A new method, which allows for the identification and prioritization of predicted cancer genes for future analysis, is presented. This method generates a gene-specific score called the "S-Score" by incorporating data from different types of analysis including mutation screening, methylation status, copy-number variation and expression profiling. The method was applied to the data from The Cancer Genome Atlas and allowed the identification of known and potentially new oncogenes and tumor suppressors associated with different clinical features including shortest term of survival in ovarian cancer patients and hormonal subtypes in breast cancer patients. Furthermore, for the first time a genome-wide search for genes that behave as oncogenes and tumor suppressors in different tumor types was performed. We envisage that the S-score can be used as a standard method for the identification and prioritization of cancer genes for follow-up studies.

The specific genes and molecules that drive physiological angiogenesis differ from those involved in pathological angiogenesis, suggesting distinct mechanisms for these seemingly related processes. Unveiling genes and pathways preferentially associated with pathologic angiogenesis is key to understanding its mechanisms, thereby facilitating development of novel approaches to managing angiogenesis-dependent diseases. To better understand these different processes, we elucidated the transcriptome of the mouse retina in the well-accepted oxygen-induced retinopathy (OIR) model of pathological angiogenesis. We identified 153 genes changed between normal and OIR retinas, which represent a molecular signature relevant to other angiogenesis-dependent processes such as cancer. These genes robustly predict the survival of breast cancer patients, which was validated in an independent 1,000-patient test cohort (40% difference in 15-year survival; p = 2.56 x 10-21). These results suggest that the OIR model reveals key genes involved in pathological angiogenesis, and these may find important applications in stratifying tumors for treatment intensification or for angiogenesis-targeted therapies.

Prostate cancer antigen 3 (PCA3) is the most specific prostate cancer biomarker but its function remains unknown. Here we identify PRUNE2, a target protein-coding gene variant, which harbors the PCA3 locus, thereby classifying PCA3 as an antisense intronic long noncoding (lnc)RNA. We show that PCA3 controls PRUNE2 levels via a unique regulatory mechanism involving formation of a PRUNE2/PCA3 double-stranded RNA that undergoes adenosine deaminase acting on RNA (ADAR)-dependent adenosine-to-inosine RNA editing. PRUNE2 expression or silencing in prostate cancer cells decreased and increased cell proliferation, respectively. Moreover, PRUNE2 and PCA3 elicited opposite effects on tumor growth in immunodeficient tumor-bearing mice. Coregulation and RNA editing of PRUNE2 and PCA3 were confirmed in human prostate cancer specimens, supporting the medical relevance of our findings. These results establish PCA3 as a dominant-negative oncogene and PRUNE2 as an unrecognized tumor suppressor gene in human prostate cancer, and their regulatory axis represents a unique molecular target for diagnostic and therapeutic intervention.