The various sperm cell types present in a simple ejaculate differ in their motility and morphology. However, little is known about the nuclear maturity of these sperm cells and their relationship with morphological and motile characteristics. Protamines are considered a good marker of sperm nuclear maturity since they are added to the DNA in the last stage of spermatogenesis. We have analyzed the P1/P2 ratio and the protamine content of subpopulations of human spermatozoa at different stages of maturation, isolated by density gradient centrifugation of ejaculated spermatozoa obtained from 3 groups of patients from our Assisted Reproduction Unit: 10 men of proven fertility, 12 oligozoospermic men, and 13 asthenozoospermic men. Four different fractions (F2‐F5) were collected from the top to the bottom of the Percoll gradient. Differences in the motion and morphology were found between the fractions in each of the groups studied, with fraction F5 being the one with the best morphology and motility. However, no significant differences in the P1/P2 ratio were found between fractions within the same group of samples, indicating that the P1/P2 ratio and the amount of protamines are relatively independent of the morphology and motility of sperm cells. In contrast, statistically significant differences were found in the P1/P2 ratio and in the relative amount of protamines between the 3 groups.

Molecular characterization of radical prostatectomy specimens after systemic therapy may identify a gene expression profile for resistance to therapy. This study assessed tumor cells from patients with prostate cancer participating in a phase II neoadjuvant docetaxel and androgen deprivation trial to identify mediators of resistance. Transcriptional level of 93 genes from a docetaxel-resistant prostate cancer cell lines microarray study was analyzed by TaqMan low-density arrays in tumors from patients with high-risk localized prostate cancer (36 surgically treated, 28 with neoadjuvant docetaxel + androgen deprivation). Gene expression was compared between groups and correlated with clinical outcome. VIM, AR and RELA were validated by immunohistochemistry. CD44 and ZEB1 expression was tested by immunofluorescence in cells and tumor samples. Parental and docetaxel-resistant castration-resistant prostate cancer cell lines were tested for epithelial-to-mesenchymal transition (EMT) markers before and after docetaxel exposure. Reversion of EMT phenotype was investigated as a docetaxel resistance reversion strategy. Expression of 63 (67.7%) genes differed between groups (P < 0.05), including genes related to androgen receptor, NF-κB transcription factor, and EMT. Increased expression of EMT markers correlated with radiologic relapse. Docetaxel-resistant cells had increased EMT and stem-like cell markers expression. ZEB1 siRNA transfection reverted docetaxel resistance and reduced CD44 expression in DU-145R and PC-3R. Before docetaxel exposure, a selected CD44⁺ subpopulation of PC-3 cells exhibited EMT phenotype and intrinsic docetaxel resistance; ZEB1/CD44⁺ subpopulations were found in tumor cell lines and primary tumors; this correlated with aggressive clinical behavior. This study identifies genes potentially related to chemotherapy resistance and supports evidence of the EMT role in docetaxel resistance and adverse clinical behavior in early prostate cancer. Mol Cancer Ther; 13(5); 1270–84. ©2014 AACR.

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.

There is a need in urological practice to identify new bladder cancer molecular markers to further develop noninvasive diagnostic tests. We analyzed bladder cancer gene expression profiles to determine the relevant differentially expressed genes and whether this differential expression is maintained in urine samples. We collected 55 tissue specimens from a total of 43 patients with bladder cancer and 12 controls, and 49 urine samples from bladder washings from a total of 36 patients with bladder cancer and 13 controls between September 2003 and December 2004. DNA microarrays (GeneChip Human Genome U133 Plus 2.0 Array) were used to identify differentially expressed genes at 3 bladder cancer stages. Selected differentially expressed genes were validated in an independent set of bladder washings by quantitative reverse transcriptase-polymerase chain reaction. Unsupervised cluster analysis of DNA microarray data showed a clear distinction in control vs tumor samples and low vs high grade tumors. Genes with at least 2-fold differential expression in controls vs tumors (2,937 probe sets or 2,295 genes) and in low vs high grade tumors (674 probe sets or 530 genes) were identified and ranked. Gene expression measurements in bladder washings of the 6 most differentially expressed genes in controls vs tumors were confirmed for the 2 over expressed genes tested by quantitative reverse transcriptase-polymerase chain reaction. All 8 selected differentially expressed genes in low vs high grade tumors were confirmed in bladder washing samples. Bladder cancer analysis by DNA microarrays provides new putative mRNA markers for bladder cancer diagnosis and/or prognosis that can be extrapolated to bladder fluids.