Commercialized Blood-, Urinary- and Tissue-Based Biomarker Tests for Prostate Cancer Diagnosis and Prognosis

Visser, Wieke C H; Jong, Hans de; Melchers, Willem J. G.; Mulders, Peter F.A.; Schalken, Jack A.

doi:10.3390/cancers12123790

Cited by 23 publications

(19 citation statements)

References 104 publications

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“…Previous reports demonstrated that PCA3 was present in urine and could be a diagnostic marker for prostate cancer [19][20][21]. A recent meta-analysis of PCA3 including 54 studies (17,575 patients) indicated that the overall ROC of PCA3 was 0.75 (95% CI: 0.71-0.79) [22].…”

Section: Discussionmentioning

confidence: 99%

A Novel Urine Exosomal lncRNA Assay to Improve the Detection of Prostate Cancer at Initial Biopsy: A Retrospective Multicenter Diagnostic Feasibility Study

Lyu

et al. 2021

Cancers

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Purpose: This study aimed at developing and validating a novel noninvasive urinary exosome-based post-DRE (digital rectal examination) lncRNA assay to diagnose PCa (prostate cancer) and clinically significant PCa (Gleason score ≥ 7) from the initial prostate biopsy. Methods: A total of 602 urine samples from eligible participants were collected. The expression levels of urinary exosomal PCA3 (prostate cancer antigen 3) and MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) were detected by qPCR (quantitative real-time PCR). Receiver operating characteristic (ROC) analysis was applied to evaluate the diagnostic performance of PCA3, MALAT1 and the lncRNA assay. A decision curve analysis (DCA) and waterfall plots were used to assess the clinical value of the lncRNA assay. Results: Urinary exosomal PCA3 and MALAT1 were overexpressed in PCa and clinically significant PCa (p < 0.001). The lncRNA assay combining PCA3 and MALAT1 had a better diagnostic performance (AUC 0.828) than the current clinical parameters in detecting PCa. More importantly, the lncRNA assay yielded an AUC of 0.831 to detect clinically significant PCa, which is much higher than that of the current clinical parameters. The lncRNA assay was superior to PSA, f/tPSA and the base model for detecting PCa and clinically significant PCa, with a higher net benefit for almost all threshold probabilities. At the cutoff value of 95% sensitivity, the lncRNA assay could avoid 24.2% unnecessary biopsies while only missing 1.2% of the cases of clinically significant PCa. Conclusion: We developed and validated a novel noninvasive post-DRE urine-based lncRNA assay that presented good diagnostic power and clinical utility for the early diagnosis of PCa and high-grade PCa.

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Section: Discussionmentioning

confidence: 99%

A Novel Urine Exosomal lncRNA Assay to Improve the Detection of Prostate Cancer at Initial Biopsy: A Retrospective Multicenter Diagnostic Feasibility Study

Lyu

et al. 2021

Cancers

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“…However, our PCA indeed uncover relevant PRAD genes found dispersed across several studies, providing new putative biomarkers and/or drivers. In this sense, the inclusion of PCA3 within our PRAD-CES seems encouraging since this LncRNA is well recognized as causative, prostate-specific and feasible biomarker which is secreted to an easy-to-inquire biological fluids [65]. Finally, as therapeutic options for poorly tractable Pca are limited, the evaluation of putative novel molecular targets populating PRAD-CES seems appealing.…”

Section: Discussionmentioning

confidence: 99%

Principal component analysis of RNA-seq data unveils a novel prostate cancer-associated gene expression signature

Perera¹,

Gonzalez

Pérez

2020

Preprint

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Prostate cancer is a highly heterogeneous disease and the second more common tumor in males. Molecular and genetic profiles are currently used to identify subtypes and to guide therapeutic intervention. However, roughly 26% of primary prostate cancers of both good and poor prognosis is driven by unknown molecular lesions. Thus, ongoing research aims at providing better prognostic biomarkers and causal molecular alterations to intervene. Here, we use Principal Component Analysis (PCA) and custom RNAseq-data normalization to identify a gene expression signature which segregates primary PRAD from normal tissues. This Core-Expression Signature (PRAD-CES) includes 33 genes and accounts for 39% of data complexity along what we call the PC1-cancer axis. The PRAD-CES is populated by protein-coding (AMACR, TP63, HPN) and RNA-genes (PCA3, ARLN1) sparsely found in previous studies, others with validated/predicted roles as biomarkers (HOXC6, TDRD1, DLX1), and/or cancer drivers (PCA3, ARLN1, PCAT-14). Of note, the PRAD-CES also comprises six over-expressed LncRNAs with no previous association with Pca biology. Overall, the PCA allows us to capture roughly 3/4 of data complexity in the first eight PCs, whereas PC1, PC2 and PC3 altogether comprise 57% of such variability. Finally, GO enrichment analysis and PCs correlation with major PRAD clinical features (i.e. Gleason Score, AR Score, TMPRSS2-ERG fusions and Tumor Cellularity) suggest that PC2 and PC3 gene signatures might describe more aggressive and inflammation-prone transitional forms of PRAD with infiltrating immunosystem. The list of surfaced genes may entail putative novel prognostic biomarkers and/or molecular alterations to intervene.

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“…Different trials have focused on improving “smart screening” through PSA‐derived blood tests (4Kscore, PHI) and postDRE urine‐based gene assays (MiPS, Select MDx). However, most of these tests have not been tested in the gray‐zone (the most uncertain risk population) cohorts of biopsy‐naïve patients with a normal DRE and a PSA between 3 and 10 ng/ml 9 . Furthermore, current clinical practice guidelines strongly recommend performing prostatic magnetic resonance imaging (pMRI) before a prostate biopsy, as pMRI has shown high sensitivity for the identification of Sig PCa.…”

Section: Introductionmentioning

confidence: 99%

Prospective study of diagnostic accuracy in the detection of high‐grade prostate cancer in biopsy‐naïve patients with clinical suspicion of prostate cancer who underwent the Select MDx test

et al. 2021

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Objectives: This study aimed to externally validate the diagnostic accuracy of the Select MDx test for Significant prostate cancer (Sig PCa) (ISUP > 1), in a contemporaneous, prospective, multicenter cohort with a prostate-specific antigen (PSA) between 3 and 10 ng/ml and a non-suspicious digital rectal examination.Methods and Participants: For all enrolled patients, the Select Mdx test, the risk calculator ERSPC3 + DRE, and a prostatic magnetic resonance imaging (MRI) were carried out. Subsequently, a systematic 12-core trans-rectal biopsy and a targeted biopsy, in the case of a prostate imaging-reporting and data system (PIRADS) > 2 lesion (max three lesions), were performed. To assess the accuracy of the Select MDx test in the detection of clinically Sig PCa, the test sensitivity was evaluated.Secondary objectives were specificity, negative predictive value (NPV), positive predictive value (PPV), and area under the curve (AUC). A direct comparison with the ERSPC + DRE risk calculator and MRI were also performed. We also studied the predictive ability to diagnose Sig PCa from the combination of the Select MDx test with MRI using clinical decision-curve analysis.Results: There were 163 patients enrolled after meeting the inclusion criteria and study protocol. The Select MDx test showed a sensitivity of 76.9% (95% CI, 63.2-87.5), 49.6% specificity (95% CI, 39.9-59.2), 82.09% (95% CI, 70.8-90.4) NPV, and 41.67% (95% CI, 31.7-52.2) PPV for the diagnosis of Sig PCa. COR analysis was also performed, which showed an AUC of 0.63 (95% CI, 0.56-0.71). There were no differences in the accuracy of Select MDx, ERSPC + DRE, or MRI. The combination

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Commercialized Blood-, Urinary- and Tissue-Based Biomarker Tests for Prostate Cancer Diagnosis and Prognosis

Cited by 23 publications

References 104 publications

A Novel Urine Exosomal lncRNA Assay to Improve the Detection of Prostate Cancer at Initial Biopsy: A Retrospective Multicenter Diagnostic Feasibility Study

A Novel Urine Exosomal lncRNA Assay to Improve the Detection of Prostate Cancer at Initial Biopsy: A Retrospective Multicenter Diagnostic Feasibility Study

Principal component analysis of RNA-seq data unveils a novel prostate cancer-associated gene expression signature

Prospective study of diagnostic accuracy in the detection of high‐grade prostate cancer in biopsy‐naïve patients with clinical suspicion of prostate cancer who underwent the Select MDx test

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