Descriptions of patient characteristics for each cohort.

<p>SD = standard deviation; ECE = extracapsular extension; SVI = seminal vesicle invasion; PSM = positive surgical margin; LNI = lymph node involvement; GC = genomic classifier; TJU = Thomas Jefferson University; Ref. = reference</p><p>*Note, three patients were excluded from this original cohort due to unknown ECE status; Overall cohort metastatic risk, range of risks for cohort, and proportion classified as high risk according to GC was based on the reweighted cohort of 808 patients from the original cohort of 216 patients.</p><p>Descriptions of patient characteristics for each cohort.</p

Simplified state transition diagram representing the treatment decisions and health state transitions post radical prostatectomy.

<p>NED represents patients with no evidence of disease.</p

Comparison of 5 and 10 year outcomes for usual care vs. genomics-based care decisions using individual level probabilities.

<p>Results are presented for the Mayo Clinic and TJU cohorts. McNemar’s test was used to test for significant differences between usual care and GC-based treatment outcomes for each cohort.</p><p>BCR = biochemical recurrence; MET = metastasis; GC = genomic classifier.</p><p>Comparison of 5 and 10 year outcomes for usual care vs. genomics-based care decisions using individual level probabilities.</p

Time in life years (LYs) in states (Subfigure A), and quality-adjusted life years (QALYs) in states (Subfigure B) for the Mayo Clinic Cohort. GC-based treatment refers to treatment decisions made based upon the genomic risk classifier assay.

<p>BCR = biochemical recurrence; NED = no evidence of disease; GC = genomic classifier.</p

Comparison of 5 and 10 year outcomes for population level probabilities vs. individual level probabilities using usual care treatment.

<p>Results are presented for the Mayo Clinic and TJU cohorts.</p><p>Comparison of 5 and 10 year outcomes for population level probabilities vs. individual level probabilities using usual care treatment.</p

Transcript levels for CCNB1, DLG7, and HMMR measured in CaP and noncancerous prostate tissue.

<p>Panels on the left compare transcript levels in CaP bulk tissue (full symbols) with the levels measured in benign prostate tissue (open symbols) from men free of CaP (BP) and in benign prostate tissue (BPC) adjacent to CaP of combined Gleason score 6 (gs6). Panels on the right display transcript levels measured in non-neoplastic prostate epithelial cells isolated by laser capture microdissection (LCM) in benign tissues (open symbols): BP, benign prostatic hyperplasia (BPH) and BPC adjacent to CaP of the indicated Gleason score (gs). Full symbols in panels on the right denote transcript levels measured in LCM-isolated CaP cells: high-grade prostatic intraepithelial neoplasia (HGPIN), the cells isolated from areas of combined Gleason scores 6 through 8 and cells isolated from lymph node metastases (met). CCNB1, cyclin B1; DLG7, discs large homolog 7; HMMR, hyaluronan-mediated motility receptor.</p

Receiver operating characteristic (ROC) analysis for DLG7.

<p>The area under the curve was 0.74 (95% CI, 068–0.80). Inset: Scatter plot of the normalized expression values for cases (red) and controls (green).</p

Three hypoxia-controlled genes associated with Gleason score and prognosis.

<p>Among the hypoxia-regulated genes significantly overexpressed in CaP, cyclin B1 (CCNB1), DLGAP5 and hyaluronan-mediated motility receptor (HMMR) were associated with Gleason score and disease outcome.</p

Summary description of the 22 markers in the genomic classifier.

*<p>Overlaps with an exon of a 'retained intron' category.</p>1<p>Based on Jiang et al. Mol Endocrinol 23∶1927-33, 2009; Massie et al. EMBO Rep 8∶871-8, 2007.</p

Discovery and Validation of a Prostate Cancer Genomic Classifier that Predicts Early Metastasis Following Radical Prostatectomy

<div><p>Purpose</p><p>Clinicopathologic 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.</p> <p>Methods</p><p>A 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.</p> <p>Results</p><p>Expression 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.</p> <p>Conclusion</p><p>A 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.</p> </div