Intratumor heterogeneity in prostate cancer.

Prostate cancer (PCa) has long been thought of as a disease with a heterogeneous phenotype. It can manifest in men as benign growths that can be safely watched or as more aggressive malignancies that can prove fatal. Recent investigations at the genomic, histopathological and molecular levels have identified tumor heterogeneity, the phenomenon of individual tumor cells presenting distinct genomic and phenotypic characteristics, as one of the most confounding and complex factors underlying PCa diagnosis, prognosis, and treatment. Despite tremendous progress made over the course of the last decade we still have an incomplete understanding of the extent and effect of intra- and inter-tumoral heterogeneity in the course of PCa progression. For example, a primary tumor can be classified into one of several molecular subgroups depending on whether the cancer has a particular gene fusion or a mutation which in turn might yield some patient-specific therapeutic regimen, but this same type of heterogeneous growth can be spatially or temporally restricted proving it difficult to detect during biopsy. We therefore present here a comprehensive review of the various studies addressing intra-tumor heterogeneity in PCa and in the context of that seen in other solid tumors. We discuss the impact of heterogeneity on clinical decision-making in treating both primary and metastatic lesions and how our understanding of this heterogeneity might help in developing better diagnostic tools and biomarkers and in guiding the selection of better therapeutic strategies.

Prospective Correlation between Likelihood of Favorable Pathology on the 17-Gene Genomic Prostate Score and Actual Pathological Outcomes at Radical Prostatectomy.

INTRODUCTION: We evaluate the Genomic Prostate Score in a prospective clinical setting and determine the cutoff point for likelihood of favorable pathology, below which definitive treatment should be advised. METHODS: Pathological data were recorded for men who had the Genomic Prostate Score performed and who ultimately underwent radical prostatectomy. Inclusion criteria were newly diagnosed prostate cancer, and NCCN classification as very low, low and low volume intermediate risk. Adverse pathology was defined as any pT3 stage and primary Gleason grade of 4 or any pattern 5. ROC analysis was used to determine the optimal cutoff point of likelihood of favorable pathology for each NCCN risk group. RESULTS: A total of 95 patients were enrolled and 50 patients (53%) underwent radical prostatectomy. Adverse pathology was found in 21 patients (42%), grouped as very low risk 0%, low risk 32.4% and low volume intermediate risk 71.4%. Among those with low risk disease, ROC analysis determined that a likelihood of favorable pathology cutoff of 76% or greater performed the best, correctly classifying 91.2% of patients with a sensitivity of 95.7%, specificity of 81.8% and AUC 0.95. For intermediate risk patients the optimal likelihood of favorable pathology cutoff was 68% or greater, with 92.3% correct, sensitivity 75%, specificity 100% and AUC 0.95. CONCLUSIONS: NCCN low risk patients had the most meaningful information provided by the Genomic Prostate Score. Men with low risk disease with a likelihood of favorable pathology threshold greater than 75% are at very low risk for adverse pathology, whereas those with a likelihood of favorable pathology of 75% or less are at high risk. This likelihood of favorable pathology threshold is greater than 69% for men with low volume intermediate risk disease. These results should help clinicians use Genomic Prostate Score information when making decisions regarding active surveillance or intervention for prostate cancer.