Open AccessEarly detection of clinically significant prostate cancer at diagnosis: a prospective study using a novel panel of TMPRSS 2: ETS fusion gene markers
Author(s) -
Chan Sam W.,
Nguyen PhuongNam,
Violette Philippe,
Brimo Fadi,
Taguchi Yosh,
Aprikian Armen,
Chen Junjian Z.
Publication year - 2013
Publication title -
cancer medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 53
ISSN - 2045-7634
DOI - 10.1002/cam4.49
Subject(s) - prostate cancer , medicine , pca3 , biopsy , prostate biopsy , cancer , tmprss2 , oncology , prostate , odds ratio , prostate specific antigen , prospective cohort study , urine , receiver operating characteristic , disease , covid-19 , infectious disease (medical specialty)
We explore noninvasive clinical applications of multiple disease‐specific fusion markers recently discovered in prostate cancer to predict the risk of cancer occurrence and aggressiveness at diagnosis. A total of 92 men who were prostate‐specific antigen ( PSA ) screened and scheduled for diagnostic biopsy were enrolled for this study. Prospectively collected urine was blind coded for laboratory tests. RNA from urine sediments was analyzed using a panel of 6 TMPRSS 2: ETS fusion markers with a sensitive quantitative PCR platform. The pathology reported 39 biopsy‐positive cases from 92 patients (42.4%). In urine test, 10 unique combinations of fusion types were detected in 32 of 92 (34.8%) prebiopsy samples. A novel combination of fusion markers, termed F x ( III , IV , ETS ), was identified with a sensitivity of 51.3% and an odds ratio of 10.1 in detecting cancer on biopsy. Incorporating a categorical variable of F x ( III , IV , ETS ) with urine PCA 3 and serum PSA , a regression model was developed to predict biopsy outcomes with an overall accuracy of 77%. Moreover, the overexpression of F x ( III , IV , or ETS ) was shown to be an independent predictor to the high‐grade cancer, with a predictive accuracy of 80% when coupled with PSA density. The individualized risk scores further stratified a high‐risk group that is composed of 92% high‐grade cancers and a low‐risk group that harbors mainly clinically insignificant cancers. In conclusion, we have identified a novel combination of fusion types very specific to the clinically significant prostate cancer and developed effective regression models to predict biopsy outcomes and aggressive cancers at diagnosis.