Early Detection Of Prostate Cancer Research Articles

Prostate cancer screening-current overview

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 ascreening test. In this nonsystematic review, we present acurrent overview of the body of evidence on prostate cancer screening with afocus on the role of magnetic resonance imaging (MRI) of the prostate. 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 aconsequence 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 adigital rectal examination (DRE) as astand-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. Early detection of PCa should be organized on apopulation level into personalized and evidence-based screening strategies. Multiparametric MRI of the prostate may play akey role in this setting.

Urinary volatile organic compounds (VOCs) based prostate cancer diagnosis via high-dimensional classification

Early detection of prostate cancer is critical for successful treatment and survival. However, current diagnostic methods such as prostate-specific antigen (PSA) testing and digital rectal examination (DRE) have limitations in accuracy, specificity, and sensitivity. Recent research suggests that urinary volatile organic compounds (VOCs) could serve as potential biomarkers for prostate cancer diagnosis. In this study, urine samples from 337 PCa-positive and 233 PCa-negative patients were collected to develop a diagnosis model. The study involves a high dimensional (HD) classification problem due to the vast number of measured VOCs. Our findings reveal that regularized logistic regression outperforms numerous other classifiers when analyzing the collected data. In particular, we have selected a regularized logistic model with the SCAD (smoothly clipped absolute deviation) penalty as the final model, which attains an AUC (area under the ROC curve) of 0.748, in contrast to a PSA-based AUC of 0.540. These results underscore the potential of VOC-based diagnosis as a clinically feasible approach for PCa screening.

Discovery and Validation of Novel microRNA Panel for Non-Invasive Prediction of Prostate Cancer.

Early diagnosis remains a challenge for prostate cancer (PCa) due to molecular heterogeneity. The purpose of our study was to explore the diagnostic potential of microRNA (miRNA) in both tissue and serum that may aid in the precise and early clinical diagnosis of PCa. The miRNA expression pattern analysis was carried out in 250 subjects (discovery and validation cohort). The Discovery Cohort included the control (n = 30) and PCa (n = 35) subjects, while the Validation Cohort included the healthy control (n = 60), benign prostate hyperplasia (BPH) (n = 55), PCa (n = 50), and castration-resistant PCa (CRPC) (n = 20) patients. The expression analysis of tissue (Discovery Cohort) and serum (Validation Cohort) was carried out by quantitative polymerase chain reaction (qPCR). The diagnostic biomarker potential was evaluated using receiver operating characteristics (ROC). Bioinformatic tools were used to explore and analyze miRNA target genes. MiRNA 4510 and miRNA 183 were significantly (p<0.001) upregulated and miRNA 329 was significantly (p<0.0001) downregulated in both PCa tissue and serum. ROC curve analysis showed excellent non-invasive biomarker potential of miRNA 4510 in both PCa (area under the curve (AUC) 0.984; p<0.001) and CRPC (AUC 0.944; p<0.001). The panel of serum miRNAs (miRNA 183 and miRNA 4510) designed for PCa had significant and greater AUC with both 100% sensitivity and specificity. Computational analysis shows that the maximum number of target genes are transcription factors that regulate oncogenes and tumor suppressors. Based on ROC curve analysis, miRNAs 4510, 329, and 711 were identified as potential non-invasive diagnostic biomarkers in the early detection of PCa. Our findings imply that a panel of miRNAs 183 and 4510 has high specificity for distinguishing PCa from healthy controls and providing therapeutic targets for better and earlier PCa therapy.

Reduced graphene oxide/gold nanoparticles based ultrasensitive resistive sensor for PCA3

Early prostate cancer detection can be improved by detecting more specific markers like PCA3 RNA. This study reports a novel and simple method for detecting PCA3 RNA using a sensor based on reduced graphene oxide (RGO), gold nanoparticles (AuNP), and a single-stranded DNA (ssDNA). The device was characterized at each fabrication step using atomic force microscopy (AFM) and field emission scanning electron microscopy (FESEM). The RGO/AuNP/ssDNA sensor exhibited a significant change in resistance (6.51–15.01%) when exposed to varying concentrations of PCA3 (0.1–100 ng/mL). The developed device showed selective response towards PCA3 (14.5% for 50 ng/mL) when compared with negative controls like phosphate buffer saline solution (0.28%), PCA3-negative control sample (1.03%), RNA extracted from lung cancer (0.88%), and breast cancer (1.17%) cell lines. The RGO/AuNP/ssDNA sensor could also be employed to quantify the PCA3 RNA present in the RNA mixture extracted from a prostate cancer cell line and the observed findings were in excellent agreement with semi-quantitative real-time polymerase chain reaction (RT-PCR) results.

Analysis of the Gene Networks and Pathways Correlated with Tissue Differentiation in Prostate Cancer.

Prostate cancer (PCa) is the most prevalent non-cutaneous cancer in men. Early PCa detection has been made possible by the adoption of screening methods based on the serum prostate-specific antigen and Gleason score (GS). The aim of this study was to correlate gene expression with the differentiation level of prostate adenocarcinomas, as indicated by GS. We used data from The Cancer Genome Atlas (TCGA) and included 497 prostate cancer patients, 52 of which also had normal tissue sample sequencing data. Gene ontology analysis revealed that higher GSs were associated with greater responses to DNA damage, telomere lengthening, and cell division. Positive correlation was found with transcription factor activator of the adenovirus gene E2 (E2F) and avian myelocytomatosis viral homolog (MYC) targets, G2M checkpoints, DNA repair, and mitotic spindles. Immune cell deconvolution revealed high M0 macrophage counts and an increase in M2 macrophages dependent on the GS. The molecular pathways most correlated with GSs were cell cycle, RNA transport, and calcium signaling (depleted). A combinatorial approach identified a set of eight genes able to differentiate by k-Nearest Neighbors (kNN) between normal tissues, low-Gleason tissues, and high-Gleason tissues with high accuracy. In conclusion, our study could be a step forward to better understanding the link between gene expression and PCa progression and aggressiveness.

Abstract 2442: Blood based novel mRNA genomic test, for screening, early detection, prognosis and monitoring of prostate cancer using a multi-center study

Abstract Background: Current screening tools, including prostate-specific antigen (PSA) and clinico-pathologic parameters, have limitations in the diagnosis and prognosis of prostate cancer. This study examined whether genomic biomarkers can improve screening and monitoring of prostate cancer. Methods: We identified a panel of 25 prostate cancer-related genes through rigorous bioinformatics, computational analyses and genetic testing. These tests, developed by Geneverify Inc. (Hayward, CA; U.S. patent # 10801072 and 10822661) were utilized and optimized by qRT-PCR to determine the diagnostic and prognostic ability of prostate cancer using blood and tissues. The log2-fold increase in gene expression was used to assign the risk score to individual patients. ROC (receiver operator characteristic), AUC (area under ROC curve), and calibration curves were generated to display the overall performance and discrimination ability to separate cancer and non-cancer specimens. Results: A total of 445 prostate cancer patients (135 blood and 310 tissue samples) and 130 normal samples were analyzed in this study. The eligibility criteria were to collect blood and surgical specimens from patients with prostate cancer. The study endpoints were to analyze mRNA genomic profiling and correlate with clinico-pathologic parameters of the patients. In the blood, a 25-panel gene-set separated prostate cancer patients (n=135) from non-cancer (n=30), AUC = 0.906 [sensitivity = 90% and specificity = 91%]. Assessment of tissue specimens from benign (n=100) and cancer patients (n=310) demonstrated similar results with AUC=0.9514 [sensitivity=95% and specificity=94%]. Interestingly, patients with Gleason grades more than 7 showed higher expression of these genes compared to Gleason Grades less than 7, suggesting the prognostic ability of the gene-set. When we compared the gene expression in blood verses tissues, there were similar patterns, suggesting that blood can be used for screening, diagnosis and risk assessment of prostate cancer. Conclusions: To our knowledge, this is the first study to investigate the role of mRNA-based genomic signatures for screening, early diagnosis and prognosis of prostate cancer using blood samples. Our results suggest that blood mRNA-genomic profiling developed by Geneverify has the ability to diagnose prostate cancer and stratify patients into distinct prognostic groups, which in turn help in making better treatment strategies. Citation Format: Yutaka Hashimoto, Shiv Verma, Guoren Deng, Dharam P. Chauhan, Sujit Nair, Dimple Chakravarty, Hirofumi Yoshino, Junya Arima, Shuichi Tatarano, Yutong Liu, Koji Hatano, Yogesh Shivakumar, Mithua Ghosh, Krishnappa Raghunath, Chitra Chandran, Narasimhan Ragavan, Hideki Enokida, Norio Nonomura, KC Balaji, Sudhir Rawal, Ashutosh Tewari, Rajvir Dahiya, Sanjay Gupta. Blood based novel mRNA genomic test, for screening, early detection, prognosis and monitoring of prostate cancer using a multi-center study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2442.

Abstract 6432: Co-expression of HERV-R, CCND1, BRAF, FOXA1, TMPRSS2, ATF4 and low expression of BAZ1B and KMT2D is associated with early detection and poor prognosis of prostate cancer in African Black men from Nigeria

Abstract Prostate cancer (CaP) is a heterogeneous disease characterized by features of non-aggressive, slow-growing disorders to fast-growing disease. Men of African ancestry have disproportionately higher incidence and mortality rates for CaP than men of European ancestry. While there is evidence for a higher genetic predisposition for incidence of CaP in men of African ancestry compared to men of European ancestry, there is paucity of molecular biology and transcriptomic studies on the role of Human endogenous retroviruses (HERVs) in relation to CaP-associated genes in CaP pathogenesis and prognosis. In this study, we performed bulk RNA sequencing (RNA-seq) on formalin-fixed paraffin-embeded (FFPE) CaP samples from Nigerian CaP patients to investigate the expression significance of HERV-R in relation to FOXA1, TMPRSS2, BAZ1B, KMT2D, ATF4 and BRAF genes. Based on this findings, we used immunohistochemistry (IHC), enzyme-linked immunosorbent assay (ELISA) and immunofluorescence (IF) to confirm the expression pattern of the HERV-R and FOXA1, TMPRSS2, BAZ1B, KMT2D, ATF4 and BRAF proteins on 45 FFPE CaP and blood plasma samples, and 5 CaP-free samples from patients in Zaria, Nigeria. Most of these patients were longitudinally followed from 2017 to date. The DESeq2 procedure was used for data processing, analysis, and differential expression analysis of the aforementioned genes. We found a significant expression of HERV-R in relation with FOXA1, TMPRSS2, BAZ1B, KMT2D, ATF4, CCND1 and BRAF in the CaP from rural Africans in Nigeria. HERV-R expression was found to be associated with increased PSA level, higher Gleason grade and poor prognosis of CaP. A CaP sample from an 80-year-old patient that was histologically diagnosed to have no malignancy seen despite high PSA level of &amp;gt;100 and poor disease outcomes shows a significant cytoplasmic expression of HERV-R, indicating that HERV-R may serve as an important biomarker for early detection. Unfortunately, we lost the 80-year-old patient to late detection before revisiting his case for proper histological diagnosis and management. In addition, some histologically diagnosed BPH samples that are apparently reported to be CaP-free show stromal cells expression of HERV-R and in some cases show expression of HERV-R in the prostatic glandular areas. In contrast, stromal cells of the CaP samples show no expression of HERV-R, but strong expression in the glandular areas. This may implicate a gradual transition from benign prostatic lesion to malignant prostatic disease. HERV-R expression in CaP may have a relationship with BRAF, CCND1, FOXA1, TMPRSS2 and ATF4 genes. These findings combined together, underscore the importance of the expanded concept of HERV-R expression and CaP associated genes in early detection of CaP and prognosis. Citation Format: Faruk Mohammed, Konrad Stawiski, Halimatu Sadiya Musa, Sani Kamarudeen Owolabi, Sani Abubakar, Solomon O. Rotimi, Adoke Kasimu Umar, Yawale Iliyasu, Ahmad Bello, Folakemi T. Odedina, Clayton C. Yates, Kevin Petrie, Franklin W. Huang, Sani Ibrahim. Co-expression of HERV-R, CCND1, BRAF, FOXA1, TMPRSS2, ATF4 and low expression of BAZ1B and KMT2D is associated with early detection and poor prognosis of prostate cancer in African Black men from Nigeria [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6432.

Abstract 2430: Enhancing urine-based cfDNA detection for prostate cancer diagnosis through increased urine input volume

Abstract Introduction: Cell-free DNA (cfDNA) extracted from urine has created new opportunities in non-invasive cancer diagnostics, particularly for prostate cancer. Detecting cfDNA in urine can be challenging due to its inherently low concentration. Increasing the input volume of urine addresses this limitation, enhancing the sensitivity of cfDNA detection. This study explores the benefit of collecting larger volumes of urine spiked with a TP53 mutation and the corresponding increase in assay sensitivity for early prostate cancer diagnosis and monitoring. Methods: Pooled urine from healthy donors was collected, preserved, processed, and extracted from 10 mL, 20 mL, 30 mL, 40 mL, and 50 mL inputs (with four replicates each) using the Revolution Max 20 cfDNA Extraction kit. Replicate samples were also extracted using a MagMAX cfDNA Isolation kit from Thermo Fisher Scientific. All samples were spiked with a cfDNA standard containing TP53 R58L mutation. The quantity and quality of extracted cfDNA were determined using the Agilent TapeStation system with the Cell-free DNA ScreenTape assay and qPCR mutation detection assay. Results: The Revolution Max 20 cfDNA kit consistently delivered a higher yield of cfDNA, demonstrating excellent extraction efficiency and quality, as shown by the Agilent Cell-free DNA ScreenTape assay. Notably, the Revolution Max 20 cfDNA kit exhibited a linear increase in yield as the sample volume grew from 10 mL to 50 mL. The MagMax kit did not provide this yield linearity. Furthermore, both methods successfully maintained the integrity of cfDNA fragmentation, which was confirmed through the Agilent Cell-free DNA ScreenTape assay. Conclusion: Compared to the MagMax kit, the Revolution Max 20 cfDNA kit outperforms in extracting cfDNA with high efficiency, as shown by the Agilent Cell-free DNA ScreenTape and the qPCR assay. The Revolution Max 20 cfDNA kit offers the unique advantage of accommodating up to 50 mL of urine in a single extraction. As input volume increases, it consistently produces high cfDNA yields while maintaining quality. In contrast, the MagMax kit is limited to an input volume of only 10 mL, necessitating the cumbersome process of dividing a 50 mL urine sample into five separate extractions and pooling the eluates. This scheme resulted in lower yields. The Agilent Cell-free DNA ScreenTape assay is a valuable tool for quickly and accurately assessing the %cfDNA quality metric. Its minimal sample volume requirement makes it an efficient quality control method for determining cfDNA samples before performing downstream testings. The enhanced capability of the Revolution Max 20 kit to yield more significant quantities of high-quality cfDNA from urine samples can profoundly impact liquid biopsy test sensitivity and the early detection of prostate cancer, potentially revolutionizing the diagnostics process. Citation Format: Nafiseh Jafari, Annika Dorn, Jason Saenz, Lauren Lee, Carlos Hernandez, Andrew Dunnigan, Mayer Saidian. Enhancing urine-based cfDNA detection for prostate cancer diagnosis through increased urine input volume [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2430.

Prostate Cancer Screening Behaviors and Health Beliefs Regarding Prostate Cancer Screening of Individuals Over 50 Years of Age: A Descriptive, Cross-Sectional Study

Purpose: This descriptive cross-sectional study was conducted to assess the prostate cancer screening behaviors and health beliefs related to prostate cancer screening among individuals aged 50 and over. &#x0D; Material and Methods: The study sample consisted of 72 men aged 50 and over receiving treatment at the orthopedics and traumatology clinic of a university hospital. Data were collected using a "Personal Information Form" and the "Prostate Cancer Screening Health Belief Model Scale." &#x0D; Results: The mean age of the participants in the study was 61.59±8.51 years. It was found that 22.2% of the participants had undergone Prostate-Specific Antigen testing, 73.6% had no knowledge about prostate cancer, and 75% had no knowledge about early detection tests for prostate cancer. Furthermore, participants who had knowledge about prostate cancer and early detection, had a family history of prostate cancer, and considered undergoing prostate examination had a higher rate of undergoing Prostate-Specific Antigen testing. Those who had never undergone a prostate examination, had no knowledge about prostate cancer and early detection tests, and did not plan to undergo prostate examination within the next six months had higher scores on the barrier perception scale, while those who had undergone Prostate-Specific Antigen testing and planned to undergo prostate examination within the next six months had higher scores on the health motivation perception scale. &#x0D; Conclusion: The study revealed a low rate of Prostate-Specific Antigen testing for early detection of prostate cancer, and participants' knowledge and health beliefs and perceptions related to prostate cancer and early detection tests were identified as key factors influencing prostate cancer screening behaviors.

Abstract 1853: Prostate specific membrane antigen (PSMA) glycoforms and prostate cancer progression

Abstract Introduction: Prostate cancer (PCa) is the most common non-skin malignancy and the second leading cause of cancer related death in men. Prostate cancer is a heterogeneous disease with diverse clinical outcomes ranging from indolent asymptomatic cases to very aggressive and potentially lethal metastatic forms of the disease. Early detection of PCa is predominantly through determination of serum PSA levels and digital rectal examinations (DRE). Subsequently, biopsy based Gleason Grade Scores and TNM staging, tumor size or mpMRI are used to assess disease severity and progression. However, due to the low specificity of PSA concentration in diagnosis and prognosis, biopsy complications, and high mpMRI costs, there is still a critical need to identify and develop novel noninvasive biomarkers that discriminate indolent from aggressive PCa upon diagnosis. Our long-term objective is to discover biomarkers for aggressive PCa, develop and to implement them into robust clinical testing minimally invasive assays for PCa risk stratification at diagnosis. The current focus is on Prostate-Specific Membrane Antigen (PSMA), a membrane bound glycoprotein, that is significantly over-expressed in aggressive and metastatic prostate carcinomas and with poor patient prognosis. The role of its glycosylation status and composition in disease progression and its glycoforms on biomarker development and therapeutics is unknown. Aberrant glycosylation of glycoproteins occurs in many cancers, and it influences disease progression. We rationalize that differential glycosylation of PSMA correlate with progression to aggressive PCa and that PSMA glycopeptides and glycoforms can be used as diagnostics and prognosticators for aggressive disease. Methods/Results: PSMA was isolated from risk Grade Group stratified post-DRE urines, seminal plasma and prostate cancer cell lines with different metastatic phenotypes cell line lysates. Intact glycopeptides were isolated, purified and analyzed by qualitative and quantitative mass spectrometry to identify site specific glycoforms. Our data demonstrate differential expression of unique PSMA glycoforms that correlate with disease risk and severity. Conclusions: Differential glycosylation of PSMA correlates with PCa disease progression to aggressive phenotypes and may have utility in disease stratification. Ongoing studies focus on determining if these qualitative and quantitative changes have diagnostic/prognostic value and if these be integrated with other PCa biomarkers to improve their prognostic power in discriminating aggressive PCa. Acknowledgements: This work was supported by the DOD, USAMRAA, through the Prostate Cancer Research Program under Award No. W81XWH18-1-0228. Opinions, interpretations, and conclusions are those of the author and are not necessarily endorsed by the USAMRAA. Citation Format: Stephen Mackay, Ian O. Oduor, Tanya Burch, Dean A. Troyer, Oliver J. Semmes, Julius O. Nyalwidhe. Prostate specific membrane antigen (PSMA) glycoforms and prostate cancer progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1853.

RAPHIA: A deep learning pipeline for the registration of MRI and whole-mount histopathology images of the prostate

Image registration can map the ground truth extent of prostate cancer from histopathology images onto MRI, facilitating the development of machine learning methods for early prostate cancer detection. Here, we present RAdiology PatHology Image Alignment (RAPHIA), an end-to-end pipeline for efficient and accurate registration of MRI and histopathology images. RAPHIA automates several time-consuming manual steps in existing approaches including prostate segmentation, estimation of the rotation angle and horizontal flipping in histopathology images, and estimation of MRI-histopathology slice correspondences. By utilizing deep learning registration networks, RAPHIA substantially reduces computational time. Furthermore, RAPHIA obviates the need for a multimodal image similarity metric by transferring histopathology image representations to MRI image representations and vice versa. With the assistance of RAPHIA, novice users achieved expert-level performance, and their mean error in estimating histopathology rotation angle was reduced by 51% (12 degrees vs 8 degrees), their mean accuracy of estimating histopathology flipping was increased by 5% (95.3% vs 100%), and their mean error in estimating MRI-histopathology slice correspondences was reduced by 45% (1.12 slices vs 0.62 slices). When compared to a recent conventional registration approach and a deep learning registration approach, RAPHIA achieved better mapping of histopathology cancer labels, with an improved mean Dice coefficient of cancer regions outlined on MRI and the deformed histopathology (0.44 vs 0.48 vs 0.50), and a reduced mean per-case processing time (51 vs 11 vs 4.5 min). The improved performance by RAPHIA allows efficient processing of large datasets for the development of machine learning models for prostate cancer detection on MRI. Our code is publicly available at: https://github.com/pimed/RAPHIA.

Personality and the use of cancer screenings - Results of the German National Cohort

ObjectiveTo determine the association between personality characteristics and use of different cancer screenings. MethodsWe used data from the German National Cohort (NAKO; mean age was 53.0 years (SD: 9.2 years)) – a population-based cohort study. A total of 132,298 individuals were included in the analyses. As outcome measures, we used (self-reported): stool examination for blood (haemoccult test, early detection of bowel cancer), colonoscopy (screening for colorectal cancer), skin examination for moles (early detection of skin cancer), breast palpation by a doctor (early detection of breast cancer), x-ray examination of the breast (“mammography”, early detection of breast cancer), cervical smear test, finger examination of the rectum (early detection of prostate cancer), and blood test for prostate cancer (determination of Prostate-Specific Antigen level). The established Big Five Inventory-SOEP was used to quantify personality factors. It was adjusted for several covariates based on the Andersen model. Unadjusted and adjusted multiple logistic regressions were computed. ResultsA higher probability of having a skin examination for moles, for example, was associated with a higher conscientiousness (OR: 1.07, p < 0.001), higher extraversion (OR: 1.03, p < 0.001), higher agreeableness (OR: 1.02, p < 0.001), lower openness to experience (OR: 0.98, p < 0.001) and higher neuroticism (OR: 1.07, p < 0.001) among the total sample. Depending on the outcome used, the associations slightly varied. ConclusionsParticularly higher levels of extraversion, neuroticism and conscientiousness are associated with the use of different cancer screenings. Such knowledge may help to better understand non-participation in cancer screening examinations from a psychological perspective.

IMPROVER (Involving Men with Prostate Cancer in Engaged Research): Assessing Patient Experience With Testing, Diagnosis, And Surveillance

BackgroundOur understanding of patient experiences with prostate cancer testing for diagnosis and surveillance is limited. The aim of this study was to collaborate with patients and clinicians to understand their lived experience and unmet needs around the early detection, diagnosis and monitoring (active surveillance) of prostate cancer. MethodsTwo focus groups were held with patients (n = 20) and healthcare professionals (n = 16), to identify the main challenges in prostate cancer detection, diagnosis, and monitoring. This information formed the basis of an online questionnaire for broader dissemination. ResultsA total of 1138 analyzable responses were obtained from people tested for prostate cancer (69% tested positive) in Europe and the US. Only 29 healthcare professionals completed the survey. Almost one-third of people reported knowing very little/nothing about prostate cancer prior to testing. Prior disease awareness was significantly higher in those who tested negative (P < .0001). Most respondents (n = 857; 75%) felt informed about the steps involved in testing. Receiving written information was a key factor; 91% of those who felt uninformed were not given any written information. Overall, most people felt “satisfied” with the typical prostate cancer tests: PSA, DRE, mpMRI, and biopsy. However, dissatisfaction for prostate biopsy (12%) was almost double that of other tests (P < .0001). Most patients understood why each test was done, and felt that their results and next steps were clearly explained to them; though PSA scored lowest in all of these fields. Apart from PSA, test satisfaction was lower when used repeatedly for surveillance, compared to once-off detection/diagnosis. ConclusionsGreater public awareness and education around prostate cancer, as well as clear and accessible written information for patients at the beginning of their cancer journey is needed. Further research is needed into alternative, less invasive tests, particularly when used repeatedly in the surveillance population.

Early detection of prostate cancer: a screening charity's perspective

CHAPS Men's Health Charity is playing a key role in raising awareness of prostate cancer in the UK. In particular, it seeks to educate both the public and health care professionals on the importance of early diagnosis and campaigns for a national prostate cancer screening programme.

(213) Assessing Primary Care Physicians Awareness of 5-Alpha Reductase Inhibitors for Men with Benign Prostatic Hyperplasia

Abstract Introduction Primary care physicians (PCPs) commonly prescribe 5-alpha-reductase inhibitors (5-ARIs) for the management of benign prostatic hyperplasia (BPH). 5-ARIs can affect prostate-specific antigen (PSA) kinetics by decreasing PSA levels by approximately half, and therefore delay the early detection of prostate cancer (PCa). Objective To determine PCPs’ level of awareness and indications for urology referral in patients treated with 5-ARIs. Methods After IRB approval, an anonymous survey was emailed to affiliated PCPs at an academic urban institution. Questions focused on residency graduation year, patient volume, knowledge of 5-ARIs and their effects on PSA, role of 5-ARIs in PCa prevention, and indications for prostate biopsy referral. PCPs were stratified by residency graduation year before or after 2010, or medical specialty of Family Medicine or Internal Medicine. Survey responses were summarized with descriptive statistics and responses between groups (residency graduation year or medical specialty) were compared using Chi-squared test. Results A total of 182 PCPs were emailed, of which 30 responded (16.5% response rate). Thirteen PCPs (43.3%) graduated residency before 2010 and 17 (56.7%) after 2010. Sixteen PCPs (53.3%) were Family Medicine physicians and 14 (46.7%) were Internists. The majority of PCPs reported that every 6 months, they saw at least one patient with BPH (96.7%), ordered at least one PSA test (86.7%), and referred at least one patient for a prostate biopsy (56.7%). Forty percent of PCPs were not aware of the suppressive effects of 5-ARIs on PSA, 70.0% would not refer a patient for a prostate biopsy who is taking 5-ARIs and has an elevated corrected PSA, 70.0% were not sure or thought that 5-ARIs may decrease the risk of high-grade PCa, and 43.3% were not sure or thought that 5-ARIs are approved for the prevention of PCa. There were no significant differences in the knowledge of 5-ARIs and their effects on PSA, role of 5-ARIs in PCa prevention, or indications for prostate biopsy referral between PCPs who graduated residency before 2010 and after 2010, or between PCPs who were Family Medicine physicians and Internists (p&amp;gt;0.05 for all). Conclusions There is a general lack of awareness amongst PCPs on the knowledge of 5-ARIs and indications for biopsy referral in patients treated with 5-ARIs. An educational opportunity exists to optimize usage of 5-ARIs and avoid delaying PCa detection. Disclosure No.

Multi-Parametric Evaluation of Prostate Cancer on MRI

Background: Prostate cancer is the most common malignancy among men globally and the second leading cause of cancer-related deaths. The increasing prevalence, particularly in aging populations, underscores the urgent need for accurate diagnostic tools to facilitate early detection, precise staging, and effective management. Traditional diagnostic methods, including Digital Rectal Examination (DRE) and Prostate-Specific Antigen (PSA) testing, have limitations in sensitivity and specificity, leading to unnecessary procedures and missed diagnoses. Objective: This study aims to evaluate the efficacy of multiparametric Magnetic Resonance Imaging (mpMRI) in the diagnosis and staging of prostate cancer, comparing its accuracy with conventional diagnostic methods and examining its role in improving patient outcomes. Methods: A retrospective descriptive cross-sectional study was conducted at the Diagnostic Center of Combined Military Hospital, Lahore, from January 2021 to June 2023. Sixty male patients suspected of having prostate cancer, based on elevated PSA levels (&gt;10 ng/mL) or clinical symptoms, were included. mpMRI scans were performed using a Siemens Avanto MRI Machine 1.5T, incorporating T2-weighted imaging, Diffusion-Weighted Imaging (DWI), and Dynamic Contrast-Enhanced (DCE) MRI. The Prostate Imaging Reporting and Data System (PI-RADS) was employed for interpretation. Statistical analysis was conducted using SPSS 26.0, with chi-square tests applied to assess the association between mpMRI findings and prostate cancer diagnosis. Results: mpMRI identified prostate cancer with a sensitivity of 85% and specificity of 88.3%, as evidenced by abnormal MRI findings in 53 out of 60 patients. Elevated PSA levels were confirmed in 90% of the cases. T2-weighted imaging demonstrated hypointensity in the peripheral zone in 70% of patients, while DWI and ADC mapping showed restricted diffusion in 85% of the cases. DCE-MRI revealed post-contrast enhancement in 40% of the participants. The PI-RADS scoring system effectively graded the severity of prostate lesions, with 38.3% of cases categorized as PI-RADS IV. Conclusion: Multiparametric MRI significantly enhances the accuracy of prostate cancer diagnosis and staging, surpassing traditional diagnostic methods in sensitivity and specificity. By providing detailed anatomical and functional information, mpMRI facilitates early detection, accurate localization, and appropriate management of prostate cancer, potentially improving patient outcomes.

A novel blood-based mRNA genomic test for screening, early detection, prognosis, and monitoring of prostate cancer: A multicenter study.

271 Background: Current screening tools, including prostate-specific antigen (PSA) and clinicopathologic parameters, have limitations in the diagnosis and prognosis of prostate cancer. This study examined whether genomic biomarkers can improve screening and monitoring of prostate cancer. Methods: We identified a panel of 25 prostate cancer-related genes through rigorous bioinformatics, computational analyses and genetic testing. These tests, developed by Geneverify Inc. (Hayward, CA; U.S. patent # 10801072 and 10822661) were utilized and optimized by qRT-PCR to determine the diagnostic and prognostic ability of prostate cancer using blood and tissues. The log2-fold increase in gene expression was used to assign the risk score to individual patients. ROC (receiver operator characteristic), AUC (area under ROC curve), and calibration curves were generated to display the overall performance and discrimination ability to separate cancer and non-cancer specimens. Results: A total of 419 prostate cancer patients (135 blood and 284 tissue samples) and 130 normal samples were analyzed in this study. The eligibility criteria were to collect blood and surgical specimens from patients with prostate cancer from 9 hospitals. The study endpoints were to analyze mRNA genomic profiling and correlate with clinicopathologic parameters of the patients. In the blood, a 25-panel gene-set separated prostate cancer patients (n=135) from non-cancer (n=30), AUC = 0.906 [sensitivity = 90% and specificity = 91%]. Assessment of tissue specimens from benign (n=100) and cancer patients (n=284) showed similar results with AUC = 0.9514 [sensitivity = 95% and specificity = 94%]. Interestingly, patients with Gleason grades (GS) &gt;7 showed higher expression of these genes compared to GS &lt;7, suggesting the prognostic ability of the gene-set. When we compared the gene expression in blood verses tissues, there were similar patterns, suggesting that blood can be used for screening, diagnosis and risk assessment of prostate cancer. Conclusions: To our knowledge, this is the first study to investigate the role of mRNA-based genomic signatures for screening, early diagnosis and prognosis of prostate cancer using blood samples. Our data suggest that blood mRNA-genomic profiling developed by Geneverify has the ability to diagnose prostate cancer and stratify patients into distinct prognostic groups, which in turn help in making better treatment strategies.

Improved prostate cancer diagnosis using a modified ResNet50-based deep learning architecture

Prostate cancer, the most common cancer in men, is influenced by age, family history, genetics, and lifestyle factors. Early detection of prostate cancer using screening methods improves outcomes, but the balance between overdiagnosis and early detection remains debated. Using Deep Learning (DL) algorithms for prostate cancer detection offers a promising solution for accurate and efficient diagnosis, particularly in cases where prostate imaging is challenging. In this paper, we propose a Prostate Cancer Detection Model (PCDM) model for the automatic diagnosis of prostate cancer. It proves its clinical applicability to aid in the early detection and management of prostate cancer in real-world healthcare environments. The PCDM model is a modified ResNet50-based architecture that integrates faster R-CNN and dual optimizers to improve the performance of the detection process. The model is trained on a large dataset of annotated medical images, and the experimental results show that the proposed model outperforms both ResNet50 and VGG19 architectures. Specifically, the proposed model achieves high sensitivity, specificity, precision, and accuracy rates of 97.40%, 97.09%, 97.56%, and 95.24%, respectively.

A Systematic Review on Artificial Intelligence Evaluating Metastatic Prostatic Cancer and Lymph Nodes on PSMA PET Scans

Early detection of metastatic prostate cancer (mPCa) is crucial. Whilst the prostate-specific membrane antigen (PSMA) PET scan has high diagnostic accuracy, it suffers from inter-reader variability, and the time-consuming reporting process. This systematic review was registered on PROSPERO (ID CRD42023456044) and aims to evaluate AI’s ability to enhance reporting, diagnostics, and predictive capabilities for mPCa on PSMA PET scans. Inclusion criteria covered studies using AI to evaluate mPCa on PSMA PET, excluding non-PSMA tracers. A search was conducted on Medline, Embase, and Scopus from inception to July 2023. After screening 249 studies, 11 remained eligible for inclusion. Due to the heterogeneity of studies, meta-analysis was precluded. The prediction model risk of bias assessment tool (PROBAST) indicated a low overall risk of bias in ten studies, though only one incorporated clinical parameters (such as age, and Gleason score). AI demonstrated a high accuracy (98%) in identifying lymph node involvement and metastatic disease, albeit with sensitivity variation (62–97%). Advantages included distinguishing bone lesions, estimating tumour burden, predicting treatment response, and automating tasks accurately. In conclusion, AI showcases promising capabilities in enhancing the diagnostic potential of PSMA PET scans for mPCa, addressing current limitations in efficiency and variability.

Health Policy for Prostate Cancer Early Detection in the European Union and the Impact of Opportunistic Screening: PRAISE-U Consortium.

With the new policy recommendation in 2022 to explore the possibilities of screening for prostate cancer by the European Commission, the landscape for prostate cancer early detection is evolving. In line with this recommendation, the PRAISE-U project aims to evaluate the early detection and diagnosis of prostate cancer through customised and risk-based screening programmes, with the goal to align protocols across European Union member states. This systematic review is part of the PRAISE-U project, with the goal to review the policy, medical guideline recommendations, and the current level of opportunistic screening presented in the scientific literature on prostate cancer early detection from 2016 to 2023 in European Union member states. An extensive literature search was performed on 1 June 2023 in a large number of databases, including Embase.com, Medline (Ovid), Web of Science Core Collection, Google Scholar, and Policy Commons. We identified 318 articles (qualitative, quantitative, and reviews), of which 41 were included in the full-text screening. Seventeen articles were ultimately identified as eligible for inclusion. The included articles revealed significant variations towards PSA-based early detection policies for prostate cancer in nine European countries. Despite official recommendations, opportunistic screening was prevalent across all nine countries regardless of recommendations for or against PSA-based early detection. This systematic review suggests that the current early detection policies are not fit for purpose. High levels of opportunistic screening and overdiagnosis persist, prompting policy recommendations for standardised guidelines, informed decision making, and increased awareness to improve efficiency and effectiveness in early detection.