All change in the prostate cancer diagnostic pathway

Integrative Chinese-Western medicine strategy to overcome docetaxel resistance in prostate cancer

ETHNOPHARMACOLOGICAL RELEVANCE

Traditional Chinese Medicines (TCMs) have emerged as a promising complementary therapy in the management of prostate cancer (PCa), particularly in addressing resistance to Docetaxel (DTX) chemotherapy.

AIM OF THE REVIEW

This review aims to elucidate the mechanisms underlying the development of resistance to DTX in PCa and explore the innovative approach of integrating TCMs in PCa treatment to overcome this resistance. Key areas of investigation include alterations in microtubule proteins, androgen receptor and androgen receptor splice variant 7, ERG rearrangement, drug efflux mechanisms, cancer stem cells, centrosome clustering, upregulation of the PI3K/AKT signaling pathway, enhanced DNA damage repair capability, and the involvement of neurotrophin receptor 1/protein kinase C.

MATERIALS AND METHODS

With "Prostate cancer", "Docetaxel", "Docetaxel resistance", "Natural compounds", "Traditional Chinese medicine", "Traditional Chinese medicine compound", "Medicinal plants" as the main keywords, PubMed, Web of Science and other online search engines were used for literature retrieval.

RESULTS

Our findings underscore the intricate interplay of molecular alterations that collectively contribute to the resistance of PCa cells to DTX. Moreover, we highlight the potential of TCMs as a promising complementary therapy, showcasing their ability to counteract DTX resistance and enhance therapeutic efficacy.

CONCLUSION

The integration of TCMs in PCa treatment emerges as an innovative approach with significant potential to overcome DTX resistance. This review not only provides insights into the mechanisms of resistance but also presents new prospects for improving the clinical outcomes of patients with PCa undergoing DTX therapy. The comprehensive understanding of these mechanisms lays the foundation for future research and the development of more effective therapeutic interventions.

Increased α2,3-sialyl N-glycosylated prostate-specific membrane antigen (PSMA) in post-DRE urine is associated with high grade group prostate cancer

INTRODUCTION

Aberrant glycosylation of proteins is an important hallmark in multiple cancers. Prostate-specific membrane antigen (PSMA), a highly glycosylated protein with 10 N-linked glycosylation sites, is an Food and Drug Administration approved theranostic for prostate cancer. However, glycosylation changes in PSMA that are associated with prostate cancer disease progression have not been fully characterized.

METHODS

We investigated whether urinary PSMA sialylation correlate with high-grade prostate cancer. Urine samples were collected from men after digital rectal examination (DRE) before prostate biopsy. Lectin-antibody enzyme-linked immunoassay was used to quantify α2,3-sialyl PSMA in post-DRE urine samples from subjects with benign prostate tumors, Grade Group 1 prostate cancer and those with Grade Group ≥2 disease.

RESULTS

There are significant increases in α2,3-sialylated PSMA in patients with Grade Group ≥2 disease compared to benign (p = 0.0009) and those with Grade Group 1 disease (p = 0.0063). There were no significant differences in α2,3-sialyl PSMA levels between Grade Group 1 and benign prostate tumors (p = 0.7947).

CONCLUSIONS

Our study shows that there are significant differences in the abundance of α2,3-sialylated PSMA in post-DRE urines from disease stratified prostate cancer patients, and the increase is correlated with progression and disease severity. The detection of increased PSMA sialyation in post-DRE urines from patients with higher Grade Group ≥2 disease states provides novel untapped potential for the development of prognostic biomarkers for prostate cancer. Specifically, quantitation of α2,3-sialylated PSMA shows potential for discriminating between benign to intermediate grade disease, which is a significant clinical challenge in staging and risk stratification of prostate cancer.

Photothermal therapy: a novel potential treatment for prostate cancer

Prostate cancer (PCa) is a leading cause of cancer-related death in men, and most PCa patients treated with androgen deprivation therapy will progress to metastatic castration-resistant prostate cancer (mCRPC) due to the lack of efficient treatment. Recently, lots of research indicated that photothermal therapy (PTT) was a promising alternative that provided an accurate and efficient prostate cancer therapy. A photothermic agent (PTA) is a basic component of PPT and is divided into organic and inorganic PTAs. Besides, the combination of PTT and other therapies, such as photodynamic therapy (PDT), immunotherapy (IT), chemotherapy (CT), etc., provides an more efficient strategy for PCa therapy. Here, we introduce basic information about PTT and summarize the PTT treatment strategies for prostate cancer. Based on recent works, we think the combination of PPT and other therapies provides a novel possibility for PCa, especially CRPC clinical treatment.

Assessing the Clinical Utility of Published Prostate Cancer Polygenic Risk Scores in a Large Biobank Data Set

BACKGROUND AND OBJECTIVE

Polygenic risk scores (PRSs) have been developed to identify men with the highest risk of prostate cancer. Our aim was to compare the performance of 16 PRSs in identifying men at risk of developing prostate cancer and then to evaluate the performance of the top-performing PRSs in differentiating individuals at risk of aggressive prostate cancer.

METHODS

For this case-control study we downloaded 16 published PRSs from the Polygenic Score Catalog on May 28, 2021 and applied them to Michigan Genomics Initiative (MGI) patients. Cases were matched to the Michigan Urological Surgery Improvement Collaborative (MUSIC) registry to obtain granular clinical and pathological data. MGI prospectively enrolls patients undergoing surgery at the University of Michigan, and MUSIC is a multi-institutional registry that prospectively tracks demographic, treatment, and clinical variables. The predictive performance of each PRS was evaluated using the area under the covariate-adjusted receiver operating characteristic curve (aAUC), and the association between PRS and disease aggressiveness according to prostate biopsy data was measured using logistic regression.

KEY FINDINGS AND LIMITATIONS

We included 18 050 patients in the analysis, of whom 15 310 were control subjects and 2740 were prostate cancer cases. The median age was 66.1 yr (interquartile range 59.9-71.6) for cases and 56.6 yr (interquartile range 42.6-66.7) for control subjects. The PRS performance in predicting the risk of developing prostate cancer according to aAUC ranged from 0.51 (95% confidence interval 0.51-0.53) to 0.67 (95% confidence interval 0.66-0.68). By contrast, there was no association between PRS and disease aggressiveness.

CONCLUSIONS AND CLINICAL IMPLICATIONS

Prostate cancer PRSs have modest real-world performance in identifying patients at higher risk of developing prostate cancer; however, they are limited in distinguishing patients with indolent versus aggressive disease.

PATIENT SUMMARY

Risk scores using data for multiple genes (called polygenic risk scores) can identify men at higher risk of developing prostate cancer. However, these scores need to be refined to be able to identify men with the highest risk for clinically significant prostate cancer.

Development and validation of a clinical-radiomics model for prediction of prostate cancer: a multicenter study

PURPOSE

To develop an early diagnosis model of prostate cancer based on clinical-radiomics to improve the accuracy of imaging diagnosis of prostate cancer.

METHODS

The multicenter study enrolled a total of 449 patients with prostate cancer from December 2017 to January 2022. We retrospectively collected information from 342 patients who underwent prostate biopsy at Minhang Hospital. We extracted T2WI images through 3D-Slice, and used mask tools to mark the prostate area manually. The radiomics features were extracted by Python using the "Pyradiomics" module. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for data dimensionality reduction and feature selection, and the radiomics score was calculated according to the correlation coefficients. Multivariate logistic regression analysis was used to develop predictive models. We incorporated the radiomics score, PI-RADS, and clinical features, and this was presented as a nomogram. The model was validated using a cohort of 107 patients from the Xuhui Hospital.

RESULTS

In total, 110 effective radiomics features were extracted. Finally, 9 features were significantly associated with the diagnosis of prostate cancer, from which we calculated the radiomics score. The predictors contained in the individualized prediction nomogram included age, fPSA/tPSA, PI-RADS, and radiomics score. The clinical-radiomics model showed good discrimination in the validation cohort (C-index = 0.88).

CONCLUSION

This study presents a clinical-radiomics model that incorporates age, fPSA/PSA, PI-RADS, and radiomics score, which can be conveniently used to facilitate individualized prediction of prostate cancer before prostate biopsy.

The impact of pre-biopsy MRI and additional testing on prostate cancer screening outcomes: A rapid review

Objective

This work aims to examine the latest evidence on the impact of pre-biopsy MRI, in addition to prostate-specific antigen (PSA) testing, on health outcomes and quality of life.

Methods

We conducted a literature search including PubMed and Cochrane Central Register of Controlled Trials (CENTRAL) databases, with a limited scan of (i) guidelines and (ii) references from trial reports, from January 2005 to 25th January 2023. Two independent reviewers selected randomised controlled trials (RCT) and cohort studies which met our inclusion criteria.

Results

One hundred thirty-seven articles were identified, and seven trial articles were selected. Trial interventions were as follows: (i) PSA blood test, (ii) additional tests such as pre-biopsy multiparametric magnetic resonance imaging (mpMRI) and Biparametric MRI (bpMRI), and (iii) MRI targeted biopsy and standard biopsy. Compared with standard biopsy, MRI-based interventions led to increased detection of clinically significant cancers in three studies and decreased detection of clinically insignificant cancer (Gleason grade 3 + 3) in four studies. However, PROstate Magnetic resonance Imaging Study (PROMIS) and Stockholm3 with MRI (STHLM3-MRI) studies reported different trends depending on the scenario studied in PROMIS (MRI triage and MRI directed biopsy vs. MRI triage and standard biopsy) and thresholds used in STHLM3-MRI (≥0·11 and ≥0·15). MRI also helped 8%-49% of men avoid biopsy, in six out of seven studies, but not in STHLM3-MRI at ≥0.11. Interestingly, the proportion of men who experienced sepsis and UTI was low across studies.

Conclusion

This review found that a combination of approaches, centred on the use of pre-biopsy MRI, may improve the detection of clinically significant cancers and reduce (i) the diagnosis of clinically insignificant cancers and (ii) unnecessary biopsies, compared with PSA testing and standard biopsy alone. However, the impact of such interventions on longer term outcomes such as prostate cancer-specific mortality has not yet been assessed.

Diagnostic performance of 18F‑DCFPyL PET vs. 68Ga‑PSMA PET/CT in patients with suspected prostate cancer: A systemic review and meta‑analysis

In this systematic review and meta-analysis, the diagnostic performance of 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/CT was compared with that of 18F-DCFPyL PET for patients with suspected prostate cancer (PCa). Up to September 2023, the PubMed, Embase and Web of Science databases were thoroughly searched for relevant papers. Studies examining the diagnostic performance of 18F-DCFPyL PET and 68Ga-PSMA PET/CT in patients with suspected PCa were included in the present review. The Quality Assessment of Diagnostic Performance Studies-2 tool was used to rate the diagnostic performance of each study. The diagnostic performance of 18F-DCFPyL PET and 68Ga-PSMA PET/CT for primary PCa was examined by 13 studies included, comprising 1,178 patients. The pooled sensitivity and specificity of 18F-DCFPyL PET were 0.92 (95% CI, 0.85-0.96) and 0.59 (95% CI, 0.08-0.96), respectively. For 68Ga-PSMA PET/CT, the pooled sensitivity and specificity were 0.96 (95% CI, 0.88-0.99) and 0.71 (95% CI, 0.57-0.82), respectively. 18F-DCFPyL PET and 68Ga-PSMA PET/CT both had an area under the receiver operating characteristic curve of 0.92 (95% CI, 0.89-0.94). In addition, the Fagan nomogram revealed that the post-test probabilities for 18F-DCFPyL PET and 68Ga-PSMA PET/CT could rise to 69 and 77% when the pre-test probability was set at 50%. In conclusion, a comparable diagnostic performance for patients with suspected PCa was determined for 18F-DCFPyL PET and 68Ga-PSMA PET/CT. However, it is crucial to keep in mind that the findings of the present meta-analysis come from investigations with modest sample sizes. Therefore, more extensive research is required to obtain more solid data.

Prostate-specific membrane antigen (PSMA) glycoforms in prostate cancer patients seminal plasma

INTRODUCTION

Prostate-specific membrane antigen (PSMA) is a US Food and Drug Administration-approved theranostic target for prostate cancer (PCa). Although PSMA is known to be glycosylated, the composition and functional roles of its N-linked glycoforms have not been fully characterized.

METHODS

PSMA was isolated from pooled seminal plasma from low-risk grade Groups 1 and 2 PCa patients. Intact glycopeptides were analyzed by mass spectrometry to identify site-specific glycoforms.

RESULTS

We observed a rich distribution of PSMA glycoforms in seminal plasma from low and low-intermediate-risk PCa patients. Some interesting generalities can be drawn based on the predicted topology of PSMA on the plasma membrane. The glycoforms at ASN-459, ASN-476, and ASN-638 residues that are located at the basal domain facing the plasma membrane in cells, are predominantly high mannose glycans. ASN-76 which is located in the interdomain region adjacent to the apical domain of the protein shows a mixture of high mannose glycans and complex glycans, whereas ASN-121, ASN-195 and ASN-336 that are located and are exposed at the apical domain of the protein predominantly possess complex sialylated and fucosylated N-linked glycans. These highly accessible glycosites display the greatest diversity in isoforms across the patient samples.

CONCLUSIONS

Our study provides novel qualitative insights into PSMA glycoforms that are present in the seminal fluid of PCa patients. The presence of a rich diversity of glycoforms in seminal plasma provides untapped potential for glycoprotein biomarker discovery and as a clinical sample for noninvasive diagnostics of male urological disorders and diseases including PCa. Specifically, our glycomics approach will be critical in uncovering PSMA glycoforms with utility in staging and risk stratification of PCa.

Rapid Near-Patient Impedimetric Sensing Platform for Prostate Cancer Diagnosis

With the global escalation of concerns surrounding prostate cancer (PCa) diagnosis, reliance on the serologic prostate-specific antigen (PSA) test remains the primary approach. However, the imperative for early PCa diagnosis necessitates more effective, accurate, and rapid diagnostic point-of-care (POC) devices to enhance the result reliability and minimize disease-related complications. Among POC approaches, electrochemical biosensors, known for their amenability and miniaturization capabilities, have emerged as promising candidates. In this study, we developed an impedimetric sensing platform to detect urinary zinc (UZn) in both artificial and clinical urine samples. Our approach lies in integrating label-free impedimetric sensing and the introduction of porosity through surface modification techniques. Leveraging a cellulose acetate/reduced graphene oxide composite, our sensor's recognition layer is engineered to exhibit enhanced porosity, critical for improving the sensitivity, capture, and interaction with UZn. The sensitivity is further amplified by incorporating zincon as an external dopant, establishing highly effective recognition sites. Our sensor demonstrates a limit of detection of 7.33 ng/mL in the 0.1-1000 ng/mL dynamic range, which aligns with the reference benchmark samples from clinical biochemistry. Our sensor results are comparable with the results of inductively coupled plasma mass spectrometry (ICP-MS) where a notable correlation of 0.991 is achieved. To validate our sensor in a real-life scenario, tests were performed on human urine samples from patients being investigated for prostate cancer. Testing clinical urine samples using our sensing platform and ICP-MS produced highly comparable results. A linear correlation with R2 = 0.964 with no significant difference between two groups (p-value = 0.936) was found, thus confirming the reliability of our sensing platform.

Prostate cancer risk stratification via eNose urine odor analysis: a preliminary report

Introduction

Prostate cancer (PCa) is known for its highly diverse clinical behavior, ranging from low-risk, slow-growing tumors to aggressive and life-threatening forms. To avoid over-treatment of low-risk PCa patients, it would be very important prior to any therapeutic intervention to appropriately classify subjects based on tumor aggressiveness. Unfortunately, there is currently no reliable test available for this purpose. The aim of the present study was to evaluate the ability of risk stratification of PCa subjects using an electronic nose (eNose) detecting PCa-specific volatile organic compounds (VOCs) in urine samples.

Methods

The study involved 120 participants who underwent diagnostic prostate biopsy followed by robot assisted radical prostatectomy (RARP). PCa risk was categorized as low, intermediate, or high based on the D'Amico risk classification and the pathological grade (PG) assessed after RARP. The eNose's ability to categorize subjects for PCa risk stratification was evaluated based on accuracy and recall metrics.

Results

The study population comprised 120 participants. When comparing eNose predictions with PG an accuracy of 79.2% (95%CI 70.8 - 86%) was found, while an accuracy of 74.2% (95%CI 65.4 - 81.7%) was found when compared to D'Amico risk classification system. Additionally, if compared low- versus -intermediate-/high-risk PCa, the eNose achieved an accuracy of 87.5% (95%CI 80.2-92.8%) based on PG or 90.8% (95%CI 84.2-95.3%) based on D'Amico risk classification. However, when using low-/-intermediate versus -high-risk PCa for PG, the accuracy was found to be 91.7% (95%CI 85.2-95.9%). Finally, an accuracy of 80.8% (95%CI72.6-87.4%) was found when compared with D'Amico risk classification.

Discussion

The findings of this study indicate that eNose may represent a valid alternative not only for early and non-invasive diagnosis of PCa, but also to categorize patients based on tumor aggressiveness. Further studies including a wider sample population will be necessary to confirm the potential clinical impact of this new technology.

A single-center, multi-factor, retrospective study to improve the diagnostic accuracy of primary prostate cancer using [68Ga]Ga-PSMA-11 total-body PET/CT imaging

PURPOSE

To improve the diagnostic accuracy of initial detection in patients with suspected primary prostate cancer (PCa).

METHODS

Eighty-four patients who underwent Gallium-68-labeled prostate-specific membrane antigen ([68Ga]Ga-PSMA-11) total-body positron emission tomography/computed tomography (PET/CT) imaging before treatment in our department were enrolled. The maximum standard uptake value (SUVmax) of the prostate (SUVmax-PSMA), liver (SUVmax-PSMA-L), and mediastinal blood pool (SUVmax-PSMA-M) was measured using [68Ga]Ga-PSMA-11 total-body PET/CT imaging. The [68Ga]Ga-PSMA-11 derived metabolic tumor volume (MTV), the total lesion (TLP), and the cross-sectional areas of focal concentration in the prostate (CAP) were also determined. Besides, the prostate-specific antigen (PSA) levels and the above imaging characteristics were analyzed using receiver operating characteristic curves to identify the cutoff value to improve the diagnostic accuracy of suspected PCa. Finally, a multivariate regression analysis was conducted to discover the independent predictor to improve the diagnostic accuracy on [68Ga]Ga-PSMA-11 total-body imaging.

RESULTS

There was no significant difference between the PCa and Non-PCa groups in age, height, weight, injected dose, except for the PSA levels, the SUVmax-PSMA, TLP, MTV, and CAP. Besides, the SUVmax-PSMA-T/L and SUVmax-PSMA-T/M derived from SUVmax-PSMA were both significantly different. In addition, the areas under the curve of PSA levels, SUVmax-PSMA, SUVmax-PSMA-T/L, SUVmax-PSMA-T/M, TLP, MTV, and CAP to predict PCa on [68Ga]Ga-PSMA-11 imaging were 0.620 (95% confidence interval (CI) 0.485-0.755), 0.864 (95% CI 0.757-0.972), 0.819 (95% CI 0.704-0.935), 0.876 (95% CI 0.771-0.980), 0.845 (95% CI 0.741-0.949), 0.820 (95% CI 0.702-0.938), 0.627 (95% CI 0.499-0.754), respectively. However, a multivariate regression analysis showed that SUVmax-PSMA was an independent predictor, with a cutoff value of 11.5 and an odds ratio of 1.221.

CONCLUSION

The SUVmax-PSMA with a cutoff value of 11.5 was an independent predictor to improve the diagnostic accuracy of PCa on [68Ga]Ga-PSMA-11 total-body imaging.

Rising use of diagnostic imaging in Australia: An analysis of Medicare-funded radiology services between 2000 and 2021

INTRODUCTION

The use of diagnostic imaging services is increasing worldwide. This has important impacts on healthcare resource allocation and potential risks to the population. This study aimed to quantify trends in medical imaging in Australia over the past two decades.

METHODS

Data were extracted from the Australian Medicare Benefits Schedule (MBS) between 2000 and 2021. Simple linear regression analyses were performed to assess changes in absolute utilisation and utilisation rate per 100,000 population of total imaging services as well as by each imaging modality. Logistic regression analysis was performed to assess changes in total imaging services as a proportion of total Medicare services over time. Chi-squared test was used to assess for change in modality composition of imaging services.

RESULTS

There were 436,255,500 imaging studies performed between 2000 and 2021. The absolute utilisation of total imaging services increased annually by an average of 864,404 (95% CI: 808,235-920,573, p < 0.001). For each consecutive year, the proportion of total Medicare services attributed to total imaging services increased by 0.01% (95% CI: 0.01-0.01, p < 0.01). There was also a statistically significant increase in the utilisation rates of imaging services per 100,000 population for each imaging modality. The number of imaging services per radiologist increased on average by 74 (95% CI: 26-122, p < 0.05) annually.

CONCLUSION

The utilisation of diagnostic imaging services has increased in Australia between 2000 and 2021, outpacing the population growth, total healthcare services, and the radiologist workforce.

Big data and artificial intelligence in cancer research

The field of oncology has witnessed an extraordinary surge in the application of big data and artificial intelligence (AI). AI development has made multiscale and multimodal data fusion and analysis possible. A new era of extracting information from complex big data is rapidly evolving. However, challenges related to efficient data curation, in-depth analysis, and utilization remain. We provide a comprehensive overview of the current state of the art in big data and computational analysis, highlighting key applications, challenges, and future opportunities in cancer research. By sketching the current landscape, we seek to foster a deeper understanding and facilitate the advancement of big data utilization in oncology, call for interdisciplinary collaborations, ultimately contributing to improved patient outcomes and a profound understanding of cancer.

Diagnostic capability of 18F-PSMA PET-MRI and pelvic MRI plus bone scan in treatment-naive prostate cancer: a single-center paired validating confirmatory study

BACKGROUND

Radical prostatectomy with pelvic lymph node dissection for the treatment of high-risk localized prostate cancer (PCa) results in long-term benefits in selected patients. But insufficient sensitivity of conventional examinations which are pelvic MRI and bone scan, limits the diagnosis of bone and lymph node metastasis of PCa. This affects the surgical management strategy of a large number of patients. The purpose of this study was to investigate whether 18F-prostate-specific membrane antigen (PSMA) PET-MRI could improve the clinical detection of PCa metastases compared with the conventional pelvic MRI plus bone scan.

MATERIALS AND METHODS

From April 2020 to April 2023, we prospectively enroled 472 patients with histologically proven PCa in our centre, and 120 patients underwent 18F-PSMA PET-MRI, multiparametric MRI, and bone scan before laparoscopic radical prostatectomy plus lymph node dissection. The accuracy of imaging results in detecting lymph node and bone metastatic lesions was compared between PSMA PET-MRI and MRI plus bone scan.

RESULTS

In diagnosing lymph node metastasis, PSMA PET-MRI had an area under the curve (AUC) of 0.844 (95% CI: 0.738-0.949, P < 0.001), sensitivity and specificity of 75% and 96%, which performed apparently better than MRI [AUC=0.615 (95% CI: 0.480-0.750, P =0.073)]. PSMA PET-MRI showed excellent expression in the diagnosis of bone metastases, with an AUC of 0.910 (95% CI: 0.840-0.981, P <0.001) compared to 0.700 (95% CI: 0.577-0.823, P =0.001) in bone scanning. PSMA PET-MRI also had higher sensitivity than bone scanning (90% vs. 43%), while lower specificity (92% vs. 97%).

CONCLUSION

PSMA PET-MRI is superior to conventional imaging at diagnosing metastases in lymph nodes and bones in PCa and can provide a more accurate stagement.

Validation of potential RNA biomarkers for prostate cancer diagnosis and monitoring in plasma and urinary extracellular vesicles

Introduction: Prostate cancer (PCa), one of the most prevalent malignancies affecting men worldwide, presents significant challenges in terms of early detection, risk stratification, and active surveillance. In recent years, liquid biopsies have emerged as a promising non-invasive approach to complement or even replace traditional tissue biopsies. Extracellular vesicles (EVs), nanosized membranous structures released by various cells into body fluids, have gained substantial attention as a source of cancer biomarkers due to their ability to encapsulate and transport a wide range of biological molecules, including RNA. In this study, we aimed to validate 15 potential RNA biomarkers, identified in a previous EV RNA sequencing study, using droplet digital PCR. Methods: The candidate biomarkers were tested in plasma and urinary EVs collected before and after radical prostatectomy from 30 PCa patients and their diagnostic potential was evaluated in a test cohort consisting of 20 benign prostate hyperplasia (BPH) and 20 PCa patients' plasma and urinary EVs. Next, the results were validated in an independent cohort of plasma EVs from 31 PCa and 31 BPH patients. Results: We found that the levels of NKX3-1 (p = 0.0008) in plasma EVs, and tRF-Phe-GAA-3b (p < 0.0001) tRF-Lys-CTT-5c (p < 0.0327), piR-28004 (p = 0.0081) and miR-375-3p (p < 0.0001) in urinary EVs significantly decreased after radical prostatectomy suggesting that the main tissue source of these RNAs is prostate and/or PCa. Two mRNA biomarkers-GLO1 and NKX3-1 showed promising diagnostic potential in distinguishing between PCa and BPH with AUC of 0.68 and 0.82, respectively, in the test cohort and AUC of 0.73 and 0.65, respectively, in the validation cohort, when tested in plasma EVs. Combining these markers in a biomarker model yielded AUC of 0.85 and 0.71 in the test and validation cohorts, respectively. Although the PSA levels in the blood could not distinguish PCa from BPH in our cohort, adding PSA to the mRNA biomarker model increased AUC from 0.71 to 0.76. Conclusion: This study identified two novel EV-enclosed RNA biomarkers-NKX3-1 and GLO1-for the detection of PCa, and highlights the complementary nature of GLO1, NKX3-1 and PSA as combined biomarkers in liquid biopsies of PCa.

Addressing image misalignments in multi-parametric prostate MRI for enhanced computer-aided diagnosis of prostate cancer

Prostate cancer (PCa) diagnosis on multi-parametric magnetic resonance images (MRI) requires radiologists with a high level of expertise. Misalignments between the MRI sequences can be caused by patient movement, elastic soft-tissue deformations, and imaging artifacts. They further increase the complexity of the task prompting radiologists to interpret the images. Recently, computer-aided diagnosis (CAD) tools have demonstrated potential for PCa diagnosis typically relying on complex co-registration of the input modalities. However, there is no consensus among research groups on whether CAD systems profit from using registration. Furthermore, alternative strategies to handle multi-modal misalignments have not been explored so far. Our study introduces and compares different strategies to cope with image misalignments and evaluates them regarding to their direct effect on diagnostic accuracy of PCa. In addition to established registration algorithms, we propose 'misalignment augmentation' as a concept to increase CAD robustness. As the results demonstrate, misalignment augmentations can not only compensate for a complete lack of registration, but if used in conjunction with registration, also improve the overall performance on an independent test set.

A cell-impermeable luminogenic probe for near-infrared imaging of prostate-specific membrane antigen in prostate cancer microenvironments

Prostate-specific membrane antigen (PSMA) imaging probes are a promising tool for the diagnosis and image-guided surgery of prostate cancer (PCa). However, PSMA-specific luminescence probes for PCa detection and heterogeneity studies with high imaging contrast are lacking. Here, we report the first near-infrared (NIR) iridium(III) complex for the wash-free and specific imaging of PSMA in PCa cells and spheroids. The conjugation of a PSMA inhibitor, Lys-urea-Glu, to an iridium(III) complex synergizes the PSMA-specific affinity and biocompatibility of the inhibitor with the desirable photophysical properties of the iridium(III) complex, including NIR emission (670 nm), high photostability and a large Stokes shift. The cellular impermeability of the probe along with its strong binding affinity to PSMA enhances its specificity for PSMA, enabling the washing-free luminescent imaging of membrane PSMA with lower cytotoxicity. The probe was successfully applied for selectively visualizing PSMA-expressing cells and for the imaging of PSMA in a multicellular PCa model with good imaging penetration, indicating its potential use in complicated and heterogeneous tumor microenvironments. Furthermore, the probe showed good imaging performance in the PCa-bearing tumor mice via targeting PSMA in vivo. This work provides a novel strategy for the development of highly sensitive and specific NIR probes for PSMA in biological systems in vitro, which is of great significance for the precise diagnosis of PCa and for elucidating PCa heterogeneity.

Analysis of genetic biomarkers, polymorphisms in ADME-related genes and their impact on pharmacotherapy for prostate cancer

Prostate cancer (PCa) is a non-cutaneous malignancy in males with wide variation in incidence rates across the globe. It is the second most reported cause of cancer death. Its etiology may have been linked to genetic polymorphisms, which are not only dominating cause of malignancy casualties but also exerts significant effects on pharmacotherapy outcomes. Although many therapeutic options are available, but suitable candidates identified by useful biomarkers can exhibit maximum therapeutic efficacy. The single-nucleotide polymorphisms (SNPs) reported in androgen receptor signaling genes influence the effectiveness of androgen receptor pathway inhibitors and androgen deprivation therapy. Furthermore, SNPs located in genes involved in transport, drug metabolism, and efflux pumps also influence the efficacy of pharmacotherapy. Hence, SNPs biomarkers provide the basis for individualized pharmacotherapy. The pharmacotherapeutic options for PCa include hormonal therapy, chemotherapy (Docetaxel, Mitoxantrone, Cabazitaxel, and Estramustine, etc.), and radiotherapy. Here, we overview the impact of SNPs reported in various genes on the pharmacotherapy for PCa and evaluate current genetic biomarkers with an emphasis on early diagnosis and individualized treatment strategy in PCa.

Assessing the Potential of Small Peptides for Altering Expression Levels of the Iron-Regulatory Genes FTH1 and TFRC and Enhancing Androgen Receptor Inhibitor Activity in In Vitro Prostate Cancer Models

Recent research highlights the key role of iron dyshomeostasis in the pathogenesis of prostate cancer (PCa). PCa cells are heavily dependent on bioavailable iron, which frequently results in the reprogramming of iron uptake and storage pathways. Although advanced-stage PCa is currently incurable, bioactive peptides capable of modulating key iron-regulatory genes may constitute a means of exploiting a metabolic adaptation necessary for tumor growth. Recent annual increases in PCa incidence have been reported, highlighting the urgent need for novel treatments. We examined the ability of LNCaP, PC3, VCaP, and VCaP-EnzR cells to form colonies in the presence of androgen receptor inhibitors (ARI) and a series of iron-gene modulating oligopeptides (FT-001-FT-008). The viability of colonies following treatment was determined with clonogenic assays, and the expression levels of FTH1 (ferritin heavy chain 1) and TFRC (transferrin receptor) were determined with quantitative polymerase chain reaction (PCR). Peptides and ARIs combined significantly reduced PCa cell growth across all phenotypes, of which two peptides were the most effective. Colony growth suppression generally correlated with the magnitude of concurrent increases in FTH1 and decreases in TFRC expression for all cells. The results of this study provide preliminary insight into a novel approach at targeting iron dysmetabolism and sensitizing PCa cells to established cancer treatments.

RAGE as a Novel Biomarker for Prostate Cancer: A Systematic Review and Meta-Analysis

The receptor for advanced glycation end-products (RAGE) has been implicated in driving prostate cancer (PCa) growth, aggression, and metastasis through the fueling of chronic inflammation in the tumor microenvironment. This systematic review and meta-analysis summarizes and analyzes the current clinical and preclinical data to provide insight into the relationships among RAGE levels and PCa, cancer grade, and molecular effects. A multi-database search was used to identify original clinical and preclinical research articles examining RAGE expression in PCa. After screening and review, nine clinical and six preclinical articles were included. The associations of RAGE differentiating benign prostate hyperplasia (BPH) or normal prostate from PCa and between tumor grades were estimated using odds ratios (ORs) and associated 95% confidence intervals (CI). Pooled estimates were calculated using random-effect models due to study heterogeneity. The clinical meta-analysis found that RAGE expression was highly likely to be increased in PCa when compared to BPH or normal prostate (OR: 11.3; 95% CI: 4.4-29.1) and that RAGE was overexpressed in high-grade PCa when compared to low-grade PCa (OR: 2.5; 95% CI: 1.8-3.4). In addition, meta-analysis estimates of preclinical studies performed by albatross plot generation found robustly positive associations among RAGE expression/activation and PCa growth and metastatic potential. This review demonstrates that RAGE expression is strongly tied to PCa progression and can serve as an effective diagnostic target to differentiate between healthy prostate, low-grade PCa, and high-grade PCa, with potential theragnostic applications.

Validation of real-time prostatic biopsies evaluation with fluorescence laser confocal microscopy

BACKGROUND

Routine processing of prostate biopsies requires conventional steps that usually take a few days. The aim of this study was to validate the use of fluorescence laser confocal microscopy (FCM) for real-time diagnostics.

METHODS

We prospectively tested images from prostate needle biopsies (75 images were evaluated by FCM and conventional slides). Two pathologists reviewed the images and assessed agreements between FCM versus conventional slides and between pathologists (κ-values). Interpretation was performed on digital images from the VivaScope 2500 confocal microscope (MAVIG GmbH, Munich, Germany; Caliber I.D., Rochester, NY, USA) placed in the urological operating room. Cancerous versus benign tissue was the primary focus, then the application of the grading system.

RESULTS

Cancer was diagnosed in 24 conventional slides (on 75 images) in which agreement among pathologists was high for both conventional (κ=0.96) and FMC (κ=0.84). 1/24 (4%) was ISUP/WHO grade group I, 12/24 (50%) II, 8/24 (33%) III, 2/24 (8%) IV and 1/24 (4%) grade V. Near perfect agreement was obtained for grades I, IV and V (κ=0.85). Grade III values achieved a moderate agreement (κ=0.55). The mean time for laser scanning was 9 minutes. For the remaining non-tumor images, agreement was nearly perfect (κ=0.81).

CONCLUSIONS

We validated the use of FCM for real-time cancer detection in prostate biopsies.

Recent advances and future perspectives in the therapeutics of prostate cancer

Prostate cancer (PC) is one of the most common cancers in males and the fifth leading reason of death. Age, ethnicity, family history, and genetic defects are major factors that determine the aggressiveness and lethality of PC. The African population is at the highest risk of developing high-grade PC. It can be challenging to distinguish between low-risk and high-risk patients due to the slow progression of PC. Prostate-specific antigen (PSA) is a revolutionary discovery for the identification of PC. However, it has led to an increase in over diagnosis and over treatment of PC in the past few decades. Even if modifications are made to the standard PSA testing, the specificity has not been found to be significant. Our understanding of PC genetics and proteomics has improved due to advances in different fields. New serum, urine, and tissue biomarkers, such as PC antigen 3 (PCA3), have led to various new diagnostic tests, such as the prostate health index, 4K score, and PCA3. These tests significantly reduce the number of unnecessary and repeat biopsies performed. Chemotherapy, radiotherapy, and prostatectomy are standard treatment options. However, newer novel hormone therapy drugs with a better response have been identified. Androgen deprivation and hormonal therapy are evolving as new and better options for managing hormone-sensitive and castration-resistant PC. This review aimed to highlight and discuss epidemiology, various risk factors, and developments in PC diagnosis and treatment regimens.

Quantitative ADC: An Additional Tool in the Evaluation of Prostate Cancer?

Prostate cancer is one of the most common tumors among the male population. Magnetic resonance imaging (MRI), standardized by the PI-RADS version 2.1 scoring system, has a fundamental role in detecting prostate cancer and evaluating its aggressiveness. Diffusion-weighted imaging sequences and apparent diffusion coefficient values, in particular, are considered fundamental for the detection and characterization of lesions. In 2016 the International Society of Urological Pathology introduced a new anatomopathological 5-grade scoring system for prostate cancer. The aim of this study is to evaluate the correlation between quantitative apparent diffusion coefficient values (ADC) derived from diffusion-weighted imaging (DWI) sequences and the International Society of Urological Pathology (ISUP) and PI-RADS groups. Our retrospective study included 143 patients with 154 suspicious lesions, observed on prostate magnetic resonance imaging and compared with the histological results of the biopsy. We observed that ADC values can aid in discriminating between not clinically significant (ISUP 1) and clinically significant (ISUP 2-5) prostate cancers. In fact, ADC values were lower in ISUP 5 lesions than in negative lesions. We also found a correlation between ADC values and PI-RADS groups; we noted lower ADC values in the PI-RADS 5 and PI-RADS 4 groups than in the PI-RADS 3 group. In conclusion, quantitative apparent diffusion coefficient values can be useful to assess the aggressiveness of prostate cancer.

Prostate cancer tissue classification by multiphoton imaging, automated image analysis and machine learning

Prostate carcinoma, a slow-growing and often indolent tumour, is the second most commonly diagnosed cancer among men worldwide. The prognosis is mainly based on the Gleason system through prostate biopsy analysis. However, new treatment and monitoring strategies depend on a more precise diagnosis. Here, we present results by multiphoton imaging for prostate tumour samples from 120 patients that allow to obtain quantitative parameters leading to specific tumour aggressiveness signatures. An automated image analysis was developed to recognise and quantify stromal fibre and neoplastic cell regions in each image. The set of metrics was able to distinguish between non-neoplastic tissue and carcinoma areas by linear discriminant analysis and random forest with accuracy of 89% ± 3%, but between Gleason groups of only 46% ± 6%. The reactive stroma analysis improved the accuracy to 65% ± 5%, clearly demonstrating that stromal parameters should be considered as additional criteria for a more accurate diagnosis.

Hollow Core-Shell Metal Oxide Heterojunctions for the Urinary Metabolic Fingerprint-Based Noninvasive Diagnostic Strategy

Urine is a preferred object for noninvasive diagnostic strategies. Urinary metabolic analysis is speculatively regarded as an ideal tool for screening diseases closely related to the genitourinary system in view of the intimate relationship between metabolomics and phenotype. Herein, we propose a urinary metabolic fingerprint-based noninvasive diagnostic strategy by designing hollow core-shell metal oxide heterojunctions (denoted as MOHs). With outstanding light absorption and electron-hole separation ability, MOHs aid in the extraction of high-performance urine metabolic fingerprints. Coupled with optimized machine learning algorithms, we establish a metabolic marker panel for accurate diagnosis of prostate cancer (PCa), which is the most common malignant tumor of the male genitourinary system, achieving accuracies of 84.72 and 83.33% in the discovery and validation sets, respectively. Furthermore, metabolite variations and related pathway analyses confirm the credibility and change correlation of key metabolic features in PCa. This work tends to advance the noninvasive diagnostic strategy toward clinical realities.

NIR-triggerable self-assembly multifunctional nanocarriers to enhance the tumor penetration and photothermal therapy efficiency for castration-resistant prostate cancer

Great challenges still remain in the management of patients with castration-resistant prostate cancer (CRPC) based on traditional treatments, and the rapid development of nanotechnology may find a breakthrough. Herein, a novel type of multifunctional self-assembly magnetic nanocarriers (IR780-MNCs) containing iron oxide nanoparticles (Fe₃O₄ NPs) and IR780 iodide was synthesized by an optimized process. With a hydrodynamic diameter of 122 nm, a surface charge of -28.5 mV and the drug loading efficiency of 89.6%, IR780-MNCs have increased cellular uptake efficiency, long-term stability, ideal photothermal conversion ability and excellent superparamagnetic behavior. The in vitro study indicated that IR780-MNCs have excellent biocompatibility and could induce significant cell apoptosis under the 808 nm laser irradiation. The in vivo study showed that IR780-MNCs highly accumulated at the tumor area could reduce the tumor volume of tumor-bearing mice by 88.5% under the 808 nm laser irradiation, but minimal damage to surrounding normal tissues. Since IR780-MNCs encapsulated a large number of 10 nm homogeneous spherical Fe₃O₄ NPs, which can be used as T₂ contrast agent, the best window for photothermal therapy can be determined through MRI. In conclusion, IR780-MNCs have initially showed excellent antitumor effect and biosafety in the treatment of CRPC. This work provides novel insights into the precise treatment of CRPC by using a safe nanoplatform based on the multifunctional nanocarriers.

MiR-124-3p inhibits tumor progression in prostate cancer by targeting EZH2

Prostate cancer (PCa) is widespread cancer with significant morbidity and mortality rates. MicroRNAs (miRNAs) have been identified as important post-transcriptional modulators in various malignancies. This study investigated the miR-124-3p effect on PCa cell proliferation, infiltration, and apoptosis. EZH2 and miR-124-3p expression levels were measured in PCa tissues. PCa cell lines DU145 and PC3 were transfected with miR-124-3p inhibitors or analogs. EZH2 and miR-124-3p linkage was validated by conducting the luciferase enzyme reporter test. The cell viability and apoptosis were assessed by flow cytometry and MTT test. Cell movement was noted during infiltration using transwell assays. EZH2, AKT, and mTOR contents were assessed using qRT-PCR and western blotting. In clinical PCa specimens, miR-124-3p and EZH2 contents were inversely correlated. Further research has demonstrated that EZH2 is the miR-124-3p direct target. Furthermore, miR-124-3p overexpression reduced EZH2 levels and lowered cell viability, infiltration, and promoted cell death, whereas miR-124-3p silencing had the opposite effect. Overexpression of miR-124-3p decreased the phosphorylation level of AKT and mTOR, whereas miR-124-3p downregulation produced the opposite result. Our findings depict that miR-124-3p prevents PCa proliferative and invasive processes while promoting apoptosis by targeting EZH2.

Clinical application of serum-based proteomics technology in human tumor research

The rapid development of proteomics technology in the past decades has led to further human understanding of tumor research, and in some ways, the technology plays a very important supporting role in the early detection of tumors. Human serum has been shown to contain a variety of proteins closely related to life activities, and the dynamic change in proteins can often reflect the physiological and pathological conditions of the body. Serum has the advantage of easy extraction, so the application of proteomics technology in serum has become a hot spot and frontier area for the study of malignant tumors. However, there are still many difficulties in the standardized use of proteomic technologies, which inevitably limit the clinical application of proteomic technologies due to the heterogeneity of human proteins leading to incomplete whole proteome populations, in addition to most serum protein markers being now not highly specific in aiding the early detection of tumors. Nevertheless, further development of proteomics technologies will greatly increase our understanding of tumor biology and help discover more new tumor biomarkers with specificity that will enable medical technology.

Tissue immunostaining of candidate prognostic proteins in metastatic and non-metastatic prostate cancer

PURPOSE

Prostate cancer (PCa) lacks specific markers capable of distinguishing aggressive tumors from those with indolent behavior. Therefore, the aim of this study was to evaluate the immunostaining of candidate proteins (PTEN, AKT, TRPM8, and NKX3.1) through the immunohistochemistry technique (IHC) on patients with metastatic and non-metastatic PCa.

METHODS

Tissues from 60 patients were divided into three groups categorized according to prognostic parameters: better prognosis (n = 20), worse prognosis (n = 23), and metastatic (n = 17). Immunostaining was analyzed by a pathologist and staining classifications were considered according to signal intensity: (0) no staining, (+) weak, and (++ and +++) intermediate to strong.

RESULTS

AKT protein was associated (p = 0.012) and correlated (p = 0.014; Tau = - 0.288) with the prognostic groups. The immunostaining for TRPM8 (p = 0.010) and NKX3.1 (p = 0.003) proteins differed between malignant tumor and non-tumoral adjacent tissue as well as for proteins in cellular locations (nucleus and cytoplasm). TRPM8 was independently associated with the ISUP grade ≥ 4 (p = 0.024; OR = 8.373; 95% CI = 1.319-53.164). The NKX3.1 showed positive and predominantly strong immunostaining in all patients in both tumoral and non-tumoral adjacent tissues. All metastatic samples had positive immunostaining, with strong intensity for NKX3.1 (p = 0.021; Tau = - 0.302). In the non-metastatic group, this strong protein staining was not observed in any patients.

CONCLUSION

This study confirmed that NKX3.1 is highly specific for prostate tissue and indicated that NKX3.1, AKT, and TRPM8 may be candidate markers for prostate cancer prognosis.

Landmarks in the evolution of prostate biopsy

Approaches and techniques used for diagnostic prostate biopsy have undergone considerable evolution over the past few decades: from the original finger-guided techniques to the latest MRI-directed strategies, from aspiration cytology to tissue core sampling, and from transrectal to transperineal approaches. In particular, increased adoption of transperineal biopsy approaches have led to reduced infectious complications and improved antibiotic stewardship. Furthermore, as image fusion has become integral, these novel techniques could be incorporated into prostate biopsy methods in the future, enabling 3D-ultrasonography fusion reconstruction, molecular targeting based on PET imaging and autonomous robotic-assisted biopsy.

Comparison of 18F-FDG PET/CT imaging with different dual time 18F-FDG PET/CT with forced diuresis in clinical diagnosis of prostate cancer

The aim of this study was to compare the capability of different dual time (interval 1, 2, 3, or 4 hours) 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) with forced diuresis to diagnose prostate cancer (PCa). A retrospective review of 273 male patients from March 2009 to June 2019, with any focal 18F-FDG uptake in the prostate gland during PET/CT imaging. Early PET/CT imaging was performed 60 minutes after FDG injection. Delayed imaging was performed 1 to 4 hours after diuretic injection. For prostate lesions with increased 18F-FDG uptake, a spheroid-shaped volume of interest was drawn, including the entire lesion, and the maximum standard uptake value (SUVmax) of the lesion was measured. The SUVmax > 2.5 after delayed imaging and the retention index > 15% were used as the diagnostic criteria for PET/CT in the diagnosis of PCa. Otherwise, it was diagnosed as the benign prostate disease. The final diagnosis was based on histological examination, associated imaging studies, or/and clinical follow-up. The results of inter-group comparison showed that the SUVmax of 1-, 2-, 3-, and 4-hour delayed imaging after diuresis in PCa group was significantly higher than that in control group (P < .05), but there was no statistical difference in SUVmax of early imaging between PCa and control group (P > .05). And the retention index of PCa group that delayed 1, 2, 3, and 4 hours after diuresis were significantly higher than those of control group, respectively (P < .05). The diagnostic sensitivity of imaging delayed 1, 2, 3, and 4 hours after diuresis was 68.8%, 81.2%, 85.7 %, and 71.4%, the specificity was 52.5%, 74.5%, 70.6%, and 65.0%, and the accuracy was respectively 58.2%, 77.4%, 76.4%, and 67.6%, the positive predictive values were 44.0%, 68.9%, 64.3%, and 58.8%, and the negative predictive value were 75.6%, 85.4%, 88.9%, and 76.5%, respectively. 18F-FDG PET/CT imaging as an imaging tool lacks certain specificity in the diagnosis of PCa, regardless of whether the imaging is delayed. The main advantage of delayed diuretic imaging in PCa is that it can significantly improve the sensitivity, especially the diagnostic effect delayed 2 hours after diuresis is better.

The Systemic Inflammation Score is Associated with the Survival of Patients with Prostate Cancer

Background

The systemic inflammation score (SIS) based on the albumin (Alb) level and lymphocyte-to-monocyte ratio (LMR), has been associated with survival in some cancers. However, its prognostic role in prostate cancer (PCa) remains unclear.

Methods

The associations between the SIS and the clinicopathological features of PCa were evaluated. The correlations between the SIS and overall survival (OS) and progression-free survival (PFS) were assessed using Kaplan-Meier analysis and the Log rank test. Univariate and multivariate Cox analyses were conducted to determine the prognostic factors for PCa. Hazard ratios and 95% confidence intervals were calculated.

Results

A total of 253 patients with PCa were included in this study. The Kaplan-Meier analysis and Log rank test suggested that patients with a higher Alb level, higher LMR, or a lower SIS had better 5-year OS and PFS compared with patients with a lower Alb level or lower LMR or higher SIS. Univariate and multivariate Cox analyses showed that drinking, prostate-specific antigen level >100 ng/mL, and neutrophil-to-lymphocyte ratio >2.09 were significant prognostic factors for OS and PFS in patients with PCa. Nomograms for 5-year OS and PFS were established with concordance index values of 0.888 and 0.824, respectively. The calibration curve was consistent between the actual observations and the prediction nomogram for OS and PFS probability at 5 years.

Conclusion

A high SIS is associated with unfavorable survival in patients with PCa. The SIS serves as a novel independent prognostic factor for OS in patients with PCa.

Value of machine learning-based transrectal multimodal ultrasound combined with PSA-related indicators in the diagnosis of clinically significant prostate cancer

OBJECTIVE

To investigate the effect of transrectal multimodal ultrasound combined with serum prostate-specific antigen (PSA)-related indicators and machine learning for the diagnosis of clinically significant prostate cancer.

METHODS

Based on Gleason score of postoperative pathological results, the subjects were divided into clinically significant prostate cancer groups(GS>6)and non-clinically significant prostate cancer groups(GS ≤ 6). The independent risk factors were obtained by univariate logistic analysis. Artificial neural network (ANN), logistic regression (LR), support vector machine (SVM), decision tree (DT), random forest (RF), and K-nearest neighbor (KNN) machine learning models were combined with clinically significant prostate cancer risk factors to establish the machine learning model, calculate the model evaluation indicators, construct the receiver operating characteristic curve (ROC), and calculate the area under the curve (AUC).

RESULTS

Independent risk factor items (P< 0.05) were entered into the machine learning model. A comparison of the evaluation indicators of the model and the area under the ROC curve showed the ANN model to be best at predicting clinically significant prostate cancer, with a sensitivity of 80%, specificity of 88.6%, F1 score of 0.897, and the AUC was 0.855.

CONCLUSION

Establishing a machine learning model by rectal multimodal ultrasound and combining it with PSA-related indicators has definite application value in predicting clinically significant prostate cancer.

Complexities of Prostate Cancer

Prostate cancer has a long disease history and a wide variety and uncertainty in individual patients' clinical progress. In recent years, we have seen a revolutionary advance in both prostate cancer patient care and in the research field. The power of deep sequencing has provided cistromic and transcriptomic knowledge of prostate cancer that has not discovered before. Our understanding of prostate cancer biology, from bedside and molecular imaging techniques, has also been greatly advanced. It is important that our current theragnostic schemes, including our diagnostic modalities, therapeutic responses, and the drugs available to target non-AR signaling should be improved. This review article discusses the current progress in the understanding of prostate cancer biology and the recent advances in diagnostic and therapeutic strategies.

Site-Specific Intact N-Linked Glycopeptide Characterization of Prostate-Specific Membrane Antigen from Metastatic Prostate Cancer Cells

The composition of N-linked glycans that are conjugated to the prostate-specific membrane antigen (PSMA) and their functional significance in prostate cancer progression have not been fully characterized. PSMA was isolated from two metastatic prostate cancer cell lines, LNCaP and MDAPCa2b, which have different tissue tropism and localization. Isolated PSMA was trypsin-digested, and intact glycopeptides were subjected to LC-HCD-EThcD-MS/MS analysis on a Tribrid Orbitrap Fusion Lumos mass spectrometer. Differential qualitative and quantitative analysis of site-specific N-glycopeptides was performed using Byonic and Byologic software. Comparative quantitative analysis demonstrates that multiple glycopeptides at asparagine residues 51, 76, 121, 195, 336, 459, 476, and 638 were in significantly different abundance in the two cell lines (p < 0.05). Biochemical analysis using endoglycosidase treatment and lectin capture confirm the MS and site occupancy data. The data demonstrate the effectiveness of the strategy for comprehensive analysis of PSMA glycopeptides. This approach will form the basis of ongoing experiments to identify site-specific glycan changes in PSMA isolated from disease-stratified clinical samples to uncover targets that may be associated with disease progression and metastatic phenotypes.

Liquid Markers Should Precede Imaging in Pre-prostate Biopsy Decision-making: Con

Liquid biomarkers have not yet reached the level of evidence to replace magnetic resonance imaging in the prebiopsy pathway for prostate cancer.

hsa_circ_0092339 acts as a molecular sponge in castration-resistant prostate cancer via the hsa-mir-940/C-MYC axis

Aims: We aimed to determine whether intronic circRNA acts as a molecular sponge in castration-resistant prostate cancer (CRPC). Materials & methods: A gene chip technique was used to conduct sequencing. A qPCR experiment was performed to verify the result. Radioimmunoprecipitation, RNA pull-down and dual-luciferase reporter assays were performed to particularly expound its function. Verification of downstream effects was carried out through qPCR and western blot, and a xenograft assay was performed in vivo for verification. Results: Intronic circRNA hsa_circ_0092339 in the nucleus was highly expressed in CRPC cell lines. hsa_circ_0092339 did not regulate the expression of its parental gene. hsa_circ_0092339 functions like a molecular sponge, preventing degradation of C-MYC mRNA by absorbing hsa-mir-940. Conclusion: hsa_circ_0092339 plays a critical role in CRPC through targeting C-MYC indirectly by absorbing hsa-mir-940.

Artificial Intelligence Algorithm-Based MRI for Differentiation Diagnosis of Prostate Cancer

The rapid increase in prostate cancer (PCa) patients is similar to that of benign prostatic hyperplasia (BPH) patients, but the treatments are quite different. In this research, magnetic resonance imaging (MRI) images under the weighted low-rank matrix restoration algorithm (RLRE) were utilized to differentiate PCa from BPH. The diagnostic effects of different sequences of MRI images were evaluated to provide a more effective examination method for the clinical differential diagnosis of PCa and BPH. 150 patients with suspected PCa were taken as the research objects. Pathological examination revealed that 137 patients had PCa and 13 patients had BPH. The pathological results were the gold standard and were compared with the MRI results of different sequences. Therefore, the accuracy of the MRI results was evaluated. The results showed that with the rise of Gaussian noise, the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) of all three algorithms gradually decreased, but the PSNR and SSIM of the RLRE algorithm were always higher than those of the RL and BM3D algorithms (P < 0.05). The sensitivity (97.08%), specificity (92.31%), accuracy (96.67%), and consistency (0.678) of the dynamic contrast enhancement (DCE) sequence were higher than those of the plain scan (86.13%, 69.23%, 84.67%, and 0.469, respectively). In conclusion, the RLRE algorithm could promote the resolution of MRI images and improve the display effect. DCE could better differentiate PCa from BPH, had great clinical application value, and was worthy of clinical promotion.

MiR-363-3p promotes prostate cancer tumor progression by targeting Dickkopf 3

BACKGROUND

Prostate cancer (PCa) is a frequent malignant tumor worldwide with high morbidity along with mortality. MicroRNAs (miRNAs) have been identified as key posttranscriptional modulators in diverse cancers. Herein, we purposed to explore the impacts of miR-363-3p on PCa growth, migration, infiltration along with apoptosis.

METHODS

The expressions of miR-363-3p along with Dickkopf 3 (DKK3) were assessed in clinical PCa specimens. We adopted the PCa cell line PC3 and transfected it using miR-363-3p repressors or mimic. The relationship of miR-363-3p with DKK3 was verified by a luciferase enzyme reporter assay. Cell viability along with apoptosis were determined by MTT assay coupled with flow cytometry analysis. Cell migration along infiltration were detected via wound healing, as well as Transwell assays. The contents of DKK3, E-cadherin, vimentin along with N-cadherin were analyzed via Western blotting accompanied with qRT-PCR.

RESULTS

MiR-363-3p was found to be inversely associated with the content of DKK3 in clinical PCa specimens. Further investigations revealed that DKK3 was miR-363-3p's direct target. Besides, overexpression of miR-363-3p decreased the contents of DKK3, promoted cell viability, migration coupled with infiltration, and reduced cell apoptosis, while silencing of miR-363-3p resulted in opposite influence. Upregulation of miR-363-3p diminished E-cadherin contents but increased vimentin along with N-cadherin protein contents in PC3 cells; in contrast, miR-363-3p downregulation produced the opposite result.

CONCLUSION

Our study indicates that miR-363-3p promotes PCa growth, migration coupled with invasion while dampening apoptosis by targeting DKK3.

Interobserver Agreement and Accuracy in Interpreting mpMRI of the Prostate: a Systematic Review

PURPOSE OF REVIEW

To present the latest evidence related to interobserver agreement and accuracy; evaluate the strengths, weaknesses, and implications of use; and outline opportunities for improvement and future development of the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) for detection of prostate cancer (PCa) on multiparametric magnetic resonance imaging (mpMRI).

RECENT FINDINGS

Our review of currently available evidence suggests that recent improvements to the PI-RADS system with PI-RADS v2.1 slightly improved interobserver agreement, with generally high sensitivity and moderate specificity for the detection of clinically significant PCa. Recent evidence additionally demonstrates substantial improvement in diagnostic specificity with PI-RADS v2.1 compared with PI-RADS v2. However, results of studies examining the comparative performance of v2.1 are limited by small sample sizes and retrospective cohorts, potentially introducing selection bias. Some studies suggest a substantial improvement between v2.1 and v2, while others report no statistically significant difference. Additionally, in PI-RADS v2.1, the interpretation and reporting of certain findings remain subjective, particularly for category 2 lesions, and reader experience continues to vary significantly. These factors further contribute to a remaining degree of interobserver variability and findings of improved performance among more experienced readers. PI-RADS v2.1 appears to show at least minimal improvement in interobserver agreement, diagnostic performance, and both sensitivity and specificity, with greater improvements seen among more experienced readers. However, given the decrescent nature of these improvements and the limited power of all studies examined, the clinical impact of this progress may be marginal. Despite improvements in PI-RADS v2.1, practitioner experience in interpreting mpMRI of the prostate remains the most important factor in prostate cancer detection.

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.

Recent advances in nanomaterials for prostate cancer detection and diagnosis

Despite the significant progress in the discovery of biomarkers and the exploitation of technologies for prostate cancer (PCa) detection and diagnosis, the initial screening of these PCa-related biomarkers using current...

Proteomic discovery of non-invasive biomarkers of localized prostate cancer using mass spectrometry

Prostate cancer is the second most frequently diagnosed non-skin cancer in men worldwide. Patient outcomes are remarkably heterogeneous and the best existing clinical prognostic tools such as International Society of Urological Pathology Grade Group, pretreatment serum PSA concentration and T-category, do not accurately predict disease outcome for individual patients. Thus, patients newly diagnosed with prostate cancer are often overtreated or undertreated, reducing quality of life and increasing disease-specific mortality. Biomarkers that can improve the risk stratification of these patients are, therefore, urgently needed. The ideal biomarker in this setting will be non-invasive and affordable, enabling longitudinal evaluation of disease status. Prostatic secretions, urine and blood can be sources of biomarker discovery, validation and clinical implementation, and mass spectrometry can be used to detect and quantify proteins in these fluids. Protein biomarkers currently in use for diagnosis, prognosis and relapse-monitoring of localized prostate cancer in fluids remain centred around PSA and its variants, and opportunities exist for clinically validating novel and complimentary candidate protein biomarkers and deploying them into the clinic.

Prostate Imaging Reporting and Data System (PI-RADS): What the radiologists need to know?

We aim to review the new modifications in MR imaging technique, image interpretation, lexicon, and scoring system of the last version of Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) in a simple and practical way. This last version of PI-RADS v2.1 describes the new technical modifications in the protocol of Multiparametric MRI (MpMRI) including T2, diffusion-weighted imaging (DWI), and dynamic contrast enhancement (DCE) parameters. It includes also; new guidelines in the image interpretation specifications in new locations (lesions located in the central zone and anterior fibromuscular stroma), clarification of T2 scoring of lesions of the transition zone, the distinction between DWI score 2 and 3 lesions in the transition zone and peripheral zone, as well as between positive and negative enhancement in DCE. Biparametric MRI (BpMRI) along with simplified PI-RADS is gaining more acceptances in the assessment of clinically significant prostatic cancer.

The emerging landscape of tumor marker panels for the identification of aggressive prostate cancer: the perspective through bibliometric analysis of an Italian translational working group in uro-oncology

Molecular heterogeneity and availability of different therapeutic strategies are relevant clinical features of prostate cancer. On this basis, there is an urgent need to identify prognostic and predictive biomarkers for an individualized therapeutic approach. In this context, researchers focused their attention on biomarkers able to discriminate potential life-threatening from organ-confined disease. Such biomarker could provide aid in clinical decision making, helping to choose the treatment which ensures the best results in terms of patient survival and quality of life. To address this need, many new laboratory tests have been proposed, with a clear tendency to use panels of combined biomarkers. In this review we evaluate current data on the application in clinical practice of the most promising laboratory tests: Phi, 4K score and Stockholm 3 as circulating biomarkers, Mi-prostate score, Exo DX Prostate and Select MD-X as urinary biomarkers, Confirm MDx, Oncotype Dx, Prolaris and Decipher as tissue biomarkers. In particular, the ability of these tests in the identification of clinically significant PCa and their potential use for precision medicine have been explored in this review.

Diagnostic Accuracy of 68Ga-PSMA PET/CT for Initial Detection in Patients With Suspected Prostate Cancer: A Systematic Review and Meta-Analysis

BACKGROUND. Early diagnosis is important in the overall management of prostate cancer (PCa). Gallium-68-labeled prostate-specific membrane antigen (PSMA) PET/CT has an established role in the detection of recurrent disease and staging of patients with intermediate- to high-risk PCa. However, only a small number of studies have evaluated its role in the initial diagnosis of PCa. OBJECTIVE. This systematic review was conducted to evaluate the diagnostic performance of 68Ga-PSMA PET/CT in the initial detection of PCa in patients with clinical or biochemical findings suspicious for PCa. EVIDENCE ACQUISITION. This systematic review followed PRISMA guidelines. Searches in PubMed, Scopus, and Embase were conducted using relevant keywords, and articles published through April 30, 2020, were included. Using histopathology results as the reference standard, the numbers of true- and false-positives and true- and false-negatives were extracted. Pooled estimates of diagnostic test accuracy-including sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and summary ROC (SROC) curve-were generated using bivariate random-effects meta-analysis. EVIDENCE SYNTHESIS. Seven studies comprising 389 patients were included in the systematic review and meta-analysis. The pooled sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio for the initial diagnosis of PCa using 68Ga-PSMA PET/CT were 0.97 (95% CI, 0.90-0.99), 0.66 (95% CI, 0.52-0.78), 2.86 (95% CI, 1.95-4.20), and 0.05 (95% CI, 0.01-0.15), respectively. The test had high accuracy; the area under the SROC curve was 0.91 (95% CI, 0.88-0.93). CONCLUSION. Gallium-68-labeled PSMA PET/CT had excellent sensitivity and negative likelihood ratio in the initial diagnosis of PCa in patients with clinical or biochemical findings suspicious for PCa. CLINICAL IMPACT. Gallium-68-labeled PSMA PET/CT had high diagnostic accuracy for the initial detection of PCa in patients with clinical or biochemical findings suspicious for PCa and has potential utility as a rule-out test for these patients.

MR method for measuring microscopic histologic soft tissue textures

PURPOSE

Provide a direct, non-invasive diagnostic measure of microscopic tissue texture in the size scale between tens of microns and the much larger scale measurable by clinical imaging. This paper presents a method and data demonstrating the ability to measure these microscopic pathologic tissue textures (histology) in the presence of subject motion in an MR scanner. This size range is vital to diagnosing a wide range of diseases.

THEORY/METHODS

MR micro-Texture (MRµT) resolves these textures by a combination of measuring a targeted set of k-values to characterize texture-as in diffraction analysis of materials, performing a selective internal excitation to isolate a volume of interest (VOI), applying a high k-value phase encode to the excited spins in the VOI, and acquiring each individual k-value data point in a single excitation-providing motion immunity and extended acquisition time for maximizing signal-to-noise ratio. Additional k-value measurements from the same tissue can be made to characterize the tissue texture in the VOI-there is no need for these additional measurements to be spatially coherent as there is no image to be reconstructed. This method was applied to phantoms and tissue specimens including human prostate tissue.

RESULTS

Data demonstrating resolution <50 µm, motion immunity, and clearly differentiating between normal and cancerous tissue textures are presented.

CONCLUSION

The data reveal textural differences not resolvable by standard MR imaging. As MRµT is a pulse sequence, it is directly translatable to MRI scanners currently in clinical practice to meet the need for further improvement in cancer imaging.

Overdiagnosis in urologic cancer : For World Journal of Urology Symposium on active surveillance in prostate and renal cancer

BACKGROUND

Cancer, which historically was diagnosed at late and incurable stages, has expanded to a heterogeneous group of conditions that vary from clinically insignificant to rapidly aggressive and lethal. This evolution is due to the widespread use of screening tests for early detection of cancer, both directed (i.e., PSA, mammography, colonoscopy) and undirected (abdominal imaging). The use of these tests has resulted in both benefits and harms. The benefits are a reduction in survival and mortality, due to significant cancers being diagnosed at a more curable stage. The harms are an increase, in some cases dramatic, in the diagnosis of clinically insignificant disease. These are called 'cancer' but not destined to affect the patient's life, even in the absence of treatment.

METHODS

Non-explicit summary of the literature on overdiagnosis of cancer.

RESULTS

The phenomenon of overdiagnosis requires two factors: the presence of a common reservoir of microfocal disease and a screening test to find it. These factors exist for breast, prostate, skin, renal, and thyroid cancers, and to a lesser degree for lung cancer. The problem of cancer overdiagnosis and overtreatment is complex, with numerous etiologies and many tradeoffs. It is a particular problem in prostate cancer but is a major issue in many other cancer sites. Screening for prostate cancer based on the best data from prospective randomized trials significantly reduces cancer mortality. However, reducing overtreatment in patients diagnosed with indolent disease is critical to the success of screening.

CONCLUSION

Active surveillance, the focus of this series of articles, is an important strategy to reduce overtreatment. This article reviews the pathological, clinical, social, and psychological aspects of overdiagnosis in cancer.