Abstract
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 prostate-specific antigen (PSA) dramatically drops when considering patients with PSA levels ranging from 3 to 10 ng/mL, the so-called grey zone. Hence, additional noninvasive diagnostic and/or prognostic PCa biomarkers are urgently needed, especially in the metabolic-status context. To assess the potential relation of urine In1-ghrelin (a ghrelin-splicing variant) levels with metabolic-related/pathological conditions (eg, obesity, diabetes, body mass index, insulin and 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. Urine In1-ghrelin levels were measured by radioimmunoassay in a clinically, metabolically, pathologically well-characterized cohort of patients without (n = 397) and with (n = 213) PCa with PSA in the grey zone. Key obesity-related factors associated with PCa risk (BMI, diabetes, glucose and insulin levels) 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 (eg, tumor stage, lymphovascular invasion). In1-ghrelin levels added significant diagnostic value to a clinical model consisting of age, suspicious digital rectal exam, 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 (area under the receiver operating characteristic curve = 0.740). Urine In1-ghrelin levels are associated with obesity-related factors and PCa risk and aggressiveness and could represent a novel and valuable noninvasive PCa biomarker, as well as a potential link in the pathophysiological relationship between obesity and PCa.
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More From: The Journal of Clinical Endocrinology & Metabolism
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