PURPOSE: Prostate cancer is predominantly indolent at diagnosis with a small fraction (15-25%) representing aggressive subtype [Gleason score (GS) 7-10], which is prone to metastatic progression. It is critical to explore non-invasive assays for the early detection of this aggressive subtype, when it still can be treated effectively. Additionally, there is an emerging need to develop markers that perform equally well across races, as racial differences in the prevalence and mortality of prostate cancer has become evident. MATERIALS AND METHODS: First-catch, non-DRE urine specimens were collected from patients undergoing diagnostic biopsy. Total RNA was extracted from urinary exosomes and a quantitative expression assay protocol using droplet digital PCR was developed for detection of candidate genes in exosomal mRNAs from urine. Clinical performance for the gene expression assay was evaluated to predict high grade cancer (GS 7-10) from low grade cancer (GS 6) and cancer negative cases at biopsy. Assay performance was examined in combination with standard of care (SOC) to determine improvement in model prediction. RESULTS: In a racially diverse patient cohort a two-gene panel (PCA3, PCGEM1), in combination with SOC variables, significantly improved the prediction of high-grade cancer at diagnosis compared to SOC variables alone (AUC=0.88 versus AUC=0.80, respectively, p= 0.016). Decision curve analysis showed that there is a benefit of adopting the gene panel for detection of high-grade cancer compared to SOC alone. CONCLUSIONS: This study highlights the potential for developing broadly applicable CaP diagnostic biomarker panels for aggressive prostate cancer using our novel gene expression assay platform.
PURPOSE:Prostate cancer is predominantly indolent at diagnosis with a small fraction (15-25%) representing aggressive subtype [Gleason score (GS) 7-10], which is prone to metastatic progression. It is critical to explore non-invasive assays for the early detection of this aggressive subtype, when it still can be treated effectively. Additionally, there is an emerging need to develop markers that perform equally well across races, as racial differences in the prevalence and mortality of prostate cancer has become evident. MATERIALS AND METHODS: First-catch, non-DRE urine specimens were collected from patients undergoing diagnostic biopsy. Total RNA was extracted from urinary exosomes and a quantitative expression assay protocol using droplet digital PCR was developed for detection of candidate genes in exosomal mRNAs from urine. Clinical performance for the gene expression assay was evaluated to predict high grade cancer (GS 7-10) from low grade cancer (GS 6) and cancer negative cases at biopsy. Assay performance was examined in combination with standard of care (SOC) to determine improvement in model prediction. RESULTS: In a racially diverse patient cohort a two-gene panel (PCA3, PCGEM1), in combination with SOC variables, significantly improved the prediction of high-grade cancer at diagnosis compared to SOC variables alone (AUC=0.88 versus AUC=0.80, respectively, p= 0.016). Decision curve analysis showed that there is a benefit of adopting the gene panel for detection of high-grade cancer compared to SOC alone. CONCLUSIONS: This study highlights the potential for developing broadly applicable CaP diagnostic biomarker panels for aggressive prostate cancer using our novel gene expression assay platform.
Authors: Haiming Huang; Jialin Du; Bo Jin; Lu Pang; Nan Duan; Chenwei Huang; Jiayin Hou; Wei Yu; Han Hao; Haixia Li Journal: Front Oncol Date: 2021-04-27 Impact factor: 6.244