone”. Hence, additional non-invasive diagnostic and/or prognostic PCa biomarkers are urgently needed, especially in the metabolic-status context.
OBJECTIVE: To assess the potential relation of urine In1-ghrelin (a ghrelin splicing variant) levels with metabolic-related/pathological conditions (e.g. obesity/diabetes/BMI/insulin-glucose levels), and to define its potential clinical value in PCa (diagnostic/prognostic capacity) and relationship with PCa-risk in patients with PSA in the grey-zone.
METHODS: Urine In1-ghrelin levels were measured by radioimmunoassay in a clinically/metabolically/pathologically well-characterized cohort of patients without (n=397) or with (n=213) PCa with PSA in the grey-zone.
RESULTS: Key obesity-related factors associated with PCa-risk (BMI/diabetes/glucose/insulin) were strongly correlated to In1-ghrelin levels. Importantly, In1-ghrelin levels were higher in PCa patients compared to control patients (with suspect of PCa but negative-biopsy). Moreover, high In1-ghrelin levels were associated with increased PCa-risk and linked to PCa-aggressiveness (e.g. tumour-stage/lymphovascular-invasion). In1-ghrelin levels added significant diagnostic value to a clinical model consisting of age, suspicious-DRE, previous-biopsy, and PSA levels. Furthermore, a multivariate model consisting of clinical and metabolic variables, including In1-ghrelin levels, showed high specificity and sensitivity to diagnose PCa (AUC=0.740).
CONCLUSIONS: Urine In1-ghrelin levels are associated with obesity-related factors and PCa risk/aggressiveness, and could represent a novel and valuable non-invasive PCa biomarker, as well as a potential link in the pathophysiological relationship between obesity and PCa.
PMID:34255835 | DOI:10.1210/clinem/dgab516
