Dataset Information

Next Generation Sequencing of urine exfoliated cells: an approach of prostate cancer microRNAs research.

ABSTRACT: There is emerging evidence that microRNAs (miRNAs) dysregulation is involved in the genesis and the progression of Prostate Cancer (PCa), thus potentially increasing their use in urological clinical practice. This is the first pilot study which utilizes Illumina Deep Sequencing to examine the entire miRNAs spectrum existent in urine exfoliated prostate cells (UEPCs) of PCa patients. A total of 11 male patients with histological diagnosis of PCa were enrolled in the present study. First-catch urine (30?mL) was collected following a prostate massage. Total RNA was extracted from urine and sequenced using an HiSeq2500 System (Illumina). QPCR assay was used to validate the highest NGS results in PCA patients and in age-matched, caucasian men. Remarkably, PCA let-7 family was down-regulated (P?

SUBMITTER: Guelfi G

PROVIDER: S-EPMC5940782 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundDespite biomarker development advances, early detection of aggressive prostate cancer (PCa) remains challenging. We previously developed a clinical-grade urine test (Michigan Prostate Score [MiPS]) for individualized aggressive PCa risk prediction. MiPS combines serum prostate-specific antigen (PSA), the TMPRSS2:ERG (T2:ERG) gene fusion, and PCA3 lncRNA in whole urine after digital rectal examination (DRE).ObjectiveTo improve on MiPS with a novel next-generation sequencing (NGS) multibiomarker urine assay for early detection of aggressive PCa.Design, setting, and participantsPreclinical development and validation of a post-DRE urine RNA NGS assay (Urine Prostate Seq [UPSeq]) assessing 84 PCa transcriptomic biomarkers, including T2:ERG, PCA3, additional PCa fusions/isoforms, mRNAs, lncRNAs, and expressed mutations. Our UPSeq model was trained on 73 patients and validated on a held-out set of 36 patients representing the spectrum of disease (benign to grade group [GG] 5 PCa).Outcome measurements and statistical analysisThe area under the receiver operating characteristic curve (AUC) of UPSeq was compared with PSA, MiPS, and other existing models/biomarkers for predicting GG ≥3 PCa.Results and limitationsUPSeq demonstrated high analytical accuracy and concordance with MiPS, and was able to detect expressed germline HOXB13 and somatic SPOP mutations. In an extreme design cohort (n = 109; benign/GG 1 vs GG ≥3 PCa, stratified to exclude GG 2 cancer in order to capture signal difference between extreme ends of disease), UPSeq showed differential expression for T2:ERG.T1E4 (1.2 vs 78.8 median normalized reads, p < 0.00001) and PCA3 (1024 vs 2521, p = 0.02), additional T2:ERG splice isoforms, and other candidate biomarkers. Using machine learning, we developed a 15-transcript model on the training set (n = 73) that outperformed serum PSA and sequencing-derived MiPS in predicting GG ≥3 PCa in the held-out validation set (n = 36; AUC 0.82 vs 0.69 and 0.69, respectively).ConclusionsThese results support the potential utility of our novel urine-based RNA NGS assay to supplement PSA for improved early detection of aggressive PCa.Patient summaryWe have developed a new urine-based test for the detection of aggressive prostate cancer, which promises improvement upon current biomarker tests.

Dataset Information

Next Generation Sequencing of urine exfoliated cells: an approach of prostate cancer microRNAs research.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets