Endocrine Abstracts

Obesity (OB) is caused by an energy imbalance that finally leads to adipose tissue dysfunction, and the appearance of multiple comorbidities, such as certain cancer types, including prostate cancer (PCa), which is one of the leading causes of cancer-related death in men population worldwide. In this context, periprostatic adipose tissue (PPAT) has recently gained increased attention as a key regulator of the pathophysiological relationship between OB and PCa. However, it has been very challenging to identify suitable and useful housekeeping genes (HKGs) in adipose tissue as reference genes for expression analyses in such pathological conditions (OB and cancer) probably due to the constant dynamic state of the adipose tissue. Therefore, the objective of the present work was to identify a set of HKGs in PPAT samples useful in studies focused on the pathophysiological relationship between OB and cancer using PCa as a cancer model. To that end, 15 potential HKGs were bibliographically selected to evaluate their expression levels by quantitative real-time PCR in a PPAT-screening cohort of normoweight (NW)/obese patients with and without PCa (discovery-cohort; n=20; 5/group). Then, results were validated using an ample set of samples [validation-cohort; n=76; 20/35 PCa patients (with NW/OB), and 6/15 patients without PCa (under NW and OB state), respectively] using a microfluidic quantitative-PCR array (Fluidigm). Stability and HKG suitability were assessed using different software (GeNorm, BestKeeper, and NormFinder). Our results demonstrate that LRP10, followed by PGK1 and RPLP0 exhibits the lowest variability in expression levels across the discovery-cohort using the two methodological approaches mentioned above. Furthermore, the expression of these three genes ranked with the best scores as HKGs using all the programs by discriminating the samples according to the BMI and the presence/absence of tumors. The same results were obtained when using the validation-cohort. Additionally, the validation of these genes was corroborated by the analysis of genes typically altered in OB and PCa conditions and previously reported to be highly dysregulated in PPAT (e.g., MMP2, MMP9, LEP, and ANGPT1). Our analyses revealed that the genes with the highest variability were HMBS, PPIG, and GUSB when the pathophysiological relationship between OB and PCa was studied, but these HKGs were valid to discriminate between non-tumor and PCa conditions. Altogether, we can conclude that LRP10, PGK1, and RPLP0 should be used as optimal HKGs for gene expression analyses in PPAT from patients with OB and/or PCa.

Fundings: MICINN (PID2019-105564RB-I00, FPU18/02485), and CIBERobn.