HSP27/Menin Expression as New Prognostic Serum Biomarkers of Prostate Cancer Aggressiveness Independent of PSA

Changes in immunophenotypes after neoadjuvant endocrine therapy for prostate cancer and their clinical significance

Background

To investigate changes in the immunophenotypes of androgen receptor (AR), prostate-specific antigen (PSA), synaptophysin (Syn), chromogranin A (CgA), p53 and Ki-67 after neoadjuvant endocrine therapy (NET) for prostate cancer (PCa) and to analyze their clinical significance.

Methods

Paired paraffin samples were collected from 40 PCa patients before and after NET, and immunohistochemistry were used to detect AR, PSA, Syn, CgA, p53 and Ki-67 expression. Based on The Cancer Genome Atlas (TCGA), Kaplan‒Meier survival curves were plotted for analysis of PSA and Ki-67 expression in relation to progression-free survival (PFS).

Results

After NET, the mean scores for PSA and Ki-67 expression in PCa patients were lower than those before NET (P < 0.05), while the mean scores for Syn and CgA expression were higher than those before NET (P < 0.05). The mean Gleason score and WHO/ISUP (World Health Organization/International Society of Urological Pathology) grade after NET were lower than those before NET (P < 0.05). In PCa patients who had not yet received NET, PSA expression correlated positively with Gleason score and WHO/ISUP grade and negatively with Ki-67 expression (P < 0.05); p53 expression correlated negatively with Gleason score and WHO/ISUP grade (P < 0.05). TCGA showed that PFS was lower in PCa patients with high PSA and Ki-67 expression (P < 0.05).

Conclusions

PSA and Ki-67 protein expressions decreased significantly in PCa patients after NET and can be used as biological markers for prognostic assessment of PCa patients. NETs may induce a neuroendocrine (NE) phenotype in PCa. Monitoring the immunophenotypes of PCa patients after NET may inform assessment of efficacy and prognosis.

SNPs-Panel Polymorphism Variations in GHRL and GHSR Genes Are Not Associated with Prostate Cancer

Prostate cancer (PCa) is a major public health problem worldwide. Recent studies have suggested that ghrelin and its receptor could be involved in the susceptibility to several cancers such as PCa, leading to their use as an important predictive way for the clinical progression and prognosis of cancer. However, conflicting results of single nucleotide polymorphisms (SNPs) with ghrelin (GHRL) and its receptor (GHSR) genes were demonstrated in different studies. Thus, the present case-control study was undertaken to investigate the association of GHRL and GHSR polymorphisms with the susceptibility to sporadic PCa. A cohort of 120 PCa patients and 95 healthy subjects were enrolled in this study. Genotyping of six SNPs was performed: three tag SNPs in GHRL (rs696217, rs4684677, rs3491141) and three tag SNPs in the GHSR (rs2922126, rs572169, rs2948694) using TaqMan. The allele and genotype distribution, as well as haplotypes frequencies and linked disequilibrium (LD), were established. Multifactor dimensionality reduction (MDR) analysis was used to study gene-gene interactions between the six SNPs. Our results showed no significant association of the target polymorphisms with PCa (p > 0.05). Nevertheless, SNPs are often just markers that help identify or delimit specific genomic regions that may harbour functional variants rather than the variants causing the disease. Furthermore, we found that one GHSR rs2922126, namely the TT genotype, was significantly more frequent in PCa patients than in controls (p = 0.040). These data suggest that this genotype could be a PCa susceptibility genotype. MDR analyses revealed that the rs2922126 and rs572169 combination was the best model, with 81.08% accuracy (p = 0.0001) for predicting susceptibility to PCa. The results also showed a precision of 98.1% (p < 0.0001) and a PR-AUC of 1.00. Our findings provide new insights into the influence of GHRL and GHSR polymorphisms and significant evidence for gene-gene interactions in PCa susceptibility, and they may guide clinical decision-making to prevent overtreatment and enhance patients' quality of life.