A 17-gene Assay to Predict Prostate Cancer Aggressiveness in the Context of Gleason Grade Heterogeneity, Tumor Multifocality, and Biopsy Undersampling

avai lable at www.sciencedirect.com journal homepage: www.europeanurology.com Genomic Prostate Score Outcome measures and statistical analysis: The main outcome measures defining aggressive PCa were clinical recurrence, PCa death, and adverse pathology at prostatec-predictive of aggressClinical validation Clinical utility tomy. Cox proportional hazards regressionmodels were used to evaluate the association between gene expression and time to event end points. Results from the prostatectomy and biopsy studies were used to develop and lock a multigene-expression-based signature, called the Genomic Prostate Score (GPS); in the validation study, logistic regression was used to test the association between the GPS and pathologic stage and grade at prostatectomy. Decision-curve analysis and risk profileswere used together with clinical and pathologic characteristics to evaluate clinical utility. Results and limitations: Of the 732 candidate genes analyzed, 288 (39%) were found to predict clinical recurrence despite heterogeneity and multifocality, and 198 (27%) were ive disease after adjustment for prostate-specific antigen, GleasonArticle inf

Sarcina Organisms in the Gastrointestinal Tract: A Clinicopathologic and Molecular Study

Sarcina organisms were first observed in and recorded from the stomach contents of a patient suffering from vomiting by John Goodsir in 1842. Since that time, their fine structure, phylogenetic classification, and biochemical characteristics have been described. Although numerous cases of fatal disease have been attributed to this organism in the veterinary literature, only a few human cases have been documented. As a result, whether this organism causes disease in humans has not been definitively established. We report the clinicopathologic findings in a series of 5 patients with Sarcina-like organisms identified in upper gastrointestinal endoscopic biopsies with molecular confirmation. Our findings have shown that the organism is most commonly found in patients with a history of gastric outlet obstruction or delayed gastric emptying. Although many of the patients do not demonstrate direct mucosal injury from the organism, the presence of a concurrent gastric ulcer puts the patient at increased risk for complications such as emphysematous gastritis or perforation. The finding of Sarcina organisms should prompt further investigation for functional causes of gastric outlet obstruction and delayed gastric emptying, such as occult malignancy

Comparison of Sanger Sequencing, Pyrosequencing, and Melting Curve Analysis for the Detection of KRAS Mutations: Diagnostic and Clinical Implications

Mutations in codons 12 and 13 of the KRAS oncogene are relatively common in colorectal and lung adenocarcinomas. Recent data indicate that these mutations result in resistance to anti-epidermal growth factor receptor therapy. Therefore, we assessed Sanger sequencing, pyrosequencing, and melting curve analysis for the detection of KRAS codon 12/13 mutations in formalin-fixed paraffin-embedded samples, including 58 primary and 42 metastatic colorectal adenocarcinomas, 63 primary and 17 metastatic lung adenocarcinomas, and 20 normal colon samples. Of 180 tumor samples, 62.2% were KRAS mutant positive, and 37.8% were negative. Melting curve analysis yielded no false positive or false negative results, but had 10% equivocal calls. Melting curve analysis also resulted in 4 cases with melting curves inconsistent with either wild-type or codon 12/13 mutations. These patterns were generated from samples with double mutants in codons 12/13 and with mutations outside of codons 12/13. Pyrosequencing yielded no false positive or false negative results as well. However, two samples from one patient yielded a pyrogram that was flagged as abnormal, but the mutation subtype could not be determined. Finally, using an electronic cutoff of 10%, Sanger sequencing showed 11.1% false positives and 6.1% false negatives. In our hands, the limit of detection for Sanger sequencing, pyrosequencing, and melting curve analysis was approximately 15 to 20%, 5%, and 10% mutant alleles, respectively

A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling.

BackgroundProstate tumor heterogeneity and biopsy undersampling pose challenges to accurate, individualized risk assessment for men with localized disease.ObjectiveTo identify and validate a biopsy-based gene expression signature that predicts clinical recurrence, prostate cancer (PCa) death, and adverse pathology.Design, setting, and participantsGene expression was quantified by reverse transcription-polymerase chain reaction for three studies-a discovery prostatectomy study (n=441), a biopsy study (n=167), and a prospectively designed, independent clinical validation study (n=395)-testing retrospectively collected needle biopsies from contemporary (1997-2011) patients with low to intermediate clinical risk who were candidates for active surveillance (AS).Outcome measures and statistical analysisThe main outcome measures defining aggressive PCa were clinical recurrence, PCa death, and adverse pathology at prostatectomy. Cox proportional hazards regression models were used to evaluate the association between gene expression and time to event end points. Results from the prostatectomy and biopsy studies were used to develop and lock a multigene-expression-based signature, called the Genomic Prostate Score (GPS); in the validation study, logistic regression was used to test the association between the GPS and pathologic stage and grade at prostatectomy. Decision-curve analysis and risk profiles were used together with clinical and pathologic characteristics to evaluate clinical utility.Results and limitationsOf the 732 candidate genes analyzed, 288 (39%) were found to predict clinical recurrence despite heterogeneity and multifocality, and 198 (27%) were predictive of aggressive disease after adjustment for prostate-specific antigen, Gleason score, and clinical stage. Further analysis identified 17 genes representing multiple biological pathways that were combined into the GPS algorithm. In the validation study, GPS predicted high-grade (odds ratio [OR] per 20 GPS units: 2.3; 95% confidence interval [CI], 1.5-3.7; p<0.001) and high-stage (OR per 20 GPS units: 1.9; 95% CI, 1.3-3.0; p=0.003) at surgical pathology. GPS predicted high-grade and/or high-stage disease after controlling for established clinical factors (p<0.005) such as an OR of 2.1 (95% CI, 1.4-3.2) when adjusting for Cancer of the Prostate Risk Assessment score. A limitation of the validation study was the inclusion of men with low-volume intermediate-risk PCa (Gleason score 3+4), for whom some providers would not consider AS.ConclusionsGenes representing multiple biological pathways discriminate PCa aggressiveness in biopsy tissue despite tumor heterogeneity, multifocality, and limited sampling at time of biopsy. The biopsy-based 17-gene GPS improves prediction of the presence or absence of adverse pathology and may help men with PCa make more informed decisions between AS and immediate treatment.Patient summaryProstate cancer (PCa) is often present in multiple locations within the prostate and has variable characteristics. We identified genes with expression associated with aggressive PCa to develop a biopsy-based, multigene signature, the Genomic Prostate Score (GPS). GPS was validated for its ability to predict men who have high-grade or high-stage PCa at diagnosis and may help men diagnosed with PCa decide between active surveillance and immediate definitive treatment