Novel fusion transcripts associate with progressive prostate cancer

Genomic Copy Number Variations in the Genomes of Leukocytes Predict Prostate Cancer Clinical Outcomes

Accurate prediction of prostate cancer clinical courses remains elusive. In this study, we performed whole genome copy number analysis on leukocytes of 273 prostate cancer patients using Affymetrix SNP6.0 chip. Copy number variations (CNV) were found across all chromosomes of the human genome. An average of 152 CNV fragments per genome was identified in the leukocytes from prostate cancer patients. The size distributions of CNV in the genome of leukocytes were highly correlative with prostate cancer aggressiveness. A prostate cancer outcome prediction model was developed based on large size ratio of CNV from the leukocyte genomes. This prediction model generated an average prediction rate of 75.2%, with sensitivity of 77.3% and specificity of 69.0% for prostate cancer recurrence. When combined with Nomogram and the status of fusion transcripts, the average prediction rate was improved to 82.5% with sensitivity of 84.8% and specificity of 78.2%. In addition, the leukocyte prediction model was 62.6% accurate in predicting short prostate specific antigen doubling time. When combined with Gleason’s grade, Nomogram and the status of fusion transcripts, the prediction model generated a correct prediction rate of 77.5% with 73.7% sensitivity and 80.1% specificity. To our knowledge, this is the first study showing that CNVs in leukocyte genomes are predictive of clinical outcomes of a human malignancy.

Discovery and Classification of Fusion Transcripts in Prostate Cancer and Normal Prostate Tissue

Fusion transcript formation is one of the fundamental mechanisms that drives the development of prostate cancer. Because of the advance of high-throughput parallel sequencing, many fusion transcripts have been discovered. However, the discovery rate of fusion transcripts specific for prostate cancer is lagging behind the discoveries made on chromosome abnormalities of prostate cancer. Recent analyses suggest that many fusion transcripts are present in both benign and cancerous tissues. Some of these fusion transcripts likely represent important components of normal gene expression in cells. It is necessary to identify the criteria and features of fusion transcripts that are specific for cancer. In this review, we discuss optimization of RNA sequencing depth for fusion transcript discovery and the characteristics of fusion transcripts in normal prostate tissues and prostate cancer. We also propose a new classification of cancer-specific fusion transcripts on the basis of their tail gene fusion protein product and the roles that these fusions may play in cancer development.

Leucine-rich repeat-containing protein 59 mediates nuclear import of cancerous inhibitor of PP2A in prostate cancer cells

Using yeast two-hybrid analysis, we identified several novel protein interactions for the oncoprotein Cancerous Inhibitor of PP2A (CIP2A) and confirmed a subset of these interactions in human cancer cell lines. Analysis of the interaction in prostate carcinoma cells between CIP2A and leucine-rich repeat-containing protein 59 (LRRC59) suggests that CIP2A is translocated into the nucleus at G2/M through its association with LRRC59. Recent work by others has demonstrated that nuclear CIP2A disrupts mitotic checkpoints, which promotes deregulation of the cell cycle and increases cancerous phenotypes. Thus, we provide a novel therapeutic mechanism for inhibiting CIP2A function in cancerous cells via targeting the CIP2A-LRRC59 interaction.

Fusing transcriptomics to progressive prostate cancer

This commentary highlights the article by Yu et al, describing a set of novel fusion transcripts strongly associated with prostate cancer prognosis.