DNA hypomethylation and oxidative stress-mediated increase in genomic instability in equine sarcoid-derived fibroblasts

It is widely accepted that equine sarcoid disease, the most common skin associated neoplasm in equids, is induced by bovine papillomavirus (BPV-1). Although BPV-1 DNA has been found in almost all examined sarcoids so far, its detailed impact on the horse's host cell metabolism is largely unknown. We used equine fibroblast cell lines originating from sarcoid biopsies to study BPV-1-associated changes on DNA methylation status and oxidative stress parameters. Sarcoid-derived fibroblasts manifested increased proliferation in vitro, transcriptional rDNA activity (NORs expression) and DNA hypomethylation compared to control cells. Cells isolated from equine sarcoids suffered from oxidative stress: the expression of antioxidant enzymes was decreased and the superoxide production was increased. Moreover, increased ploidy, oxidative DNA damage and micronuclei formation was monitored in sarcoid cells. We postulate that both altered DNA methylation status and redox milieu may affect genomic stability in BPV-1-infected cells and in turn contribute to sarcoid pathology.

Sarcoid-derived fibroblasts: links between genomic instability, energy metabolism and senescence.

Bovine papillomavirus 1 (BPV-1) is a well recognized etiopathogenetic factor in a cancer-like state in horses, namely equine sarcoid disease. Nevertheless, little is known about BPV-1-mediated cell transforming effects. It was shown that BPV-1 triggers genomic instability through DNA hypomethylation and oxidative stress. In the present study, we further characterized BPV-1-positive fibroblasts derived from sarcoid tumors. The focus was on cancer-like features of sarcoid-derived fibroblasts, including cell cycle perturbation, comprehensive DNA damage analysis, end-replication problem, energy metabolism and oncogene-induced premature senescence. The S phase of the cell cycle, polyploidy events, DNA double strand breaks (DSBs) and DNA single strand breaks (SSBs) were increased in BPV-1-positive cells compared to control fibroblasts. BPV-1-mediated oxidative stress may contribute to telomere dysfunction in sarcoid-derived fibroblasts. Loss of mitochondrial membrane potential and concurrent elevation in intracellular ATP production may be a consequence of changes in energy-supplying pathways in BPV-1-positive cells which is also typical for cancer cells. Shifts in energy metabolism may support rapid proliferation in cells infected by BPV-1. Nevertheless, sarcoid-derived fibroblasts representing a heterogeneous cell fraction vary in some aspects of metabolic phenotype due to a dual role of BPV-1 in cell transformation and oncogene-induced premature senescence. This was shown with increased senescence-associated β-galactosidase (SA-β-gal) activity. Taken together, metabolic phenotypes in sarcoid-derived fibroblasts are plastic, which are similar to greater plasticity of cancer tissues than normal tissues.

The C-terminal domain of coilin interacts with Sm proteins and U snRNPs

Coilin is the signature protein of the Cajal body (CB), a nuclear suborganelle involved in the biogenesis of small nuclear ribonucleoproteins (snRNPs). Newly imported Sm-class snRNPs are thought to traffic through CBs before proceeding to their final nuclear destinations. Loss of coilin function in mice leads to significant viability and fertility problems. Coilin interacts directly with the spinal muscular atrophy (SMA) protein via dimethylarginine residues in its C-terminal domain. Although coilin hypomethylation results in delocalization of survival of motor neurons (SMN) from CBs, high concentrations of snRNPs remain within these structures. Thus, CBs appear to be involved in snRNP maturation, but factors that tether snRNPs to CBs have not been described. In this report, we demonstrate that the coilin C-terminal domain binds directly to various Sm and Lsm proteins via their Sm motifs. We show that the region of coilin responsible for this binding activity is separable from that which binds to SMN. Interestingly, U2, U4, U5, and U6 snRNPs interact with the coilin C-terminal domain in a glutathione S-transferase (GST)-pulldown assay, whereas U1 and U7 snRNPs do not. Thus, the ability to interact with free Sm (and Lsm) proteins as well as with intact snRNPs, indicates that coilin and CBs may facilitate the modification of newly formed snRNPs, the regeneration of 'mature' snRNPs, or the reclamation of unassembled snRNP components.

Methylation of PITX2, HOXD3, RASSF1 and TDRD1 predicts biochemical recurrence in high-risk prostate cancer

PURPOSE To explore differential methylation of HAAO, HOXD3, LGALS3, PITX2, RASSF1 and TDRD1 as a molecular tool to predict biochemical recurrence (BCR) in patients with high-risk prostate cancer (PCa). METHODS A multiplexed nested methylation-specific PCR was applied to quantify promoter methylation of the selected markers in five cell lines, 42 benign prostatic hyperplasia (BPH) and 71 high-risk PCa tumor samples. Uni- and multivariate Cox regression models were used to assess the importance of the methylation level in predicting BCR. RESULTS A PCa-specific methylation marker HAAO in combination with HOXD3 and a hypomethylation marker TDRD1 distinguished PCa samples (>90 % of tumor cells each) from BPH with a sensitivity of 0.99 and a specificity of 0.95. High methylation of PITX2, HOXD3 and RASSF1, as well as low methylation of TDRD1, appeared to be significantly associated with a higher risk for BCR (HR 3.96, 3.44, 2.80 and 2.85, correspondingly) after correcting for established risk factors. When DNA methylation was treated as a continuous variable, a two-gene model PITX2 × 0.020677 + HOXD3 × 0.0043132 proved to be the best predictor of BCR (HR 4.85) compared with the individual markers. This finding was confirmed in an independent set of 52 high-risk PCa tumor samples (HR 11.89). CONCLUSIONS Differential promoter methylation of HOXD3, PITX2, RASSF1 and TDRD1 emerges as an independent predictor of BCR in high-risk PCa patients. A two-gene continuous DNA methylation model "PITX2 × 0.020677 + HOXD3 × 0.0043132" is a better predictor of BCR compared with individual markers.