Diagnosis accuracy of PCA3 level in patients with prostate cancer: a systematic review with meta-analysis

miRNA Expression Patterns in Early- and Late-Stage Prostate Cancer Patients: High-Throughput Analysis

Prostate cancer (PCa) is one of the most common types of cancer among men. To date, there have been no specific markers identified for the diagnosis and prognosis or response to treatment of this disease. Thus, there is an urgent need for promising markers, which may be fulfilled by small non-coding RNAs known as microRNAs (miRNAs). Therefore, the present study aimed to investigate the miRNA profile in tissue samples obtained from patients with PCa using microarrays, followed by reverse transcriptase quantitative PCRs (RT-qPCRs). In the discovery phase, 754 miRNAs were screened in tissues obtained from patients (n = 46) with PCa in early and late stages. Expression levels of miRNA-324-3p, miRNA-429, miRNA-570, and miRNA-616 were found to be downregulated, and miRNA-423-5p expression was upregulated in patients with early-stage cancer compared to the late-stage ones. These five miRNAs were further validated in an independent cohort of samples (n = 39) collected from patients with PCa using RT-qPCR-based assays. MiRNA-324-3p, miRNA-429, miRNA-570, and miRNA-616 expression levels remained significantly downregulated in early-stage cancer tissues compared to late-stage tissues. Remarkably, for a combination of three miRNAs, PSA levels and Gleason scores were able to discriminate between patients with early-stage PCa and late-stage PCa, with an AUC of 95%, a sensitivity of 86%, and a specificity close to 94%. Thus, the data obtained in this study suggest a possible involvement of the identified miRNAs in the pathogenesis of PCa, and they may also have the potential to be developed into diagnostic and prognostic tools for PCa. However, further studies with a larger cohort are needed.

Prediction of clinically significant prostate cancer through urine metabolomic signatures: A large-scale validated study

PURPOSE

Currently, there are no accurate markers for predicting potentially lethal prostate cancer (PC) before biopsy. This study aimed to develop urine tests to predict clinically significant PC (sPC) in men at risk.

METHODS

Urine samples from 928 men, namely, 660 PC patients and 268 benign subjects, were analyzed by gas chromatography/quadrupole time-of-flight mass spectrophotometry (GC/Q-TOF MS) metabolomic profiling to construct four predictive models. Model I discriminated between PC and benign cases. Models II, III, and GS, respectively, predicted sPC in those classified as having favorable intermediate risk or higher, unfavorable intermediate risk or higher (according to the National Comprehensive Cancer Network risk groupings), and a Gleason sum (GS) of ≥ 7. Multivariable logistic regression was used to evaluate the area under the receiver operating characteristic curves (AUC).

RESULTS

In Models I, II, III, and GS, the best AUCs (0.94, 0.85, 0.82, and 0.80, respectively; training cohort, N = 603) involved 26, 24, 26, and 22 metabolites, respectively. The addition of five clinical risk factors (serum prostate-specific antigen, patient age, previous negative biopsy, digital rectal examination, and family history) significantly improved the AUCs of the models (0.95, 0.92, 0.92, and 0.87, respectively). At 90% sensitivity, 48%, 47%, 50%, and 36% of unnecessary biopsies could be avoided. These models were successfully validated against an independent validation cohort (N = 325). Decision curve analysis showed a significant clinical net benefit with each combined model at low threshold probabilities. Models II and III were more robust and clinically relevant than Model GS.

CONCLUSION

This urine test, which combines urine metabolic markers and clinical factors, may be used to predict sPC and thereby inform the necessity of biopsy in men with an elevated PC risk.

Follow-Up Biomarkers in the Evolution of Prostate Cancer, Levels of S100A4 as a Detector in Plasma

The management and screening of prostate cancer (PC) is still the main problem in clinical practice. In this study, we investigated the role of aggressiveness genetic markers for PC stratification. We analyzed 201 plasma samples from PC patients and controls by digital PCR. For selection and validation, 26 formalin-fixed paraffin-embedded tissues, 12 fresh tissues, and 24 plasma samples were characterized by RNA-Seq, immunochemistry, immunofluorescence, Western blot, and extracellular-vesicles analyses. We identified three novel non-invasive biomarkers; all with an increased expression pattern in patients (PCA3: p = 0.002, S100A4: p ≤ 0.0001 and MRC2: p = 0.005). S100A4 presents the most informative AUC (area under the curve) (0.735). Combination of S100A4, MRC2, and PCA3 increases the discriminatory power between patients and controls and between different more and less aggressive stages (AUC = 0.761, p ≤ 0.0001). However, although a sensitivity of 97.47% in PCA3 and a specificity of 90.32% in S100A4 was reached, the detection signal level could be variable in some analyses owing to tumor heterogeneity. This is the first time that the role of S100A4 and MRC2 has been described in PC aggressiveness. Moreover, the combination of S100A4, MRC2, and PCA3 has never been described as a non-invasive biomarker for PC screening and aggressiveness.

Intermittent Hormone Therapy Models Analysis and Bayesian Model Comparison for Prostate Cancer

The prostate is an exocrine gland of the male reproductive system dependent on androgens (testosterone and dihydrotestosterone) for development and maintenance. First-line therapy for prostate cancer includes androgen deprivation therapy (ADT), depriving both the normal and malignant prostate cells of androgens required for proliferation and survival. A significant problem with continuous ADT at the maximum tolerable dose is the insurgence of cancer cell resistance. In recent years, intermittent ADT has been proposed as an alternative to continuous ADT, limiting toxicities and delaying time-to-progression. Several mathematical models with different biological resistance mechanisms have been considered to simulate intermittent ADT response dynamics. We present a comparison between 13 of these intermittent dynamical models and assess their ability to describe prostate-specific antigen (PSA) dynamics. The models are calibrated to longitudinal PSA data from the Canadian Prospective Phase II Trial of intermittent ADT for locally advanced prostate cancer. We perform Bayesian inference and model analysis over the models’ space of parameters on- and off-treatment to determine each model’s strength and weakness in describing the patient-specific PSA dynamics. Additionally, we carry out a classical Bayesian model comparison on the models’ evidence to determine the models with the highest likelihood to simulate the clinically observed dynamics. Our analysis identifies several models with critical abilities to disentangle between relapsing and not relapsing patients, together with parameter intervals where the critical points’ basin of attraction might be exploited for clinical purposes. Finally, within the Bayesian model comparison framework, we identify the most compelling models in the description of the clinical data.

Impact of lifestyle in prostate cancer patients. What should we do?

Objective:

This review aimed to analyze interventions raised within primary and tertiary prevention concerning the disease's incidence, progression, and recurrence of Prostate Cancer (PCa). Priority was given to the multidisciplinary approach of PCa patients with an emphasis on modifiable risk factors.

Materials and Methods:

We conducted a comprehensive literature review in the following databases: Embase, Central, and Medline. We included the most recent evidence assessing cohort studies, case-control studies, clinical trials, and systematic reviews published in the last five years. We only included studies in adults and in vitro or cell culture studies. The review was limited to English and Spanish articles.

Results:

Preventive interventions at all levels are the cornerstone of adherence to disease treatment and progression avoidance. The relationship in terms of healthy lifestyles is related to greater survival. The risk of developing cancer is associated to different eating habits, determined by geographic variations, possibly related to different genetic susceptibilities.

Discussion:

PCa is the second most common cancer in men, representing a leading cause of death among men in Latin America. Prevention strategies and healthy lifestyles are associated with higher survival rates in PCa patients. Also, screening for anxiety and the presence of symptoms related to mood disorders is essential in the patient's follow-up concerning their perception of the condition.

Novel Prostate Cancer Biomarkers: Aetiology, Clinical Performance and Sensing Applications

The review initially provides a short introduction to prostate cancer (PCa) incidence, mortality, and diagnostics. Next, the need for novel biomarkers for PCa diagnostics is briefly discussed. The core of the review provides details about PCa aetiology, alternative biomarkers available for PCa diagnostics besides prostate specific antigen and their biosensing. In particular, low molecular mass biomolecules (ions and metabolites) and high molecular mass biomolecules (proteins, RNA, DNA, glycoproteins, enzymes) are discussed, along with clinical performance parameters.

Up-Regulation of LINC00665 Facilitates the Malignant Progression of Prostate Cancer by Epigenetically Silencing KLF2 Through EZH2 and LSD1

This study aimed to explore the function of LINC00665 on the proliferation and metastasis of prostate cancer (PCa), and the potential regulatory mechanisms were also investigated. The expression level of LINC00665 in 50 pairs of PCa tissues and adjacent ones was studied by qRT-PCR, and the associations between LINC00665 and clinicopathological characteristics of PCa patients were analyzed. Control group (sh-NC) and LINC00665 knock-down group (sh-LINC00665) were set in 22RV1 and DU145 cells, respectively. The biological functions of LINC00665 in PCa cell lines were assessed by CCK-8, EdU, Transwell assays, and the nude mouse xenograft model was used to evaluate the tumorigenicity in vivo. In addition, qRT-PCR, Western Blot, RIP and ChIP assays were also used to determine the regulation mechanism of LINC00665 in PCa cell lines. In this study, our results showed that LINC00665 expression level in PCa cancer tissues was significantly up-regulated, compared with that in adjacent ones. Besides, similar results were found in PCa cell lines. Knock-down of LINC00665 significantly attenuated the proliferation and migration ability in 22RV1 and DU145 cells, compared to sh-NC. Mechanically, LINC00665 could interact with EZH2 and LSD1, recruiting them to KLF2 promoter region to inhibit its transcription. Moreover, the tumor-suppressive effects mediated by sh-LINC00665 were significantly reversed through the down-regulation of KLF2. Also, the suppression of LINC00665 impaired tumor growth of PCa in vivo. In summary, LINC00665 exerted the oncogenic functions in PCa cell lines by epigenetically silencing KLF2 expression by binding to EZH2 and LSD1, illuminating a novel mechanism of LINC00665 in the malignant progression of PCa and furnishing a prospective therapeutic biomarker to combat PCa.