Development of a multivariable risk model integrating urinary cell DNA methylation and cell-free RNA data for the detection of significant prostate cancer.

BACKGROUND: Prostate cancer exhibits severe clinical heterogeneity and there is a critical need for clinically implementable tools able to precisely and noninvasively identify patients that can either be safely removed from treatment pathways or those requiring further follow up. Our objectives were to develop a multivariable risk prediction model through the integration of clinical, urine-derived cell-free messenger RNA (cf-RNA) and urine cell DNA methylation data capable of noninvasively detecting significant prostate cancer in biopsy naïve patients. METHODS: Post-digital rectal examination urine samples previously analyzed separately for both cellular methylation and cf-RNA expression within the Movember GAP1 urine biomarker cohort were selected for a fully integrated analysis (n = 207). A robust feature selection framework, based on bootstrap resampling and permutation, was utilized to find the optimal combination of clinical and urinary markers in a random forest model, deemed ExoMeth. Out-of-bag predictions from ExoMeth were used for diagnostic evaluation in men with a clinical suspicion of prostate cancer (PSA ≥ 4 ng/mL, adverse digital rectal examination, age, or lower urinary tract symptoms). RESULTS: As ExoMeth risk score (range, 0-1) increased, the likelihood of high-grade disease being detected on biopsy was significantly greater (odds ratio = 2.04 per 0.1 ExoMeth increase, 95% confidence interval [CI]: 1.78-2.35). On an initial TRUS biopsy, ExoMeth accurately predicted the presence of Gleason score ≥3 + 4, area under the receiver-operator characteristic curve (AUC) = 0.89 (95% CI: 0.84-0.93) and was additionally capable of detecting any cancer on biopsy, AUC = 0.91 (95% CI: 0.87-0.95). Application of ExoMeth provided a net benefit over current standards of care and has the potential to reduce unnecessary biopsies by 66% when a risk threshold of 0.25 is accepted. CONCLUSION: Integration of urinary biomarkers across multiple assay methods has greater diagnostic ability than either method in isolation, providing superior predictive ability of biopsy outcomes. ExoMeth represents a more holistic view of urinary biomarkers and has the potential to result in substantial changes to how patients suspected of harboring prostate cancer are diagnosed.

The proto-oncoprotein SYT interacts with SYT-interacting protein/co-activator activator (SIP/CoAA), a human nuclear receptor co-activator with similarity to EWS and TLS/FUS family of proteins.

The proto-oncoprotein SYT is involved in the unique translocation t(X;18) found in synovial sarcoma SYT-SSX fusions. SYT has a conserved N-terminal domain (SNH domain) that interacts with the human paralog of Drosophila Brahma (hBRM) and Brahma-related gene 1 (BRG1) chromatin remodeling proteins and a C-terminal transactivating sequence rich in glutamine, proline, glycine, and tyrosine (QPGY domain). Here we reported the isolation of the ribonucleoprotein SYT-interacting protein/co-activator activator (SIP/CoAA), which specifically binds the QPGY domain of SYT and also the SYT-SSX2 translocation fusion. SIP/CoAA is a general nuclear co-activator and an RNA splicing modulator that contains two RNA recognition motifs and multiple hexapeptide repeats. We showed that the region consisting of the hexapeptide motif (YQ domain) is similar to the hexapeptide repeat domain found in EWS and in TLS/FUS family proteins. The YQ domain also resembles the QPGY region of SYT itself and like all these other domains acts as a transcriptional activator in reporter assays. Most interestingly, the last 84 amino acids adjacent to YQ down-modulate by 25-fold the YQ transactivation of the reporter gene, and both domains are important for SIP/CoAA binding to SYT. In addition, SYT acts together with SIP/CoAA in stimulating estrogen and glucocorticoid receptor-dependent transcriptional activation. Activation is hormone-dependent and requires functional hBRM and/or BRG1. The stimulation is strongly reduced if the N-terminal region of hBRM/BRG1 (amino acids 1-211) is deleted. This region encompasses the SNF11 binding domain (amino acids 156-211), which interacts specifically with SYT in vivo and in vitro.