PurposeClinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis.MethodsA nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry who underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 who experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set.ResultsExpression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67–0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression.ConclusionA genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer.

Purpose Prostate cancer patients with locally advanced disease after radical prostatectomy (RP) are candidates for secondary therapy. However, this higher risk population is heterogeneous and many will not metastasize even when conservatively managed. Given the limited specificity of pathologic features to predict metastasis, newer risk-prediction models are needed. This represents a validation study of a genomic classifier (GC) that predicts post-RP metastasis in a high-risk population. Materials and Methods A case-cohort design was used to sample 1,010 post-RP patients at high risk of recurrence treated between 2000-2006. Patients had preoperative PSA >20 ng/mL, Gleason ≥8, pT3b or GPSM score ≥10. Patients with metastasis at diagnosis or any prior treatment for prostate cancer were excluded. 20% random sampling created a subcohort that included all cases with metastasis. 22-marker GC scores were generated for 219 patients with available genomic data. Receiver operating characteristic and decision curves, competing risk, and weighted regression models assessed GC performance. Results GC had area under the curve of 0.79 for predicting 5-year metastasis post-RP. Decision curves showed that net benefit of GC exceeded clinical-only models. GC was the predominant predictor of metastasis in multivariable analysis. Cumulative incidence of metastasis at 5 years post-RP was 2.4%, 6.0% and 22.5% for patients with low (60% of patients), intermediate (21% of patients), and high (19% of patients) GC scores, respectively (p<0.001). Conclusions These results indicate that genomic information from the primary tumor can identify patients with adverse pathology who are most at risk for metastasis and potentially lethal prostate cancer.

Long-term population viability of Fraser River sockeye salmon (Oncorhynchus nerka) is threatened by unusually high levels of mortality as they swim to their spawning areas before they spawn. Functional genomic studies on biopsied gill tissue from tagged wild adults that were tracked through ocean and river environments revealed physiological profiles predictive of successful migration and spawning. We identified a common genomic profile that was correlated with survival in each study. In ocean-tagged fish, a mortality-related genomic signature was associated with a 13.5-fold greater chance of dying en route. In river-tagged fish, the same genomic signature was associated with a 50% increase in mortality before reaching the spawning grounds in one of three stocks tested. At the spawning grounds, the same signature was associated with 3.7-fold greater odds of dying without spawning. Functional analysis raises the possibility that the mortality-related signature reflects a viral infection.

Elevated river water temperature in the Fraser River, British Columbia, Canada, has been associated with enhanced mortality of adult sockeye salmon (Oncorhynchus nerka) during their upriver migration to spawning grounds. We undertook a study to assess the effects of elevated water temperatures on the gill transcriptome and blood plasma variables in wild-caught sockeye salmon. Naturally migrating sockeye salmon returning to the Fraser River were collected and held at ecologically relevant temperatures of 14°C and 19°C for seven days, a period representing a significant portion of their upstream migration. After seven days, sockeye salmon held at 19°C stimulated heat shock response genes as well as many genes associated with an immune response when compared with fish held at 14°C. Additionally, fish at 19°C had elevated plasma chloride and lactate, suggestive of a disturbance in osmoregulatory homeostasis and a stress response detectable in the blood plasma. Fish that died prematurely over the course of the holding study were compared with time-matched surviving fish; the former fish were characterized by an upregulation of several transcription factors associated with apoptosis and downregulation of genes involved in immune function and antioxidant activity. Ornithine decarboxylase (ODC1) was the most significantly upregulated gene in dying salmon, which suggests an association with cellular apoptosis. We hypothesize that the observed decrease in plasma ions and increases in plasma cortisol that occur in dying fish may be linked to the increase in ODC1. By highlighting these underlying physiological mechanisms, this study enhances our understanding of the processes involved in premature mortality and temperature stress in Pacific salmon during migration to spawning grounds.

Characterizing the cellular stress response (CSR) of species at ecologically relevant temperatures is useful for determining whether populations and species can successfully respond to current climatic extremes and future warming. In this study, populations of wild-caught adult pink (Oncorhynchus gorbuscha) and sockeye (Oncorhynchus nerka) salmon from the Fraser River, British Columbia, Canada, were experimentally treated to ecologically relevant ‘cool’ or ‘warm’ water temperatures to uncover common transcriptomic responses to elevated water temperature in non-lethally sampled gill tissue. We detected the differential expression of 49 microarray features (29 unique annotated genes and one gene with unknown function) associated with protein folding, protein synthesis, metabolism, oxidative stress and ion transport that were common between populations and species of Pacific salmon held at 19°C compared with fish held at a cooler temperature (13 or 14°C). There was higher mortality in fish held at 19°C, which suggests a possible relationship between a temperature-induced CSR and mortality in these species. Our results suggest that frequently encountered water temperatures ≥19°C, which are capable of inducing a common CSR across species and populations, may increase risk of upstream spawning migration failure for pink and sockeye salmon.