Identification of a Candidate Gene Panel for the Early Diagnosis of Prostate Cancer

Established and emerging liquid biomarkers for prostate cancer detection: A review

Prostate cancer remains one of the most frequently diagnosed cancers among men in the world today. Since its introduction in 1987 and FDA approval in 1994, prostate specific antigen (PSA) has reduced prostate cancer specific mortality considerably. However, the positive and negative predictive value of PSA is less than ideal and can lead to the over-detection of clinically insignificant prostate cancer. In the search for better screening measures to identify this cohort, liquid biomarkers for prostate cancer have emerged. In this review we will explore the commonly used urine and blood based prostate cancer liquid biomarkers. We detail the mechanism of each test and the validation studies that underscore their efficacy. Additionally, we will examine each test's effect on shared decision making as well as their cost efficacy in clinical practice.

Liquid Biomarkers in Prostate Cancer Diagnosis: Current Status and Emerging Prospects

Prostate cancer (PCa) is a major health concern that necessitates appropriate diagnostic approaches for timely intervention. This review critically evaluates the role of liquid biopsy techniques, focusing on blood- and urine-based biomarkers, in overcoming the limitations of conventional diagnostic methods. The 4Kscore test and Prostate Health Index have demonstrated efficacy in distinguishing PCa from benign conditions. Urinary biomarker tests such as PCa antigen 3, MyProstateScore, SelectMDx, and ExoDx Prostate IntelliScore test have revolutionized risk stratification and minimized unnecessary biopsies. Emerging biomarkers, including non-coding RNAs, circulating tumor DNA, and prostate-specific antigen (PSA) glycosylation, offer valuable insights into PCa biology, enabling personalized treatment strategies. Advancements in non-invasive liquid biomarkers for PCa diagnosis may facilitate the stratification of patients and avoid unnecessary biopsies, particularly when PSA is in the gray area of 4 to 10 ng/mL.

Prostate tumor markers: diagnosis, prognosis and management

Prostate cancer (PCA) is the second most common type of cancer in the world. Nevertheless, diagnosis is still based on nonspecific methods, or invasive methods which makes clinical decision and diagnosis difficult, generating risk of both underdiagnosis and overdiagnosis. Given the high prevalence, morbidity and mortality of PCA, new strategies are needed for its diagnosis. A review of the literature on available biomarkers for PCA was performed, using the following terms: prostate cancer AND marker OR biomarker. The search was carried out in Pubmed, Science Direct, Web of Science and Clinical Trial. A total of 35 articles were used, and PHI (Prostate Health Index) and the 4Kscore tests were identified as the best well-established serum markers. These tests are based on the evaluation of expression levels of several molecules. For analysis of urine samples, Progensa, ExoDXProstate, and Mi Prostate Score Urine Test are available. All these tests have the potential to help diagnosis, avoiding unnecessary biopsies, but they are used only in association with digital rectal examination and PSA level data. The search for biomarkers that can help in the diagnosis and therapeutic management of PCA is still in its initial phase, requiring more efforts for an effective clinical application.

Diagnostic Accuracy of Liquid Biomarkers for Clinically Significant Prostate Cancer Detection: A Systematic Review and Diagnostic Meta-analysis of Multiple Thresholds

CONTEXT

Many liquid biomarkers have entered clinical practice with the praise to improve the detection of clinically significant prostate cancer (csPCa), helping avoid unnecessary prostate biopsies.

OBJECTIVE

We aimed to assess the diagnostic accuracy of multianalyte biomarkers for csPCa detection using multiple thresholds.

EVIDENCE ACQUISITION

A comprehensive literature search was done through PubMed, Web of Science, and Scopus in March 2023 for prospective and retrospective studies reporting the diagnostic performance of liquid biomarkers for detecting csPCa. The outcomes of interest were the diagnostic performance of liquid biomarkers for csPCa detection and identification of optimal thresholds for each biomarker.

EVIDENCE SYNTHESIS

Overall, 49 studies were eligible for this meta-analysis. Using each representative threshold based on the Youden Index, the pooled sensitivity and specificity for detecting csPCa were 0.85 and 0.37 for prostate cancer gene 3 (PCA3), 0.85 and 0.52 for prostate health index (PHI), 0.87 and 0.58 for four kallikrein (4K), 0.82 and 0.56 for SelectMDx, 0.85 and 0.54 for ExoDx, and 0.82 and 0.59 for mi prostate score (MPS), respectively. The diagnostic odds ratio was highest for 4K (8.84), followed by MPS (7.0) and PHI (6.28). According to the meta-analysis incorporating multiple thresholds, the corresponding sensitivity was 0.77 for 4K, 0.69 for PHI, and 0.63 for PCA3; specificity was 0.72 for PHI, 0.70 for 4K, and 0.69 for PCA3.

CONCLUSIONS

Regarding the detection of csPCa, 4K had the highest diagnostic performance among the commercial liquid biomarkers. Based on the optimal thresholds calculated by the present meta-analysis, 4K had the highest sensitivity and PHI had the highest specificity for detecting csPCa. Nevertheless, clinical decision-making requires combination strategies between liquid and imaging biomarkers.

PATIENT SUMMARY

Novel biomarkers for prostate cancer detection were useful for more accurate diagnosis of clinically significant prostate cancer to avoid unnecessary biopsies.

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.

Beyond blood biomarkers: the role of SelectMDX in clinically significant prostate cancer identification

INTRODUCTION

New potential biomarkers to pre-intervention identification of a clinically significant prostate cancer (csPCa) will prevent overdiagnosis and overtreatment and limit quality of life impairment of PCa patients.

AREAS COVERED

We have developed a comprehensive review focusing our research on the increasing knowledge of the role of SelectMDX® in csPCa detection. Areas identified as clinically relevant are the ability of SelectMDX® to predict csPCa in active surveillance setting, its predictive ability when combined with multiparametric MRI and the role of SelectMDX® in the landscape of urinary biomarkers.

EXPERT OPINION

Several PCa biomarkers have been developed either alone or in combination with clinical variables to improve csPCa detection. SelectMDX® score includes genomic markers, age, PSA, prostate volume, and digital rectal examination. Several studies have shown consistency in the ability to improve detection of csPCa, avoidance of unnecessary prostate biopsies, helpful in decision-making for clinical benefit of PCa patients with future well designed, and impactful studies.

Tumor-Associated Fibroblast-Derived Exosomal circDennd1b Promotes Pituitary Adenoma Progression by Modulating the miR-145-5p/ONECUT2 Axis and Activating the MAPK Pathway

TAF participated in the progression of various cancers, including PA via the release of soluble factors. Exosomes belonged to extracellular vesicles, which were revealed as a crucial participator in intercellular communication. However, the expression pattern and effect of TAF-derived exosomes remained largely unknown in PA. In the present study, we performed in silico analysis based on public RNA-seq datasets to generate the circRNA/miRNA regulatory network. The qRT-PCR, Western blotting, RNA pull-down, and luciferase assay were performed to investigate the effect of TAF-derived exosomes. TAF-derived exosomal circDennd1b was significantly upregulated in PA and promoted the proliferation, migration, and invasion of PA cells via sponging miR-145-5p in PA cells. In addition, miR-145-5p directly regulated One Cut homeobox 2 (ONECUT2/OC2) expression and inhibited the promoting effect of ONECUT2 on PA. We further demonstrated that ONECUT2 transcriptionally increased fibroblast growth factor receptor 3 (FGFR3) expression, which further activates the mitogen-activated protein kinases (MAPK) pathway, thus promoting PA progression. Moreover, the suppression of TAFs by ABT-263 and ONECUT2 by CSRM617 inhibited the growth of PA. In conclusion, our study illustrated that TAF-derived exosomal circDennd1b affected PA progression via regulating ONECUT2 expression, which provides a potential therapeutic strategy against aggressive PA.

Comprehensive analysis of distal-less homeobox family gene expression in colon cancer

BACKGROUND

The distal-less homeobox (DLX) gene family plays an important role in the development of several tumors. However, the expression pattern, prognostic and diagnostic value, possible regulatory mechanisms, and the relationship between DLX family genes and immune infiltration in colon cancer have not been systematically reported.

AIM

We aimed to comprehensively analyze the biological role of the DLX gene family in the pathogenesis of colon cancer.

METHODS

Colon cancer tissue and normal colon tissue samples were collected from the Cancer Genome Atlas and Gene Expression Omnibus databases. Wilcoxon rank sum test and t-test were used to assess DLX gene family expression between colon cancer tissue and unpaired normal colon tissue. cBioPortal was used to analyze DLX gene family variants. R software was used to analyze DLX gene expression in colon cancer and the relationship between DLX gene family expression and clinical features and correlation heat map. The survival package and Cox regression module were used to assess the prognostic value of the DLX gene family. The pROC package was used to analyze the diagnostic value of the DLX gene family. R software was used to analyze the possible regulatory mechanisms of DLX gene family members and related genes. The GSVA package was used to analyze the relationship between the DLX gene family and immune infiltration. The ggplot2, the survminer package, and the clusterProfiler package were used for visualization.

RESULTS

DLX1/2/3/4/5 were significantly aberrantly expressed in colon cancer patients. The expression of DLX genes were associated with M stage, pathologic stage, primary therapy outcome, residual tumor, lymphatic invasion, T stage, N stage, age, perineural invasion, and history of colon polyps. DLX5 was independently correlated with the prognosis of colon cancer in multivariate analysis. DLX1/2/3/4/5/6 were involved in the development and progression of colon cancer by participating in immune infiltration and associated pathways, including the Hippo signaling pathway, the Wnt signaling pathway, several signaling pathways regulating the pluripotency of stem cells, and Staphylococcus aureus infection.

CONCLUSION

The results of this study suggest a possible role for the DLX gene family as potential diagnostic or prognostic biomarkers and therapeutic targets in colon cancer.

Transcriptome Profiling of Circulating Tumor Cells to Predict Clinical Outcomes in Metastatic Castration-Resistant Prostate Cancer

The clinical utility of circulating tumor cells (CTC) as a non-invasive multipurpose biomarker is broadly recognized. The earliest methods for enriching CTCs from whole blood rely on antibody-based positive selection. The prognostic utility of CTC enumeration using positive selection with the FDA-approved CellSearch^TM system has been demonstrated in numerous studies. The capture of cells with specific protein phenotypes does not fully represent cancer heterogeneity and therefore does not realize the prognostic potential of CTC liquid biopsies. To avoid this selection bias, CTC enrichment based on size and deformability may provide better fidelity, i.e., facilitate the characterization of CTCs with any phenotype. In this study, the recently FDA-approved Parsortix^® technology was used to enrich CTCs from prostate cancer (PCa) patients for transcriptome analysis using HyCEAD^TM technology. A tailored PCa gene panel allowed us to stratify metastatic castration-resistant prostate cancer (mCRPC) patients with clinical outcomes. In addition, our findings suggest that targeted CTC transcriptome profiling may be predictive of therapy response.

Cuproptosis signature and PLCD3 predicts immune infiltration and drug responses in osteosarcoma

Osteosarcoma (OS) is a cancer that is frequently found in children and adolescents and has made little improvement in terms of prognosis in recent years. A recently discovered type of programmed cell death called cuproptosis is mediated by copper ions and the tricarboxylic acid (TCA) cycle. The expression patterns, roles, and prognostic and predictive capabilities of the cuproptosis regulating genes were investigated in this work. TARGET and GEO provided transcriptional profiling of OS. To find different cuproptosis gene expression patterns, consensus clustering was used. To identify hub genes linked to cuproptosis, differential expression (DE) and weighted gene co-expression network analysis (WGCNA) were used. Cox regression and Random Survival Forest were used to build an evaluation model for prognosis. For various clusters/subgroups, GSVA, mRNAsi, and other immune infiltration experiments were carried out. The drug-responsive study was carried out by the Oncopredict algorithm. Cuproptosis genes displayed two unique patterns of expression, and high expression of FDX1 was associated with a poor outcome in OS patients. The TCA cycle and other tumor-promoting pathways were validated by the functional study, and activation of the cuproptosis genes may also be connected with immunosuppressive state. The robust survival prediction ability of a five-gene prognostic model was verified. This rating method also took stemness and immunosuppressive characteristics into account. Additionally, it can be associated with a higher sensitivity to medications that block PI3K/AKT/mTOR signaling as well as numerous chemoresistances. U2OS cell migration and proliferation may be encouraged by PLCD3. The relevance of PLCD3 in immunotherapy prediction was verified. The prognostic significance, expressing patterns, and functions of cuproptosis in OS were revealed in this work on a preliminary basis. The cuproptosis-related scoring model worked well for predicting prognosis and chemoresistance.

Gene-Transcript Expression in Urine Supernatant and Urine Cell-Sediment Are Different but Equally Useful for Detecting Prostate Cancer

There is considerable interest in urine as a non-invasive liquid biopsy to detect prostate cancer (PCa). PCa-specific transcripts such as the TMPRSS2:ERG fusion gene can be found in both urine extracellular vesicles (EVs) and urine cell-sediment (Cell) but the relative usefulness of these and other genes in each fraction in PCa detection has not been fully elucidated. Urine samples from 76 men (PCa n = 40, non-cancer n = 36) were analysed by NanoString for 154 PCa-associated genes-probes, 11 tissue-specific, and six housekeeping. Comparison to qRT-PCR data for four genes (PCA3, OR51E2, FOLH1, and RPLP2) was strong (r = 0.51-0.95, Spearman p < 0.00001). Comparing EV to Cells, differential gene expression analysis found 57 gene-probes significantly more highly expressed in 100 ng of amplified cDNA products from the EV fraction, and 26 in Cells (p < 0.05; edgeR). Expression levels of prostate-specific genes (KLK2, KLK3) measured were ~20× higher in EVs, while PTPRC (white-blood Cells) was ~1000× higher in Cells. Boruta analysis identified 11 gene-probes as useful in detecting PCa: two were useful in both fractions (PCA3, HOXC6), five in EVs alone (GJB1, RPS10, TMPRSS2:ERG, ERG_Exons_4-5, HPN) and four from Cell (ERG_Exons_6-7, OR51E2, SPINK1, IMPDH2), suggesting that it is beneficial to fractionate whole urine prior to analysis. The five housekeeping genes were not significantly differentially expressed between PCa and non-cancer samples. Expression signatures from Cell, EV and combined data did not show evidence for one fraction providing superior information over the other.

Biomarkers of Aggressive Prostate Cancer at Diagnosis

In the United States, prostate cancer (CaP) remains the second leading cause of cancer deaths in men. CaP is predominantly indolent at diagnosis, with a small fraction (25-30%) representing an aggressive subtype (Gleason score 7-10) that is prone to metastatic progression. This fact, coupled with the criticism surrounding the role of prostate specific antigen in prostate cancer screening, demonstrates the current need for a biomarker(s) that can identify clinically significant CaP and avoid unnecessary biopsy procedures and psychological implications of being diagnosed with low-risk prostate cancer. Although several diagnostic biomarkers are available to clinicians, very few comparative trials have been performed to assess the clinical effectiveness of these biomarkers. It is of note, however, that a majority of these clinical trials have been over-represented by men of Caucasian origin, despite the fact that African American men have a 1.7 times higher incidence and 2.1 times higher rate of mortality from prostate cancer. Biomarkers for CaP diagnosis based on the tissue of origin include urine-based gene expression assays (PCA3, Select MDx, ExoDx Prostate IntelliScore, Mi-Prostate Score, PCA3-PCGEM1 gene panel), blood-based protein biomarkers (4K, PHI), and tissue-based DNA biomarker (Confirm MDx). Another potential direction that has emerged to aid in the CaP diagnosis include multi-parametric magnetic resonance imaging (mpMRI) and bi-parametric magnetic resonance imaging (bpMRI), which in conjunction with clinically validated biomarkers may provide a better approach to predict clinically significant CaP at diagnosis. In this review, we discuss some of the adjunctive biomarker tests along with newer imaging modalities that are currently available to help clinicians decide which patients are at risk of having high-grade CaP on prostate biopsy with the emphasis on clinical utility of the tests across African American (AA) and Caucasian (CA) men.

Identification of molecular subtypes and a prognostic signature based on chromatin regulators related genes in prostate cancer

The clinical and molecular phenotypes of prostate cancer (PCa) exhibit substantial heterogeneity, ranging from indolent to metastatic disease. In this study, we aimed to identify PCa subtypes and construct a gene signature that can predict the recurrence-free survival (RFS) of PCa patients based on chromatin regulators genes (CRGs). Strikingly, we identified two heterogeneous subtypes with distinct clinical and molecular characteristics. Furthermore, by performing differential analysis between the two CRGs subtypes, we successfully constructed a gene signature to predict PCa prognosis. The signature, comprising four genes (MXD3, SSTR1, AMH and PPFIA2), was utilized to classify PCa patients into two risk groups; the high-risk group was characterized by poor prognosis and more aggressive clinical features. Moreover, we investigated the immune profile, mutation landscape and molecular pathways in each of the groups. Additionally, drug-susceptibility testing was performed to explore sensitive drugs for high-risk patients. Furthermore, we found that MXD3 downregulation suppressed the proliferation of PCa cell lines in vitro. Overall, our results highlight the signature based on CRGs as a powerful tool for predicting RFS of PCa patients, as well as an indicator for personalized treatment of those patients.

Accuracy of novel urinary biomarker tests in the diagnosis of prostate cancer: A systematic review and network meta-analysis

Objective

The purpose of this study was to conduct a network meta-analysis comparing the diagnostic value of different urinary markers for prostate cancer.

Methods

As of June 2022, the literature was retrieved by searching Pubmed, EMBASE, Web of Science databases and other databases. The methodological quality of included studies was assessed using the Cochrane Collaboration’s risk of bias tool, and publication bias was assessed using funnel plots. The surface under the cumulative ranking curve (SUCRA) values ​​was used to determine the most effective diagnostic method and the data were analyzed accordingly using data analysis software.

Results

A total of 16 articles was included including 9952 patients. The ranking results of network meta-analysis showed that the diagnostic performance of the four urine markers Selectmdx, MIPS, PCA3 and EPI was better than that of PSA. Among them, the specificity, positive predictive value and diagnostic accuracy of Selectmdx ranked first in the SUCRA ranking (SUCRA values: 85.2%, 88.3%, 97.1%), and the sensitivity ranked second in the SUCRA ranking (SUCRA value: 54.4%), and the negative predictive value ranked fourth in SUCRA (SUCRA value: 51.6%). The most sensitive screening tool was MIPS (SUCRA value: 67.1%), and it was also the second screening tool ranked higher in specificity, positive predictive value, negative predictive value and diagnostic accuracy (SUCRA value: 56.5%, respectively)., 57.1%, 67.9%, 74.3%). The high negative predictive value SUCRA ranking is EPI (SUCRA value: 68.0%), its sensitivity ranks third (SUCRA value: 45.6%), and its specificity, positive predictive value and diagnostic accuracy are ranked fourth (SUCRA values are: 45%, 38.2%, 35.8%).

Conclusion

According to the network ranking diagram, we finally concluded that Selectmdx and MIPS can be used as the most suitable urine markers for prostate cancer screening and diagnosis. To further explore the diagnostic value of different urinary markers in the screening of PCa patients.

Systematic Review Registration

https://inplasy.com/, identifier INPLASY202290094.

A novel prognostic model for prostate cancer based on androgen biosynthetic and catabolic pathways

Prostate cancer (PCa) is one of the most common malignancies in males globally, and its pathogenesis is significantly related to androgen. As one of the important treatments for prostate cancer, androgen deprivation therapy (ADT) inhibits tumor proliferation by controlling androgen levels, either surgically or pharmacologically. However, patients treated with ADT inevitably develop biochemical recurrence and advance to castration-resistant prostate cancer which has been reported to be associated with androgen biosynthetic and catabolic pathways. Thus, gene expression profiles and clinical information of PCa patients were collected from TCGA, MSKCC, and GEO databases for consensus clustering based on androgen biosynthetic and catabolic pathways. Subsequently, a novel prognostic model containing 13 genes (AFF3, B4GALNT4, CD38, CHRNA2, CST2, ADGRF5, KLK14, LRRC31, MT1F, MT1G, SFTPA2, SLC7A4, TDRD1) was constructed by univariate cox regression, lasso regression, and multivariate cox regression. Patients were divided into two groups based on their risk scores: high risk (HS) and low risk (LS), and survival analysis was used to determine the difference in biochemical recurrence-free time between the two. The results were validated on the MSKCC dataset and the GEO dataset. Functional enrichment analysis revealed some pivotal pathways that may have an impact on the prognosis of patients including the CDK-RB-E2F axis, G2M checkpoint, and KRAS signaling. In addition, somatic mutation, immune infiltration, and drug sensitivity analyses were performed to further explore the characteristics of HS and LS groups. Besides, two potential therapeutic targets, BIRC5 and RHOC, were identified by us in prostate cancer. These results indicate that the prognostic model may serve as a predictive tool to guide clinical treatment and provide new insight into the basic research in prostate cancer.

PSMA PET-CT in the Diagnosis and Staging of Prostate Cancer

Prostate cancer is the most common cancer and the second leading cause of cancer death in men. The imaging assessment and treatment of prostate cancer has vastly improved over the past decade. The introduction of PSMA PET-CT has improved the detection of loco-regional and metastatic disease. PSMA PET-CT also has a role in the primary diagnosis and staging, in detecting biochemical recurrence after curative treatment and in metastasis-directed therapy. In this paper we review the role of PSMA PET-CT in prostate cancer.

The involvement of homeobox-C 4 in predicting prognosis and unraveling immune landscape across multiple cancers via integrated analysis

Background: There has been growing evidence that the aberrantly expressed Homeobox-C 4 (HOXC4) plays crucial roles in the development of some cancer types. However, it remains unclear as far as its expression patterns and prognostic significance are concerned, as is tumor immunity.

Methods: To investigate the expression levels and prognostic implications of HOXC4, multiple data sources were used in conjunction with quantitative real-time polymerase chain reaction (qRT-PCR) verification. Afterward, diverse immunological-related analyses, along with anti-cancer drug sensitivity, were performed in a number of cancer types. A further exploration of the underlying mechanisms of HOXC4 in tumorigenesis and immunity was carried out using the Gene Set Enrichment Analysis (GSEA) and the Gene Set Variation Analysis (GSVA).

Results: Based on extensive database mining, HOXC4 was ubiquitously expressed across 21 tumor cell lines and significantly higher than that of normal tissues in 21 tumor types. The outcome of survival analysis including overall survival (OS), disease-free interval (DFI), disease-specific survival (DSS) and progression-free interval (PFI) revealed that upregulation of HOXC4 expression in several cancers was associated with worse prognosis. Additionally, HOXC4 was observed to correlate closely with colon adenocarcinoma (COAD), head and neck squamous cell carcinoma (HNSC), lower grade glioma (LGG), liver hepatocellular carcinoma (LIHC), rectum adenocarcinoma (READ), and thyroid carcinoma (THCA) in terms of tumor immune cells infiltration. As a result of our comprehensive pan-cancer study, we have identified a significant link between the expression of HOXC4 and the efficacy of immunotherapy-related treatments, together with anti-cancer drug sensitivity. As a final note, HOXC4 was found to modulate multiple signaling pathways involved in tumorigenesis and immunity.

Conclusion: HOXC4 has been implicated in our study for the first time as an oncogene in cancers with a poor prognosis, potentially laying the groundwork for promising clinical biomarkers and immunotherapy approaches.

Combination of PI-RADS score and mRNA urine test—A novel scoring system for improved detection of prostate cancer

Available tests to detect clinically significant prostate cancer frequently lead to overdiagnosis and overtreatment. Our study assessed the feasibility of combining a urinary biomarker-based risk score (SelectMDx^®) and multiparametric MRI outcomes in order to identify patients with prostate cancer on prostate biopsy with increased accuracy and reliability. Samples of 74 men with suspicion of prostate cancer and available multiparametric MRI were analysed in a prospective cross-sectional study design. First-voided urine for determination of HOXC6 and DLX1 mRNA levels was collected after digital rectal examination and prior to MRI/ultrasound fusion-guided prostate biopsy. All multiparametric MRI images were centrally reviewed by two experienced radiologists blinded for urine test results and biopsy outcome. The PI-RADS v2 was used. SelectMDx^® score, PI-RADS and Gleason Sore were obtained. Associations between Gleason Score, PI-RADS scores and SelectMDx^® were assessed using ANOVA and t-test. Sensitivity and specificity were assessed and evaluated as area-under-the-curve of the receiver operating characteristic. Upon biopsy, 59.5% of patients were diagnosed with prostate cancer, whereby 40.6% had high-grade prostate cancer (GS ≥ 7a). SelectMDx^® scores were significantly higher for patients with positive biopsy findings (49.07 ± 25.99% vs. 22.00 ± 26.43%; p < 0.001). SelectMDx^® scores increased with higher PI-RADS scores. Combining SelectMDx^®, history of prior biopsy with benign histology and PI-RADS scores into a novel scoring system led to significant prostate cancer detection rates with tiered detection rate of 39%, 58%, 81% and 100% for Gleason grade group II, III, IV, and V, respectively. The area-under-the-curve for our novel sum score in receiver operating characteristic analysis was 0.84. The synergistic combination of two non-invasive tests into a sum score with increased sensitivity may help avoiding unnecessary biopsies for initial prostate cancer diagnosis. For confirmation, further prospective studies with larger sample sizes and univariate and multivariate regression analyses and decision curve analyses are required.

Developing a Multimodal Model for Detecting Higher-Grade Prostate Cancer Using Biomarkers and Risk Factors

A technique to predict crucial clinical prostate cancer (PC) is desperately required to prevent diagnostic errors and overdiagnosis. To create a multimodal model that incorporates long-established messenger RNA (mRNA) indicators and conventional risk variables for identifying individuals with severe PC on prostatic biopsies. Urinary has gathered for mRNA analysis following a DRE and before a prostatic examination in two prospective multimodal investigations. A first group (n = 489) generated the multimodal risk score, which was then medically verified in a second group (n = 283). The reverse transcription qualitative polymerase chain reaction determined the mRNA phase. Logistic regression was applied to predict risk in patients and incorporate health risks. The area under the curve (AUC) was used to compare models, and clinical efficacy was assessed by using a DCA. The amounts of sixth homeobox clustering and first distal-less homeobox mRNA have been strongly predictive of high-grade PC detection. In the control subjects, the multimodal method achieved a total AUC of 0.90, with the most important aspects being the messenger riboneuclic acid features' PSA densities and previous cancer-negative tests as a nonsignificant design ability to contribute to PSA, aging, and background. An AUC of 0.86 was observed for one more model that added DRE as an extra risk component. Two methods were satisfactorily verified without any significant changes within the area under the curve in the validation group. DCA showed a massive net advantage and the highest decrease in inappropriate costs.

Construction of a Comprehensive Diagnostic Scoring Model for Prostate Cancer Based on a Novel Six-Gene Panel

Accumulating evidence indicates that the N6-methyladenosine (m⁶A) modification plays a critical role in human cancers. Given the current understanding of m⁶A modification, this process is believed to be dynamically regulated by m⁶A regulators. Although the discovery of m⁶A regulators has greatly enhanced our understanding of the mechanism underlying m⁶A modification in cancers, the function and role of m⁶A in the context of prostate cancer (PCa) remain unclear. Here, we aimed to establish a comprehensive diagnostic scoring model that can act as a complement to prostate-specific antigen (PSA) screening. To achieve this, we first drew the landscape of m⁶A regulators and constructed a LASSO-Cox model using three risk genes (METTL14, HNRNP2AB1, and YTHDF2). Particularly, METTL14 expression was found to be significantly related to overall survival, tumor T stage, relapse rate, and tumor microenvironment of PCa patients, showing that it has important prognostic value. Furthermore, for the sake of improving the predictive ability, we presented a comprehensive diagnostic scoring model based on a novel 6-gene panel by combining with genes found in our previous study, and its application potential was further validated by the whole TCGA and ICGC cohorts. Our study provides additional clues and insights regarding the treatment and diagnosis of PCa patients.

Accuracy of SelectMDx compared to mpMRI in the diagnosis of prostate cancer: a systematic review and diagnostic meta-analysis

BACKGROUND

The SelectMDx test is a promising biomarker that is developed based on detecting urinary messenger RNA in combination with clinical prostate cancer (PCa) risk factors. We aimed to compare SelectMDx and mpMRI as a diagnostic test in detecting PCa and high grade(HG)-PCa in men suspected to have PCa.

METHODS

According to PRISMA, a systematic search was performed using major web databases for studies published before September 30, 2021. Studies that compared sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of SelectMDx and/or mpMRI were included. The bivariate random model that plotted sensitivity, specificity, PPV, NPV, and likelihood ratio (LR) for PCa and HG-PCa detection was applied to compare SelectMDx, mpMRI, and combination strategies (both positive and one or both positive).

RESULTS

Seven studies comprising 1328 patients who had undergone SelectMDx and mpMRI to detect PCa were included. Regarding PCa detection, SelectMDx had a pooled sensitivity of 81%, specificity of 69.8%, PPV of 64.7%, NPV of 85%, and LRs of +2.68 to -0.27, while mpMRI had a pooled sensitivity of 80.8%, specificity of 73.4%, PPV of 72.4%, NPV of 83.5%, and LRs of +3.03 to -0.26. The one or both positive strategy had the highest sensitivity (96.3%), NPV (95.7%), and the lowest -LR (0.06). While the both positive strategy had the highest specificity (80.9%), the PPV (76.5%) and +LR (3.68). In the scenario of PI-RADS 3 lesions not being biopsied in case of a negative SelectMDx (n = 44), unnecessary biopsies would be reduced by 42% (44/105) while the risk of missing HG-PCa would be 9% (4/44).

CONCLUSION

The performance of SelectMDx is comparable to that of mpMRI with regards to PCa and HG-PCa detection. In addition, this biomarker could help refine the clinical decision-making regarding the necessity of a biopsy in patients suspected to has been PCa.

Expression Profiles of HOXC6 Predict the Survival of Glioblastoma Patients and Correlate with Cell Cycle

The goal of this study was to investigate the homeobox (HOX) gene expression status and its prognostic value in glioblastoma multiforme (GBM) and to uncover the biological processes related to its expression. The prognostic value of HOX genes in GBM was systematically investigated by a genome-wide analysis of HOX gene expression profiles in GBM patient samples in The Cancer Genome Atlas (TCGA) project (microarray dataset) and validation datasets. Using the differentially expressed gene (DEG) analysis and a Cox regression model, we discovered that the HOXC6 could stratify patients into significantly different survival (p = 0.0012, log-rank test) groups in the training cohort. TCGA RNA-seq and GSE16011 datasets were used for validation. Multivariate Cox and stratification analysis indicated that HOXC6 was an independent prognostic factor after adjusting for other clinical covariates. Bioinformatic analysis suggested that the HOXC6 might be involved in the cell cycle-related biological processes and pathways that are well established in the context of glioblastoma tumorigenesis. We further explored the bioinformatic implications by gene set enrichment analysis (GSEA). Tumor cell biology experiments verified the role of HOXC6 in proliferation and cell cycle progression. In conclusion, HOXC6 might be a candidate biomarker gene for individual treatment optimization of glioblastoma. HOXC6 expression has a significant prognostic value and is related to the cell cycle process in glioblastoma.

Urothelial carcinoembryonic antigen 1 score for early detection of prostate cancer and risk prediction

UCA1 score appears useful in detecting nonhigh-risk (including very low-, low-, or intermediate-risk) prostate cancer. Combination of the PSA level and the UCA1 score may significantly reduce the burden of prostate biopsy.

Liquid biomarkers for early detection of prostate cancer and summary of available data for their use in African-American men

BACKGROUND

Several liquid biomarker tests have been developed to account for the limitations of prostate specific antigen (PSA) screening prior to prostate biopsy. African ancestry is an established risk factor for prostate cancer (PCa) and must be particularly considered when evaluating patients with liquid biomarkers. While multiple tests have been developed over decades of exploration, recent advances can help patients and physicians incorporate data into a broader clinical context.

METHODS

We sought to review currently available liquid biomarker tests in a practical, clinically directed fashion with particular focus on performance in men with African ancestry. We reviewed discovery and validation studies and highlight important considerations for each test.

RESULTS

We discuss the advantages and limitations of percent free PSA, Prostate Health Index, Progensa® PCA3, ExoDx® Prostate Test, SelectMDx®, 4Kscore® Test, and Mi-Prostate Score and summarize salient studies on their use. A literature review of evidence specifically for men with African ancestry was conducted and available studies were summarized.

CONCLUSIONS

Liquid biomarkers can be useful tools for aiding in risk stratification prior to prostate biopsy. Use of such tests should be individualized based on a thorough knowledge of supporting evidence and the goals of the patient and physician. Further study should prioritize evaluation of such biomarkers in men with African ancestry.

The ReIMAGINE prostate cancer risk study protocol: A prospective cohort study in men with a suspicion of prostate cancer who are referred onto an MRI-based diagnostic pathway with donation of tissue, blood and urine for biomarker analyses

INTRODUCTION

The ReIMAGINE Consortium was conceived to develop risk-stratification models that might incorporate the full range of novel prostate cancer (PCa) diagnostics (both commercial and academic).

METHODS

ReIMAGINE Risk is an ethics approved (19/LO/1128) multicentre, prospective, observational cohort study which will recruit 1000 treatment-naive men undergoing a multi-parametric MRI (mpMRI) due to an elevated PSA (≤20ng/ml) or abnormal prostate examination who subsequently had a suspicious mpMRI (score≥3, stage ≤T3bN0M0). Primary outcomes include the detection of ≥Gleason 7 PCa at baseline and time to clinical progression, metastasis and death. Baseline blood, urine, and biopsy cores for fresh prostate tissue samples (2 targeted and 1 non-targeted) will be biobanked for future analysis. High-resolution scanning of pathology whole-slide imaging and MRI-DICOM images will be collected. Consortium partners will be granted access to data and biobanks to develop and validate biomarkers using correlation to mpMRI, biopsy-based disease status and long-term clinical outcomes.

RESULTS

Recruitment began in September 2019(n = 533). A first site opened in September 2019 (n = 296), a second in November 2019 (n = 210) and a third in December 2020 (n = 27). Acceptance to the study has been 65% and a mean of 36.5ml(SD+/-10.0), 12.9ml(SD+/-3.7) and 2.8ml(SD+/-0.7) urine, plasma and serum donated for research, respectively. There are currently 4 academic and 15 commercial partners spanning imaging (~9 radiomics, artificial intelligence/machine learning), fluidic (~3 blood-based and ~2urine-based) and tissue-based (~1) biomarkers.

CONCLUSION

The consortium will develop, or adjust, risk models for PCa, and provide a platform for evaluating the role of novel diagnostics in the era of pre-biopsy MRI and targeted biopsy.

Prostate cancer biomarkers: a practical review based on different clinical scenarios

Traditionally, diagnosis and staging of prostate cancer (PCa) have been based on prostate-specific antigen (PSA) level, digital rectal examination (DRE), and transrectal ultrasound (TRUS) guided prostate biopsy. Biomarkers have been introduced into clinical practice to reduce the overdiagnosis and overtreatment of low-grade PCa and increase the success of personalized therapies for high-grade and high-stage PCa. The purpose of this review was to describe available PCa biomarkers and examine their use in clinical practice. A nonsystematic literature review was performed using PubMed and Scopus to retrieve papers related to PCa biomarkers. In addition, we manually searched websites of major urological associations for PCa guidelines to evaluate available evidence and recommendations on the role of biomarkers and their potential contribution to PCa decision-making. In addition to PSA and its derivates, thirteen blood, urine, and tissue biomarkers are mentioned in various PCa guidelines. Retrospective studies have shown their utility in three main clinical scenarios: (1) deciding whether to perform a biopsy, (2) distinguishing patients who require active treatment from those who can benefit from active surveillance, and (3) defining a subset of high-risk PCa patients who can benefit from additional therapies after RP. Several validated PCa biomarkers have become commercially available in recent years. Guidelines now recommend offering these tests in situations in which the assay result, when considered in combination with routine clinical factors, is likely to affect management. However, the lack of direct comparisons and the unproven benefits, in terms of long-term survival and cost-effectiveness, prevent these biomarkers from being integrated into routine clinical use.

Development of a novel miR-3648-related gene signature as a prognostic biomarker in esophageal adenocarcinoma

Background

Esophageal adenocarcinoma (EA) is a typical immunogenic malignant tumor with a dismal 5-year survival rate lower than 20%. Although miRNA-3648 (miR-3648) is expressed abnormally in EA, its impact on the tumor immune microenvironment remains unknown. In this study, we sought to identify immune-related genes (IRGs) that are targeted by miR-3648 and develop an EA multigene signature.

Methods

The gene expression data of 87 EA tumor samples and 67 normal tissue samples from The Cancer Genome Atlas (TCGA) database and the Genotype-Tissue Expression (GTEx) database were downloaded, respectively. Weighted gene co-expression network analysis (WGCNA), the CIBERSORT algorithm, and Cox regression analysis were applied to identify IRGs and to construct a prognostic signature and nomogram.

Results

MiR-3648 was expectedly highly expressed in EA tumor tissues (P=2.6e-8), and related to the infiltration of activated natural killer cells (NK cells) and activated CD4 T lymphocytes (CD4 cells). A total of 70 miR-3648-targeted genes related to immune cell infiltration were identified. Among them, 4 genes (C10orf55, DLL4, PANX2, and NKAIN1) were closely related to overall survival (OS), and were thus selected to construct a 4-gene risk score (RS). The RS had a superior capability to predict OS [area under the curve (AUC) =0.740 for 1 year; AUC =0.717 for 3 years; AUC =0.622 for 5 years]. A higher score was indicative of a poorer prognosis than a lower score [hazard ratio (HR) =2.71; 95% confidence interval (CI): 1.45-5.09; P=0.002]. Furthermore, the nomogram formed by combining the RS and the TNM classification of malignant tumors (TNM stage) improved the accuracy of survival prediction [Harrell's concordance index (C-index) =0.698].

Conclusions

MiR-3648 may play a critical role in EA pathogenesis. The novel 4-gene signature may serve as a prognostic tool to manage patients with EA.

Circulating RNAs in prostate cancer patients

Growing bodies of evidence have demonstrated that the identification of prostate cancer (PCa) biomarkers in the patients' blood and urine may remarkably improve PCa diagnosis and progression monitoring. Among diverse cancer-derived circulating materials, extracellular RNA molecules (exRNAs) represent a compelling component to investigate cancer-related alterations. Once outside the intracellular environment, exRNAs circulate in biofluids either in association with protein complexes or encapsulated inside extracellular vesicles (EVs). Notably, EV-associated RNAs (EV-RNAs) were used for the development of several assays (such as the FDA-approved Progensa Prostate Cancer Antigen 3 (PCA3 test) aiming at improving early PCa detection. EV-RNAs encompass a mixture of species, including small non-coding RNAs (e.g. miRNA and circRNA), lncRNAs and mRNAs. Several methods have been proposed to isolate EVs and relevant RNAs, and to perform RNA-Seq studies to identify potential cancer biomarkers. However, EVs in the circulation of a cancer patient include a multitude of diverse populations that are released by both cancer and normal cells from different tissues, thereby leading to a heterogeneous EV-RNA-associated transcriptional signal. Decrypting the complexity of such a composite signal is nowadays the major challenge faced in the identification of specific tumor-associated RNAs. Multiple deconvolution algorithms have been proposed so far to infer the enrichment of cancer-specific signals from gene expression data. However, novel strategies for EVs sorting and sequencing of RNA associated to single EVs populations will remarkably facilitate the identification of cancer-related molecules. Altogether, the studies summarized here demonstrate the high potential of using EV-RNA biomarkers in PCa and highlight the urgent need of improving technologies and computational approaches to characterize specific EVs populations and their relevant RNA cargo.

Characteristics of α2,3-sialyl N-glycosylated PSA as a biomarker for clinically significant prostate cancer in men with elevated PSA level

BACKGROUND

The presence of glycosylated isoforms of prostate-specific antigen (PSA) in prostate cancer (PC) cells is a potential marker of their aggressiveness. We characterized the origin of α2,3-sialylated prostate-specific antigen (S23PSA) by tissue-based sialylation-related gene expression and studied the performance of S23PSA density (S23PSAD) alone and in combination with multiparametric magnetic resonance imaging (MRI) for the detection of clinically significant prostate cancer in men with elevated PSA.

METHODS

Tissue-based quantification of S23PSA and sialyltransferase and sialidase gene expression was evaluated in 71 radical prostatectomy specimens. The diagnostic performance of S23PSAD was studied in 1099 men retrospectively enrolled in a multicenter systematic biopsy (SBx) cohort. We correlated the S23PSAD with Prostate Imaging Reporting and Data System (PI-RADS) scores in 98 men prospectively enrolled in a single-center MRI-targeted biopsy (MRI-TBx) cohort. The primary outcome was the PC-diagnostic performance of the S23PSAD, the secondary outcome was the avoidable biopsy rate of S23PSAD combined with DRE and total PSA (tPSA), and with or without PI-RADS.

RESULTS

S23PSA was significantly higher in Gleason pattern 4 and 5 compared with benign prostate tissue. In the retrospective cohort, the performance of S23PSAD for detecting PC was superior to tPSA or PSA density (PSAD) (AUC: 0.7758 vs. 0.6360 and 0.7509, respectively). In the prospective cohort, S23PSAD was superior to tPSA, PSAD, and PI-RADS (AUC: 0.7725 vs. 0.5901, 0.7439 and 0.7305, respectively), and S23PSAD + PI-RADS + DRE + tPSA was superior to DRE + tPSA+PI-RADS with avoidance rate of MRI-TBx (13% vs. 1%) at 30% risk threshold.

CONCLUSIONS

The diagnostic performance of S23PSAD was superior to conventional strategies but comparable to mpMRI.

The Role and Significance of Bioumoral Markers in Prostate Cancer

The prostate is one of the most clinically accessible internal organs of the genitourinary tract in men. For decades, the only method of screening for prostate cancer (PCa) has been digital rectal examination of 1990s significantly increased the incidence and prevalence of PCa and consequently the morbidity and mortality associated with this disease. In addition, the different types of oncology treatment methods have been linked to specific complications and side effects, which would affect the patient's quality of life. In the first two decades of the 21st century, over-detection and over-treatment of PCa patients has generated enormous costs for health systems, especially in Europe and the United States. The Prostate Specific Antigen (PSA) is still the most common and accessible screening blood test for PCa, but with low sensibility and specificity at lower values (<10 ng/mL). Therefore, in order to avoid unnecessary biopsies, several screening tests (blood, urine, or genetic) have been developed. This review analyzes the most used bioumoral markers for PCa screening and also those that could predict the evolution of metastases of patients diagnosed with PCa.

Blood and urine biomarkers in prostate cancer: Are we ready for reflex testing in men with an elevated prostate-specific antigen?

Objective

There is no consensus on the role of biomarkers in determining the utility of prostate biopsy in men with elevated prostate-specific antigen (PSA). There are numerous biomarkers such as prostate health index, 4Kscore, prostate cancer antigen 3, ExoDX, SelectMDx, and Mi-Prostate Score that may be useful in this decision-making process. However, it is unclear whether any of these tests are accurate and cost-effective enough to warrant being a widespread reflex test following an elevated PSA. Our goal was to report on the clinical utility of these blood and urine biomarkers in prostate cancer screening.

Methods

We performed a systematic review of studies published between January 2000 and October 2020 to report the available parameters and cost-effectiveness of the aforementioned diagnostic tests. We focus on the negative predictive value, the area under the curve, and the decision curve analysis in comparing reflexive tests due to their relevance in evaluating diagnostic screening tests.

Results

Overall, the biomarkers are roughly equivalent in predictive accuracy. Each test has additional clinical utility to the current diagnostic standard of care, but the added benefit is not substantial to justify using the test reflexively after an elevated PSA.

Conclusions

Our findings suggest these biomarkers should not be used in binary fashion and should be understood in the context of pre-existing risk predictors, patient's ethnicity, cost of the test, patient life-expectancy, and patient goals. There are more recent diagnostic tools such as multi-parametric magnetic resonance imaging, polygenic single-nucleotide panels, IsoPSA, and miR Sentinel tests that are promising in the realm of prostate cancer screening and need to be investigated further to be considered a consensus reflexive test in the setting of prostate cancer screening.

miR-184 delays cell proliferation, migration and invasion in prostate cancer by directly suppressing DLX1

A number of previous studies have reported that dysregulated miR-184 expression is associated with the development of cancer. The aim of the present study was to investigate the role of miR-184 in prostate cancer (PC) and the mechanism underlying its effects. Data from human tumor tissue samples were collected from The CEancer Genome Atlas to determine the expression levels of miR-184 and DLX1. The miR-184 mimic and pcDNA3.1-DLX1 plasmid were utilized to induce overexpression of miR-184 and DLX1 in Du145 cells, respectively. Cell Counting Kit-8, wound healing and Transwell assays were performed to examine the effects of miR-184 on the aggressiveness of PC cells. Dual-luciferase reporter gene assay was used to investigate the association between miR-184 and DLX1, and reverse transcription-quantitative PCR and western blot analyses were utilized to determine the mRNA and protein levels. miR-184 expression was found to be downregulated whereas DLX1 was upregulated in PC tissues compared with normal prostate tissues. Cell propagation, migration and invasion were all inhibited by miR-184 upregulation in Du145 cells. Dual luciferase reporter assay confirmed the association between miR-184 and DLX1. The inhibitory effect of miR-184 mimic on cell behaviors was reversed by upregulation of DLX1. These findings suggest that miR-184 plays a beneficial role in suppressing the tumorigenesis of PC by directly targeting DLX1, and it may represent a potential therapeutic strategy for PC.

Transcriptional network involving ERG and AR orchestrates Distal-less homeobox-1 mediated prostate cancer progression

Distal-less homeobox-1 (DLX1) is a well-established non-invasive biomarker for prostate cancer (PCa) diagnosis, however, its mechanistic underpinnings in disease pathobiology are not known. Here, we reveal the oncogenic role of DLX1 and show that abrogating its function leads to reduced tumorigenesis and metastases. We observed that ~60% of advanced-stage and metastatic patients display higher DLX1 levels. Moreover, ~96% of TMPRSS2-ERG fusion-positive and ~70% of androgen receptor (AR)-positive patients show elevated DLX1, associated with aggressive disease and poor survival. Mechanistically, ERG coordinates with enhancer-bound AR and FOXA1 to drive transcriptional upregulation of DLX1 in ERG-positive background. However, in ERG-negative context, AR/AR-V7 and FOXA1 suffice to upregulate DLX1. Notably, inhibiting ERG/AR-mediated DLX1 transcription using BET inhibitor (BETi) or/and anti-androgen drugs reduce its expression and downstream oncogenic effects. Conclusively, this study establishes DLX1 as a direct-target of ERG/AR with an oncogenic role and demonstrates the clinical significance of BETi and anti-androgens for DLX1-positive patients.

MiR-129-5p/DLX1 signalling axis mediates functions of prostate cancer during malignant progression

We mainly corroborated the potential mechanism of DLX1 and miR-129-5p in prostate cancer cells. DLX1 was upregulated in cancer cells according to qRT-PCR assay. We evaluated the functional changes of the transfected cells via Transwell assay, CCK-8 assay and wound healing assay. DLX1 was confirmed as a cancer promoter. In addition, qRT-PCR showed down-regulated miR-129-5p expression in prostate cancer. We further used dual-luciferase reporter detection to elucidate the targeting between these two genes. The inhibition of miR-129-5p on tumour was verified. Besides, co-transfection of oe-DLX1 and miR-129-5p mimics attenuated this inhibition. These data demonstrated functions of DLX1/miR-129-5p axis in prostate cancer: miR-129-5p hindered the biological functions of cancer cells via inhibiting DLX1 expression. We provide a novel biomarker for prostate cancer.

Tumour markers of prostate cancer: The post-PSA era

Although PSA-based prostate cancer (PCa) screening had a positive impact in reducing PCa mortality, it also led to overdiagnosis, overtreatment and to a significant number of unnecessary biopsies. In the post-PSA era, new biomarkers have emerged that can complement the information given by PSA, towards a better cancer diagnostic specificity, and also allow a better estimate of the aggressiveness of the disease and its clinical outcome. That means those markers have the potential to assist the clinician in the decision-making processes, such as whether or not to perform a biopsy, and to make the best treatment choice among the new therapeutic options available, including active surveillance (AS) in lower risk disease. In this article, we will review several of those more recent diagnostic markers (4Kscore®, [-2]proPSA and Prostate Health Index (PHI), SelectMDx®, ConfirmMDx®, Progensa® Prostate Cancer Antigen 3, Mi-Prostate Score, ExoDx™ Prostate Test, the Stockholm-3 test and ERSPC risk calculators) and prognostic markers (OncotypeDX® Genomic Prostate Score, Prolaris®, Decipher® and ProMark®). We will also address some new liquid biopsy approaches - circulating tumour cells and cell-free DNA (cfDNA) - with a potential role in metastatic castration-resistant PCa and will briefly give some future perspectives, mostly outlooking epigenetic markers.

Biomarkers for detection of clinically significant prostate cancer: contemporary clinical data and future directions

Use of serum prostate-specific antigen (PSA) testing for early detection of prostate cancer appears to reduce cancer-specific mortality. Due to the limited specificity of PSA for clinically significant [Grade Group (GG) ≥2] cancer, however, screening carries substantial risks, including frequent unnecessary prostate biopsies and overdetection of non-aggressive cancers. To that end, serum and urine biomarkers with improved specificity for GG ≥2 cancer have been proposed for clinical use following PSA. In the current article, we present clinical validation data for five such biomarkers: PHI, 4Kscore, SelectMDx, ExoDx, and MPS. For all studies, we specify the study population (overall biopsy referral vs. pre-specified PSA ranges), previous biopsy status (biopsy-naïve vs. previous negative biopsy), and the proportion of subjects diagnosed with GG ≥2 cancer. Outcomes include test performance characteristics: sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV). Published data were used to compute the number of unnecessary biopsies avoided and number of GG ≥2 cancers missed if the biomarker had been used clinically to select for prostate biopsy. The evidence review is preceded by a primer on these and other clinically-relevant summary statistics.

Next-Generation Sequencing in Cancer

Objective

In this article, we provide a gestalt idea about NGS technologies and their applications in cancer research and molecular diagnosis.

Background

Next-generation sequencing (NGS) advancements like DNA sequencing and RNA sequencing allow uncovering of genomic, transcriptomic, and epigenomic scenes of individual malignant growths. An assortment of genomic abnormalities can be screened at the same time, for example common and uncommon variations, auxiliary variations like insertions and deletions, copy-number variation, and fusion transcripts.

Conclusion

NGS innovations together with bioinformatics investigation, which extend our insight, are progressively used to analyze multiple genes in a cost-effective way and have been applied in examining clinical cancer samples and offering NGS-based molecular diagnosis.

Application

NGS is progressively significant as a device for the diagnosis of cancers.

A 25-year perspective on evaluation and understanding of biomarkers in urologic cancers

The past 25 years have witnessed an explosion of investigative attempts to identify clinically useful biomarkers which can have meaningful impacts for patients with urologic cancers. However, in spite of the enormous amount of research aiming to identify markers with the hope of impacting patient care, only a handful have proven to have true clinical utility. Improvements in targeted imaging, pan-omics evaluation, and genetic sequencing at the tissue and single-cell levels have yielded many potential targets for continued biomarker investigation. This article, as one in this series for the 25th Anniversary Issue of Urologic Oncology: Seminars and Original Investigations, serves to give a perspective on our progress and failures over the past quarter-century in our highest volume urologic cancers: prostate, bladder, and kidney cancers.

Tissue- and Liquid-Based Biomarkers in Prostate Cancer Precision Medicine

Worldwide, prostate cancer (PC) is the second-most-frequently diagnosed male cancer and the fifth-most-common cause of all cancer-related deaths. Suspicion of PC in a patient is largely based upon clinical signs and the use of prostate-specific antigen (PSA) levels. Although PSA levels have been criticised for a lack of specificity, leading to PC over-diagnosis, it is still the most commonly used biomarker in PC management. Unfortunately, PC is extremely heterogeneous, and it can be difficult to stratify patients whose tumours are unlikely to progress from those that are aggressive and require treatment intensification. Although PC-specific biomarker research has previously focused on disease diagnosis, there is an unmet clinical need for novel prognostic, predictive and treatment response biomarkers that can be used to provide a precision medicine approach to PC management. In particular, the identification of biomarkers at the time of screening/diagnosis that can provide an indication of disease aggressiveness is perhaps the greatest current unmet clinical need in PC management. Largely through advances in genomic and proteomic techniques, exciting pre-clinical and clinical research is continuing to identify potential tissue, blood and urine-based PC-specific biomarkers that may in the future supplement or replace current standard practices. In this review, we describe how PC-specific biomarker research is progressing, including the evolution of PSA-based tests and those novel assays that have gained clinical approval. We also describe alternative diagnostic biomarkers to PSA, in addition to biomarkers that can predict PC aggressiveness and biomarkers that can predict response to certain therapies. We believe that novel biomarker research has the potential to make significant improvements to the clinical management of this disease in the near future.

Prostate Cancer Biomarkers: From diagnosis to prognosis and precision-guided therapeutics

Prostate cancer (PCa) is one of the most commonly diagnosed malignancies and among the leading causes of cancer-related death worldwide. It is a highly heterogeneous disease, ranging from remarkably slow progression or inertia to highly aggressive and fatal disease. As therapeutic decision-making, clinical trial design and outcome highly depend on the appropriate stratification of patients to risk groups, it is imperative to differentiate between benign versus more aggressive states. The incorporation of clinically valuable prognostic and predictive biomarkers is also potentially amenable in this process, in the timely prevention of metastatic disease and in the decision for therapy selection. This review summarizes the progress that has so far been made in the identification of the genomic events that can be used for the classification, prediction and prognostication of PCa, and as major targets for clinical intervention. We include an extensive list of emerging biomarkers for which there is enough preclinical evidence to suggest that they may constitute crucial targets for achieving significant advances in the management of the disease. Finally, we highlight the main challenges that are associated with the identification of clinically significant PCa biomarkers and recommend possible ways to overcome such limitations.

Re-Evaluate Fusion Genes in Prostate Cancer

Background:

Thousands of gene fusions have been reported in prostate cancer, but their authenticity, incidence, and tumor specificity have not been thoroughly evaluated, nor have their genomic characteristics been carefully explored.

Methods:

We developed FusionVet to dedicatedly validate known fusion genes using RNA-seq alignments. Using FusionVet, we re-assessed 2727 gene fusions reported from 36 studies using the RNA-seq data generated by The Cancer Genome Atlas (TCGA). We also explored their genomic characteristics and interrogated the transcriptomic and DNA methylomic consequences of the E26 transformation-specific (ETS) fusions.

Results:

We found that nearly two-thirds of reported fusions are intra-chromosomal, and 80% of them were formed between 2 protein-coding genes. Although most (76%) genes were fused to only 1 partner, we observed many fusion hub genes that have multiple fusion partners, including ETS family genes, androgen receptor signaling pathway genes, tumor suppressor genes, and proto-oncogenes. More than 90% of the reported fusions cannot be validated by TCGA RNA-seq data. For those fusions that can be validated, 5% were detected from tumor and normal samples with similar frequencies, and only 4% (120 fusions) were tumor-specific. The occurrences of ERG, ETV1, and ETV4 fusions were mutually exclusive, and their fusion statuses were tightly associated with overexpressions. Besides, we found ERG fusions were significantly co-occurred with PTEN deletion but mutually exclusive with common genomic alterations such as SPOP mutation and FOXA1 mutation.

Conclusions:

Most of the reported fusion genes cannot be validated by TCGA samples. The ETS family and androgen response genes were significantly enriched in prostate cancer–specific fusion genes. Transcription activity was significantly repressed, and the DNA methylation was significantly increased in samples carrying ERG fusion.

Active Surveillance in Prostate Cancer: Role of Available Biomarkers in Daily Practice

Prostate cancer (PCa) is the most commonly diagnosed cancer in men. The diagnosis is currently based on PSA levels, which are associated with overdiagnosis and overtreatment. Moreover, most PCas are localized tumours; hence, many patients with low-/very low-risk PCa could benefit from active surveillance (AS) programs instead of more aggressive, active treatments. Heterogeneity within inclusion criteria and follow-up strategies are the main controversial issues that AS presently faces. Many biomarkers are currently under investigation in this setting; however, none has yet demonstrated enough diagnostic ability as an independent predictor of pathological or clinical progression. This work aims to review the currently available literature on tissue, blood and urine biomarkers validated in clinical practice for the management of AS patients.

Development of Parallel Reaction Monitoring Assays for the Detection of Aggressive Prostate Cancer Using Urinary Glycoproteins

Recently, we have found that two urinary glycoproteins, prostatic acid phosphatase (ACPP) and clusterin (CLU), combined with serum prostate-specific antigen (PSA) can serve as a three-signature panel for detecting aggressive prostate cancer (PCa) based on a quantitative glycoproteomic study. To facilitate the translation of candidates into clinically applicable tests, robust and accurate targeted parallel reaction monitoring (PRM) assays that can be widely adopted in multiple labs were developed in this study. The developed PRM assays for the urinary glycopeptides, FLN*ESYK from ACPP and EDALN*ETR from CLU, demonstrated good repeatability and a sufficient working range covering three to four orders of magnitude, and their performance in differentiating aggressive PCa was assessed by the quantitative analysis of urine specimens collected from 69 nonaggressive (Gleason score = 6) and 73 aggressive (Gleason ≥ 8) PCa patients. When ACPP combined with CLU, the discrimination power was improved from an area under a curve (AUC) of 0.66 to 0.78. By combining ACPP, CLU, and serum PSA to form a three-signature panel, the AUC was further improved to 0.83 (sensitivity: 84.9%, specificity: 66.7%). Since the serum PSA test alone had an AUC of 0.68, our results demonstrated that the new urinary glycopeptide PRM assays can serve as an adjunct to the serum PSA test to achieve better predictive power toward aggressive PCa. In summary, our developed PRM assays for urinary glycopeptides were successfully applied to clinical PCa urine samples with a promising performance in aggressive PCa detection.

Prospective assessment of two-gene urinary test with multiparametric magnetic resonance imaging of the prostate for men undergoing primary prostate biopsy

PURPOSE

To evaluate the diagnostic accuracy of SelectMDx and its association with multiparametric magnetic resonance (mpMRI) in predicting prostate cancer (PCa) and clinically significant PCa (csPCa) on prostate biopsies among men scheduled for initial prostate biopsy.

METHODS

In this single-center prospective study, 52 men scheduled for initial prostate biopsy, based on elevated total PSA level (> 3 ng/ml) or abnormal digital rectal examination, were consecutively included. All subjects underwent SelectMDx, PSA determination and mpMRI.

RESULTS

SelectMDx score was positive in 94.1 and 100% of PCa and csPCa, respectively, and in only 8.6% of negative cases at biopsy. The probability for a csPCa at the SelectMDx score was significantly (p = 0.002) higher in csPCa (median value 52.0%) than in all PCa (median value 30.0%). SelectMDx showed slightly lower sensitivity (94.1 versus 100.0%) but higher specificity (91.4%) than total PSA (17.1%), and the same sensitivity but higher specificity than mpMRI (80.0%) in predicting PCa at biopsy. The association of SelectMDx plus mpMRI rather than PSA density (PSAD) plus mpMRI showed higher specificity (both 91.4%) compared to the association of PSA plus mpMRI (85.7%). In terms of csPCa predictive value, SelectMDx showed higher specificity (73.3%) than PSA (13.3%) and mpMRI (64.4%); as for the association of SelectMDx plus mpMRI (75.6%) versus PSA plus mpMRI (68.9%), the association of PSAD plus mpMRI showed the highest specificity (80.0%).

CONCLUSION

Our results of SelectMDx can be confirmed as significant but their impact on clinical practice together with a cost-effectiveness evaluation should be investigated in a larger prospective multicenter analysis.

Liquid biopsy reveals KLK3 mRNA as a prognostic marker for progression free survival in patients with metastatic castration-resistant prostate cancer undergoing first-line abiraterone acetate and prednisone treatment

Circulating RNAs extracted from liquid biopsies represent a promising source of cancer‐ and therapy‐related biomarkers. We screened whole blood from patients with metastatic castration‐resistant prostate cancer (mCRPC) following their first‐line treatment with abiraterone acetate and prednisone (AA‐P) to identify circulating RNAs that may correlate with progression‐free survival (PFS). In a prospective multicenter observational study, 53 patients with mCRPC were included after they started first‐line AA‐P treatment. Blood was drawn at baseline, 1, 3, and 6 months after treatment initiation. The levels of predefined circulating RNAs earlier identified as being upregulated in patients with mCRPC (e.g., microRNAs, long noncoding RNAs, and mRNAs), were analyzed. Uni‐ and multivariable Cox regression and Kaplan–Meier analyses were used to analyze the prognostic value of the various circulating RNAs for PFS along treatment. Detectable levels of kallikrein‐related peptidase 3 (KLK3) mRNA at baseline were demonstrated to be an independent prognostic marker for PFS (201 vs 501 days, P = 0.00054). Three months after AA‐P treatment initiation, KLK3 could not be detected in the blood of responding patients, but was still detectable in 56% of the patients with early progression. Our study confirmed that KLK3 mRNA detection in whole blood is an independent prognostic marker in mCRPC patients receiving AA‐P treatment. Furthermore, the levels of circulating KLK3 mRNA in patients receiving AA‐P treatment might reflect treatment response or early signs of progression.

Androgen receptor signalling confers clonogenic and migratory advantages in urothelial cell carcinoma of the bladder

Bladder urothelial cell carcinoma (UCC) incidence is about three times higher in men compared with women. There are several indications for the involvement of hormonal factors in the aetiology of UCC. Here, we provide evidence of androgen signalling in UCC progression. Microarray and qPCR analysis revealed that the androgen receptor (AR) mRNA level is upregulated in a subset of UCC cases. In an AR‐positive UCC‐derived cell line model, UM‐UC‐3‐AR, androgen treatment increased clonogenic capacity inducing the formation of big stem cell‐like holoclones, while AR knockdown or treatment with the AR antagonist enzalutamide abrogated this clonogenic advantage. Additionally, blockage of AR signalling reduced the cell migration potential of androgen‐stimulated UM‐UC‐3‐AR cells. These phenotypic changes were accompanied by a rewiring of the transcriptome with almost 300 genes being differentially regulated by androgens, some of which correlated with AR expression in UCC patients in two independent data sets. Our results demonstrate that AR signals in UCC favouring the development of an aggressive phenotype and highlights its potential as a therapeutic target for bladder cancer.