Background:There is relatively little methylation array data available specifically for oral squamous cell carcinoma (OSCC). This study aims to compare the DNA methylome across a large cohort of tumour/normal pairs.Methods:DNA was extracted from 44 OSCCs and paired normal mucosa. DNA methylation analysis employed the Illumina GoldenGate high-throughput array comprising 1505 CpG loci selected from 807 epigenetically regulated genes. This data was correlated with extracapsular spread (ECS), human papilloma virus (HPV) status, recurrence and 5-year survival.Results:Differential methylation levels of a number of genes distinguished the tumour tissue sample from the matched normal. Putative methylation signatures for ECS and recurrence were identified. The concept of concordant methylation or CpG island methylator phenotype (CIMP) in OSCC is supported by our data, with an association between ‘CIMP-high' and worse prognosis. Epigenetic deregulation of NOTCH4 signalling in OSCC was also observed, as part of a possible methylation signature for recurrence, with parallels to recently discovered NOTCH mutations in HNSCC. Differences in methylation in HPV-driven cases were seen, but are less significant than that has been recently proposed in other series.Conclusion:Although OSCC seems as much an ‘epigenetic' as a genetic disease, the translational potential of cancer epigenetics has yet to be fully exploited. This data points to the application of epigenetic biomarkers and targets available to further the development of therapy in OSCC.

We show protein kinase C-zeta (PKC-ζ) to be a novel predictive biomarker for survival from prostate cancer (P < 0.001). We also confirm that transcription of the PRKC-ζ gene is crucial to the malignant phenotype of human prostate cancer. Following siRNA silencing of PRKC-ζ in PC3-M prostate cancer cells, stable transfectant cell line si-PRKC-ζ-PC3-M(T1-6) is phenotypically nonmalignant in vitro and in vivo. Genome-wide expression analysis identified 373 genes to be differentially expressed in the knockdown cells and 4 key gene networks to be significantly perturbed during phenotype modulation. Functional interconnection between some of the modulated genes is revealed, although these may be within different regulatory pathways, emphasizing the complexity of their mutual interdependence. Genes with altered expression following PRKC-ζ knockdown include HSPB1, RAD51, and ID1 that we have previously described to be critical in prostatic malignancy. Because expression of PRKC-ζ is functionally involved in promoting the malignant phenotype, we propose PKC-ζ as a novel and biologically relevant target for therapeutic intervention in prostate cancer.

BackgroundWe investigated whether combinations of serum cytokines, used with logistic disease predictor models, could facilitate the detection of pancreatic ductal adenocarcinoma (PDAC).MethodsThe serum levels of 27 cytokines were measured in 241 subjects, 127 with PDAC, 49 with chronic pancreatitis, 20 with benign biliary obstruction and 45 healthy controls. Samples were split randomly into independent training and test sets. Cytokine biomarker panels were selected by identifying the top performing cytokines in best fit logistic regression models during multiple rounds of resampling from the training dataset. Disease prediction by logistic models, built using the resulting cytokine panels, was evaluated with training and test sets and further examined using resampled performance evaluation.ResultsFor the discrimination of PDAC patients from patients with benign disease, a panel of IP-10, IL-6, PDGF plus CA19-9 offered improved diagnostic performance over CA19-9 alone in the training (AUC 0.838 vs. 0.678) and independent test set (AUC 0.884 vs. 0.798). For the discrimination of PDAC from CP, a panel of IL-8, CA19-9, IL-6 and IP-10 offered improved diagnostic performance over CA19-9 alone with the training (AUC 0.880 vs. 0.758) and test set (AUC 0.912 vs. 0.848). Finally, for the discrimination of PDAC in the presence of jaundice from benign controls with jaundice, a panel of IP-10, IL-8, IL-1b and PDGF demonstrated improvement over CA19-9 in the training (AUC 0.810 vs. 0.614) and test set (AUC 0.857 vs. 0.659).ConclusionsThese findings support the potential role for cytokine panels in the discrimination of PDAC from patients with benign pancreatic diseases and warrant additional study.

We provide novel functional data that posttranscriptional silencing of gene RPL19 using RNAi not only abrogates the malignant phenotype of PC-3M prostate cancer cells but is selective with respect to transcription and translation of other genes. Reducing RPL19 transcription modulates a subset of genes, evidenced by gene expression array analysis and Western blotting, but does not compromise cell proliferation or apoptosis in-vitro. However, growth of xenografted tumors containing the knocked-down RPL19 in-vivo is significantly reduced. Analysis of the modulated genes reveals induction of the non-malignant phenotype principally to involve perturbation of networks of transcription factors and cellular adhesion genes. The data provide evidence that extra-ribosomal regulatory functions of RPL19, beyond protein synthesis, are critical regulators of cellular phenotype. Targeting key members of affected networks identified by gene expression analysis raises the possibility of therapeutically stabilizing a benign phenotype generated by modulating the expression of an individual gene and thereafter constraining a malignant phenotype while leaving non-malignant tissues unaffected.