A Novel Predictor Tool of Biochemical Recurrence after Radical Prostatectomy Based on a Five-MicroRNA Tissue Signature

Prostate cancer and the cell cycle: Focusing on the role of microRNAs

Prostate cancer is the most frequent solid tumor in terms of incidence and ranks second only to lung cancer in terms of cancer mortality among men. It has a considerably high mortality rate; around 375,000 deaths occurred worldwide in 2020. In 2024, the American Cancer Society estimated that the number of new prostate cancer cases will be around 299,010 cases, and the estimated deaths will be around 32,250 deaths only in the USA. Cell cycle dysregulation is inevitable in cancer etiology and is targeted by various therapies in cancer treatment. MicroRNAs (miRNAs) are small, endogenous, non-coding regulatory molecules involved in both normal and abnormal cellular events. One of the cellular processes regulated by miRNAs is the cell cycle. Although there are some exceptions, tumor suppressor miRNAs could potentially arrest the cell cycle by downregulating several molecular machineries involved in catalyzing the cell cycle progression. In contrast, oncogenic miRNAs (oncomirs) help the cell cycle to progress by targeting various regulatory proteins such as retinoblastoma (Rb) or cell cycle inhibitors such as p21 or p27, and hence may contribute to prostate cancer progression; however, this is not always the case. In this review, we emphasize how a dysregulated miRNA expression profile is linked to an abnormal cell cycle progression in prostate cancer, which subsequently paves the way to a new therapeutic option for prostate cancer.

Evaluation of miR-148a-3p and miR-106a-5p as Biomarkers for Prostate Cancer: Pilot Study

MicroRNAs (miRNAs) are a class of small non-coding RNAs that may function as tumor suppressors or oncogenes. Alteration of their expression levels has been linked to a range of human malignancies, including cancer. The objective of this investigation is to assess the relative expression levels of certain miRNAs to distinguish between prostate cancer (PCa) from benign prostatic hyperplasia (BPH). Blood plasma was collected from 66 patients diagnosed with BPH and 58 patients with PCa. Real-time PCR technology was used to evaluate the relative expression among the two groups for miR-106a-5p and miR-148a-3p. The significant downregulation of both miRNAs in plasma from PCa versus BPH patients suggests their potential utility as diagnostic biomarkers for distinguishing between these conditions. The concurrent utilization of these two miRNAs slightly enhanced the sensitivity for discrimination among the two analyzed groups, as shown in ROC curve analysis. Further validation of these miRNAs in larger patient cohorts and across different stages of PCa may strengthen their candidacy as clinically relevant biomarkers for diagnosis and prognosis.

Evaluation of AR, AR-V7, and p160 family as biomarkers for prostate cancer: insights into the clinical significance and disease progression

PURPOSE

To assess the role of the p160 family, AR, and AR-V7 in different initial presentations of prostate cancer and their association with clinical endpoints related to tumor progression.

METHODS

The study sample comprises 155 patients who underwent radical prostatectomy and 11 healthy peripheral zone biopsies as the control group. Gene expression was quantified by qPCR from the tissue specimens. The statistical analysis investigated correlations between gene expression levels, associations with disease presence, and clinicopathological features. Additionally, ROC curves were applied for distinct PCa presentations, and time-to-event analysis was used for clinical endpoints.

RESULTS

The AR-V7 diagnostic performance for any PCa yielded an AUC of 0.77 (p < 0.05). For locally advanced PCa, the AR-V7 AUC was 0.65 (p < 0.05). Moreover, the metastasis group had a higher expression of SRC-1 than the non-metastatic group (p < 0.05), showing a shorter time to metastasis in the over-expressed group (p = 0.005). Patients with disease recurrence had super-expression of AR levels (p < 0.0005), with a shorter time-to-recurrence in the super-expression group (p < 0.0001).

CONCLUSION

Upregulation of SRC-1 indicates a higher risk of progression to metastatic disease in a shorter period, which warrants further research to be applied as a clinical tool. Additionally, AR may be used as a predictor for PCa recurrence. Furthermore, AR-V7 may be helpful as a diagnostic tool for PCa and locally advanced cancer, comparable with other investigated tools.

Lineage Plasticity and Stemness Phenotypes in Prostate Cancer: Harnessing the Power of Integrated "Omics" Approaches to Explore Measurable Metrics

Prostate cancer (PCa), the most frequent and second most lethal cancer type in men in developed countries, is a highly heterogeneous disease. PCa heterogeneity, therapy resistance, stemness, and lethal progression have been attributed to lineage plasticity, which refers to the ability of neoplastic cells to undergo phenotypic changes under microenvironmental pressures by switching between developmental cell states. What remains to be elucidated is how to identify measurements of lineage plasticity, how to implement them to inform preclinical and clinical research, and, further, how to classify patients and inform therapeutic strategies in the clinic. Recent research has highlighted the crucial role of next-generation sequencing technologies in identifying potential biomarkers associated with lineage plasticity. Here, we review the genomic, transcriptomic, and epigenetic events that have been described in PCa and highlight those with significance for lineage plasticity. We further focus on their relevance in PCa research and their benefits in PCa patient classification. Finally, we explore ways in which bioinformatic analyses can be used to determine lineage plasticity based on large omics analyses and algorithms that can shed light on upstream and downstream events. Most importantly, an integrated multiomics approach may soon allow for the identification of a lineage plasticity signature, which would revolutionize the molecular classification of PCa patients.

MicroRNAs as clinical tools for diagnosis, prognosis, and therapy in prostate cancer

Prostate cancer (PCa) is one of the most commonly diagnosed cancers among men worldwide. Despite the presence of accumulated clinical strategies for PCa management, limited prognostic/sensitive biomarkers are available to follow up on disease occurrence and progression. MicroRNAs (miRNAs) are small non-coding RNAs that control gene expression through post-transcriptional regulation of their complementary target messenger RNA (mRNA). MiRNAs modulate fundamental biological processes and play crucial roles in the pathology of various diseases, including PCa. Multiple evidence proved an aberrant miRNA expression profile in PCa, which is actively involved in the carcinogenic process. The robust and pleiotropic impact of miRNAs on PCa suggests them as potential candidates to help more understand the molecular landscape of the disease, which is likely to provide tools for early diagnosis and prognosis as well as additional therapeutic strategies to manage prostate tumors. Here, we emphasize the most consistently reported dysregulated miRNAs and highlight the contribution of their altered downstream targets with PCa hallmarks. Also, we report the potential effectiveness of using miRNAs as diagnostic/prognostic biomarkers in PCa and the high-throughput profiling technologies that are being used in their detection. Another key aspect to be discussed in this review is the promising implication of miRNAs molecules as therapeutic tools and targets for fighting PCa.

Circulating microRNA profiling for prediction of oncological outcomes in prostate cancer patients following radical prostatectomy

BACKGROUND

Although radical prostatectomy is associated with good long-term oncological outcomes, approximately 30% of patients present biochemical recurrence, whereupon salvage treatments are required. Identification of novel molecular biomarkers to predict cancer behavior is clinically important. Here, we developed a novel microRNA (miRNA)-based prognostic model for patients who underwent radical prostatectomy.

METHODS

We retrospectively investigated the clinical records of 295 patients who underwent radical prostatectomy between 2009 and 2017. We randomly assigned these cases into training or validation sets. The prognostic model was constructed using Fisher linear discriminant analysis in the training set, and we evaluated its performance in the validation set.

RESULTS

Overall, 72 patients had biochemical recurrence. A prediction model was constructed using a combination of three miRNAs (miR-3147, miR-4513, and miR-4728-5p) and two pathological factors (pathological T stage and Gleason score). In the validation set, the predictive performance of the model was confirmed to be accurate (area under the receiver operating characteristic curve: 0.80; sensitivity: 0.78; specificity: 0.76). Additionally, Kaplan-Meier analysis revealed that the patients with a low prediction index had significantly longer recurrence-free survival than those with a high index (p < 0.001).

CONCLUSIONS

Circulating miRNA profiles can provide information to predict recurrence after prostatectomy. Our model may be helpful for physicians to decide follow-up strategies for patients.

The Development of a Gleason Score-Related Gene Signature for Predicting the Prognosis of Prostate Cancer

The recurrence of prostate cancer (PCa) is intrinsically linked to increased mortality. The goal of this study was to develop an efficient and reliable prognosis prediction signature for PCa patients. The training cohort was acquired from The Cancer Genome Atlas (TCGA) dataset, while the validation cohort was obtained from the Gene Expression Omnibus (GEO) dataset (GSE70769). To explore the Gleason score (GS)-based prediction signature, we screened the differentially expressed genes (DEGs) between low- and high-GS groups, and then univariate Cox regression survival analysis and multiple Cox analyses were performed sequentially using the training cohort. The testing cohort was used to evaluate and validate the prognostic model's effectiveness, accuracy, and clinical practicability. In addition, the correlation analyses between the risk score and clinical features, as well as immune infiltration, were performed. We constructed and optimized a valid and credible model for predicting the prognosis of PCa recurrence using four GS-associated genes (SFRP4, FEV, COL1A1, SULF1). Furthermore, ROC and Kaplan-Meier analysis revealed a higher predictive efficiency for biochemical recurrence (BCR). The results showed that the risk model was an independent prognostic factor. Moreover, the risk score was associated with clinical features and immune infiltration. Finally, the risk model was validated in a testing cohort. Our data support that the GS-based four-gene signature acts as a novel signature for predicting BCR in PCa patients.

Biased holoenzyme assembly of protein phosphatase 2A (PP2A): From cancer to small molecules

Protein phosphatase 2A (PP2A) is a family of serine threonine phosphatases responsible for regulating protein phosphorylation, thus opposing the activity of cellular kinases. PP2A is composed of a catalytic subunit (PP2A Cα/β) and scaffolding subunit (PP2A Aα/β) and various substrate-directing B regulatory subunits. PP2A biogenesis is regulated at multiple levels. For example, the sequestration of the free catalytic subunit during the process of biogenesis avoids promiscuous phosphatase activity. Posttranslational modifications of PP2A C direct PP2A heterotrimeric formation. Additionally, PP2A functions as a haploinsufficient tumor suppressor, where attenuated PP2A enzymatic activity creates a permissive environment for oncogenic transformation. Recent work studying PP2A in cancer showed that its role in tumorigenesis is more nuanced, with some holoenzymes being tumor suppressive, while others are required for oncogenic transformation. In cancer biology, PP2A function is modulated through various mechanisms including the displacement of specific B regulatory subunits by DNA tumor viral antigens, by recurrent mutations, and through loss of carboxymethyl-sensitive heterotrimeric complexes. In aggregate, these alterations bias PP2A activity away from its tumor suppressive functions and toward oncogenic ones. From a therapeutic perspective, molecular glues and disruptors present opportunities for both the selective stabilization of tumor-suppressive holoenzymes and disruption of holoenzymes that are pro-oncogenic. Collectively, these approaches represent an attractive cancer therapy for a wide range of tumor types. This review will discuss the mechanisms by which PP2A holoenzyme formation is dysregulated in cancer and the current therapies that are aimed at biasing heterotrimer formation of PP2A for the treatment of cancer.

MicroRNAs as biomarkers for prostate cancer prognosis: a systematic review and a systematic reanalysis of public data

Background

Reliable prognostic biomarkers to distinguish indolent from aggressive prostate cancer (PCa) are lacking. Many studies investigated microRNAs (miRs) as PCa prognostic biomarkers, often reporting inconsistent findings. We present a systematic review of these; also systematic reanalysis of public miR-profile datasets to identify tissue-derived miRs prognostic of biochemical recurrence (BCR) in patients undergoing radical prostatectomy.

Methods

Independent PubMed searches were performed for relevant articles from January 2007 to December 2019. For the review, 128 studies were included. Pooled-hazard-ratios (HRs) for miRs in multiple studies were calculated using a random-effects model (REM). For the reanalysis, five studies were included and Cox proportional-hazard models, testing miR association with BCR, performed for miRs profiled in all.

Results

Systematic review identified 120 miRs as prognostic. Five (let-7b-5p, miR-145-5p, miR152-3p, miR-195-5p, miR-224-5p) were consistently associated with progression in multiple cohorts/studies. In the reanalysis, ten (let-7a-5p, miR-148a-3p, miR-203a-3p, miR-26b-5p, miR30a-3p, miR-30c-5p, miR-30e-3p, miR-374a-5p, miR-425-3p, miR-582-5p) were significantly prognostic of BCR. Of these, miR-148a-3p (HR = 0.80/95% CI = 0.68-0.94) and miR-582-5p (HR = 0.73/95% CI = 0.61-0.87) were also reported in prior publication(s) in the review.

Conclusions

Fifteen miRs were consistently associated with disease progression in multiple publications or datasets. Further research into their biological roles is warranted to support investigations into their performance as prognostic PCa biomarkers.

Prognostic value of miR-21 for prostate cancer: a systematic review and meta-analysis

Elevated levels of miR-21 expression are associated with many cancers, suggesting it may be a promising clinical biomarker. In prostate cancer (PCa), however, there is still no consensus about the usefulness of miR-21 as an indicator of disease progression. This systematic review and meta-analysis was conducted to investigate the value of miR-21 expression as a prognostic measurement in PCa patients. Medline (Ovid), EMBASE, Web of Science, Scopus and Cochrane Library databases were systematically searched for relevant publications between 2010 to 2021. Studies exploring the relationship between miR-21 expression, PCa prognosis and clinicopathological factors were selected for review. Those reporting hazard ratio (HR) and 95% confidence intervals (CIs) were subject to meta-analyses. Fixed-effect models were employed to calculated pooled HRs and 95% CIs. Risk of bias in each study was assessed using QUIPS tool. Certainty of evidence in each meta-analysis was assessed using GRADE guidelines. A total of 64 studies were included in the systematic review. Of these, 11 were eligible for inclusion in meta-analysis. Meta-analyses revealed that high miR-21 expression was associated with poor prognosis: HR = 1.58 (95% CI = 1.19–2.09) for biochemical recurrence, MODERATE certainty; HR = 1.46 (95% CI = 1.06–2.01) for death, VERY LOW certainty; and HR = 1.26 (95% CI = 0.70–2.27) for disease progression, VERY LOW certainty. Qualitative summary revealed elevated miR-21 expression was significantly positively associated with PCa stage, Gleason score and risk groups. This systematic review and meta-analysis suggests that elevated levels of miR-21 are associated with poor prognosis in PCa patients. miR-21 expression may therefore be a useful prognostic biomarker in this disease.

Regulation of Neuroendocrine-like Differentiation in Prostate Cancer by Non-Coding RNAs

Neuroendocrine prostate cancer (NEPC) represents a variant of prostate cancer that occurs in response to treatment resistance or, to a much lesser extent, de novo. Unravelling the molecular mechanisms behind transdifferentiation of cancer cells to neuroendocrine-like cancer cells is essential for development of new treatment opportunities. This review focuses on summarizing the role of small molecules, predominantly microRNAs, in this phenomenon. A published literature search was performed to identify microRNAs, which are reported and experimentally validated to modulate neuroendocrine markers and/or regulators and to affect the complex neuroendocrine phenotype. Next, available patients’ expression datasets were surveyed to identify deregulated microRNAs, and their effect on NEPC and prostate cancer progression is summarized. Finally, possibilities of miRNA detection and quantification in body fluids of prostate cancer patients and their possible use as liquid biopsy in prostate cancer monitoring are discussed. All the addressed clinical and experimental contexts point to an association of NEPC with upregulation of miR-375 and downregulation of miR-34a and miR-19b-3p. Together, this review provides an overview of different roles of non-coding RNAs in the emergence of neuroendocrine prostate cancer.

Identification of patients at risk for biochemical recurrence after radical prostatectomy with intra-operative frozen section

OBJECTIVE

To identify patients at risk for biochemical recurrence (BCR) of prostate cancer (PCa) after radical prostatectomy (RP) with intra-operative whole-mount frozen section (FS) of the prostate.

MATERIAL AND METHODS

We examined differences in BCR between patients with initial negative surgical margins at FS, patients with final negative surgical margins with initial positive margins at FS without residual PCa after secondary tumour resection, and patients with final negative surgical margins with initially positive margins at FS with residual PCa in the secondary tumour resection specimen. Institutional data of 883 consecutive patients undergoing RP were collected. Intra-operative whole-mount FS was routinely used to check for margin status and, if necessary, to resect more periprostatic tissue in order to achieve negative margins. Patients with lymph node-positive disease or final positive surgical margins were excluded from the analysis. Kaplan-Meier curves and multivariable Cox proportional hazards regression analyses adjusting for clinical covariates were employed to examine differences in biochemical recurrence-free survival (BRFS) according to the resection status mentioned above.

RESULTS

The median follow-up was 22.4 months. The 1- and 2-year BRFS rates in patients with (81.0% and 72.9%, respectively; P = 0.001) and without residual PCa (90.3% and 82.3%, respectively; P = 0.033) after secondary tumour resection were significantly lower compared to patients with initial R0 status (93.4% and 90.9%, respectively). On multivariable Cox regression only residual PCa in the secondary tumour resection was associated with a higher risk of BCR compared to initial R0 status (hazard ratio 1.99, 95% confidence interval 1.01-3.92; P = 0.046).

CONCLUSION

Despite being classified as having a negative surgical margin, patients with residual PCa in the secondary tumour resection specimen face a high risk of BCR. These findings warrant closer post-RP surveillance of this particular subgroup. Further research of this high-risk subset of patients should focus on examining whether these patients benefit from early salvage therapy and how resection status impacts oncological outcomes in the changing landscape of PCa treatment.

Clinical outcomes associated with prostate cancer conspicuity on biparametric and multiparametric MRI: a protocol for a systematic review and meta-analysis of biochemical recurrence following radical prostatectomy

INTRODUCTION

There is an increasing body of evidence to suggest that visibility of prostate cancer on magnetic resonance (MRI) may be related to likelihood of adverse pathological outcomes. Biochemical recurrence (BCR) after radical prostatectomy remains a significant clinical challenge and a means of predicting likelihood of this prior to surgery could inform treatment choice. It appears that MRI could be a potential candidate strategy for BCR prediction, and as such, there is a need to review extant literature on the prognostic capability of MRI. Here, we describe a protocol for a systematic review and meta-analysis of the utility of biparametric MRI (bpMRI) and multiparametric MRI (mpMRI) in predicting BCR following radical prostatectomy for prostate cancer treatment.

METHODS AND ANALYSIS

PubMed, MEDLINE, Embase and Cochrane databases will be searched and screening will be guided by the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. In order to meet the inclusion criteria, papers must be English-language articles involving patients who have had bpMRI or mpMRI for suspected prostate cancer and have undergone radical prostatectomy as definitive therapy. Patients must have had prostate-specific antigen monitoring before and after surgery. All relevant papers published from July 1977 to October 2020 will be eligible for inclusion. The Newcastle-Ottawa score will be used to determine the quality and bias of the studies. This protocol is written in-line with the PRISMA protocol 2015 checklist.

ETHICS AND DISSEMINATION

There are no relevant ethical concerns. Dissemination of this protocol will be via peer-reviewed journals as well as national and international conferences.

PROSPERO REGISTRATION NUMBER

CRD42020206074.

A Glycolysis-Related Five-Gene Signature Predicts Biochemical Recurrence-Free Survival in Patients With Prostate Adenocarcinoma

Prostate cancer (PCa) is one of the most frequently diagnosed cancers in males worldwide. Approximately 25% of all patients experience biochemical recurrence (BCR) after radical prostatectomy (RP) and BCR indicates increased risk for metastasis and castration resistance. PCa patients with highly glycolytic tumors have a worse prognosis. Thus, this study aimed to explore glycolysis-based predictive biomarkers for BCR. Expression data and clinical information of PCa samples were retrieved from three publicly available datasets. One from The Cancer Genome Atlas (TCGA) dataset was used as the training cohort, and two from the Gene Expression Omnibus (GEO) dataset (GSE54460 and GSE70769) were used as validation cohorts. Using the training cohort, univariate Cox regression survival analysis, robust likelihood-based survival model, and stepwise multiply Cox analysis were sequentially applied to explore predictive glycolysis-related candidates. A five-gene risk score was then constructed based on the Cox coefficient as the following: (−0.8367*GYS2) + (0.3448*STMN1) + (0.3595*PPFIA4) + (−0.1940*KDELR3) + (0.4779*ABCB6). Receiver operating characteristic curve (ROC) analysis was used to identify the optimal cut-off point, and patients were divided into low risk and high risk groups. Kaplan–Meier analysis revealed that high risk group had significantly shorter BCR free survival time as compared with that in low risk group in training and validation cohorts. In conclusion, our data support the glycolysis-based five-gene signature as a novel and robust signature for predicting BCR of PCa patients.

Urinary exosomal microRNA profiling in intermediate-risk prostate cancer

MicroRNAs (miRNAs) of urine exosomes have emerged as biomarkers for urological cancers, owing to their high stability. MiRNAs have been linked to factors associated with aggressive prostate cancer such as biochemical recurrence (BCR) and metastasis. In this study, we aimed to identify urinary exosomal miRNAs as prognostic markers associated with BCR in intermediate-risk prostate cancer. We profiled the expression levels of miRNAs via next generation sequencing in urinary exosomes from 21 non-BCR patients and 6 BCR patients of intermediate-risk prostate cancer. A total of 21 urinary exosomal miRNAs were found to be differentially expressed (> twofold) in BCR patients compared to non-BCR patients. For external validation, we validated these results using quantitative reverse transcription PCR in an independent cohort of 28 non-BCR patients and 26 BCR patients. A validation analysis revealed that three miRNAs (miR-26a-5p, miR-532-5p, and miR-99b-3p) were upregulated in exosomes from BCR patients. The univariate and multivariate Cox regression analyses showed that miR-532-5p was an important predictive factor for BCR of intermediate-risk prostate cancer. In conclusion, miR-532-5p in urine exosomes might be a potential biomarker for predicting BCR, which is a poor prognosis in patients with intermediate-risk prostate cancer. Further research is needed on the biological functions and mechanisms of this miRNA.

Identification and validation of a six immune-related gene signature for prediction of biochemical recurrence in localized prostate cancer following radical prostatectomy

Background

Prostate cancer (PCa) is the second lethal heterogeneous cancer among males worldwide, and approximately 20% of PCa patients following radical prostatectomy (RP) will undergo biochemical recurrence (BCR). This study is aimed to identify the immune-related gene signature that can predict BCR in localized PCa following RP.

Methods

Expression profile of genes together with clinical parameters from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus database (GEO) and the immune-related genes from the Molecular Signatures Database v4.0 were applied to construct and validate the gene signature. The Cox regression analyses were conducted to identify the candidate genes and establish the gene signature. To estimate the prognostic power of the risk score, the time-dependent receiver operating characteristic (ROC) analysis and Harrell's index of concordance (C-index) were utilized. We also established a nomogram to forecast the probability of patients' survival.

Results

A total of 268 patients from the TCGA and 77 patients from GSE70770 and six immune-related genes (SCIN, THY1, TBX1, NOTCH4, MAL, BNIP3L) were eventually selected. The Kaplan-Meier analysis demonstrated that patients in the low-risk group had a significantly longer recurrence-free survival (RFS) compared to those in the high-risk group. In the multivariate Cox model, the signature was identified as an independent prognostic factor, which was significantly associated with RFS (TCGA: HR =5.232, 95% CI: 1.762-15.538, P=0.003; GSE70770: HR =2.158, 95% CI: 1.051-4.432, P=0.036). Moreover, the C-index got improved after incorporating the risk score into original clinicopathological parameters. In addition, the novel nomogram was constructed to better predict the 1-, 3- and 5-year RFS.

Conclusions

This signature could serve as an independent prognostic factor for BCR. Incorporation of our signature into traditional risk classification might further stratify patients with different prognosis, which could assist practitioners in developing clinical decision-making.

A new risk stratification system of prostate cancer to identify high-risk biochemical recurrence patients

Background

Biochemical recurrence (BCR) is considered a decisive risk factor for clinical recurrence and the metastasis of prostate cancer (PCa). Therefore, we developed and validated a signature which could be used to accurately predict BCR risk and aid in the selection of PCa treatments.

Methods

A comprehensive genome-wide analysis of data concerning PCa from previous datasets of the Cancer Genome Atlas (TCGA) and the gene expression omnibus (GEO) was performed. Lasso and Cox regression analyses were performed to develop and validate a novel signature to help predict BCR risk. Moreover, a nomogram was constructed by combining the signature and clinical variables.

Results

A total of 977 patients were involved in the study. This consisted of patients from the TCGA (n=405), GSE21034 (n=131), GSE70770 (n=193) and GSE116918 (n=248) datasets. A 9-mRNA signature was identified in the TCGA dataset (composed of C9orf152, EPHX2, ASPM, MMP11, CENPF, KIF4A, COL1A1, ASPN, and FANCI) which was significantly associated with BCR (HR =3.72, 95% CI: 2.30-6.00, P<0.0001). This signature was validated in the GSE21034 (HR =7.54, 95% CI: 3.15-18.06, P=0.019), GSE70770 (HR =2.52, 95% CI: 1.50-4.22, P=0.0025) and GSE116918 datasets (HR =4.75, 95% CI: 2.51-9.02, P=0.0035). Multivariate Cox regression and stratified analysis showed that the 9-mRNA signature was a clinical factor independent of prostate-specific antigen (PSA), Gleason score (GS), or AJCC T staging. The mean AUC for 5-year BCR-free survival predictions of the 9-mRNA signature (0.81) was higher than the AUC for PSA, GS, or AJCC T staging (0.52-0.73). Furthermore, we combined the 9-mRNA signature with PSA, GS, or AJCC T staging and demonstrated that this could enhance prognostic accuracy.

Conclusions

The proposed 9-mRNA signature is a promising biomarker for predicting BCR-free survival in PCa. However, further controlled trials are needed to validate our results and explore a role in individualized management of PCa.

Circular RNAs and Their Linear Transcripts as Diagnostic and Prognostic Tissue Biomarkers in Prostate Cancer after Prostatectomy in Combination with Clinicopathological Factors

As new biomarkers, circular RNAs (circRNAs) have been largely unexplored in prostate cancer (PCa). Using an integrative approach, we aimed to evaluate the potential of circRNAs and their linear transcripts (linRNAs) to act as (i) diagnostic biomarkers for differentiation between normal and tumor tissue and (ii) prognostic biomarkers for the prediction of biochemical recurrence (BCR) after radical prostatectomy. In a first step, eight circRNAs (circATXN10, circCRIM1, circCSNK1G3, circGUCY1A2, circLPP, circNEAT1, circRHOBTB3, and circSTIL) were identified as differentially expressed via a genome-wide circRNA-based microarray analysis of six PCa samples. Additional bioinformatics and literature data were applied for this selection process. In total, 115 malignant PCa and 79 adjacent normal tissue samples were examined using robust RT-qPCR assays specifically established for the circRNAs and their linear counterparts. Their diagnostic and prognostic potential was evaluated using receiver operating characteristic curves, Cox regressions, decision curve analyses, and C-statistic calculations of prognostic indices. The combination of circATXN10 and linSTIL showed a high discriminative ability between malignant and adjacent normal tissue PCa. The combination of linGUCY1A2, linNEAT1, and linSTIL proved to be the best predictive RNA-signature for BCR. The combination of this RNA signature with five established reference models based on only clinicopathological factors resulted in an improved predictive accuracy for BCR in these models. This is an encouraging study for PCa to evaluate circRNAs and their linRNAs in an integrative approach, and the results showed their clinical potential in combination with standard clinicopathological variables.

The PP2A subunit PR130 is a key regulator of cell development and oncogenic transformation

Protein phosphatase 2A (PP2A) is a major serine/threonine phosphatase. This enzyme is involved in a plethora of cellular processes, including apoptosis, autophagy, cell proliferation, and DNA repair. Remarkably, PP2A can act as a context-dependent tumor suppressor or promoter. Active PP2A complexes consist of structural (PP2A-A), regulatory (PP2A-B), and catalytic (PP2A-C) subunits. The regulatory subunits define the substrate specificity and the subcellular localization of the holoenzyme. Here we condense the increasing evidence that the PP2A B-type subunit PR130 is a critical regulator of cell identity and oncogenic transformation. We summarize knowledge on the biological functions of PR130 in normal and transformed cells, targets of the PP2A-PR130 complex, and how diverse extra- and intracellular stimuli control the expression and activity of PR130. We additionally review the impact of PP2A-PR130 on cardiac functions, neuronal processes, and anti-viral defense and how this might affect cancer development and therapy.

MiR-93/miR-375: Diagnostic Potential, Aggressiveness Correlation and Common Target Genes in Prostate Cancer

Dysregulation of miRNAs has a fundamental role in the initiation, development and progression of prostate cancer (PCa). The potential of miRNA in gene therapy and diagnostic applications is well documented. To further improve miRNAs' ability to distinguish between PCa and benign prostatic hyperplasia (BPH) patients, nine miRNA (-21, -27b, -93, -141, -205, -221, -182, -375 and let-7a) with the highest reported differentiation power were chosen and for the first time used in comparative studies of serum and prostate tissue samples. Spearman correlations and response operating characteristic (ROC) analyses were applied to assess the capability of the miRNAs present in serum to discriminate between PCa and BPH patients. The present study clearly demonstrates that miR-93 and miR-375 could be taken into consideration as single blood-based non-invasive molecules to distinguish PCa from BPH patients. We indicate that these two miRNAs have six common, PCa-related, target genes (CCND2, MAP3K2, MXI1, PAFAH1B1, YOD1, ZFYVE26) that share the molecular function of protein binding (GO:0005515 term). A high diagnostic value of the new serum derived miR-182 (AUC = 0.881, 95% confidence interval, CI = 0.816-0.946, p < 0.0001, sensitivity and specificity were 85% and 79%, respectively) is also described.

A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

BACKGROUND

Prostate cancer (PCa) is the second leading cause of cancer death in men in 2018. Thus, the evaluation of prognosis is crucial for clinical treatment decision of human PCa patients. We aim to establishing an effective and reliable model to predict the outcome of PCa patients.

METHODS

We first identified differentially expressed genes between prostate cancer and normal prostate in TCGA-PRAD and then performed WGCNA to initially identify the candidate Gleason score related genes. Then, the candidate genes were applied to construct a LASSO Cox regression analysis model. Numerous independent validation cohorts, time-dependent receiver operating characteristic (ROC), univariate cox regression analysis, nomogram were used to test the effectiveness, accuracy and clinical utility of the prognostic model. Furthermore, functional analysis and immune cells infiltration were performed.

RESULTS

Gleason score-related differentially expressed candidates were identified and used to build up the outcome model in TCGA-PRAD cohort and was validated in MSKCC cohort. We found the 3-gene outcome model (CDC45, ESPL1 and RAD54L) had good performance in predicting recurrence free survival, metastasis free survival and overall survival of PCa patients. Time-dependent ROC and nomogram indicated an ideal predictive accuracy and clinical utility of the outcome model. Moreover, outcome model was enriched in 28 pathways by GSVA and GSEA. In addition, the risk score was positively correlated with memory B cells, native CD4 T cells, activated CD4 memory T cells and eosinophil, and negatively correlated with plasma cells, resting CD4 memory T cells, resting mast cells and neutrophil.

CONCLUSIONS

In summary, our outcome model proves to be an effective prognostic model for predicting the risk of prognosis in PCa.

PSA and PSA Kinetics Thresholds for the Presence of 68Ga-PSMA-11 PET/CT-Detectable Lesions in Patients With Biochemical Recurrent Prostate Cancer

⁶⁸Ga-PSMA-11 positron-emission tomography/computed tomography (PET/CT) is commonly used for restaging recurrent prostate cancer (PC) in European clinical practice. The goal of this study is to determine the optimum time for performing these PET/CT scans in a large cohort of patients by identifying the prostate-specific-antigen (PSA) and PSA kinetics thresholds for detecting and localizing recurrent PC. This retrospective analysis includes 581 patients with biochemical recurrence (BC) by definition. The performance of ⁶⁸Ga-PSMA-11 PET/CT in relation to the PSA value at the scan time as well as PSA kinetics was assessed by the receiver-operating-characteristic-curve (ROC) generated by plotting sensitivity versus 1-specificity. Malignant prostatic lesions were identified in 77%. For patients that were treated with radical prostatectomy (RP) a PSA value of 1.24 ng/mL was found to be the optimal cutoff level for predicting positive and negative scans, while for patients previously treated with radiotherapy (RT) it was 5.75 ng/mL. In RP-patients with PSA value <1.24 ng/mL, 52% scans were positive, whereas patients with PSA ≥1.24 ng/mL had positive scan results in 87%. RT-patients with PSA <5.75 ng/mL had positive scans in 86% and for those with PSA ≥5.75 ng/mL 94% had positive scans. This study identifies the PSA and PSA kinetics threshold levels for the presence of ⁶⁸Ga-PSMA-11 PET/CT-detectable PC-lesions in BC patients.

A Three-Gene Classifier Associated With MicroRNA-Mediated Regulation Predicts Prostate Cancer Recurrence After Radical Prostatectomy

BACKGROUND AND OBJECTIVE

After radical prostatectomy (RP), prostate cancer (PCa) patients may experience biochemical recurrence (BCR) and clinical recurrence, which remains a dominant issue in PCa treatment. The purpose of this study was to identify a protein-coding gene classifier associated with microRNA (miRNA)-mediated regulation to provide a comprehensive prognostic index to predict PCa recurrence after RP.

METHODS

Candidate classifiers were constructed using two machine-learning algorithms (a least absolute shrinkage and selector operation [LASSO]-based classifier and a decision tree-based classifier) based on a discovery cohort (n = 156) from The Cancer Genome Atlas (TCGA) database. After selecting the LASSO-based classifier based on the prediction accuracy, both an internal validation cohort (n = 333) and an external validation cohort (n = 100) were used to examined the classifier using survival analysis, time-dependent receiver operating characteristic (ROC) curve analysis, and univariate and multivariate Cox proportional hazards regression analyses. Functional enrichment analysis of co-expressed genes was carried out to explore the underlying moleculer mechanisms of the genes included in the classifier.

RESULTS

We constructed a three-gene classifier that included FAM72B, GNE, and TRIM46, and we identified four upstream prognostic miRNAs (hsa-miR-133a-3p, hsa-miR-222-3p, hsa-miR-1301-3p, and hsa-miR-30c-2-3p). The classifier exhibited a remarkable ability (area under the curve [AUC] = 0.927) to distinguish PCa patients with high and low Gleason scores in the discovery cohort. Furthermore, it was significantly associated with clinical recurrence (p < 0.0001, log rank statistic = 20.7, AUC = 0.733) and could serve as an independent prognostic factor of recurrence-free survival (hazard ratio: 1.708, 95% CI: 1.180-2.472, p < 0.001). Additionally, it was a predictor of BCR according to BCR-free survival analysis (p = 0.0338, log rank statistic = 4.51).

CONCLUSIONS

The three-gene classifier associated with miRNA-mediated regulation may serve as a novel prognostic biomarker for PCa patients after RP.