Serum miRNAs Support the Indication for MRI-Ultrasound Fusion-Guided Biopsy of the Prostate in Patients with Low-PI-RADS Lesions

Magnetic Resonance Imaging, Clinical, and Biopsy Findings in Suspected Prostate Cancer: A Systematic Review and Meta-Analysis

Importance

Multiple strategies integrating magnetic resonance imaging (MRI) and clinical data have been proposed to determine the need for a prostate biopsy in men with suspected clinically significant prostate cancer (csPCa) (Gleason score ≥3 + 4). However, inconsistencies across different strategies create challenges for drawing a definitive conclusion.

Objective

To determine the optimal prostate biopsy decision-making strategy for avoiding unnecessary biopsies and minimizing the risk of missing csPCa by combining MRI Prostate Imaging Reporting & Data System (PI-RADS) and clinical data.

Data Sources

PubMed, Ovid MEDLINE, Embase, Web of Science, and Cochrane Library from inception to July 1, 2022.

Study Selection

English-language studies that evaluated men with suspected but not confirmed csPCa who underwent MRI PI-RADS followed by prostate biopsy were included. Each study had proposed a biopsy plan by combining PI-RADS and clinical data.

Data Extraction and Synthesis

Studies were independently assessed for eligibility for inclusion. Quality of studies was appraised using the Quality Assessment of Diagnostic Accuracy Studies 2 tool and the Newcastle-Ottawa Scale. Mixed-effects meta-analyses and meta-regression models with multimodel inference were performed. Reporting of this study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline.

Main Outcomes and Measures

Independent risk factors of csPCa were determined by performing meta-regression between the rate of csPCa and PI-RADS and clinical parameters. Yields of different biopsy strategies were assessed by performing diagnostic meta-analysis.

Results

The analyses included 72 studies comprising 36 366 patients. Univariable meta-regression showed that PI-RADS 4 (β-coefficient [SE], 7.82 [3.85]; P = .045) and PI-RADS 5 (β-coefficient [SE], 23.18 [4.46]; P < .001) lesions, but not PI-RADS 3 lesions (β-coefficient [SE], -4.08 [3.06]; P = .19), were significantly associated with a higher risk of csPCa. When considered jointly in a multivariable model, prostate-specific antigen density (PSAD) was the only clinical variable significantly associated with csPCa (β-coefficient [SE], 15.50 [5.14]; P < .001) besides PI-RADS 5 (β-coefficient [SE], 9.19 [3.33]; P < .001). Avoiding biopsy in patients with lesions with PI-RADS category of 3 or less and PSAD less than 0.10 (vs <0.15) ng/mL2 resulted in reducing 30% (vs 48%) of unnecessary biopsies (compared with performing biopsy in all suspected patients), with an estimated sensitivity of 97% (vs 95%) and number needed to harm of 17 (vs 15).

Conclusions and Relevance

These findings suggest that in patients with suspected csPCa, patient-tailored prostate biopsy decisions based on PI-RADS and PSAD could prevent unnecessary procedures while maintaining high sensitivity.

Development and validation of a clinical decision support system based on PSA, microRNAs, and MRI for the detection of prostate cancer

OBJECTIVES

The aims of this study are to develop and validate a clinical decision support system based on demographics, prostate-specific antigen (PSA), microRNA (miRNA), and MRI for the detection of prostate cancer (PCa) and clinical significant (cs) PCa, and to assess if this system performs better compared to MRI alone.

METHODS

This retrospective, multicenter, observational study included 222 patients (mean age 66, range 46-75 years) who underwent prostate MRI, miRNA (let-7a-5p and miR-103a-3p) assessment, and biopsy. Monoparametric and multiparametric models including age, PSA, miRNA, and MRI outcome were trained on 65% of the data and then validated on the remaining 35% to predict both PCa (any Gleason grade [GG]) and csPCa (GG ≥ 2 vs GG = 1/negative). Accuracy, sensitivity, specificity, positive and negative predictive value (NPV), and area under the receiver operating characteristic curve were calculated.

RESULTS

MRI outcome was the best predictor in the monoparametric model for both detection of PCa, with sensitivity of 90% (95%CI 73-98%) and NPV of 93% (95%CI 82-98%), and for csPCa identification, with sensitivity of 91% (95%CI 72-99%) and NPV of 95% (95%CI 84-99%). Sensitivity and NPV of PSA + miRNA for the detection of csPCa were not statistically different from the other models including MRI alone.

CONCLUSION

MRI stand-alone yielded the best prediction models for both PCa and csPCa detection in biopsy-naïve patients. The use of miRNAs let-7a-5p and miR-103a-3p did not improve classification performances compared to MRI stand-alone results.

CLINICAL RELEVANCE STATEMENT

The use of miRNA (let-7a-5p and miR-103a-3p), PSA, and MRI in a clinical decision support system (CDSS) does not improve MRI stand-alone performance in the detection of PCa and csPCa.

KEY POINTS

• Clinical decision support systems including MRI improve the detection of both prostate cancer and clinically significant prostate cancer with respect to PSA test and/or microRNA. • The use of miRNAs let-7a-5p and miR-103a-3p did not significantly improve MRI stand-alone performance. • Results of this study were in line with previous works on MRI and microRNA.

An Overview of 10th Anniversary of Cells-Advances in Cell Nuclei: Function, Transport and Receptors

The year 2021 marked the 10^th anniversary of the publication of Cells [...].

Combined miR-486 and GP88 (Progranulin) Serum Levels Are Suggested as Supportive Biomarkers for Therapy Decision in Elderly Prostate Cancer Patients

Our study aimed to assess the applicability of miR-486 in combination with soluble GP88 protein as a diagnostic and/or predictive biomarker for prostate cancer (PCa) patients. miR-486 and GP88 levels in serum samples from 136 patients undergoing MRI-guided biopsy of the prostate were assessed by qRT−PCR and ELISA, respectively. Of these, 86 patients received a histologically confirmed diagnosis of PCa. Neither marker showed an association with the diagnosis of cancer. PCa patients were separated based on (i) treatment into patients with active surveillance or patients with any type of curative treatment and (ii) age into elderly (>68 years) patients and younger patients (≤68 years). In elderly patients (N = 41) with the intention of curative treatment at optimized cut-off values, significantly higher GP88 levels (p = 0.018) and lower miR-486 levels (p = 0.014) were observed. The total PSA level and ISUP biopsy grade were used in a baseline model for predicting definitive therapy. The baseline model exhibited an area under the curve (AUC) of 0.783 (p = 0.005). The addition of the serum biomarkers miR-486 and GP88 to the baseline model yielded an improved model with an AUC of 0.808 (p = 0.002). Altogether, combined miR-486 and GP88 serum levels are associated with and are therefore suggested as supportive biomarkers for therapy decisions, particularly in elderly PCa patients.

Evaluation of micro-RNA in extracellular vesicles from blood of patients with prostate cancer

Extracellular vesicles (EVs) contain various types of molecules including micro-RNAs, so isolating EVs can be an effective way to analyze and diagnose diseases. A lot of micro-RNAs have been known in relation to prostate cancer (PCa), and we evaluate miR-21, miR-141, and miR-221 in EVs and compare them with prostate-specific antigen (PSA). EVs were isolated from plasma of 38 patients with prostate cancer and 8 patients with benign prostatic hyperplasia (BPH), using a method that showed the highest recovery of RNA. Isolation of EVs concentrated micro-RNAs, reducing the cycle threshold (Ct) value of RT-qPCR amplification of micro-RNA such as miR-16 by 5.12 and miR-191 by 4.65, compared to the values before EV isolation. Normalization of target micro-RNAs was done using miR-191. For miR-221, the mean expression level of patients with localized PCa was significantly higher than that of the control group, having 33.45 times higher expression than the control group (p < 0.01). Area under curve (AUC) between BPH and PCa for miR-221 was 0.98 (p < 0.0001), which was better than AUC for prostate-specific antigen (PSA) level in serum for the same patients. The levels of miR-21 and miR-141 in EVs did not show significant changes in patients with PCa compared to the control group in this study. This study suggests isolating EVs can be a helpful approach in analyzing micro-RNAs with regard to disease.