Digital Rectal Examination for Prostate Cancer Screening in Primary Care: A Systematic Review and Meta-Analysis

Digital Rectal Exam in Prostate Cancer Screening and Elevated PSA Work-up-Is there a role anymore?

PURPOSE OF REVIEW

Prostate cancer (PCa) screening tools, particularly digital rectal examination (DRE), are under scrutiny. This review assesses the utility of DRE in PCa screening.

RECENT FINDINGS

Recent studies reaffirm the DRE's sensitivity and specificity, a higher PCa detection rate with PSA in conjunction with DRE, and a slightly elevated risk of clinically significant PCa (CSPC) in those with elevated PSA and suspicious DRE. Studies confirm high accuracy of MRI in identifying CSPC, with ongoing research exploring its screening potential. DRE alone lacks accuracy for PCa screening, often resulting in missed diagnoses and unnecessary biopsies. Its supplementary use with PSA marginally increases detection rates of identifying a small percentage of CSPC, but the benefit remains questionable. Emerging evidence suggests MRI has the potential as a superior screening tool compared to DRE, although direct comparative studies are lacking. Overall, the DRE has a limited role in current PCa screening.

Natural language processing pipeline to extract prostate cancer-related information from clinical notes

OBJECTIVES

To develop an automated pipeline for extracting prostate cancer-related information from clinical notes.

MATERIALS AND METHODS

This retrospective study included 23,225 patients who underwent prostate MRI between 2017 and 2022. Cancer risk factors (family history of cancer and digital rectal exam findings), pre-MRI prostate pathology, and treatment history of prostate cancer were extracted from free-text clinical notes in English as binary or multi-class classification tasks. Any sentence containing pre-defined keywords was extracted from clinical notes within one year before the MRI. After manually creating sentence-level datasets with ground truth, Bidirectional Encoder Representations from Transformers (BERT)-based sentence-level models were fine-tuned using the extracted sentence as input and the category as output. The patient-level output was determined by compilation of multiple sentence-level outputs using tree-based models. Sentence-level classification performance was evaluated using the area under the receiver operating characteristic curve (AUC) on 15% of the sentence-level dataset (sentence-level test set). The patient-level classification performance was evaluated on the patient-level test set created by radiologists by reviewing the clinical notes of 603 patients. Accuracy and sensitivity were compared between the pipeline and radiologists.

RESULTS

Sentence-level AUCs were ≥ 0.94. The pipeline showed higher patient-level sensitivity for extracting cancer risk factors (e.g., family history of prostate cancer, 96.5% vs. 77.9%, p < 0.001), but lower accuracy in classifying pre-MRI prostate pathology (92.5% vs. 95.9%, p = 0.002) and treatment history of prostate cancer (95.5% vs. 97.7%, p = 0.03) than radiologists, respectively.

CONCLUSION

The proposed pipeline showed promising performance, especially for extracting cancer risk factors from patient's clinical notes.

CLINICAL RELEVANCE STATEMENT

The natural language processing pipeline showed a higher sensitivity for extracting prostate cancer risk factors than radiologists and may help efficiently gather relevant text information when interpreting prostate MRI.

KEY POINTS

When interpreting prostate MRI, it is necessary to extract prostate cancer-related information from clinical notes. This pipeline extracted the presence of prostate cancer risk factors with higher sensitivity than radiologists. Natural language processing may help radiologists efficiently gather relevant prostate cancer-related text information.

Development and validation of an imageless machine-learning algorithm for the initial screening of prostate cancer

PURPOSE

Prostate specific antigen (PSA) testing is a low-cost screening method for prostate cancer (PCa). However, its accuracy is limited. While progress is being made using medical imaging for PCa screening, PSA testing can still be improved as an easily accessible first step in the screening process. We aimed to develop and validate a new model by further personalizing the analysis of PSA with demographic, medical history, lifestyle parameters, and digital rectal examination (DRE) results.

METHODS

Using data from 34,224 patients in the screening arm of the PLCO trial (22,188 for the training set and 12,036 for the validation set), we applied a gradient-boosting model whose features (Model 1) were one PSA value and the personal variables available in the PLCO trial except those that signaled an ex-ante assumption of PCa. A second algorithm (Model 2) included a DRE result. The primary outcome was the occurrence of PCa, while the aggressiveness of PCa was a secondary outcome. ROC analyses were used to compare both models to other initial screening tests.

RESULTS

The areas under the curve (AUC) for Model 2 was 0.894 overall and 0.908 for patients with a suspicious DRE, compared to 0.808 for PSA for patients with a suspicious DRE. The AUC for Model 1 was 0.814 compared to 0.821 for PSA. Model 2 predicted 58% more high-risk PCa than PSA ≥4 combined with an abnormal DRE and had a positive predictive value of 74.7% (vs. 50.6%).

CONCLUSION

Personalizing the interpretation of PSA values and DRE results with a gradient-boosting model showed promising results as a potential novel, low-cost method for the initial screening of PCa. The importance of DRE, when included in such a model, was also highlighted.

Photoacoustic imaging in prostate cancer: A new paradigm for diagnosis and management

The global health issue of prostate cancer (PCa) requires better diagnosis and treatment. Photoacoustic imaging (PAI) may change PCa management. This review examines PAI's principles, diagnostic role, and therapeutic guidance. PAI uses optical light excitation and ultrasonic detection for high-resolution functional and molecular imaging. PAI uses endogenous and exogenous contrast agents to distinguish cancerous and benign prostate tissues with greater sensitivity and specificity than PSA testing and TRUS-guided biopsy. In addition to diagnosing, PAI can guide and monitor PCa therapy. Its real-time imaging allows precise biopsies and brachytherapy seed placement. Photoacoustic temperature imaging allows non-invasive monitoring of thermal therapies like cryotherapy, improving treatment precision and success. Transurethral illumination probes, innovative contrast agents, integration with other imaging modalities, and machine learning analysis are being developed to overcome depth and data complexity restrictions. PAI could become an essential tool for PCa diagnosis and therapeutic guidance as the field advances.

[Prostate cancer screening-current overview]

BACKGROUND

The harm-to-benefit ratio of prostate cancer (PCa) screening remains controversial mainly due to the unfavorable test characteristics of prostate-specific antigen (PSA) as a screening test.

METHODS

In this nonsystematic review, we present a current overview of the body of evidence on prostate cancer screening with a focus on the role of magnetic resonance imaging (MRI) of the prostate.

RESULTS

Evidence generated in large randomized controlled trials showed that PSA-based screening significantly decreases cancer-specific mortality. The main obstacle in developing and implementing PCa screening strategies is the resulting overdiagnosis and as a consequence overtreatment of indolent cancers. Opportunistic screening is characterized by an adverse benefit-to-harm ratio and should, therefore, not be recommended. The German Statutory Early Detection Program for prostate cancer, which consists of a digital rectal examination (DRE) as a stand-alone screening test, is not evidence-based, neither specific nor sensitive enough and results in unnecessary diagnostics. The European Commission recently urged member states to develop population-based and organized risk-adapted PSA-based screening programs, which are currently tested in the ongoing German PROBASE trial. Finetuning of the diagnostic pathway following PSA-testing seems key to improve its positive and negative predictive value and thereby making PCa screening more accurate. Incorporation of prostatic MRI into screening strategies leads to more accurate diagnosis of clinically significant prostate cancer, while diagnosis of indolent cancers is reduced. In the future, molecular liquid-based biomarkers have the potential to complement or even replace PSA in PCa screening and further personalize screening strategies. Active surveillance as an alternative to immediate radical therapy of demographically increasing PCa diagnoses can potentially further improve the benefit-to-harm ratio of organized screening.

CONCLUSION

Early detection of PCa should be organized on a population level into personalized and evidence-based screening strategies. Multiparametric MRI of the prostate may play a key role in this setting.

Performance of an ultra-fast deep-learning accelerated MRI screening protocol for prostate cancer compared to a standard multiparametric protocol

OBJECTIVES

To establish and evaluate an ultra-fast MRI screening protocol for prostate cancer (PCa) in comparison to the standard multiparametric (mp) protocol, reducing scan time and maintaining adequate diagnostic performance.

MATERIALS AND METHODS

This prospective single-center study included consecutive biopsy-naïve patients with suspected PCa between December 2022 and March 2023. A PI-RADSv2.1 conform mpMRI protocol was acquired in a 3 T scanner (scan time: 25 min 45 sec). In addition, two deep-learning (DL) accelerated sequences (T2- and diffusion-weighted) were acquired, serving as a screening protocol (scan time: 3 min 28 sec). Two readers evaluated image quality and the probability of PCa regarding PI-RADSv2.1 scores in two sessions. The diagnostic performance of the screening protocol with mpMRI serving as the reference standard was derived. Inter- and intra-reader agreements were evaluated using weighted kappa statistics.

RESULTS

We included 77 patients with 97 lesions (mean age: 66 years; SD: 7.7). Diagnostic performance of the screening protocol was excellent with a sensitivity and specificity of 100%/100% and 89%/98% (cut-off ≥ PI-RADS 4) for reader 1 (R1) and reader 2 (R2), respectively. Mean image quality was 3.96 (R1) and 4.35 (R2) for the standard protocol vs. 4.74 and 4.57 for the screening protocol (p < 0.05). Inter-reader agreement was moderate (κ: 0.55) for the screening protocol and substantial (κ: 0.61) for the multiparametric protocol.

CONCLUSION

The ultra-fast screening protocol showed similar diagnostic performance and better imaging quality compared to the mpMRI in under 15% of scan time, improving efficacy and enabling the implementation of screening protocols in clinical routine.

CLINICAL RELEVANCE STATEMENT

The ultra-fast protocol enables examinations without contrast administration, drastically reducing scan time to 3.5 min with similar diagnostic performance and better imaging quality. This facilitates patient-friendly, efficient examinations and addresses the conflict of increasing demand for examinations at currently exhausted capacities.

KEY POINTS

Time-consuming MRI protocols are in conflict with an expected increase in examinations required for prostate cancer screening. An ultra-fast MRI protocol shows similar performance and better image quality compared to the standard protocol. Deep-learning acceleration facilitates efficient and patient-friendly examinations, thus improving prostate cancer screening capacity.

The Performance of Different Parametric Ultrasounds in Prostate Cancer Diagnosis: Correlation with Radical Prostatectomy Specimens

BACKGROUND

Prostate cancer is a prevalent cancer among men. Multiparametric ultrasound [mpUS] is a diagnostic instrument that uses various types of ultrasounds to diagnose it. This systematic review aims to evaluate the performance of different parametric ultrasounds in diagnosing prostate cancer by associating with radical prostatectomy specimens.

METHODOLOGY

A review was performed on various ultrasound parameters using five databases. Systematic review tools were utilized to eliminate duplicates and identify relevant results. Reviewers used the Quality Assessment of Diagnostic Accuracy Results [QUADAS-2] to evaluate the bias and applicability of the study outcomes.

RESULT

Between 2012 and 2023, eleven studies were conducted to evaluate the performance of the different ultrasound parametric procedures in detecting prostate cancer using grayscale TRUS, SWE, CEUS, and mpUS. The high sensitivity of these procedures was found at 55%, 88.6%, 81%, and 74%, respectively. The specificity of these procedures was found to be 93.4%, 97%, 88%, and 59%, respectively. This high sensitivity and specificity may be associated with the large lesion size. The studies revealed that the sensitivity of these procedures in diagnosing clinically significant prostate cancer was 55%, 73%, 70%, and 74%, respectively, while the specificity was 61%, 78.2%, 62%, and 59%, respectively.

CONCLUSIONS

The mpUS procedure provides high sensitivity and specificity in PCa detection, especially for clinically significant prostate cancer.

Quantification of extravasation and binding of PSMA-targeted nanobubbles by modelling the second-wave phenomenon

PURPOSE

With about ten-fold smaller diameter than MBs, nanobubbles (NBs) were developed as new-generation ultrasound contrast agents (UCA) able to extravasate and target specific receptors expressed on extravascular cancer cells, such as the prostate-specific membrane antigen (PSMA). It has been shown that PSMA-targeted NBs (PSMA-NBs) can bind to specific prostate cancer (PCa) cells and exhibit a prolonged retention effect (PRE), observable by NB-based CEUS (NB-CEUS). However, previous analyses of PRE were mainly limited to the semi-quantitative assessment of the time-intensity curve (TIC) in an entire tumor ROI, possibly losing information on tumor spatial heterogeneity and local characteristics. When analyzing the pixel-level TICs of free NB-based CEUS, we observed a unique second-wave phenomenon: The first pass of the NB wave (bolus) is usually accompanied by a second wave in the time range of 3 to 15 min after the bolus injection. Such a phenomenon was shown to be potentially valuable in supporting the diagnostics of cancerous lesions.

PROCEDURES

Seven male athymic nude mice were included and implanted with a tumor expressing PSMA (PSMA+) and tumors not expressing PSMA (PSMA-) on two flanks. Using either free NBs or PSMA-NBs, the characteristics of pixel-level TICs were estimated by a specialized model accounting for the two-wave phenomenon, compared with a conventional model describing only one wave. The estimated parameters by the two models were presented as parametric maps to visualize the PRE of PSMA-NBs in a dual-tumor mouse model. The effectiveness of the two models were also assessed by comparing the estimated parameters in the PSMA+ and PSMA- tumors through Mann-Whitney U test and quartile difference.

RESULTS

Two parameters, the peak time and residual factor of the second wave, by the second-wave model were significantly different between PSMA+ and PSMA- tumors when using PSMA-NBs. Compared with the TICs of free NBs, TICs of PSMA-NBs present higher peak intensity and a more delayed second wave, especially in the PSMA+ tumor.

CONCLUSIONS

The estimation of parametric maps allows the estimation and visualization of specific binding of PSMA-NBs in PCa. The incorporation of the second-wave phenomenon enrich our understanding of NB kinetics in vivo and can possibly contribute to improved diagnostics of PCa in the future.

An artificial intelligence model based on transrectal ultrasound images of biopsy needle tract tissues to differentiate prostate cancer

PURPOSE

We aimed to develop an artificial intelligence (AI) model based on transrectal ultrasonography (TRUS) images of biopsy needle tract (BNT) tissues for predicting prostate cancer (PCa) and to compare the PCa diagnostic performance of the radiologist model and clinical model.

METHODS

A total of 1696 2D prostate TRUS images were involved from 142 patients between July 2021 and May 2022. The ResNet50 network model was utilized to train classification models with different input methods: original image (Whole model), BNT (Needle model), and combined image [Feature Pyramid Networks (FPN) model]. The training set, validation set, and test set were randomly assigned, then randomized 5-fold cross-validation between the training set and validation set was performed. The diagnostic effectiveness of AI models and image combination was accessed by an independent testing set. Then, the optimal AI model and image combination were selected to compare the diagnostic efficacy with that of senior radiologists and the clinical model.

RESULTS

In the test set, the area under the curve, specificity, and sensitivity of the FPN model were 0.934, 0.966, and 0.829, respectively; the diagnostic efficacy was improved compared with the Whole and Needle models, with statistically significant differences (P < 0.05), and was better than that of senior radiologists (area under the curve: 0.667). The FPN model detected more PCa compared with senior physicians (82.9% vs. 55.8%), with a 61.3% decrease in the false-positive rate and a 23.2% increase in overall accuracy (0.887 vs. 0.655).

CONCLUSION

The proposed FPN model can offer a new method for prostate tissue classification, improve the diagnostic performance, and may be a helpful tool to guide prostate biopsy.

Effect of health belief model-based educational intervention on prostate cancer prevention; knowledge, practices, and intentions

BACKGROUND

Prostate cancer screening is a crucial preventive element for improving the survival rates of prostate cancer. Therefore, our research objective was to investigate the effect of health belief model-based education on prostate cancer knowledge, health beliefs, and preventive health practices among adult and older adult males.

METHODS

A one-group pre-test/post-test quasi-experimental study design was carried out at the one-day outpatient clinics affiliated to General Alexandria Main University Hospital. We enrolled 110 men aged 45-75 years old in a health belief model-based educational intervention program. Various questionnaires were utilized to gather data before, immediately after, and three months following the intervention. These questionnaires included the socio-demographic questionnaire, Prostate Cancer Knowledge Questionnaire (PCKQ), Prostate Cancer Screening-Health Belief Model Scale (HBM-PCS), Prostate Cancer Preventive Practices Questionnaire (PCPPQ), and one question regarding the intention to undergo PC screening.

RESULTS

Participants' knowledge about prostate cancer screening improved significantly immediately after the program and this positive change was maintained at the follow-up (p = 0.000). Furthermore, participants' perceptions and preventive practices towards prostate cancer screening had changed significantly after program completion and at follow-up (p = 0.000). After program completion, many of the participants (92.7%) expressed their intention to undergo prostate cancer screening within the coming six months (p = 0.000). The younger age group (45-49 years) showed higher scores in their perception of prostate screening (p = 0.001). Higher education and income were significantly associated with higher scores in the three scales (p = 0.000 in all scales).

CONCLUSION

The study findings emphasized the effectiveness of the designed health educational program based on the HBM on PC preventive behaviors, through significantly improving participants' knowledge level, perceptions, practices, and intentions to PC screening. The program is highly recommended for prostate cancer preventive health practices among both adult and older adult males.

Precise diagnosis and risk stratification of prostate cancer by comprehensive serum metabolic fingerprints: a prediction model study

OBJECTIVES

Prostate cancer (PCa) is one of the most common malignancies in men worldwide and has caused increasing clinical morbidity and mortality, making timely diagnosis and accurate staging crucial. The authors introduced a novel approach based on mass spectrometry for precise diagnosis and stratification of PCa to facilitate clinical decision-making.

METHODS

Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry analysis of trace blood samples was combined with machine learning algorithms to construct diagnostic and stratification models. A total of 367 subjects, comprising 181 with PCa and 186 with non-PCa were enrolled. Additional 60 subjects, comprising 30 with PCa and 30 with non-PCa were enrolled as an external cohort for validation. Subsequent metabolomic analysis was carried out using Autoflex MALDI-TOF, and the mass spectra were introduced into various algorithms to construct different models.

RESULTS

Serum metabolic fingerprints were successfully obtained from 181 patients with PCa and 186 patients with non-PCa. The diagnostic model based on the eight signals demonstrated a remarkable area under curve of 100% and was validated in the external cohort with the area under curve of 87.3%. Fifteen signals were selected for enrichment analysis, revealing the potential metabolic pathways that facilitate tumorigenesis. Furthermore, the stage prediction model with an overall accuracy of 85.9% precisely classified subjects with localized disease and those with metastasis. The risk stratification model, with an overall accuracy of 89.6%, precisely classified the subjects as low-risk and high-risk.

CONCLUSIONS

Our study facilitated the timely diagnosis and risk stratification of PCa and provided new insights into the underlying mechanisms of metabolic alterations in PCa.

Prediction of Gleason score in prostate cancer patients based on radiomic features of transrectal ultrasound images

OBJECTIVES

The aim of this study was to develop a model for predicting the Gleason score of patients with prostate cancer based on ultrasound images.

METHODS

Transrectal ultrasound images of 838 prostate cancer patients from The Cancer Imaging Archive database were included in this cross-section study. Data were randomly divided into the training set and testing set (ratio 7:3). A total of 103 radiomic features were extracted from the ultrasound image. Lasso regression was used to select radiomic features. Random forest and broad learning system (BLS) methods were utilized to develop the model. The area under the curve (AUC) was calculated to evaluate the model performance.

RESULTS

After the screening, 10 radiomic features were selected. The AUC and accuracy of the radiomic feature variables random forest model in the testing set were 0.727 (95% CI, 0.694-0.760) and 0.646 (95% CI, 0.620-0.673), respectively. When PSA and radiomic feature variables were included in the random forest model, the AUC and accuracy of the model were 0.770 (95% CI, 0.740-0.800) and 0.713 (95% CI, 0.688-0.738), respectively. While the BLS method was utilized to construct the model, the AUC and accuracy of the model were 0.726 (95% CI, 0.693-0.759) and 0.698 (95% CI, 0.673-0.723), respectively. In predictions for different Gleason grades, the highest AUC of 0.847 (95% CI, 0.749-0.945) was found to predict Gleason grade 5 (Gleason score ≥9).

CONCLUSIONS

A model based on transrectal ultrasound image features showed a good ability to predict Gleason scores in prostate cancer patients.

ADVANCES IN KNOWLEDGE

This study used ultrasound-based radiomics to predict the Gleason score of patients with prostate cancer.

Impact of Prostate Cancer in Eastern Europe and Approaches to Treatment and Policy

Prostate cancer is among the most prevalent cancer globally and within Eastern Europe, where there are also higher levels of mortality compared with Western Europe. Cancer control plans exist in most countries in the region. Attention should be given to devising and implementing optimal screening initiatives. Our review has identified that a lack of resources and health system dysfunctions hamper progress in ameliorating the burden of prostate cancer. Regional cooperation is needed as well as drawing on guidelines and findings from elsewhere. Health institutions must also know the latest developments and set up systems that allow swift adoption.

Comparing the Performance of Digital Rectal Examination and Prostate-specific Antigen as a Screening Test for Prostate Cancer: A Systematic Review and Meta-analysis

BACKGROUND AND OBJECTIVE

Although digital rectal examination (DRE) is recommended in combination with prostate-specific antigen (PSA) for detection of prostate cancer (PCa), there are limited data to support its use as a screening/early detection test. Our objective was to assess the diagnostic value of DRE in screening for early detection of PCa.

METHODS

In August 2023, we queried the PubMed, Scopus, and Web of Science databases to identify prospective studies simultaneously investigating the diagnostic performance of DRE and PSA for PCa screening. The primary endpoints were the positive predictive value (PPV) and cancer detection rate (CDR) of DRE. Secondary endpoints included the PPV and CDR of both PSA alone and in combination with DRE. We conducted meta-regression analysis to compare the CDR and PPV of different screening strategies. This meta-analysis is registered on PROSPERO (CRD42023446940).

KEY FINDINGS AND LIMITATIONS

We identified eight studies involving 85 738 participants, of which three were randomized controlled trials and five were prospective diagnostic studies, that reported the PPV and CDR of both DRE and PSA for the same cohort. Our analysis revealed a pooled PPV of 0.21 (95% confidence interval [CI] 0.13-0.33) for DRE, which is similar to the PPV of PSA (0.22, 95% CI 0.15-0.30; p = 0.9), with no benefit from combining DRE and PSA (PPV 0.19, 95% CI 0.13-0.26; p = 0.5). However, the CDR of DRE (0.01, 95% CI: 0.01-0.02) was significantly lower than that of PSA (0.03, 95% CI 0.02-0.03; p < 0.05) and the combination of DRE and PSA (0.03, 95% CI 0.02-0.04; p < 0.05). The screening strategy combining DRE and PSA was not different to that of PSA alone in terms of CDR (p = 0.5) and PPV (p = 0.5).

CONCLUSIONS AND CLINICAL IMPLICATIONS

Our comprehensive review and meta-analysis indicates that both as an independent test and as a supplementary measure to PSA for PCa detection, DRE exhibits a notably low diagnostic value. The collective findings from the included studies suggest that, in the absence of clinical symptoms and signs, DRE could be potentially omitted from PCa screening and early detection strategies.

PATIENT SUMMARY

Our review shows that the screening performance of digital rectal examination for detection of prostate cancer is not particularly impressive, suggesting that it might not be necessary to conduct this examination routinely.

68Ga-prostate specific membrane antigen-11 PET/CT versus multiparametric MRI in the detection of primary prostate cancer: A systematic review and head-to-head comparative meta-analysis

PURPOSE

The goal of this study was to evaluate the effectiveness of two diagnostic methods, 68Ga-PSMA-11 PET/CT and mpMRI, in detecting primary prostate cancer without limitations on the Gleason score.

METHODS

We conducted a comprehensive literature review, searching databases such as PubMed, Embase, and Web of Science until June 2023. Our objective was to identify studies that compared the efficacy of 68Ga-PSMA-11 PET/CT and mpMRI in detecting primary prostate cancer. To determine heterogeneity, the I2 statistic was used. Meta-regression analysis and leave-one-out sensitivity analysis were conducted to identify potential sources of heterogeneity.

RESULTS

Initially, 1286 publications were found, but after careful evaluation, only 16 studies involving 1227 patients were analyzed thoroughly. The results showed that the 68Ga-PSMA-11 PET/CT method had a pooled sensitivity and specificity of 0.87 (95 % CI: 0.80-0.92) and 0.80 (95 % CI: 0.69-0.89), respectively, for diagnosing prostatic cancer. Similarly, the values for mpMRI were determined as 0.84 (95 % CI: 0.75-0.92) and 0.74 (95 % CI: 0.61-0.86), respectively. There were no significant differences in diagnostic effectiveness observed when comparing two primary prostate cancer methodologies (pooled sensitivity P = 0.62, pooled specificity P = 0.50). Despite this, the funnel plots showed symmetry and the Egger test results (P values > 0.05) suggested there was no publication bias.

CONCLUSIONS

After an extensive meta-analysis, it was found that both 68Ga-PSMA-11 PET/CT and mpMRI demonstrate similar diagnostic effectiveness in detecting primary prostate cancer. Future larger prospective studies are warranted to investigate this issue further.

Machine learning based on radiomics features combing B-mode transrectal ultrasound and contrast-enhanced ultrasound to improve peripheral zone prostate cancer detection

PURPOSE

To construct machine learning models based on radiomics features combing conventional transrectal ultrasound (B-mode) and contrast-enhanced ultrasound (CEUS) to improve prostate cancer (PCa) detection in peripheral zone (PZ).

METHODS

A prospective study of 166 men (72 benign, 94 malignant lesions) with targeted biopsy-confirmed pathology who underwent B-mode and CEUS examinations was performed. Risk factors, including age, serum total prostate-specific antigen (tPSA), free PSA (fPSA), f/t PSA, prostate volume and prostate-specific antigen density (PSAD), were collected. Time-intensity curves were obtained using SonoLiver software for all lesions in regions of interest. Four parameters were collected as risk factors: the maximum intensity (IMAX), rise time (RT), time to peak (TTP), and mean transit time (MTT). Radiomics features were extracted from the target lesions from B-mode and CEUS imaging. Multivariable logistic regression analysis was used to construct the model.

RESULTS

A total of 3306 features were extracted from seven categories. Finally, 32 features were screened out from radiomics models. Five models were developed to predict PCa: the B-mode radiomics model (B model), CEUS radiomics model (CEUS model), B-CEUS combined radiomics model (B-CEUS model), risk factors model, and risk factors-radiomics combined model (combined model). Age, PSAD, tPSA, and RT were significant independent predictors in discriminating benign and malignant PZ lesions (P < 0.05). The risk factors model combing these four predictors showed better discrimination in the validation cohort (area under the curve [AUC], 0.84) than the radiomics images (AUC, 0.79 on B model; AUC, 0.78 on CEUS model; AUC, 0.83 on B-CEUS model), and the combined model (AUC: 0.89) achieved the greatest predictive efficacy.

CONCLUSION

The prediction model including B-mode and CEUS radiomics signatures and risk factors represents a promising diagnostic tool for PCa detection in PZ, which may contribute to clinical decision-making.

Targeted Therapy for Prostate Cancer by Prostate-Specific Membrane Antigen-Targeted Small-Molecule Drug Conjugates

In the aging global population, prostate cancer is a worldwide health problem because the incidence rate of this disease increases at advanced ages. Although early-stage prostate cancer can be treated by total prostatectomy, the surgery causes side effects, such as incontinence and dysuria, that lower QOL. Once the disease progresses to metastatic castration-resistant prostate cancer (mCRPC), there are no effective chemotherapeutic agents without systematic side effects. Therefore, targeted therapies for mCPRC are urgently needed. Traditional antibody-drug conjugate treatments for prostate cancer have been tested in clinical trials and several side effects have been observed. Meanwhile, small-molecule drug conjugates (SMDCs) have certain advantages over antibody drug conjugates in terms of non-immunogenicity, reproducibility, and permeability. In this review, prostate-specific membrane antigen-targeted SMDCs for treating prostate cancer are summarized.

Quantifying the Impact of Cancer on the Viscoelastic Properties of the Prostate Gland using a Quasi-Linear Viscoelastic Model

Pathological disorders can alter the mechanical properties of biological tissues, and studying such changes can help to better understand the disease progression. The prostate gland is no exception, as previous studies have shown that cancer can affect its mechanical properties. However, most of these studies have focused on the elastic properties of the tissue and have overlooked the impact of cancer on its viscous response. To address this gap, we used a quasi-linear viscoelastic model to investigate the impact of cancer on both the elastic and viscous characteristics of the prostate gland. By comparing the viscoelastic properties of segments influenced by cancer and those unaffected by cancer in 49 fresh prostates, removed within two hours after prostatectomy surgery, we were able to determine the influence of cancer grade and tumor volume on the tissue. Our findings suggest that tumor volume significantly affects both the elastic modulus and viscosity of the prostate (p-value less than 2%). Specifically, we showed that cancer increases Young's modulus and shear relaxation modulus by 20%. These results have implications for using mechanical properties of the prostate as a potential biomarker for cancer. However, developing an in vivo apparatus to measure these properties remains a challenge that needs to be addressed in future research. STATEMENT OF SIGNIFICANCE: This study is the first to explore how cancer impacts the mechanical properties of prostate tissues using a quasi-linear viscoelastic model. We examined 49 fresh prostate samples collected immediately after surgery and correlated their properties with cancer presence identified in pathology reports. Our results demonstrate a 20% change in the viscoelastic properties of the prostate due to cancer. We initially validated our approach using tissue-mimicking phantoms and then applied it to differentiate between cancerous and normal prostate tissues. These findings offer potential for early cancer detection by assessing these properties. However, conducting these tests in vivo remains a challenge for future research.

The Potential of Extracellular Matrix- and Integrin Adhesion Complex-Related Molecules for Prostate Cancer Biomarker Discovery

Prostate cancer is among the top five cancer types according to incidence and mortality. One of the main obstacles in prostate cancer management is the inability to foresee its course, which ranges from slow growth throughout years that requires minimum or no intervention to highly aggressive disease that spreads quickly and resists treatment. Therefore, it is not surprising that numerous studies have attempted to find biomarkers of prostate cancer occurrence, risk stratification, therapy response, and patient outcome. However, only a few prostate cancer biomarkers are used in clinics, which shows how difficult it is to find a novel biomarker. Cell adhesion to the extracellular matrix (ECM) through integrins is among the essential processes that govern its fate. Upon activation and ligation, integrins form multi-protein intracellular structures called integrin adhesion complexes (IACs). In this review article, the focus is put on the biomarker potential of the ECM- and IAC-related molecules stemming from both body fluids and prostate cancer tissue. The processes that they are involved in, such as tumor stiffening, bone turnover, and communication via exosomes, and their biomarker potential are also reviewed.

Clinical stage and grade migration of localized prostate cancer at diagnosis during the past decade

OBJECTIVES

Early 2010s data suggest a reverse stage and grade migration towards more aggressive prostate cancer (PCa) at diagnosis, accelerated by the 2012 US Preventive Services Task Force recommendation against PSA screening. Using the National Cancer Database, we investigated the impact of the 2018 USPSTF recommendation and the COVID-19 outbreak on this shift. We hypothesized that the COVID-19 outbreak would further contribute to a stage and grade migration towards more aggressive disease.

MATERIAL AND METHODS

We identified men with localized PCa diagnosed between 2010 and 2020. We analyzed the shift in the proportion of PCa stratified according to D'Amico risk classification. We used multivariable logistic regression models to assess the association between year of diagnosis and dichotomous variables related to clinical stage and grade of PCa. Predicted probabilities with 95% CI were computed through marginal effect analyses.

RESULTS

We identified 910,898 men with localized PCa. The proportion of low-risk PCa almost halved from 34.9% in 2010 to 17.7% in 2020 (P < 0.001). Compared to 2010, we found in each year increased odds of: PSA≥10 ng/dL starting from 2012 (aOR2012 1.05; 95% CI, 1.02-1.08); cT3-T4 starting from 2015 (aOR2015 1.10; 95% CI, 1.03-1.17); ISUP GG 3-5 starting from 2011 (aOR2011 1.06; 95% CI, 1.03-1.08); and consequently, D'Amico intermediate/high-risk class starting from 2011 (aOR2011 1.03; 95% CI, 1.01-1.05). Fluctuations in the probabilities of PSA≥10 ng/dL and cT3-T4 at diagnosis were observed over time (all P < 0.001). The probability of PSA≥10 ng/dL peaked at 29.0% (95% CI, 28.0%-29.0%) in 2018, while the probability of cT3-T4 peaked at 3.7% (95% CI, 3.6%-3.8%) in 2020. All other outcome variables demonstrated a consistent upward shift (all P < 0.001), with the highest probabilities in 2020 for ISUP GG 3-5 (42.3%, 95% CI, 41.9%-42.6%) and D'Amico intermediate/high-risk (81.3%, 95% CI, 81.0%-81.6%).

CONCLUSIONS

Our study confirms an enduring shift towards a higher proportion of aggressive PCa at diagnosis, likely influenced by the COVID-19 pandemic. The impact of the 2018 USPSTF PCa screening recommendation on the proportion of aggressive PCa seems restricted and likely affected by the pandemic outbreak. Future investigations should evaluate the long-term effects of the 2018 USPSTF recommendations in the postpandemic setting.

Digital Rectal Examination Is Not a Useful Screening Test for Prostate Cancer

BACKGROUND

Annual digital rectal examination (DRE) is recommended as a stand-alone screening test for prostate cancer (PCa) in Germany for 45+ yr olds. DRE diagnostic performance in men as young as 45 yr old has not been proved by a screening trial.

OBJECTIVE

To determine DRE diagnostic performance in a screening trial.

DESIGN, SETTING, AND PARTICIPANTS

This analysis was conducted within the multicentric, randomized PROBASE trial, which enrolled >46 000 men at age 45 to test risk-adapted prostate-specific antigen (PSA) screening for PCa.

INTERVENTION

(1) DRE was analyzed as a one-time, stand-alone screening offer at age 45 in 6537 men in one arm of the trial and (2) PCa detection by DRE was evaluated at the time of PSA-screen-driven biopsies (N = 578).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

(1) True-/false-positive detection rates of DRE as compared with PSA screening and (2) DRE outcome at the time of a prostate biopsy were evaluated.

RESULTS AND LIMITATIONS

(1) A prospective analysis of 57 men with suspicious DRE at age 45 revealed three PCa. Detection rate by DRE was 0.05% (three of 6537) as compared with a four-fold higher rate by PSA screening (48 of 23 301, 0.21%). The true-positive detection rate by DRE relative to screening by PSA was 0.22 (95% confidence interval [CI] = [0.07-0.72]) and the false-positive detection rate by DRE was 2.2 (95% CI = [1.50-3.17]). (2) Among PSA-screen-detected PCa cases, 86% had unsuspicious DRE (sensitivity relative to PSA was 14%), with the majority of these tumors (86%) located in the potentially accessible zones of the prostate as seen by magnetic resonance imaging.

CONCLUSIONS

The performance of stand-alone DRE to screen for PCa is poor. DRE should not be recommended as a PCa screening test in young men. Furthermore, DRE does not improve the detection of PSA-screen-detected PCa.

PATIENT SUMMARY

Our report demonstrated the poor diagnostic performance of digital rectal examination in the screening for prostate cancer in young men.

A transfer learning nomogram for predicting prostate cancer and benign conditions on MRI

BACKGROUND

Deep learning has been used to detect or characterize prostate cancer (PCa) on medical images. The present study was designed to develop an integrated transfer learning nomogram (TLN) for the prediction of PCa and benign conditions (BCs) on magnetic resonance imaging (MRI).

METHODS

In this retrospective study, a total of 709 patients with pathologically confirmed PCa and BCs from two institutions were included and divided into training (n = 309), internal validation (n = 200), and external validation (n = 200) cohorts. A transfer learning signature (TLS) that was pretrained with the whole slide images of PCa and fine-tuned on prebiopsy MRI images was constructed. A TLN that integrated the TLS, the Prostate Imaging-Reporting and Data System (PI-RADS) score, and the clinical factor was developed by multivariate logistic regression. The performance of the TLS, clinical model (CM), and TLN were evaluated in the validation cohorts using the receiver operating characteristic (ROC) curve, the Delong test, the integrated discrimination improvement (IDI), and decision curve analysis.

RESULTS

TLS, PI-RADS score, and age were selected for TLN construction. The TLN yielded areas under the curve of 0.9757 (95% CI, 0.9613-0.9902), 0.9255 (95% CI, 0.8873-0.9638), and 0.8766 (95% CI, 0.8267-0.9264) in the training, internal validation, and external validation cohorts, respectively, for the discrimination of PCa and BCs. The TLN outperformed the TLS and the CM in both the internal and external validation cohorts. The decision curve showed that the TLN added more net benefit than the CM.

CONCLUSIONS

The proposed TLN has the potential to be used as a noninvasive tool for PCa and BCs differentiation.

Clinical-Genomic Risk Group Classification of Suspicious Lesions on Prostate Multiparametric-MRI

The utilization of multi-parametric MRI (mpMRI) in clinical decisions regarding prostate cancer patients' management has recently increased. After biopsy, clinicians can assess risk using National Comprehensive Cancer Network (NCCN) risk stratification schema and commercially available genomic classifiers, such as Decipher. We built radiomics-based models to predict lesions/patients at low risk prior to biopsy based on an established three-tier clinical-genomic classification system. Radiomic features were extracted from regions of positive biopsies and Normally Appearing Tissues (NAT) on T2-weighted and Diffusion-weighted Imaging. Using only clinical information available prior to biopsy, five models for predicting low-risk lesions/patients were evaluated, based on: 1: Clinical variables; 2: Lesion-based radiomic features; 3: Lesion and NAT radiomics; 4: Clinical and lesion-based radiomics; and 5: Clinical, lesion and NAT radiomic features. Eighty-three mpMRI exams from 78 men were analyzed. Models 1 and 2 performed similarly (Area under the receiver operating characteristic curve were 0.835 and 0.838, respectively), but radiomics significantly improved the lesion-based performance of the model in a subset analysis of patients with a negative Digital Rectal Exam (DRE). Adding normal tissue radiomics significantly improved the performance in all cases. Similar patterns were observed on patient-level models. To the best of our knowledge, this is the first study to demonstrate that machine learning radiomics-based models can predict patients' risk using combined clinical-genomic classification.

The Olfaction Ability of Medical Detection Canine to Detect Prostate Cancer From Urine Samples: Progress Captured in Systematic Review and Meta-Analysis

Background

To date, early cancer detection is considered vital to reduce the global cancer burden through low-cost, but accurate screening modalities. The anatomical positioning of prostate cancer (PCa) created a potentially distinctive diagnostic method through the identification of volatile organic compounds (VOCs) in urine, which might be detectable not by humans but by canine species. This review aimed to capture the potential of the medical detection canine (MDC) to detect PCa by providing its diagnostic accuracy estimation on urine odor testing.

Methods

Databases, e.g., MEDLINE, Cochrane, ScienceDirect, and ProQuest, were searched to identify the studies. We focused on accessible original research, comparing the diagnostic utility of trained female MDC and histopathology examination as the gold standard for PCa diagnosis. The statistical analysis was performed in Meta-DiSc 1.4 and presented in diagnostic values, i.e., sensitivity (Sn), specificity (Sp), positive or negative likelihood ratio (LR+ or LR-), diagnostic odd ratio (DOR), and area under the curve (AUC) value, to conclude the Sn-Sp in a single outcome.

Results

Female German Shepherds were the most commonly utilized MDC from the five studies included in the final analysis. We estimate the pooled diagnostic value of eight different MDCs, with the findings as follows: Sn (0.95 (0.94 - 0.97)), Sp (0.92 (0.90 - 0.93)), LR+ (4.48 (1.90 - 10.58)), LR- (0.12 (0.01 - 1.42)), DOR (35.39 (2.90 - 432.53)), and an AUC value of 0.9232.

Conclusions

MDC's olfaction ability holds considerable potential on its diagnostic accuracies to distinguish the urine of PCa individuals by identifying its volatilome property.

Delta radiomic patterns on serial bi-parametric MRI are associated with pathologic upgrading in prostate cancer patients on active surveillance: preliminary findings

Objective

The aim of this study was to quantify radiomic changes in prostate cancer (PCa) progression on serial MRI among patients on active surveillance (AS) and evaluate their association with pathologic progression on biopsy.

Methods

This retrospective study comprised N = 121 biopsy-proven PCa patients on AS at a single institution, of whom N = 50 at baseline conformed to the inclusion criteria. ISUP Gleason Grade Groups (GGG) were obtained from 12-core TRUS-guided systematic biopsies at baseline and follow-up. A biopsy upgrade (AS+) was defined as an increase in GGG (or in number of positive cores) and no upgrade (AS-) was defined when GGG remained the same during a median period of 18 months. Of N = 50 patients at baseline, N = 30 had MRI scans available at follow-up (median interval = 18 months) and were included for delta radiomic analysis. A total of 252 radiomic features were extracted from the PCa region of interest identified by board-certified radiologists on 3T bi-parametric MRI [T2-weighted (T2W) and apparent diffusion coefficient (ADC)]. Delta radiomic features were computed as the difference of radiomic feature between baseline and follow-up scans. The association of AS+ with age, prostate-specific antigen (PSA), Prostate Imaging Reporting and Data System (PIRADS v2.1) score, and tumor size was evaluated at baseline and follow-up. Various prediction models were built using random forest (RF) classifier within a threefold cross-validation framework leveraging baseline radiomics (Cbr), baseline radiomics + baseline clinical (Cbrbcl), delta radiomics (CΔr), delta radiomics + baseline clinical (CΔrbcl), and delta radiomics + delta clinical (CΔrΔcl).

Results

An AUC of 0.64 ± 0.09 was obtained for Cbr, which increased to 0.70 ± 0.18 with the integration of clinical variables (Cbrbcl). CΔr yielded an AUC of 0.74 ± 0.15. Integrating delta radiomics with baseline clinical variables yielded an AUC of 0.77 ± 0.23. CΔrΔclresulted in the best AUC of 0.84 ± 0.20 (p < 0.05) among all combinations.

Conclusion

Our preliminary findings suggest that delta radiomics were more strongly associated with upgrade events compared to PIRADS and other clinical variables. Delta radiomics on serial MRI in combination with changes in clinical variables (PSA and tumor volume) between baseline and follow-up showed the strongest association with biopsy upgrade in PCa patients on AS. Further independent multi-site validation of these preliminary findings is warranted.

Biomolecule-functionalized nanoformulations for prostate cancer theranostics

BACKGROUND

Even with the advancement in the areas of cancer nanotechnology, prostate cancer still poses a major threat to men's health. Nanomaterials and nanomaterial-derived theranostic systems have been explored for diagnosis, imaging, and therapy for different types of cancer still, for prostate cancer they have not delivered at full potential because of the limitations like in vivo biocompatibility, immune responses, precise targetability, and therapeutic outcome associated with the nanostructured system.

AIM OF REVIEW

Functionalizing nanomaterials with different biomolecules and bioactive agents provides advantages like specificity towards cancerous tumors, improved circulation time, and modulation of the immune response leading to early diagnosis and targeted delivery of cargo at the site of action.

KEY SCIENTIFIC CONCEPTS OF REVIEW

In this review, we have emphasized the classification and comparison of various nanomaterials based on biofunctionalization strategy and source of biomolecules such that it can be used for possible translation in clinical settings and future developments. This review highlighted the opportunities for embedding highly specific biological targeting moieties (antibody, aptamer, oligonucleotides, biopolymer, peptides, etc.) on nanoparticles which can improve the detection of prostate cancer-associated biomarkers at a very low limit of detection, direct visualization of prostate tumors and lastly for its therapy. Lastly, special emphasis was given to biomimetic nanomaterials which include functionalization with extracellular vesicles, exosomes and viral particles and their application for prostate cancer early detection and drug delivery. The present review paves a new pathway for next-generation biofunctionalized nanomaterials for prostate cancer theranostic application and their possibility in clinical translation.

Evaluation of Patients Referred for Abnormal Digital Rectal Examination With Normal Prostate-Specific Antigen on Best Timed Pathway for Prostate Cancer

Introduction Currently, there is no recommendation for adjustments to the Best Timed Pathway for Prostate cancer (BTiPP) depending on whether the referral is for raised prostate-specific antigen (PSA) or malignant-feeling prostate on digital rectal examination (DRE). Therefore, all patients undergo MRI scanning. We aim to establish if patients with abnormal DRE only (without raised PSA) should have an adjusted pathway by comparing the biopsy rate and diagnostic yield after an MRI scan. Methods All BTiPP 2021 referral patient notes were reviewed. The patients were categorized into the aDRE group (abnormal DRE with normal PSA) or the rPSA group (raised PSA with or without abnormal DRE). Data and results for MRI and prostate biopsy were evaluated. Diagnostic yield was defined as the percentage of patients who underwent an MRI, who were diagnosed with biopsy-proven cancer. Results 68.5% (74/108) and 70.9% (282/398) of patients underwent upfront MRI in the aDRE and rPSA groups, respectively. Following MRI, the biopsy rate (28.4% (21/74) vs. 42.9% (121/282) (p=0.02)) and the biopsy-proven diagnostic yield (20.3% (15/74) vs. 36.9% (104/282) (p<0.01)) were both significantly lower in the aDRE group. 58% (43/74) of patients in the aDRE group had no posterior lesions on MRI. Only 6.7% (1/15) of biopsy-proven cancers in the aDRE group were solely anterior. Conclusions After MRI, the biopsy rate and diagnostic yield were significantly lower in the aDRE group compared to the rPSA group. Furthermore, a majority of patients referred for aDRE had a normal posterior prostate appearance on MRI. An adjusted pathway for patients referred for aDRE with normal PSA, with DRE by a urologist prior to MRI, should be considered as it would likely reduce unnecessary investigations, treatment, and patient anxiety. These data suggest that this would not risk missing significant cancers.

A Qualitative Study of Barriers to Anal Cancer Screenings in US Veterans Living with HIV

People living with human immunodeficiency virus (HIV) are at high risk for anal cancer. Anal cancer screenings are recommended annually for US veterans with HIV. Screenings can identify treatable precursor lesions and prevent cancer development. In a previous study, we found screening rate to be only 15%. Semistructured interviews were conducted with Veterans Affairs (VA) providers who treat veterans living with HIV. Participants described their experiences with anal cancer screenings. Researchers developed a codebook based on Theoretical Domains Framework (TDF) and coded data using thematic analysis to identify barriers to anal cancer screenings. Twenty-three interviews were conducted with VA providers representing 10 regions. Barriers identified corresponded with five targetable TDF domains: Knowledge, Skills, Environmental Context/Resources, Professional Roles/Identities, and Social Influence. Many providers lacked knowledge of screening protocols. Knowledgeable providers often lacked needed resources, including swabs, clinic space, reliable pathology, access to high-resolution anoscopy, or leadership support to implement a screening program. Providers mentioned competing priorities in the care of veterans with HIV infection and lack of skilled/trained personnel to perform the tests. It was often unclear which provider specialty should "own" screening responsibilities. Additional factors included patient discomfort with screening exams. Anal cancer screening protocols are recommended but not widely adopted in VA. There is a critical need to address barriers to anal cancer screenings in veterans. The TDF domains identified align with five intervention domains to target, including education, training, resource/environment, delineation of provider roles, and improved counseling efforts. Targeting these barriers may help improve the uptake of anal cancer screenings within VA.

Prostate Cancer: Genetics, Epigenetics and the Need for Immunological Biomarkers

Epidemiological data highlight prostate cancer as a significant global health issue, with high incidence and substantial impact on patients' quality of life. The prevalence of this disease is associated with various factors, including age, heredity, and race. Recent research in prostate cancer genetics has identified several genetic variants that may be associated with an increased risk of developing the disease. However, despite the significance of these findings, genetic markers for prostate cancer are not currently utilized in clinical practice as reliable indicators of the disease. In addition to genetics, epigenetic alterations also play a crucial role in prostate cancer development. Aberrant DNA methylation, changes in chromatin structure, and microRNA (miRNA) expression are major epigenetic events that influence oncogenesis. Existing markers for prostate cancer, such as prostate-specific antigen (PSA), have limitations in terms of sensitivity and specificity. The cost of testing, follow-up procedures, and treatment for false-positive results and overdiagnosis contributes to the overall healthcare expenditure. Improving the effectiveness of prostate cancer diagnosis and prognosis requires either narrowing the risk group by identifying new genetic factors or enhancing the sensitivity and specificity of existing markers. Immunological biomarkers (both circulating and intra-tumoral), including markers of immune response and immune dysfunction, represent a potentially useful area of research for enhancing the diagnosis and prognosis of prostate cancer. Our review emphasizes the need for developing novel immunological biomarkers to improve the diagnosis, prognosis, and management of prostate cancer. We highlight the most recent achievements in the identification of biomarkers provided by circulating monocytes and tumor-associated macrophages (TAMs). We highlight that monocyte-derived and TAM-derived biomarkers can enable to establish the missing links between genetic predisposition, hormonal metabolism and immune responses in prostate cancer.

Prospective analysis of the diagnostic accuracy of digital rectal examination and magnetic resonance imaging for T staging of prostate cancer

Background

Accurate staging of prostate cancer (PCa) is the basis for the risk stratification to select targeted treatment. Therefore, this study aimed to compare the diagnostic accuracy rates of magnetic resonance imaging (MRI) and digital rectal examination (DRE) for preoperative T staging of potentially resectable PCa.

Methods

From March 2021 to March 2022, patients with PCa with T staging by prostate biopsy were included. All examinations used postoperative histopathologic T staging as the reference standard. All patients underwent DRE and MRI before the puncture. Two blinded urologists and radiologists independently evaluated DRE and MRI, respectively. Before the examination, patients were then divided into early- (T1, T2) and late-(T3, T4) stage cancer. Analysis of a paired sample sign test was performed to determine differences between DRE and MRI.

Results

A total of 136 study participants with PCa were evaluated histopathologically, of whom 71% (97/136) and 29% (39/136) were at the early- and late-stage cancer, respectively. MRI had a significantly higher accuracy (91.9% vs. 76.5%, P < 0.001) compared with DRE. Further, MRI showed a higher sensitivity than DRE to diagnose early PCa (92.8% vs. 74.2%; P < 0.001). However, the specificity was not significantly different between them (89.7% vs. 82.1%; P = 0.375). Area under the curve (receiver operating curve) values were calculated as 0.78 ± 0.038 (95% confidence interval [CI], 0.71-0.86), 0.91 ± 0.028 (95% CI, 0.86-0.97), and 0.872 ± 0.028 (95% CI, 0.80-0.92) for DRE-, MRI-, MRI + DRE-based PCa predictions, respectively. The prediction performance of MRI was better than that of DRE (DeLong test, z = 3.632, P = 0.0003) and MRI + DRE (DeLong test, z = 3.715, P = 0.0002).

Conclusion

For resectable PCa, the diagnostic potential of MRI in assessing the T stage was higher than that of DRE. However, DRE is still valuable, especially for patients with locally advanced PCa.

Advancements in MRI-Based Radiomics and Artificial Intelligence for Prostate Cancer: A Comprehensive Review and Future Prospects

The use of multiparametric magnetic resonance imaging (mpMRI) has become a common technique used in guiding biopsy and developing treatment plans for prostate lesions. While this technique is effective, non-invasive methods such as radiomics have gained popularity for extracting imaging features to develop predictive models for clinical tasks. The aim is to minimize invasive processes for improved management of prostate cancer (PCa). This study reviews recent research progress in MRI-based radiomics for PCa, including the radiomics pipeline and potential factors affecting personalized diagnosis. The integration of artificial intelligence (AI) with medical imaging is also discussed, in line with the development trend of radiogenomics and multi-omics. The survey highlights the need for more data from multiple institutions to avoid bias and generalize the predictive model. The AI-based radiomics model is considered a promising clinical tool with good prospects for application.

SSPT-bpMRI: A Self-supervised Pre-training Scheme for Improving Prostate Cancer Detection and Diagnosis in Bi-parametric MRI. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023;2023:1-4. [PMID: 38083363 DOI: 10.1109/embc40787.2023.10340280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Prostate cancer (PCa) is one of the most prevalent cancers in men. Early diagnosis plays a pivotal role in reducing the mortality rate from clinically significant PCa (csPCa). In recent years, bi-parametric magnetic resonance imaging (bpMRI) has attracted great attention for the detection and diagnosis of csPCa. bpMRI is able to overcome some limitations of multi-parametric MRI (mpMRI) such as the use of contrast agents, the time-consuming for imaging and the costs, and achieve detection performance comparable to mpMRI. However, inter-reader agreements are currently low for prostate MRI. Advancements in artificial intelligence (AI) have propelled the development of deep learning (DL)-based computer-aided detection and diagnosis system (CAD). However, most of the existing DL models developed for csPCa identification are restricted by the scale of data and the scarcity in labels. In this paper, we propose a self-supervised pre-training scheme named SSPT-bpMRI with an image restoration pretext task integrating four different image transformations to improve the performance of DL algorithms. Specially, we explored the potential value of the self-supervised pre-training in fully supervised and weakly supervised situations. Experiments on the publicly available PI-CAI dataset demonstrate that our model outperforms the fully supervised or weakly supervised model alone.

Mucins as Potential Biomarkers for Early Detection of Cancer

Early detection significantly correlates with improved survival in cancer patients. So far, a limited number of biomarkers have been validated to diagnose cancers at an early stage. Considering the leading cancer types that contribute to more than 50% of deaths in the USA, we discuss the ongoing endeavors toward early detection of lung, breast, ovarian, colon, prostate, liver, and pancreatic cancers to highlight the significance of mucin glycoproteins in cancer diagnosis. As mucin deregulation is one of the earliest events in most epithelial malignancies following oncogenic transformation, these high-molecular-weight glycoproteins are considered potential candidates for biomarker development. The diagnostic potential of mucins is mainly attributed to their deregulated expression, altered glycosylation, splicing, and ability to induce autoantibodies. Secretory and shed mucins are commonly detected in patients' sera, body fluids, and tumor biopsies. For instance, CA125, also called MUC16, is one of the biomarkers implemented for the diagnosis of ovarian cancer and is currently being investigated for other malignancies. Similarly, MUC5AC, a secretory mucin, is a potential biomarker for pancreatic cancer. Moreover, anti-mucin autoantibodies and mucin-packaged exosomes have opened new avenues of biomarker development for early cancer diagnosis. In this review, we discuss the diagnostic potential of mucins in epithelial cancers and provide evidence and a rationale for developing a mucin-based biomarker panel for early cancer detection.

Damaged Masculinity: How Honor Endorsement Can Influence Prostate Cancer Screening Decision-Making and Prostate Cancer Mortality Rates

Prior research has established factors that contribute to the likelihood that men seek out prostate cancer screenings. The current study addresses how endorsing the ideology found in cultures of honor may serve as a barrier to prostate cancer screenings. Two studies were conducted which analyzed the impact of stigma on men's decisions to seek out prostate cancer screenings (Study 1) as well as how prostate cancer deaths may be higher in the culture of honor regions due to men's reticence to seek out screenings (Study 2). Results suggest that older, honor-endorsing men are less likely to have ever sought out a prostate cancer screening due to screening stigma and that an honor-oriented region (southern and western United States) displays higher rates of prostate cancer death than a non-honor-oriented region (northern United States). These findings suggest that honor may be a cultural framework to consider when practitioners address patients' screening-related concerns.

Prostate cancer in transgender women: considerations for screening, diagnosis and management

Transgender individuals represent 0.55% of the US population, equivalent to 1.4 million transgender adults. In transgender women, feminisation can include a number of medical and surgical interventions. The main goal is to deprive the phenotypically masculine body of androgens and simultaneously provide oestrogen therapy for feminisation. In gender-confirming surgery (GCS) for transgender females, the prostate is usually not removed. Due to limitations of existing cohort studies, the true incidence of prostate cancer in transgender females is unknown but is thought to be less than the incidence among cis-gender males. It is unclear how prostate cancer develops in androgen-deprived conditions in these patients. Six out of eleven case reports in the literature presented with metastatic disease. It is thought that androgen receptor-mediated mechanisms or tumour-promoting effects of oestrogen may be responsible. Due to the low incidence of prostate cancer identified in transgender women, there is little evidence to drive specific screening recommendations in this patient subpopulation. The treatment of early and locally advanced prostate cancer in these patients warrants an individualised thoughtful approach with input from patients' reconstructive surgeons. Both surgical and radiation treatment for prostate cancer in these patients can profoundly impact the patient's quality of life. In this review, we discuss the evidence surrounding screening and treatment of prostate cancer in transgender women and consider the current gaps in our knowledge in providing evidence-based guidance at the molecular, genomic and epidemiological level, for clinical decision-making in the management of these patients.

Prediction of prostate cancer recurrence after radiation therapy using multiparametric magnetic resonance imaging and spectroscopy: assessment of prognostic factors on pretreatment imaging

BACKGROUND

To assess whether data from pre-therapeutic multiparametric magnetic resonance imaging (mpMRI) combined with three-dimensional magnetic resonance spectroscopy (3D MRS) provide prognostic factors of biochemical relapse in patients with localized prostate cancer treated by external radiotherapy or brachytherapy.

METHODS

In our single institution observational retrospective study we included a cohort of 230 patients treated by external radiotherapy or brachytherapy who had an initial mpMRI with 3D MRS from January 2008 to December 2015 for newly diagnosed localized prostatic cancer, proven histologically. Three trained radiologists recorded tumor characteristics, MRI T-stage and metabolic abnormalities from 3D MRS data. Univariate and multivariate Cox analyzes explored the relationship between clinical and imaging variables to highlight prognostic factors for recurrence, using biochemical relapse as the primary endpoint.

RESULTS

mpMRI data analysis allowed to reclassify 21.7% of the patients in a MRI National Comprehensive Cancer Network (NCCN) group higher than their initial clinical T-stage, but also to detect a lesion in 78% of the patients considered as clinically T1c. After a median of follow-up of 8.7 years (IQR, 6.6-10.1) following cancer diagnosis, 36 (16%) patients developed a biochemical relapse. The multivariate Cox analysis demonstrated the existence of 3 independent factors for prediction of biochemical recurrence: extracapsular extension (ECE) (HR =3.33; 95% CI: 1.93-5.73; P<0.01), choline/citrate ratio in healthy tissue in the transition zone (TZ) (HR =2.96; 95% CI: 1.06-8.28; P=0.04) and the NCCN Magnetic Resonance Imaging classification (intermediate versus low-risk, HR =3.06; 95% CI: 1.13-8.30; P<0.01).

CONCLUSIONS

Combination of mpMRI and 3DMRS could aid in the prognostic stratification of localized prostate cancer treated by radiotherapy or brachytherapy, by combining accurate evaluation of tumor extension, and quantification of prostate metabolism.

Prostate cancer screening: Continued controversies and novel biomarker advancements

Prostate cancer (PCa) screening remains one of the most controversial topics in clinical and public health. Despite being the second most common cancer in men worldwide, recommendations for screening using prostate-specific antigen (PSA) are unclear. Early detection and the resulting postscreening treatment lead to overdiagnosis and overtreatment of otherwise indolent cases. In addition, several unwanted harms are associated with PCa screening process. This literature review focuses on the limitations of PSA-specific PCa screening, reasons behind the screening controversy, and the novel biomarkers and advanced innovative methodologies that improve the limitations of traditional screening using PSA. With the verdict of whether or not to screen not yet unanimous, we hope to aid in resolution of the long-standing debate.

A cable driven robotic palpation system with contact force sensing based on cable tension observation

BACKGROUND

Prostate Cancer screening based on manual palpation is subjective. Robotic palpation systems can objectively acquire stiffness conditions of the prostate.

METHODS

A 2DoF cable driven robotic system for prostate palpation is proposed. An indirect method to estimate the contact force based on cable tension observation is presented. Kinematic models and a joint angle estimation method to determine the tip position of the probe are derived. Positioning accuracy was verified using an optical marker tracking system and by displacement measurement, respectively. The contact force estimation method was validated on silicone phantom samples.

RESULTS

A good consistence between the estimated and measured contact force was observed. The contact force was correlated with the elastic modulus of each silicone phantom. There was also a good agreement between the theoretical and the measured tip position.

CONCLUSION

In the proposed palpation system, the indirect contact force estimation method is viable and holds potential for the stiffness assessment of the prostate. The tip position vital for palpation can be determined through estimated joint angles.

Kinetic Analysis of Prostate-Specific Antigen Interaction with Monoclonal Antibodies for Development of a Magnetic Immunoassay Based on Nontransparent Fiber Structures

Prostate cancer is the second most common cancer diagnosed in men worldwide. Measuring the prostate-specific antigen (PSA) is regarded as essential during prostate cancer screening. Early diagnosis of this disease relapse after radical prostatectomy requires extremely sensitive methods. This research presents an approach to development of an ultrasensitive magnetic sandwich immunoassay, which demonstrates the limit of PSA detection in human serum of 19 pg/mL at a dynamic range exceeding 3.5 orders of concentration. Such attractive performance stems, inter alia, from the kinetic analysis of monoclonal antibodies (mAbs) against free PSA to select the mAbs exhibiting best kinetic characteristics and specificity. The analysis is carried out with a label-free multiplex spectral-correlation interferometry compatible with inexpensive single-use glass sensor chips. The high sensitivity of developed PSA immunoassay is due to electronic quantification of magnetic nanolabels functionalized by the selected mAbs and three-dimension porous filters used as an extended solid phase. The assay is promising for PSA monitoring after radical prostatectomy. The proposed versatile approach can be applied for the rational design of highly sensitive tests for detection of other analytes in many fields, including in vitro diagnostics, veterinary, food safety, etc.

Combination of PI-RADS score and PSAD can improve the diagnostic accuracy of prostate cancer and reduce unnecessary prostate biopsies

OBJECTIVES

The purpose of this study is to evaluate the diagnostic accuracy of the clinical variables of patients with prostate cancer (PCa) and to provide a strategy to reduce unnecessary biopsies.

PATIENTS AND METHODS

A Chinese cohort that consists of 833 consecutive patients who underwent prostate biopsies from January 2018 to April 2022 was collected in this retrospective study. Diagnostic ability for total PCa and clinically significant PCa (csPCa) was evaluated by prostate imaging-reporting and data system (PI-RADS) score and other clinical variables. Univariate and multivariable logistic regression analyses were performed to figure out the independent predictors. Diagnostic accuracy was estimated by plotting receiver operating characteristic curves.

RESULTS

The results of univariate and multivariable analyses demonstrated that the PI-RADS score (P < 0.001, OR: 5.724, 95% CI: 4.517-7.253)/(P < 0.001, OR: 5.199, 95% CI: 4.039-6.488) and prostate-specific antigen density (PSAD) (P < 0.001, OR: 2.756, 95% CI: 1.560-4.870)/(P < 0.001, OR: 4.726, 95% CI: 2.661-8.396) were the independent clinical factors for predicting total PCa/csPCa. The combination of the PI-RADS score and PSAD presented the best diagnostic performance for the detection of PCa and csPCa. For the diagnostic criterion of "PI-RADS score ≥ 3 or PSAD ≥ 0.3", the sensitivity and negative predictive values were 94.0% and 93.1% for the diagnosis of total PCa and 99.2% and 99.3% for the diagnosis of csPCa, respectively. For the diagnostic criterion "PI-RADS score >3 and PSAD ≥ 0.3", the specificity and positive predictive values were 96.8% and 92.6% for the diagnosis of total PCa and 93.5% and 82.4% for the diagnosis of csPCa, respectively.

CONCLUSIONS

The combination of the PI-RADS score and PSAD can implement the extraordinary diagnostic performance of PCa. Many patients may safely execute active surveillance or take systematic treatment without prostate biopsies by stratification according to the PI-RADS score and the value of PSAD.

Screening for prostate cancer: protocol for updating multiple systematic reviews to inform a Canadian Task Force on Preventive Health Care guideline update

PURPOSE

To inform updated recommendations by the Canadian Task Force on Preventive Health Care on screening for prostate cancer in adults aged 18 years and older in primary care. This protocol outlines the planned scope and methods for a series of systematic reviews.

METHODS

Updates of two systematic reviews and a de novo review will be conducted to synthesize the evidence on the benefits and harms of screening for prostate cancer with a prostate-specific antigen (PSA) and/or digital rectal examination (DRE) (with or without additional information) and patient values and preferences. Outcomes for the benefits of screening include reduced prostate cancer mortality, all-cause mortality, and incidence of metastatic prostate cancer. Outcomes for the harms of screening include false-positive screening tests, overdiagnosis, complications due to biopsy, and complications of treatment including incontinence (urinary or bowel), and erectile dysfunction. The quality of life or functioning (overall and disease-specific) and psychological effects outcomes are considered as a possible benefit or harm. Outcomes for the values and preferences review include quantitative or qualitative information regarding the choice to screen or intention to undergo screening. For the reviews on benefits or harms, we will search for randomized controlled trials, quasi-randomized, and controlled studies in MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials. For the review on values and preferences, we will search for experimental or observational studies in MEDLINE, Embase, and PsycInfo. For all reviews, we will also search websites of relevant organizations, gray literature, and reference lists of included studies. Title and abstract screening, full-text review, data extraction, and risk of bias assessments will be completed independently by pairs of reviewers with any disagreements resolved by consensus or by consulting with a third reviewer. The GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach will be used to assess the certainty of the evidence for each outcome.

DISCUSSION

The series of systematic reviews will be used by the Canadian Task Force on Preventive Health Care to update their 2014 guideline on screening for prostate cancer in adults aged 18 years and older. Systematic review registration This review has been registered with PROSPERO (CRD42022314407) and is available on the Open Science Framework (osf.io/dm32k).

A Clinically Significant Prostate Cancer Predictive Model Using Digital Rectal Examination Prostate Volume Category to Stratify Initial Prostate Cancer Suspicion and Reduce Magnetic Resonance Imaging Demand

A predictive model including age, PCa family history, biopsy status (initial vs repeat), DRE (normal vs abnormal), serum prostate-specific antigen (PSA), and DRE prostate volume ca-tegory was developed to stratify initial PCa suspicion in 1486 men with PSA > 3 ng/mL and/or abnormal DRE, in whom mpMRI followed; 2- to 4-core TRUS-guided biopsies where Prostate Imaging Report and Data System (PI-RADS) > 3 lesions and/or 12-core TRUS systematic biopsies were performed in one academic institution between 1 January 2016−31 December 2019. The csPCa detection rate, defined as International Society of Uro-Pathology grade group 2 or higher, was 36.9%. An external validation of designed BCN-RC 1 was carried out on 946 men from two other institutions in the same metropolitan area, using the same criteria of PCa suspicion and diagnostic approach, yielded a csPCa detection rate of 40.8%. The areas under the receiver operating characteristic curves of BCN-RC 1 were 0.823 (95% CI: 0.800−0.846) in the development cohort and 0.837 (95% CI: 0.811−0.863) in the validation cohort (p = 0.447). In both cohorts, BCN-RC 1 exhibited net benefit over performing mpMRI in all men from 8 and 12% risk thresholds, respectively. At 0.95 sensitivity of csPCa, the specificities of BCN-RC 1 were 0.24 (95% CI: 0.22−0.26) in the development cohort and 0.34 (95% CI: 0.31−0.37) in the validation cohort (p < 0.001). The percentages of avoided mpMRI scans were 17.2% in the development cohort and 22.3% in the validation cohort, missing between 1.8% and 2% of csPCa among men at risk of PCa. In summary, BCN-RC 1 can stratify initial PCa suspicion, reducing the demand of mpMRI, with an acceptable loss of csPCa.

Metastatic Prostate Adenocarcinoma Presenting as Acute Quadriplegia: A Case Report and Racial Disparity Analysis

Prostate cancer is the most frequently diagnosed malignancy in males with the highest incidence and mortality among African Americans. Most prostate cancers are low-grade and slowly progressive.  Prostate cancer can be asymptomatic in the early stages, as exemplified by diagnosis through incidental findings, but typically manifests as a change in urinary habits and characteristics, including frequency and dysuria. If diagnosed at the time of distant metastases, then the patient may complain of bone pain in the hips, legs, or feet, or lower extremity edema.

We present the case of a 74-year-old African American male with no past medical history who presented to the emergency department with acute quadriplegia secondary to metastatic spinal cord compression. The patient required admission to the intensive care unit (ICU) and his quadriplegia was successfully treated with cervical arthrodesis, laminectomy, spinal instrumentation, and fusion, high-dose intravenous (IV) steroids, and physical and occupational therapy.

Overall, the purpose of this case report is to critically review and investigate the factors behind a patient's atypical, rare, and underreported initial presentation of metastatic prostate cancer. The study discusses the literature on advancements in prostate cancer screening and highlights the importance of a broad differential. Most remarkably, the vignette prompts an analysis of the racial disparity gap in prostate cancer diagnosis and treatment demonstrates the need for further research toward improved health outcomes, and proposes multiple avenues to promote health equity.

miRNAs as molecular biomarkers for prostate cancer

MicroRNAs (miRNAs) are short noncoding RNA able to regulate specific mRNA stability, thus influencing target gene expression. Disrupted levels of several miRNA have been associated with prostate cancer, the leading cause of cancer death among men and the fifth leading cause of death worldwide. Here, we investigated whether miR-145, miR-148, and miR-185 circulating levels in plasma could be used as molecular biomarkers, to allow distinguishing between individuals with benign prostatic hyperplasia, precancerous lesion, and prostate cancer. In this study, we recruited 170 urological clinic patients with suspected prostate cancer who underwent prostate biopsy. Total RNA was isolated from plasma, and TaqMan MicroRNA assays were used to analyze miR-145, miR-185, and miR-148 expression. First, differential miRNA expression among patient groups was evaluated. Then, miRNA levels were combined with clinical assessment outcomes, including results from invasive tests, using multivariate analysis to examine their ability in discriminating among the three patient groups. Our results suggest that miRNA is a promising molecular tool for clinical management of at-risk patients.

Digital rectal examination impact on PSA derivatives and prostate biopsy triggers: a contemporary study

OBJECTIVE

To evaluate the impact of the digital rectal exam (DRE) on PSA measurements and clinical decision-making.

METHODS

Healthy male volunteers between 50 and 70 years old were recruited during a 30-day public screening program. PSA levels were measured using two different methods (standard enhanced chemiluminescence immunoassay-ECLIA, and novel immunochromatography assay-ICA/rapid PSA) in the same blood sample. Two blood samples were drawn; first before DRE and the second 30-40 min after DRE. The effect of DRE on PSA levels and its impact on clinical decision-making for individual patients were evaluated based on different biopsy trigger cutoffs.

RESULTS

ECLIA-PSA was measured in 74 participants both pre- and 37 ± 5 min post-DRE, mean age 57.2 ± 8.3 years, and mean prostate volume 33.6 (20-80) cm³. Both total and free ECLIA-PSA increased significantly after DRE (mean increase of 0.47 and 0.26 ng/ml, respectively, both p < 0.001). Different internationally accepted biopsy triggers were reached after DRE only: 5 total PSA > 3 ng/ml, 13 increase > 0.75 ng/ml, 3 PSA density > 0.15, and 1 free/total PSA < 0.18. On two occasions, patients were pushed away from biopsy trigger after DRE due to free/total PSA > 0.18. ICA-PSA was detectable (> 2.0 ng/ml) in 5 of 45 measured samples (11%) before DRE and 13/45 (29%) after DRE, p = 0.0316. Four among five detectable ICA-PSA tests increased after DRE.

CONCLUSION

Performing DRE immediately before PSA measurement might change the clinical decision-making on a significant number of occasions (roughly 1 in 3); even though the mean increase (0.47 ng/ml) looks deceivingly small. Further studies are required that include gold standard tests (biopsy, or imaging).

More than Meets the Eye: Using Textural Analysis and Artificial Intelligence as Decision Support Tools in Prostate Cancer Diagnosis—A Systematic Review

(1) Introduction: Multiparametric magnetic resonance imaging (mpMRI) is the main imagistic tool employed to assess patients suspected of harboring prostate cancer (PCa), setting the indication for targeted prostate biopsy. However, both mpMRI and targeted prostate biopsy are operator dependent. The past decade has been marked by the emerging domain of radiomics and artificial intelligence (AI), with extended application in medical diagnosis and treatment processes. (2) Aim: To present the current state of the art regarding decision support tools based on texture analysis and AI for the prediction of aggressiveness and biopsy assistance. (3) Materials and Methods: We performed literature research using PubMed MeSH, Scopus and WoS (Web of Science) databases and screened the retrieved papers using PRISMA principles. Articles that addressed PCa diagnosis and staging assisted by texture analysis and AI algorithms were included. (4) Results: 359 papers were retrieved using the keywords “prostate cancer”, “MRI”, “radiomics”, “textural analysis”, “artificial intelligence”, “computer assisted diagnosis”, out of which 35 were included in the final review. In total, 24 articles were presenting PCa diagnosis and prediction of aggressiveness, 7 addressed extracapsular extension assessment and 4 tackled computer-assisted targeted prostate biopsies. (5) Conclusions: The fusion of radiomics and AI has the potential of becoming an everyday tool in the process of diagnosis and staging of the prostate malignancies.

The Impact of Lifestyle on Prostate Cancer: A Road to the Discovery of New Biomarkers

Prostate cancer (PCa) is one of the most common cancers among men, and its incidence has been rising through the years. Several risk factors have been associated with this disease and unhealthy lifestyles and inflammation were appointed as major contributors for PCa development, progression, and severity. Despite the advantages associated with the currently used diagnostic tools [prostate-specific antigen(PSA) serum levels and digital rectal examination (DRE)], the development of effective approaches for PCa diagnosis is still necessary. Finding lifestyle-associated proteins that may predict the development of PCa seems to be a promising strategy to improve PCa diagnosis. In this context, several biomarkers have been identified, including circulating biomarkers (CRP, insulin, C-peptide, TNFα-R2, adiponectin, IL-6, total PSA, free PSA, and p2PSA), urine biomarkers (PCA3, guanidine, phenylacetylglycine, and glycine), proteins expressed in exosomes (afamin, vitamin D-binding protein, and filamin A), and miRNAs expressed in prostate tissue (miRNA-21, miRNA-101, and miRNA-182). In conclusion, exploring the impact of lifestyle and inflammation on PCa development and progression may open doors to the identification of new biomarkers. The discovery of new PCa diagnostic biomarkers should contribute to reduce overdiagnosis and overtreatment.

Correlation between stage of prostate cancer and tyrosine and tryptophan in urine samples measured electrochemically

Prostate cancer (PCa) is the second most common cancer in men and one of the leading causes of cancer-related deaths. Early detection is the key to successful treatment and provides the greatest chance to cure the patient. Currently, early detection involves screening for prostate-specific antigen levels in blood, which is not a tumor-specific biomarker. There is a critical need to develop clinically useful methods for screening for more reliable biomarkers. Here, we introduce an electrochemical biosensor that measures the concentrations of the amino acids tyrosine and tryptophan, and propose it as a possible diagnostic and prognostic tool for PCa. The limits of detection of tyrosine and tryptophan using the electrochemical sensors were 1.15 and 1.13 μmol/L in 1:10 urine: PBS, respectively. This study is the first to present electrochemical measurements of tyrosine and tryptophan directly in patient urine samples. We demonstrated an inverse correlation between the measured electrochemical signals and the severity of PCa. The most notable observation was a significant difference between controls and metastatic PCa patients (P ≤ 0.001). This observation was further validated using Liquid-Chromatography-Mass Spectrometry. Our data provides the basis for further research with electrochemical measurements of tyrosine and tryptophan as potential biomarkers for PCa.