👤 Milan Kral

Prostate cancer (PCa) is the second leading cause of cancer-related deaths in men in Western countries, and there is still an urgent need for a better understanding of PCa progression to inspire new treatment strategies. Skp2 is a substrate-recruiting component of the E3 ubiquitin ligase complex, whose activity is regulated through neddylation. Slug is a transcriptional repressor involved in the epithelial-to-mesenchymal transition, which may contribute to therapy resistance. Although Skp2 has previously been associated with a mesenchymal phenotype and prostate cancer progression, the relationship with Slug deserves further elucidation. We have previously shown that a high Gleason score (≥8) is associated with higher Skp2 and lower E-cadherin expression. In this study, significantly increased expression of Skp2, AR, and Slug, along with E-cadherin downregulation, was observed in primary prostate cancer in patients who already had lymph node metastases. Skp2 was slightly correlated with Slug and AR in the whole cohort (Rs 0.32 and 0.37, respectively), which was enhanced for both proteins in patients with high Gleason scores (Rs 0.56 and 0.53, respectively) and, in the case of Slug, also in patients with metastasis to lymph nodes (Rs 0.56). Coexpression of Skp2 and Slug was confirmed in prostate cancer tissues by multiplex immunohistochemistry and confocal microscopy. The same relationship between these two proteins was observed in three sets of prostate epithelial cell lines (PC3, DU145, and E2) and their mesenchymal counterparts. Chemical inhibition of Skp2, but not RNA interference, modestly decreased Slug protein in PC3 and its docetaxel-resistant subline PC3 DR12. Importantly, chemical inhibition of Skp2 by MLN4924 upregulated p27 and decreased Slug expression in PC3, PC3 DR12, and LAPC4 cells. Novel treatment strategies targeting Skp2 and Slug by the neddylation blockade may be promising in advanced prostate cancer, as recently documented for other aggressive solid tumors. Show less

Genome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To overcome the limited scope that common variants provide, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome. Using samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. For prevalent events, a total of 27,349 participants of European ancestry, including 1831 prevalent MI cases and 2518 prevalent CHD cases were used. For incident cases, a total of 55,736 participants of European ancestry were included (3,031 incident MI cases and 5,425 incident CHD cases). There were 1,860 all-cause deaths among the 3,751 MI and CHD cases from six cohorts that contributed to the analysis of all-cause mortality. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR = 1.80, 95% confidence interval: 1.43, 2.27; P = 7.12 × 10-7). We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) ≥ 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event. This study identified one known locus (ANGPTL4) and four new loci (PLCL1, RC3H2, TMPRSS5, and LDLRAD1) associated with cardiovascular disease risk that warrant further investigation. Show less

The DNA damage checkpoints provide an anti-cancer barrier in diverse tumour types, however this concept has remained unexplored in prostate cancer (CaP). Furthermore, targeting DNA repair defects by PARP1 inhibitors (PARPi) as a cancer treatment strategy is emerging yet requires suitable predictive biomarkers. To address these issues, we performed immunohistochemical analysis of multiple markers of DNA damage signalling, oxidative stress, DNA repair and cell cycle control pathways during progression of human prostate disease from benign hyperplasia, through intraepithelial neoplasia to CaP, complemented by genetic analyses of TMPRSS2-ERG rearrangement and NQO1, an anti-oxidant factor and p53 protector. The DNA damage checkpoint barrier (γH2AX, pATM, p53) mechanism was activated during CaP tumorigenesis, albeit less and with delayed culmination compared to other cancers, possibly reflecting lower replication stress (slow proliferation despite cases of Rb loss and cyclin D1 overexpression) and progressive loss of ATM activator NKX3.1. Oxidative stress (8-oxoguanine lesions) and NQO1 increased during disease progression. NQO1 genotypes of 390 men did not indicate predisposition to CaP, yet loss of NQO1 in CaP suggested potential progression-opposing tumour suppressor role. TMPRSS2-ERG rearrangement and PTEN loss, events sensitizing to PARPi, occurred frequently along with heterogeneous loss of DNA repair factors 53BP1, JMJD1C and Rev7 (all studied here for the first time in CaP) whose defects may cause resistance to PARPi. Overall, our results reveal an unorthodox DNA damage checkpoint barrier scenario in CaP tumorigenesis, and provide novel insights into oxidative stress and DNA repair, with implications for biomarker guidance of future targeted therapy of CaP. Show less

OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants. Show less