Can urinary PCA3 supplement PSA in the early detection of prostate cancer?

From microscopes to molecules: The evolution of prostate cancer diagnostics

In the ever-evolving landscape of oncology, the battle against prostate cancer (PCa) stands at a transformative juncture, propelled by the integration of molecular diagnostics into traditional cytopathological frameworks. This synthesis not only heralds a new epoch of precision medicine but also significantly enhances our understanding of the disease's genetic intricacies. Our comprehensive review navigates through the latest advancements in molecular biomarkers and their detection technologies, illuminating the potential these innovations hold for the clinical realm. With PCa persisting as one of the most common malignancies among men globally, the quest for early and precise diagnostic methods has never been more critical. The spotlight in this endeavor shines on the molecular diagnostics that reveal the genetic underpinnings of PCa, offering insights into its onset, progression, and resistance to conventional therapies. Among the genetic aberrations, the TMPRSS2-ERG fusion and mutations in genes such as phosphatase and tensin homolog (PTEN) and myelocytomatosis viral oncogene homolog (MYC) are identified as significant players in the disease's pathology, providing not only diagnostic markers but also potential therapeutic targets. This review underscores a multimodal diagnostic approach, merging molecular diagnostics with cytopathology, as a cornerstone in managing PCa effectively. This strategy promises a future where treatment is not only tailored to the individual's genetic makeup but also anticipates the disease's trajectory, offering hope for improved prognosis and quality of life for patients.

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.

Predicting prostate cancer progression with a Multi-lncRNA expression-based risk score and nomogram integrating ISUP grading

Prostate cancer is a highly heterogeneous disease; therefore, estimating patient prognosis accurately is challenging due to the lack of biomarkers with sufficient specificity and sensitivity. One of the current challenges lies in integrating genomic and transcriptomic data with clinico-pathological features and in incorporating their application in everyday clinical practice. Therefore, we aimed to model a risk score and nomogram containing long non-coding RNA (lncRNA) expression and clinico-pathological data to better predict the probability of prostate cancer progression. We performed bioinformatics analyses to identify lncRNAs differentially expressed across various prostate cancer stages and associated with progression-free survival. This information was further integrated into a prognostic risk score and nomogram containing transcriptomic and clinico-pathological features to estimate the risk of disease progression. We used RNA-seq data from 5 datasets from public repositories (total n = 178) comprising different stages of prostate cancer: pre-treatment primary prostate adenocarcinomas, post-treatment tumors and metastatic castration resistant prostate cancer. We found 30 lncRNAs with consistent differential expression in all comparisons made using two R-based packages. Multivariate progression-free survival analysis including the ISUP group as covariate, revealed that 7/30 lncRNAs were significantly associated with time-to-progression. Next, we combined the expression of these 7 lncRNAs into a multi-lncRNA score and dichotomized the patients into low- or high-score. Patients with a high-score showed a 4-fold risk of disease progression (HR = 4.30, 95 %CI = 2.66-6.97, p = 3.1e-9). Furthermore, we modelled a combined risk-score containing information on the multi-lncRNA score and ISUP group. We found that patients with a high-risk score had nearly 8-fold risk of progression (HR = 7.65, 95 %CI = 4.05-14.44, p = 3.4e-10). Finally, we created and validated a nomogram to help uro-oncologists to better predict patient's risk of progression at 3- and 5-years post-diagnosis. In conclusion, the integration of lncRNA expression data and clinico-pathological features of prostate tumors into predictive models might aid in tailored disease risk assessment and treatment for patients with prostate cancer.

Development and Validation of an 18-Gene Urine Test for High-Grade Prostate Cancer

Importance

Benefits of prostate cancer (PCa) screening with prostate-specific antigen (PSA) alone are largely offset by excess negative biopsies and overdetection of indolent cancers resulting from the poor specificity of PSA for high-grade PCa (ie, grade group [GG] 2 or greater).

Objective

To develop a multiplex urinary panel for high-grade PCa and validate its external performance relative to current guideline-endorsed biomarkers.

Design, Setting, and Participants

RNA sequencing analysis of 58 724 genes identified 54 markers of PCa, including 17 markers uniquely overexpressed by high-grade cancers. Gene expression and clinical factors were modeled in a new urinary test for high-grade PCa (MyProstateScore 2.0 [MPS2]). Optimal models were developed in parallel without prostate volume (MPS2) and with prostate volume (MPS2+). The locked models underwent blinded external validation in a prospective National Cancer Institute trial cohort. Data were collected from January 2008 to December 2020, and data were analyzed from November 2022 to November 2023.

Exposure

Protocolized blood and urine collection and transrectal ultrasound-guided systematic prostate biopsy.

Main Outcomes and Measures

Multiple biomarker tests were assessed in the validation cohort, including serum PSA alone, the Prostate Cancer Prevention Trial risk calculator, and the Prostate Health Index (PHI) as well as derived multiplex 2-gene and 3-gene models, the original 2-gene MPS test, and the 18-gene MPS2 models. Under a testing approach with 95% sensitivity for PCa of GG 2 or greater, measures of diagnostic accuracy and clinical consequences of testing were calculated. Cancers of GG 3 or greater were assessed secondarily.

Results

Of 761 men included in the development cohort, the median (IQR) age was 63 (58-68) years, and the median (IQR) PSA level was 5.6 (4.6-7.2) ng/mL; of 743 men included in the validation cohort, the median (IQR) age was 62 (57-68) years, and the median (IQR) PSA level was 5.6 (4.1-8.0) ng/mL. In the validation cohort, 151 (20.3%) had high-grade PCa on biopsy. Area under the receiver operating characteristic curve values were 0.60 using PSA alone, 0.66 using the risk calculator, 0.77 using PHI, 0.76 using the derived multiplex 2-gene model, 0.72 using the derived multiplex 3-gene model, and 0.74 using the original MPS model compared with 0.81 using the MPS2 model and 0.82 using the MPS2+ model. At 95% sensitivity, the MPS2 model would have reduced unnecessary biopsies performed in the initial biopsy population (range for other tests, 15% to 30%; range for MPS2, 35% to 42%) and repeat biopsy population (range for other tests, 9% to 21%; range for MPS2, 46% to 51%). Across pertinent subgroups, the MPS2 models had negative predictive values of 95% to 99% for cancers of GG 2 or greater and of 99% for cancers of GG 3 or greater.

Conclusions and Relevance

In this study, a new 18-gene PCa test had higher diagnostic accuracy for high-grade PCa relative to existing biomarker tests. Clinically, use of this test would have meaningfully reduced unnecessary biopsies performed while maintaining highly sensitive detection of high-grade cancers. These data support use of this new PCa biomarker test in patients with elevated PSA levels to reduce the potential harms of PCa screening while preserving its long-term benefits.

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 cancer: Novel genetic and immunologic biomarkers

Prostate cancer (PCa) is considered one of the most prevalent male malignancies worldwide with a global burden estimated to increase over the next two decades. Due to significant mortality and debilitation of survival, early diagnosis has been described as key. Unfortunately, current diagnostic serum-based strategies have low specificity and sensitivity. Histologic examination is invasive and not useful for treatment and monitoring purposes. Hence, a plethora of studies have been conducted to identify and validate an efficient noninvasive approach in the diagnosis, staging, and prognosis of PCa. These investigations may be categorized as genetic (non-coding biomarkers and gene markers), immunologic (immune cells, interleukins, cytokines, antibodies, and auto-antibodies), and heterogenous (PSA-related markers, PHI-related indices, and urinary biomarkers) subgroups. This review examines current approaches and potential strategies using biomarker panels in PCa.

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.

How to Integrate Prostate Cancer Biomarkers in Urology Clinical Practice: An Update

Nowadays, the management of prostate cancer has become more and more challenging due to the increasing number of available treatment options, therapeutic agents, and our understanding of its carcinogenesis and disease progression. Moreover, currently available risk stratification systems used to facilitate clinical decision-making have limitations, particularly in providing a personalized and patient-centered management strategy. Although prognosis and prostate cancer-specific survival have improved in recent years, the heterogenous behavior of the disease among patients included in the same risk prognostic group negatively impacts not only our clinical decision-making but also oncological outcomes, irrespective of the treatment strategy. Several biomarkers, along with available tests, have been developed to help clinicians in difficult decision-making scenarios and guide management strategies. In this review article, we focus on the scientific evidence that supports the clinical use of several biomarkers considered by professional urological societies (and included in uro-oncological guidelines) in the diagnosis process and specific difficult management strategies for clinically localized or advanced prostate cancer.

Advancements in Biomarkers of Prostate Cancer: A Review

Prostate cancer (PCa) is one of the most prevalent and deadly cancers among men, particularly affecting men of African descent and contributing significantly to cancer-related morbidity and mortality worldwide. The disease varies widely, from slow-developing forms to highly aggressive or potentially fatal variants. Accurate risk stratification is crucial for making therapeutic decisions and designing adequate clinical trials. This review assesses a broad spectrum of diagnostic and prognostic biomarkers, many of which are incorporated into clinical guidelines, including the Prostate Health Index (PHI), 4Kscore, STHLM3, PCA3, SelectMDx, ExoDx Prostate Intelliscore (EPI), and MiPS. It also highlights emerging biomarkers with preclinical support, such as urinary non-coding RNAs and DNA methylation patterns. Additionally, the review explores the role of tumor-associated microbiota in PCa, offering new insights into its potential contributions to disease understanding. By examining the latest advancements in PCa biomarkers, this review enhances understanding their roles in disease management.

Clinical Biofluid Assays for Prostate Cancer

This mini review summarizes the currently available clinical biofluid assays for PCa. The second most prevalent cancer worldwide is PCa. PCa is a heterogeneous disease, with a large percentage of prostate tumors being indolent, and with a relatively slow metastatic potential. However, due to the high case numbers, the absolute number of PCa-related deaths is still high. In fact, it causes the second highest number of cancer deaths in American men. As a first step for the diagnosis of PCa, the PSA test has been widely used. However, it has low specificity, which results in a high number of false positives leading to overdiagnosis and overtreatment. Newer derivatives of the original PSA test, including the Food and Drug Administration (FDA)-approved 4K (four kallikreins) and the PHI (Prostate Health Index) blood tests, have higher specificities. Tissue-based PCa tests are problematic as biopsies are invasive and have limited accuracy due to prostate tumor heterogeneity. Liquid biopsies offer a minimally or non-invasive choice for the patients, while providing a more representative reflection of the spatial heterogeneity in the prostate. In addition to the abovementioned blood-based tests, urine is a promising source of PCa biomarkers, offering a supplementary avenue for early detection and improved tumor classification. Four urine-based PCa tests are either FDA- or CLIA-approved: PCA3 (PROGENSA), ExoDX Prostate Intelliscore, MiPS, and SelectMDx. We will discuss these urine-based, as well as the blood-based, clinical PCa tests in more detail. We also briefly discuss a few promising biofluid marker candidates (DNA methylation, micro-RNAs) which are not in clinical application. As no single assay is perfect, we envision that a combination of biomarkers, together with imaging, will become the preferred practice.

Diagnostic value of total serum/free prostate specific antigen and prostate cancer antigen-3 levels in prostate cancer

BACKGROUND

The purpose of this study was to compare serum total and free prostate specific antigen (PSA) levels and serum prostate cancer antigen-3 (PCA3) levels in patients with prostate cancer in 2018 and 2019.

METHODS

This research was a prospective case-control study. The case group included all patients with suspected prostate cancer, and the control group included individuals without prostate disease who were referred to Ali Asghar and Nour Hospital in Isfahan, Iran, from October 2018 to October 2020. The serum total PSA, free PSA, and PCA3 levels in both groups were measured using the ELISA method with standard kits and compared between the groups.

RESULTS

The two groups were matched in terms of age and body mass index (BMI). The results showed that the mean free PSA level in the control group was significantly higher than that in the case group (P<0.05). Conversely, the mean total PSA level in the case group was significantly higher than that in the control group (P<0.05). However, no significant difference was observed in the mean PCA3 levels between the case and control groups. In addition, the total PSA variable with a cutoff of ≤3.14 exhibited 93% sensitivity and 82% specificity, demonstrating the highest diagnostic accuracy in distinguishing between prostate cancer and healthy individuals. Similarly, the PCA3 value with a cutoff of ≤3.5 had a sensitivity and specificity of 70% and 72%, respectively.

CONCLUSION

Overall, the study results indicated that total PSA and PCA3 levels have higher diagnostic accuracy in distinguishing patients with suspected prostate cancer from healthy individuals.

Knockdown of KIF15 suppresses proliferation of prostate cancer cells and induces apoptosis through PI3K/Akt signaling pathway

Prostate cancer is one of the most common malignancies in men, which has been considered a public health threat. KIF15 is a kind of driver protein, and its abnormal expression is closely related to the occurrence and development of malignant tumors. The purpose of the study was to explore the significance and role of KIF15 in prostate cancer and to show some potential value for prostate cancer. Immunohistochemistry analysis showed that KIF15 was highly expressed in prostate cancer tissues, which was also positively correlated with T Infiltrate. The loss-of-function and gain-of-function assays based on prostate cancer cells indicated that the change in KIF15 expression could significantly affect cell proliferation, tumorigenesis, migration, and cell apoptosis. The inhibition of prostate cancer development by KIF15 knockdown was also assured in vivo. The Human Apoptosis Antibody Array showed that CD40L, cytoC, DR6, and p21 were up-regulated upon KIF15 knockdown, while IGF-I and Survivin were down-regulated. Moreover, the involvement of the PI3K/Akt pathway in the KIF15-mediated regulation of prostate cancer was preliminarily proved. In summary, KIF15 was identified to play an important role in the development or biological progress of prostate cancer and is considered to possess the potential to be used as a therapeutic target.

MyProstateScore in men considering repeat biopsy: validation of a simple testing approach

BACKGROUND

Men with persistent risk of Grade Group (GG) ≥ 2 cancer after a negative biopsy present a unique clinical challenge. The validated MyProstateScore test is clinically-available for pre-biopsy risk stratification. In biopsy-naïve patients, we recently validated a straightforward testing approach to rule-out GG ≥ 2 cancer with 98% negative predictive value (NPV) and 97% sensitivity. In the current study, we established a practical MPS-based testing approach in men with a previous negative biopsy being considered for repeat biopsy.

METHODS

Patients provided post-digital rectal examination urine prior to repeat biopsy. MyProstateScore was calculated using the validated, locked model including urinary PCA3 and TMPRSS2:ERG scores with serum PSA. In a clinically-appropriate primary (i.e., training) cohort, we identified a lower (rule-out) threshold approximating 90% sensitivity and an upper (rule-in) threshold approximating 80% specificity for GG ≥ 2 cancer. These thresholds were applied to an external validation cohort, and performance measures and clinical outcomes associated with their use were calculated.

RESULTS

MyProstateScore thresholds of 15 and 40 met pre-defined performance criteria in the primary cohort (422 patients; median PSA 6.4, IQR 4.3-9.1). In the 268-patient validation cohort, 25 men (9.3%) had GG ≥ 2 cancer on repeat biopsy. The rule-out threshold of 15 provided 100% NPV and sensitivity for GG ≥ 2 cancer and would have prevented 23% of unnecessary biopsies. Use of MyProstateScore >40 to rule-in biopsy would have prevented 67% of biopsies while maintaining 95% NPV. In the validation cohort, the prevalence of GG ≥ 2 cancer was 0% for MyProstateScore 0-15, 6.5% for MyProstateScore 15-40, and 19% for MyProstateScore >40.

CONCLUSIONS

In patients who previously underwent a negative prostate biopsy, the MyProstateScore values of 15 and 40 yielded clinically-actionable rule-in and rule-out risk groups. Using this straightforward testing approach, MyProstateScore can meaningfully inform patients and physicians weighing the need for repeat biopsy.

Early Detection of Prostate Cancer: AUA/SUO Guideline Part II: Considerations for a Prostate Biopsy

PURPOSE

The summary presented herein covers recommendations on the early detection of prostate cancer and provides a framework to facilitate clinical decision-making in the implementation of prostate cancer screening, biopsy, and follow-up. This is Part II of a two-part series focusing on initial and repeat biopsies, and biopsy technique. Please refer to Part I for discussion of initial prostate cancer screening recommendations.

MATERIALS AND METHODS

The systematic review utilized to inform this guideline was conducted by an independent methodological consultant. The systematic review was based on searches in Ovid MEDLINE and Embase and Cochrane Database of Systematic Reviews (January 1, 2000-November 21, 2022). Searches were supplemented by reviewing reference lists of relevant articles.

RESULTS

The Early Detection of Prostate Cancer Panel developed evidence- and consensus-based guideline statements to provide guidance in prostate cancer screening, initial and repeat biopsies, and biopsy technique.

CONCLUSIONS

The evaluation of prostate cancer risk should be focused on the detection of clinically significant prostate cancer (Grade Group 2 or higher [GG2+]). The use of laboratory biomarkers, prostate MRI, and biopsy techniques described herein may improve detection and safety when a prostate biopsy is deemed necessary following prostate cancer screening.

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.

Clinical performance of magnetic resonance imaging and biomarkers for prostate cancer diagnosis in men at high genetic risk

OBJECTIVES

To evaluate different scenarios for the management of early diagnosis of cancer (PCa) in men at high genetic risk, using recently developed blood and urinary molecular biomarkers in combination with clinical information alongside multiparametric magnetic resonance imaging (mpMRI).

PATIENTS AND METHODS

A total of 322 patients with a high genetic risk (familial or personal history of cancers or a predisposing germline variant) were included in this study. The primary outcome was the detection rates of PCa (positive biopsy) or clinically significant PCa (biopsy with International Society of Urological Pathology [ISUP] grade >1). Clinical parameters included age, body mass index, ancestry, and germline mutational status, mpMRI, prostate-specific antigen density (PSAD), Prostate Health Index and urinary markers (Prostate Cancer Associated 3, SelectMdx™ and T2:ERG score) were assessed. Sensitivity (Se) and specificity (Sp) for each marker at their recommended cut-off for clinical practice were calculated. Comparison between diagnoses accuracy of each procedure and scenario was computed using mutual information based and direct effect contribution using a supervised Bayesian network approach.

RESULTS

A mpMRI Prostate Imaging-Reporting and Data System (PI-RADS) score ≥3 showed higher Se than mpMRI PI-RADS score ≥4 for detection of PCa (82% vs 61%) and for the detection of ISUP grade >1 lesions (96% vs 80%). mpMRI PI-RADS score ≥3 performed better than a PSA level of ≥3 ng/mL (Se 96%, Sp 53% vs Se 91%, Sp 8%) for detection of clinically significant PCa. In case of negative mpMRI results, the supervised Bayesian network approach showed that urinary markers (with the same accuracy for all) and PSAD of ≥0.10 ng/mL/mL were the most useful indicators of decision to biopsy.

CONCLUSIONS

We found that screening men at high genetic risk of PCa must be based on mpMRI without pre-screening based on a PSA level of >3 ng/mL, to avoid missing too many ISUP grade >1 tumours and to significantly reduce the number of unnecessary biopsies. However, urinary markers or a PSAD of ≥0.10 ng/mL/mL when mpMRI was negative increased the detection of ISUP grade >1 cancers. We suggest that a baseline mpMRI be discussed for men at high genetic risk from the age of 40 years.

PCA3 and TMPRSS2: ERG Urine Level as Diagnostic Biomarker of Prostate Cancer

Background

Prostate cancer is a highly prevalent urological carcinoma with an increasing incidence in Indonesia and all around the world. Early diagnosis can greatly affect treatment outcomes and increase life expectancy. Several biomarkers for detecting prostate cancer have been studied and showed great promise.

Purpose

This study aims to analyze prostate cancer antigen 3 (PCA3) as well as transmembrane serine protease 2:ERG (TMPRSS2:ERG) for diagnosing and serving as urine biomarkers in predicting prostate cancer incidences.

Methods

We conducted an analytical study to assess the utility of PCA3 and TMPRSS2:ERG for detecting prostate cancer. Thirty samples were included in this study to see the utilization of PCA3 and TMPRSS2:ERG as diagnostic biomarkers of prostate cancer. A urine sample was taken and the PCA3 test was performed using the PCA3 PROGENSA test, while the TMPRSS2:ERG was performed using the chemiluminescent DNA probe method with a hybridization protection test.

Results

The average age of the subject was 61.07±8.3 years. Based on calculations using the Mann-Whitney test, there was a significant relationship between prostate-Specific Antigen (PSA) overexpression (p<0.001), TMPRSS2:ERG (p=0.001), and PCA3 (p=0.003) with prostate cancer incidence. The sensitivity of PCA3 and TMPRSS2:ERG in detecting prostate cancer was 76.9% and 92.3%, respectively. Hence, TMPRSS2:ERG and PCA3 can be used as biomarkers for the occurrence of prostate cancer. We also performed a Kruskal-Wallis test; however, there was no significant relationship between PSA (p=0.236), TMPRSS2:ERG (p=0.801), and PCA3 (p=0.091) with the Gleason score.

Conclusion

There is a significant correlation between overexpression of PSA, TMPRSS2:ERG and PCA3 with the incidence of prostate cancer, and TMPRSS2:ERG and PCA3 can be used as biomarkers of prostate cancer.

The performance and limitations of PCA3, TMPRSS2:ERG, HOXC6 and DLX1 urinary markers combined in the improvement of prostate cancer diagnostics

BACKGROUND

Prostate cancer (PCa) is the second most commonly diagnosed cancer in men. To date, the role of the combined application of long non-coding RNAs (PCA3, DLX1, HOXC6, TMPRSS2:ERG) for obtaining the most accurate method of detection of PCa has not yet been comprehensively investigated.

METHODS

In total 240 persons were included in the retrospective study. Among them were 150 patients with confirmed PCa, 30 patients with benign prostatic hyperplasia, 30 patients with active chronic prostatitis and 30 healthy volunteers. In all patients, the urine samples were collected prior to biopsy or treatment. Polymerase chain reaction with reverse transcription was performed to detect the expression level of PCA3, HOXC6, DLX1 and the presence of the TMPRSS2:ERG transcript.

RESULTS

PCA3 was detected in urine samples in all cases. Using a PCA3 score of 56 allowed the differentiation between PCa and all other cases with a sensitivity of 61% and specificity of 96% (p<0.001) while a PCA3 score threshold value of 50 resulted in a differentiation between clinically significant PCa (ISUP grades 2-5) and all other cases with a sensitivity of 93% and specificity of 93% (p<0.001). The TMPRSS2:ERG expression in urine was detected exclusively in the group of patients with PCa and only in 16% of all cases.

CONCLUSIONS

PCA3 score detected in urine demonstrated moderate sensitivity and good specificity in differentiation between PCa and non-PCa and high sensitivity and specificity in differentiation between clinically significant PCa and non-PCa.

Urinary exosomal prostate-specific antigen is a noninvasive biomarker to detect prostate cancer: Not only old wine in new bottles

The study aimed at evaluating the performance of urinary exosomal prostate-specific antigen (UE-PSA) to predict the results of initial prostate biopsies and discriminate clinically significant prostate cancer (Gleason score ≥ 7, csPCa) from nonsignificant PCa (Gleason score < 7, nsPCa) plus benign patients. Two hundred seventy-two consecutive participants were admitted who underwent a prostate biopsy. The UE-PSA expression was detected by enzyme-linked immunosorbent assay (ELISA). The predictive power and clinical value of UE-PSA was assessed by receiver operating characteristic (ROC), decision curve analysis (DCA) and waterfall plots. UE-PSA was upregulated in PCa compared to benign patients (P < .001) and csPCa compared to nsPCa plus benign patients (P < .001). UE-PSA achieved an AUC of 0.953 (0.905-0.989) in distinguishing PCa from benign patients and an AUC of 0.879 (0.808-0.941) in predicting csPCa from nsPCa plus benign patients. These results were validated in an additional multicenter cohort. In addition, DCA showed that UE-PSA achieved the highest net benefit at almost any threshold probability compared to tPSA and %fPSA. As the waterfall plot showed, the UE-PSA assay could avoid 57.6% (155 cases) and 34.6% (93 cases) unnecessary biopsies while only missing 2.6% (7 cases) and 1.5% (4 cases) of the cases of csPCa at the cutoff value of 90% and 95% sensitivity, respectively. We validated that UE-PSA presented great diagnostic power and clinical utility to diagnose PCa and csPCa. UE-PSA could be a promising noninvasive biomarker to improve PCa detection.

Identification of m6A/m5C/m1A-associated LncRNAs for prognostic assessment and immunotherapy in pancreatic cancer

Methylation of RNA plays an important role in cancer. Classical forms of such modifications include N6-methyladenine (m6A), 5-methylcytosine (m5C), and N1-methyladenine (m1A). Methylation-regulated long non-coding (lnc) RNAs are involved in various biological processes, such as tumor proliferation, apoptosis, immune escape, invasion, and metastasis. Therefore, we performed an analysis of transcriptomic and clinical data of pancreatic cancer samples in The Cancer Genome Atlas (TCGA). Using the co-expression method, we summarized 44 m6A/m5C/m1A-related genes and obtained 218 methylation-associated lncRNAs. Next, with COX regression, we screened 39 lncRNAs that are strongly associated with prognosis and found that their expression differed significantly between normal tissues and pancreatic cancer samples (P < 0.001). We then used the least absolute shrinkage and selection operator (LASSO) to construct a risk model comprising seven lncRNAs. In validation set, the nomogram generated by combining clinical characteristics accurately predicted the survival probability of pancreatic cancer patients at 1, 2, and 3 years after diagnosis (AUC = 0.652, 0.686, and 0.740, respectively). Tumor microenvironment analysis showed that the high-risk group had significantly more resting memory CD4 T cells, M0 macrophages, and activated dendritic cells and fewer naïve B cells, plasma cells, and CD8 T cells than the low-risk group (both P < 0.05). Most immune-checkpoint genes were significantly different between the high- and low-risk groups (P < 0.05). The Tumor Immune Dysfunction and Exclusion score showed that high-risk patients benefited more from treatment with immune checkpoint inhibitors (P < 0.001). Overall survival was also lower in high-risk patients with more tumor mutations than in low-risk patients with fewer mutations (P < 0.001). Finally, we explored the sensitivity of the high- and low-risk groups to seven candidate drugs. Our findings indicated that m6A/m5C/m1A-associated lncRNAs are potentially useful biomarkers for the early diagnosis and estimating the prognosis of, and ascertaining the responses to immunotherapy in, patients with pancreatic cancer.

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.

Hsa_circ_0001944 enhanced GSPT1 expression via sponging miR-498 to promote proliferation and invasion of gastric cancer

BACKGROUND

Gastric cancer (GC) is the fifth most common malignant tumor and the third leading cause of cancer-related deaths worldwide. CircRNAs may provide new insights into the development of GC by acting as oncogenes or tumor suppressors. In this study, we aim to examine the biological role of hsa_circ_0001944 (circFIRRE) in tumor progression of GC.

METHODS

The bioinformatic analysis, qPCR, Western blotting, and immunohistochemistry were fulfilled to detect the expression of hsa_circ_0001944, miR-498, and GSPT1 in gastric cancer. Gain or loss of function approaches were used to investigate the biological functions of hsa_circ_0001944. MTS, EDU, wound healing, and transwell assays were performed to study the proliferation, invasion, and migration of GC cells. These molecular mechanisms were detected by luciferase reporter assays and chromatin immunoprecipitation assays.

RESULTS

We screened out hsa_circ_0001944, whose expression was significantly increased in gastric cancer tissues. Knockdown of hsa_circ_0001944 significantly suppressed the cell proliferation, invasion, and migration. Mechanistic investigations showed that hsa_circ_0001944 can bind to and sponge miR-498. Moreover, hsa_circ_0001944 sponged miR-498 to increase GSPT1 expression, thereby promoted excessive proliferation and maintained the malignant phenotype of GC cells.

CONCLUSION

The present study demonstrates the hsa_circ_0001944/miR-498/GSPT1 axis contributes to GC development. This may provide a target for GC therapy and potential prognostic biomarker.

Ultrasound-based radiomics score for pre-biopsy prediction of prostate cancer to reduce unnecessary biopsies

BACKGROUND

Patients undergoing prostate biopsies (PBs) suffer from low positive rates and potential risk for complications. This study aimed to develop and validate an ultrasound (US)-based radiomics score for pre-biopsy prediction of prostate cancer (PCa) and subsequently reduce unnecessary PBs.

METHODS

Between December 2015 and March 2018, 196 patients undergoing initial transrectal ultrasound (TRUS)-guided PBs were retrospectively enrolled and randomly assigned to the training or validation cohort at a ratio of 7:3. A total of 1044 radiomics features were extracted from grayscale US images of each prostate nodule. After feature selection through the least absolute shrinkage and selection operator (LASSO) regression model, the radiomics score was developed from the training cohort. The prediction nomograms were developed using multivariate logistic regression analysis based on the radiomics score and clinical risk factors. The performance of the nomograms was assessed and compared in terms of discrimination, calibration, and clinical usefulness.

RESULTS

The radiomics score consisted of five selected features. Multivariate logistic regression analysis demonstrated that the radiomics score, age, total prostate-specific antigen (tPSA), and prostate volume were independent factors for prediction of PCa (all p < 0.05). The integrated nomogram incorporating the radiomics score and three clinical risk factors reached an area under the curve (AUC) of 0.835 (95% confidence interval [CI], 0.729-0.941), thereby outperforming the clinical nomogram which based on only clinical factors and yielded an AUC of 0.752 (95% CI, 0.618-0.886) (p = 0.04). Both nomograms showed good calibration. Decision curve analysis indicated that using the integrated nomogram would add more benefit than using the clinical nomogram.

CONCLUSION

The radiomics score was an independent factor for pre-biopsy prediction of PCa. Addition of the radiomics score to the clinical nomogram shows incremental prognostic value and may help clinicians make precise decisions to reduce unnecessary PBs.

Molecular Biomarkers for the Detection of Clinically Significant Prostate Cancer: A Systematic Review and Meta-analysis

Context

Prostate cancer (PCa) is the second most common type of cancer in men. Individualized risk stratification is crucial to adjust decision-making. A variety of molecular biomarkers have been developed in order to identify patients at risk of clinically significant PCa (csPCa) defined by the most common PCa risk stratification systems.

Objective

The present study aims to examine the effectiveness (diagnostic accuracy) of blood or urine-based PCa biomarkers to identify patients at high risk of csPCa.

Evidence acquisition

A systematic review of the literature was conducted. Medline and EMBASE were searched from inception to March 2021. Randomized or nonrandomized clinical trials, and cohort and case-control studies were eligible for inclusion. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Pooled estimates of sensitivity, specificity, and area under the curve were obtained.

Evidence synthesis

Sixty-five studies (N = 34 287) were included. Not all studies included prostate-specific antigen-selected patients. The pooled data showed that the Prostate Health Index (PHI), with any cutoff point between 15 and 30, had sensitivity of 0.95-1.00 and specificity of 0.14-0.33 for csPCa detection. The pooled estimates for SelectMDx test sensitivity and specificity were 0.84 and 0.49, respectively.

Conclusions

The PHI test has a high diagnostic accuracy rate for csPCa detection, and its incorporation in the diagnostic process could reduce unnecessary biopsies. However, there is a lack of evidence on patient-important outcomes and thus more research is needed.

Patient summary

It has been possible to verify that the application of biomarkers could help detect prostate cancer (PCa) patients with a higher risk of poorer evolution. The Prostate Health Index shows an ability to identify 95-100 for every 100 patients suffering from clinically significant PCa who take the test, preventing unnecessary biopsies in 14-33% of men without PCa or insignificant PCa.

Biomarkers in Urological Cancers

Urological tumours have become one of the most common cancers in the last decade. It is important to apply an approach that evaluates many factors related to the patient and the disease carefully to minimize cancer-associated morbidity and mortality. The clinical use of cancer biomarkers is a valuable part of the clinical management of urological cancers. These biomarkers may lead to optimized detection, treatment, and follow-up of urological cancers. With the development of molecular research, newly developed biomarkers and next-generation sequencing have also contributed to patient management. In this chapter, we will present biomarkers in the most common urological cancers under subheadings of bladder cancer, prostate cancer, kidney cancer, and testicular cancer. Additionally, due to the development that occurred in the next-generation sequencing (NGS), all the above-mentioned malignancies are evaluated with regard to NGS.

Detection of Prostate Cancer Biomarker PCA3 by using Aptasensors

BACKGROUND

Prostate cancer cells have very high PCA3 messenger RNA levels, which turns it into one of the new biomarkers for prostate cancer prognosis and diagnosis.

OBJECTIVE

Our goal here is to development a new aptasensor to detect PCA3 release by cancer cell.

METHODS

DNA hairpin containing PCA3 aptamer was thiolated, conjugated to methylene blue (MB) redox probe and immobilized on gold electrode through self-assembly to detect label-free cancer cells.

RESULTS

Our data have evidenced stable and sensitive sensor presenting wide linear detection range (0-150 ng/mL). In addition, monitoring PCA3 released by a different type of prostate cells can provide in-depth knowledge about prostate cancer dynamics; therefore, it is a powerful platform for earlier clinical diagnostic. The released PCA3 can vary depending on the type of adopted prostate cells.

CONCLUSION

PCA3 release was monitored in a group of cells for 2 h; it showed significantly higher expression in both LNCaP and PC-3 cells. This strategy provides unique and simple methodology to achieve more sensitive and specific PCA3 detection; thus, it emerged as promising tool for early cost-effective diagnosis.

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.

Drift compensation on electronic nose data for non-invasive diagnosis of prostate cancer by urine analysis

Diagnostic protocol for prostate cancer (KP) is affected by poor accuracy and high false-positive rate. The most promising innovative approach is based on urine analysis by electronic noses (ENs), highlighting a specific correlation between urine alteration and KP presence. Although EN could be exploited to develop non-invasive KP diagnostic tools, no study has already introduced EN into clinical practice, most probably because of drift issues that hinder EN scaling up from research objects to large-scale diagnostic devices. This study, proposing an EN for non-invasive KP detection, describes the data processing protocol applied to a urine headspace dataset acquired over 9 months, comprising 81 patients with KP and 41 controls, for compensating the drift. It proved effective in mitigating drift on 1-year-old sensors by restoring accuracy from 55% up to 80%, achieved by new sensors not subjected to drift. The model achieved, on double-blind validation, a balanced accuracy of 76.2% (CI_95% 51.9–92.3).

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Urine odor alteration due to prostate cancer can be detected by electronic noses

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Sensors drift hinders electronic nose scaling up to large-scale diagnostic devices

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OSC mitigates drift on 1-year-old sensors, restoring accuracy from 55% up to 80%

Role of Precision Oncology in Type II Endometrial and Prostate Cancers in the African Population: Global Cancer Genomics Disparities

Precision oncology can be defined as molecular profiling of tumors to identify targetable alterations. Emerging research reports the high mortality rates associated with type II endometrial cancer in black women and with prostate cancer in men of African ancestry. The lack of adequate genetic reference information from the African genome is one of the major obstacles in exploring the benefits of precision oncology in the African context. Whilst external factors such as the geography, environment, health-care access and socio-economic status may contribute greatly towards the disparities observed in type II endometrial and prostate cancers in black populations compared to Caucasians, the contribution of African ancestry to the contribution of genetics to the etiology of these cancers cannot be ignored. Non-coding RNAs (ncRNAs) continue to emerge as important regulators of gene expression and the key molecular pathways involved in tumorigenesis. Particular attention is focused on activated/repressed genes and associated pathways, while the redundant pathways (pathways that have the same outcome or activate the same downstream effectors) are often ignored. However, comprehensive evidence to understand the relationship between type II endometrial cancer, prostate cancer and African ancestry remains poorly understood. The sub-Saharan African (SSA) region has both the highest incidence and mortality of both type II endometrial and prostate cancers. Understanding how the entire transcriptomic landscape of these two reproductive cancers is regulated by ncRNAs in an African cohort may help elucidate the relationship between race and pathological disparities of these two diseases. This review focuses on global disparities in medicine, PCa and ECa. The role of precision oncology in PCa and ECa in the African population will also be discussed.

Natural Products as the Modulators of Oxidative Stress: An Herbal Approach in the Management of Prostate Cancer

Prostate cancer is the most commonly diagnosed and frequently occurred cancer in the males globally. The current treatment strategies available to treat prostate cancer are not much effective and express various adverse effects. Hence, there is an urgent need to identify novel treatment that can improve patient outcome. From times immemorial, natural products are highly recognized for novel drug development for various diseases including cancer. Cancer cells generally maintain higher basal levels of reactive oxygen species (ROS) when compared to normal cells due to its high metabolic rate. However, initiation of excess intracellular ROS production can not be tolerated by the cancer cells and induce several cell death signals which are in contrast to normal cells. Therefore, small molecules of natural origin that induce ROS can potentially kill cancer cells in specific and provide a better opportunity to develop a novel drug therapy. In this review, we elaborated various classes of medicinal compounds and their mechanism of killing prostate cancer cells through direct or indirect ROS generation. This can generate a novel thought to develop promising drug candidate to treat prostate cancer patients.

Biomarkers for prostate cancer detection and risk stratification

Although prostate cancer (PCa) is the most commonly diagnosed cancer in men, most patients do not die from the disease. Prostate specific antigen (PSA), the most widely used oncologic biomarker, has revolutionized screening and early detection, resulting in reduced proportion of patients presenting with advanced disease. However, given the inherent limitations of PSA, additional diagnostic and prognostic tools are needed to facilitate early detection and accurate risk stratification of disease. Serum, urine, and tissue-based biomarkers are increasingly being incorporated into the clinical care paradigm, but there is still a limited understanding of how to use them most effectively. In the current article, we review test characteristics and clinical performance data for both serum [4 K score, prostate health index (phi)] and urine [SelectMDx, ExoDx Prostate Intelliscore, MyProstateScore (MPS), and PCa antigen 3 (PCA3)] biomarkers to aid decisions regarding initial or repeat biopsies as well as tissue-based biomarkers (Confirm MDx, Decipher, Oncotype Dx, and Polaris) aimed at risk stratifying patients and identifying those patients most likely to benefit from treatment versus surveillance or monotherapy versus multi-modal therapy.

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.

Association of MyProstateScore (MPS) with prostate cancer grade in the radical prostatectomy specimen

BACKGROUND

To evaluate the association between urinary MyProstateScore (MPS) and pathologic grade group (GG) at surgery in men diagnosed with GG1 prostate cancer (PCa) on biopsy.

METHODS

Using an institutional biospecimen protocol, we identified men with GG1 PCa on biopsy and PSA ≤10 ng/ml who underwent radical prostatectomy (RP) at the University of Michigan. MPS was retrospectively calculated using prospectively collected, post-DRE urine samples. The primary outcome was upgrading on RP pathology, defined as GG ≥ 2. The associations of MPS, PSA, and PSA density (PSAD) with upgrading were assessed on univariable logistic regression, and the predictive accuracy of each marker was estimated by the area under the receiver operating characteristic curve (AUC).

RESULTS

There were 52 men with urinary specimens available that met study criteria, based on biopsy Gleason Grade and specimen collection. At RP, 17 men (33%) had GG1 cancer and 35 (67%) had GG ≥ 2 cancer. Preoperative MPS was significantly higher in patients with GG ≥ 2 cancer at surgery (median 37.8 [IQR, 22.2-52.4]) as compared to GG1 (19.3 [IQR, 9.2-29.4]; P = 0.001). On univariable logistic regression, increasing MPS values were significantly associated with upgrading (odds ratio 1.07 per one-unit MPS increase, 95% confidence interval 1.02-1.12, P = 0.004), while PSA and PSAD were not significantly associated with upgrading. Similarly, the discriminative ability of the MPS model (AUC 0.78) for upgrading at RP was higher compared to models based on PSA (AUC 0.52) and PSAD (AUC 0.62).

CONCLUSIONS

In men diagnosed with GG1 PCa who underwent surgery, MPS was significantly associated with RP cancer grade. In this limited cohort of men, these findings suggest that MPS could help identify patients with undetected high-grade cancer. Additional studies are needed to better characterize this association.

Optimization of training and measurement protocol for eNose analysis of urine headspace aimed at prostate cancer diagnosis

More than one million new cases of prostate cancer (PCa) were reported worldwide in 2020, and a significant increase of PCa incidence up to 2040 is estimated. Despite potential treatability in early stages, PCa diagnosis is challenging because of late symptoms' onset and limits of current screening procedures. It has been now accepted that cell transformation leads to release of volatile organic compounds in biologic fluids, including urine. Thus, several studies proposed the possibility to develop new diagnostic tools based on urine analysis. Among these, electronic noses (eNoses) represent one of the most promising devices, because of their potential to provide a non-invasive diagnosis. Here we describe the approach aimed at defining the experimental protocol for eNose application for PCa diagnosis. Our research investigates effects of sample preparation and analysis on eNose responses and repeatability. The dependence of eNose diagnostic performance on urine portion analysed, techniques involved for extracting urine volatiles and conditioning temperature were analysed. 192 subjects (132 PCa patients and 60 controls) were involved. The developed experimental protocol has resulted in accuracy, sensitivity and specificity of 83% (CI_95% 77-89), 82% (CI_95% 73-88) and 87% (CI_95% 75-94), respectively. Our findings define eNoses as valuable diagnostic tool allowing rapid and non-invasive PCa diagnosis.

Modified Predictive Model and Nomogram by Incorporating Prebiopsy Biparametric Magnetic Resonance Imaging With Clinical Indicators for Prostate Biopsy Decision Making

Purpose

The purpose of this study is to explore the value of combining bpMRI and clinical indicators in the diagnosis of clinically significant prostate cancer (csPCa), and developing a prediction model and Nomogram to guide clinical decision-making.

Methods

We retrospectively analyzed 530 patients who underwent prostate biopsy due to elevated serum prostate specific antigen (PSA) levels and/or suspicious digital rectal examination (DRE). Enrolled patients were randomly assigned to the training group (n = 371, 70%) and validation group (n = 159, 30%). All patients underwent prostate bpMRI examination, and T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) sequences were collected before biopsy and were scored, which were respectively named T2WI score and DWI score according to Prostate Imaging Reporting and Data System version 2 (PI-RADS v.2) scoring protocol, and then PI-RADS scoring was performed. We defined a new bpMRI-based parameter named Total score (Total score = T2WI score + DWI score). PI-RADS score and Total score were separately included in the multivariate analysis of the training group to determine independent predictors for csPCa and establish prediction models. Then, prediction models and clinical indicators were compared by analyzing the area under the curve (AUC) and decision curves. A Nomogram for predicting csPCa was established using data from the training group.

Results

In the training group, 160 (43.1%) patients had prostate cancer (PCa), including 128 (34.5%) with csPCa. Multivariate regression analysis showed that the PI-RADS score, Total score, f/tPSA, and PSA density (PSAD) were independent predictors of csPCa. The prediction model that was defined by Total score, f/tPSA, and PSAD had the highest discriminatory power of csPCa (AUC = 0.931), and the diagnostic sensitivity and specificity were 85.1% and 87.5%, respectively. Decision curve analysis (DCA) showed that the prediction model achieved an optimal overall net benefit in both the training group and the validation group. In addition, the Nomogram predicted csPCa revealed good estimation when compared with clinical indicators.

Conclusion

The prediction model and Nomogram based on bpMRI and clinical indicators exhibit a satisfactory predictive value and improved risk stratification for csPCa, which could be used for clinical biopsy decision-making.

Angiogenesis and Anti-Angiogenic Treatment in Prostate Cancer: Mechanisms of Action and Molecular Targets

Prostate cancer (PC) is the most common cancer in men and the second leading cause of cancer-related death worldwide. Many therapeutic advances over the last two decades have led to an improvement in the survival of patients with metastatic PC, yet the majority of these patients still succumb to their disease. Antiagiogenic therapies have shown substantial benefits for many types of cancer but only a marginal benefit for PC. Ongoing clinical trials investigate antiangiogenic monotherapies or combination therapies. Despite the important role of angiogenesis in PC, clinical trials in refractory castration-resistant PC (CRPC) have demonstrated increased toxicity with no clinical benefit. A better understanding of the mechanism of angiogenesis may help to understand the failure of trials, possibly leading to the development of new targeted anti-angiogenic therapies in PC. These could include the identification of specific subsets of patients who might benefit from these therapeutic strategies. This paper provides a comprehensive review of the pathways involved in the angiogenesis, the chemotherapeutic agents with antiangiogenic activity, the available studies on anti-angiogenic agents and the potential mechanisms of resistance.

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.

LncRNA expression and SDHB mutations in pheochromocytomas and paragangliomas

Although pheochromocytomas and paragangliomas (PPGLs) are usual low-grade neoplasms, the metastatic forms of these lesions are associated with high morbidity and mortality. Recent studies have discovered multiple aberrantly expressed long non-coding RNAs (lncRNAs) in cancers that may have regulatory roles in tumor pathogenesis and metastasis; however, the roles of some lncRNAs in PPGLs are still unknown. The expression levels of lncRNAs including metastasis-associated lung adenocarcinoma transcript (MALAT1), prostate cancer antigen 3 (PCA3), and HOX transcript antisense intergenic RNA (HOTAIR) in PPGLs were analyzed by in situ hybridization, using two tissue microarrays (TMAs). The pheochromocytoma (PCC) TMA consisted of normal adrenal medulla (N = 25), non-metastatic PCCs (N = 76) and metastatic PCCs (N = 5) while the paraganglioma (PGL) TMA had 73 non-metastatic PGLs and 5 metastatic PGLs. Immunohistochemical staining was performed on all samples with an anti-SDHB antibody. The correlations between lncRNA expression, loss of SDHB expression and clinical characteristics including tumor progression and disease prognosis were investigated. The expression levels of MALAT1 and PCA3 were significantly elevated (2.5-3.9 folds) in both non-metastatic and metastatic PCCs compared to normal adrenal medulla, although there were no significant differences between the non-metastatic and metastatic neoplasms. In contrast to non-metastatic PGLs, metastatic PGLs had significantly upregulated expression of MALAT1, PCA3, and HOTAIR. SDHB loss was more frequently observed in PGLs (25 of 78), especially in metastatic PGLs (5 of 5), compared to PCCs (2 of 81) and in 0 of 5 metastatic PCCs. Patients with SDHB loss, in contrast to SDHB retained, were younger at diagnosis, had higher rates of tumor recurrence, metastatic disease, and mortality. In addition, PGLs with SDHB loss had significantly increased expression of PCA3 compared to tumors with intact SDHB expression. Our findings suggest that specific lncRNAs may be involved in the SDHx signaling pathways in the tumorigenesis and in the development of PPGL.

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.

The Role of Non-Coding RNAs in the Regulation of the Proto-Oncogene MYC in Different Types of Cancer

Alterations in the expression level of the MYC gene are often found in the cells of various malignant tumors. Overexpressed MYC has been shown to stimulate the main processes of oncogenesis: uncontrolled growth, unlimited cell divisions, avoidance of apoptosis and immune response, changes in cellular metabolism, genomic instability, metastasis, and angiogenesis. Thus, controlling the expression of MYC is considered as an approach for targeted cancer treatment. Since c-Myc is also a crucial regulator of many cellular processes in healthy cells, it is necessary to find ways for selective regulation of MYC expression in tumor cells. Many recent studies have demonstrated that non-coding RNAs play an important role in the regulation of the transcription and translation of this gene and some RNAs directly interact with the c-Myc protein, affecting its stability. In this review, we summarize current data on the regulation of MYC by various non-coding RNAs that can potentially be targeted in specific tumor types.

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 Liquid Biopsy Biomarkers' Clinical Utility in Diagnosis and Prognosis

Prostate cancer (PCa) is the most common cancer in men worldwide. The current gold standard for diagnosing PCa relies on a transrectal ultrasound-guided systematic core needle biopsy indicated after detection changes in a digital rectal examination (DRE) and elevated prostate-specific antigen (PSA) level in the blood serum. PSA is a marker produced by prostate cells, not just cancer cells. Therefore, an elevated PSA level may be associated with other symptoms such as benign prostatic hyperplasia or inflammation of the prostate gland. Due to this marker's low specificity, a common problem is overdiagnosis, which leads to unnecessary biopsies and overtreatment. This is associated with various treatment complications (such as bleeding or infection) and generates unnecessary costs. Therefore, there is no doubt that the improvement of the current procedure by applying effective, sensitive and specific markers is an urgent need. Several non-invasive, cost-effective, high-accuracy liquid biopsy diagnostic biomarkers such as Progensa PCA3, MyProstateScore ExoDx, SelectMDx, PHI, 4K, Stockholm3 and ConfirmMDx have been developed in recent years. This article compares current knowledge about them and their potential application in clinical practice.

Potential clinical use of miRNA molecules in the diagnosis of prostate cancer

Prostate cancer (PCa) is the most common type of cancer among men in Europe and this applies to almost the whole world. Current recommendations for screening and diagnosis are based on prostate specific antigen (PSA) measurements and the digital rectal examination (DRE). Both of them trigger the prostate biopsy. Limited specificity of the PSA test brings, however, a need to develop new and better diagnostic tools. In the last few years, new approaches for providing significantly better biomarkers, an alternative to PSA, have been introduced. Modern biomarkers show improvement not only as a diagnostic procedure, but also for staging, evaluating aggressiveness and managing the therapeutic process. The most promising group are molecular markers; among them microRNAs (miRNAs, miRs) are most frequent. miRNAs represent a class of about 22 nucleotides long, small non-coding RNAs, which are involved in gene expression regulation at the post-transcriptional level. This article reports a revision about the role of miRNAs in PCa including data of Adreno Receptor (AR) signaling, cell cycle, epithelial mesenchymal transition (EMT) process, cancer stem cells (CSCs) regulation and even the role of miRNAs as PCa therapeutic tool. Finding better PCa biomarkers, replacing the current PSA measurement, is firmly needed in modern oncology practice.

Long non-coding RNAs correlate with genomic stability in prostate cancer: A clinical outcome and survival analysis

BACKGROUND

Long non-coding RNAs (lncRNAs) participate in the regulation of genomic stability. Understanding their biological functions can help us identify the mechanisms of the occurrence and progression of cancers and can provide theoretical guidance and the basis for treatment.

RESULTS

Based on the mutation hypothesis, we proposed a computational framework to identify genomic instability-related lncRNAs. Based on the differentially-expressed lncRNAs (DElncRNAs), we constructed a genomic instability-derived lncRNA signature (GILncSig) to calculate and stratify outcomes in patients with prostate cancer. It is an independent predictor of overall survival. The area under the curve = 0.805. This value may be more significant than the classic prognostic markers TP53 and Speckle-type POZ protein (SPOP) in terms of outcome prediction.

CONCLUSIONS

In summary, we conducted a computation approach and resource for mining genome instability-related lncRNAs. It may turn out to be highly significant for genomic instability and customized decision-making for patients with prostate cancer. It also may lead to effective methods and resources to study the molecular mechanism of genomic instability-related lncRNAs.

Long Intergenic Non-Coding RNAs in HNSCC: From "Junk DNA" to Important Prognostic Factor

Head and neck squamous cell carcinoma is one of the most common and fatal cancers worldwide. Even a multimodal approach consisting of standard chemo- and radiotherapy along with surgical resection is only effective in approximately 50% of the cases. The rest of the patients develop a relapse of the disease and acquire resistance to treatment. Especially this group of individuals needs novel, personalized, targeted therapy. The first step to discovering such solutions is to investigate the tumor microenvironment, thus understanding the role and mechanism of the function of coding and non-coding sequences of the human genome. In recent years, RNA molecules gained great interest when the complex character of their impact on our biology allowed them to come out of the shadows of the "junk DNA" label. Furthermore, long non-coding RNAs (lncRNA), specifically the intergenic subgroup (lincRNA), are one of the most aberrantly expressed in several malignancies, which makes them particularly promising future diagnostic biomarkers and therapeutic targets. This review contains characteristics of known and validated lincRNAs in HNSCC, such as XIST, MALAT, HOTAIR, HOTTIP, lincRNA-p21, LINC02487, LINC02195, LINC00668, LINC00519, LINC00511, LINC00460, LINC00312, and LINC00052, with a description of their prognostic abilities. Even though much work remains to be done, lincRNAs are important factors in cancer biology that will become valuable biomarkers of tumor stage, outcome prognosis, and contribution to personalized medicine.