Early Diagnosis Of Prostate Cancer Research Articles

Ultrasensitive Detection of Prostate Specific Antigen by an Unlabeled Fluorescence Aptasensor Based on the AIE Effect.

The accurate and sensitive detection of prostate specific antigen (PSA) is vital for the early diagnosis and treatment of prostate cancer. To this end, an unlabeled fluorescent aptasensor was constructed by using a novel Compound B {1,1'-(1,4-phenylene) bis(3-ethyl-1H-imidazol-3-ium) iodide} with aggregation-induced emission (AIE) activity as a fluorescence signal and NH2-Fe3O4 particle as an adsorption platform. Compound B could combine with prostate specific antigen aptamers (PSA-Apt) to form a PSA-Apt/B complex, which further generated the AIE effect. Then, PSA was added to the PSA-Apt/B solution. PSA combined with PSA-Apt/B to form the PSA-Apt/B/PSA complex. Next, NH2-Fe3O4 magnetic particles were added to the solution. Given that PSA-Apt/B/PSA would no longer combine with NH2-Fe3O4 magnetic particles, the PSA-Apt/B/PSA complex remained in the supernate after magnet separation, and the supernate showed strong fluorescence (I). When no PSA was added to the PSA-Apt/B solution, PSA-Apt/B could combine with NH2-Fe3O4 magnetic particles and would be sucked into the bottom of the test tube by magnet, and the supernate would show weak fluorescence (I0). Result showed that the difference between the above-mentioned two fluorescence values (∆I = I - I0) had an excellent linear relationship with the PSA concentration within the concentration range of 0.01-10ng/mL, and its limit of detection was 3pg/mL (S/N = 3). In addition, the sensor has high accuracy and can be directly used to test PSA in actual serum samples.

Colorimetric and Photothermal Dual-Modal Switching Lateral Flow Immunoassay Based on a Forced Dispersion Prussian Blue Nanocomposite for the Sensitive Detection of Prostate-Specific Antigen.

Prostate-specific antigen (PSA) is a key marker for a prostate cancer diagnosis. The low sensitivity of traditional lateral flow immunoassay (LFIA) methods makes them unsuitable for point-of-care testing. Herein, we designed a nanozyme by in situ growth of Prussian blue (PB) within the pores of dendritic mesoporous silica (DMSN). The PB was forcibly dispersed into the pores of DMSN, leading to an increase in exposed active sites. Consequently, the atom utilization is enhanced, resulting in superior peroxidase (POD)-like activity compared to that of cubic PB. Antibody-modified DMSN@PB nanozymes serve as immunological probes in an enzymatic-enhanced colorimetric and photothermal dual-signal LFIA for PSA detection. After systematic optimization, the LFIA based on DMSN@PB successfully achieves a 4-fold amplification of the colorimetric signal within 7 min through catalytic oxidation of the chromogenic substrate by POD-like activity. Moreover, DMSN@PB exhibits an excellent photothermal conversion ability under 808 nm laser irradiation. Accordingly, photothermal signals are introduced to improve the anti-interference ability and sensitivity of LFIA, exhibiting a wide linear range (1-40 ng mL-1) and a low PSA detection limit (0.202 ng mL-1), which satisfies the early detection level of prostate cancer. This research provides a more accurate and reliable visualization analysis methodology for the early diagnosis of prostate cancer.

Synergistic enhancement mediated sensitive SERS-based immunoassay of PSA using versatile PDMS@AgNPs@ZIF-67 biomimetic substrates

Among various biomimetic polymer materials, polydimethylsiloxane (PDMS) stands out as an ideal matrix for surface-enhanced Raman scattering (SERS) due to its unique intrinsic Raman signal and tenacity. In order to realize the precise detection of prostate-specific antigen (PSA), we proposed a sandwich-type SERS-active immunostructure composed of PDMS@silver nanoparticles (Ag NPs)@ZIF-67 biomimetic film as the immunosubstrate and gold nanorods (Au NRs) as immunoprobes. Due to the synergistic effect of electromagnetic enhancement facilitated by biomimetic surfaces and chemical enhancement achieved by ZIF-67, this structure enabled an ultrasensitive and selective detection of PSA across a broad range from 10−3 to 10−9 mg/mL. The achieved limit of detection was as low as 3.0 × 10−10 mg/mL. Particularly, the intrinsic Raman signal of PDMS matrix at 2905cm−1 was employed as a potential internal standard (IS) in the detection, achieving a high coefficient of determination (R2) value of 0.996. This multifunctional SERS substrate-mediated immunoassay holds vast potential for early diagnosis of prostate cancer, offering promising prospects for clinical applications.

From pixels to pathology: A novel dual-pathway multi-scale hierarchical upsampling network for MRI-based prostate zonal segmentation

Prostate cancer is a prevalent and life-threatening disease characterized by abnormal cell growth within the prostate gland. Early and accurate diagnosis of prostate cancer is crucial for effective treatment planning. Magnetic Resonance Imaging (MRI) is valuable for diagnosing and assessing prostate cancer. Medical professionals use MRI to create segmentation for detecting prostate cancer. However, existing segmentation methods are limited in accurately delineating anatomical structures and tumor regions within the prostate. This research proposes an innovative methodology for advancing MRI-based prostate segmentation. The objective is to encompass anatomical and tumor zones within the prostate, facilitating precise diagnosis and treatment planning. The proposed dual-pathway multi-scale hierarchical upsampling network introduces significant modifications compared to the traditional UNet-based architecture. It outperforms previous studies, demonstrating superior performance in anatomical segmentation on both the ProstateX and Prostate158 datasets. It achieves an intersection over union of 0.8449 and a dice similarity coefficient of 0.9872 on ProstateX, as well as an intersection over union of 0.8065 and a dice similarity coefficient of 0.9831 on Prostate158, suppressing previous research by a significant margin. These results highlight the potential of this approach to advance the utility of MRI in diagnosing and planning the treatment of prostate-related pathologies, benefiting both patients and healthcare practitioners.

Salivary MiR-193A-5P, MiR-375, MiR-141, MiR-25 and MiR-449B levels can be used as a new non-invasive diagnostic panel for early and accurate diagnosis of prostate cancer

Salivary MiR-193A-5P, MiR-375, MiR-141, MiR-25 and MiR-449B levels can be used as a new non-invasive diagnostic panel for early and accurate diagnosis of prostate cancer

Prostate cancer, its implications and awareness in the South Asian population: a retrospective cross-sectional cohort analysis

Introduction: The second most frequent form of cancer in males and the main reason for cancer-related deaths worldwide is prostate cancer (PC). Despite being less common than in Western nations, PC incidence and death rates have been rising throughout South Asia. This study intends to evaluate how well-informed and knowledgeable the South Asian public is about PC, its symptoms, and screening procedures among men and women. Methods: From August to September of 2022, a cross-sectional survey was carried out throughout South Asia. Participants in the research had to be at least 24 years old, and it used a practical sampling approach. A self-created questionnaire with both closed- and open-ended questions was used to gather the data. SPSS was used to conduct statistical analysis, including χ 2 tests for relationships. Results: A total of 378 individuals, comprising 57.6% men and 41.8% women, were involved in the study. Only 45.0% of participants were aware of prostate specific antigen testing for early PC diagnosis, however, 81.7% of people recognized what the prostate gland was. Approximately 87% of individuals had never received a screening for PC. Compared to males, women showed a stronger understanding of PC and its screening techniques. Notably, 94.7% believed the likelihood of effective therapy was increased by early identification. Conclusion: While women demonstrated better levels of knowledge, the study’s findings show that the general population in South Asia suffers from a serious shortage of reliable knowledge concerning PC. To promote early identification, lower morbidity, and enhance treatment success, awareness-raising and educational initiatives are essential, with a focus on both sexes. This study establishes the foundation for future research and emphasizes the necessity for targeted educational programmes in the area.

Computer-aided detection of prostate cancer in early stages using multi-parameter MRI: A promising approach for early diagnosis.

Transrectal ultrasound-guided prostate biopsy is the gold standard diagnostic test for prostate cancer, but it is an invasive examination of non-targeted puncture and has a high false-negative rate. In this study, we aimed to develop a computer-assisted prostate cancer diagnosis method based on multiparametric MRI (mpMRI) images. We retrospectively collected 106 patients who underwent radical prostatectomy after diagnosis with prostate biopsy. mpMRI images, including T2 weighted imaging (T2WI), diffusion weighted imaging (DWI), and dynamic-contrast enhanced (DCE), and were accordingly analyzed. We extracted the region of interest (ROI) about the tumor and benign area on the three sequential MRI axial images at the same level. The ROI data of 433 mpMRI images were obtained, of which 202 were benign and 231 were malignant. Of those, 50 benign and 50 malignant images were used for training, and the 333 images were used for verification. Five main feature groups, including histogram, GLCM, GLGCM, wavelet-based multi-fractional Brownian motion features and Minkowski function features, were extracted from the mpMRI images. The selected characteristic parameters were analyzed by MATLAB software, and three analysis methods with higher accuracy were selected. Through prostate cancer identification based on mpMRI images, we found that the system uses 58 texture features and 3 classification algorithms, including Support Vector Machine (SVM), K-nearest Neighbor (KNN), and Ensemble Learning (EL), performed well. In the T2WI-based classification results, the SVM achieved the optimal accuracy and AUC values of 64.3% and 0.67. In the DCE-based classification results, the SVM achieved the optimal accuracy and AUC values of 72.2% and 0.77. In the DWI-based classification results, the ensemble learning achieved optimal accuracy as well as AUC values of 75.1% and 0.82. In the classification results based on all data combinations, the SVM achieved the optimal accuracy and AUC values of 66.4% and 0.73. The proposed computer-aided diagnosis system provides a good assessment of the diagnosis of the prostate cancer, which may reduce the burden of radiologists and improve the early diagnosis of prostate cancer.

Evaluating Leukocyte Telomere Length and Myeloid-Derived Suppressor Cells as Biomarkers for Prostate Cancer.

Leukocyte telomere length (LTL) and myeloid-derived suppressor cells (MDSC) are associated with aging and the development and progression of cancer. However, the exact nature of this relationship remains unclear. Our study aimed to investigate the potential of LTL and MDSC as diagnostic biomarkers for prostate cancer while also seeking to deepen our understanding of the relationship of these potential biomarkers to each other. Our study involved patients undergoing a prostate biopsy. We analyzed the relative LTL in genomic DNA obtained from peripheral blood leukocytes as well as the percentage of MDSC and their subtypes in peripheral blood mononuclear cells (PBMC). Our evaluation focused on examining the relationship between LTL and MDSC and pathological diagnoses as well as investigating the correlation between LTL and MDSC levels. In our study of 102 participants, 56 were pathologically diagnosed with localized prostate cancer (cancer group), while 46 tested negative (control group). The cancer group exhibited significantly shorter LTL in comparison to the control group (p = 0.024). Additionally, the cancer group showed a tendency towards a higher percentage of monocytic MDSC (M-MDSC), although this difference did not reach statistical significance (p = 0.056). Our multivariate logistic regression analysis revealed that patients with shorter LTL and higher percentages of M-MDSC had a 2.98-fold (95% CI = 1.001-8.869, p = 0.049) and 3.03-fold (95% CI = 1.152-7.977, p = 0.025) increased risk of prostate cancer diagnosis, respectively. There was also a significant negative correlation between LTL and M-MDSC. (r = -0.347, p < 0.001). Our research has established a correlation between LTL and MDSC in patients undergoing biopsy for prostate cancer. Notably, we observed that individuals with localized prostate cancer tend to have shorter LTL and a higher percentage of M-MDSC prior to their diagnosis. These findings suggest that LTL and M-MDSC could potentially serve as adjunctive biomarkers for the early diagnosis of prostate cancer.

Integral role of metabolic profiling in patients with prostate cancer

Prostate cancer is the most diagnosed malignant neoplasm among males worldwide. Over the past few years, there has been a need to find alternative methods for early diagnosis of prostate cancer. There is evidence that metabolic dysfunction is a characteristic feature of the carcinogenesis of prostate cancer, with various metabolites acting as biomarkers of tumor growth. Metabolomics is a young science that arose at the junction of molecular biology, biochemistry and genetics. The complete set of substrates and metabolic products is a metabolic profile, or metabolome. The metabolome of prostate cancer is formed by substances formed as a result of metabolic changes in response to the occurrence of a malignant process in the prostate. Unique data on metabolic changes have already been obtained, allowing us to rethink the carcinogenesis of prostate cancer. The study of the metabolome opens up new opportunities for early diagnosis, prognosis and treatment of prostate cancer.

Machine learning-based analysis of 68Ga-PSMA-11 PET/CT images for estimation of prostate tumor grade.

Early diagnosis of prostate cancer, the most common malignancy in men, can improve patient outcomes. Since the tissue sampling procedures are invasive and sometimes inconclusive, an alternative image-based method can prevent possible complications and facilitate treatment management. We aim to propose a machine-learning model for tumor grade estimation based on 68Ga-PSMA-11 PET/CT images in prostate cancer patients. This study included 90 eligible participants out of 244 biopsy-proven prostate cancer patients who underwent staging 68Ga-PSMA-11 PET/CT imaging. The patients were divided into high and low-intermediate groups based on their Gleason scores. The PET-only images were manually segmented, both lesion-based and whole prostate, by two experienced nuclear medicine physicians. Four feature selection algorithms and five classifiers were applied to Combat-harmonized and non-harmonized datasets. To evaluate the model's generalizability across different institutions, we performed leave-one-center-out cross-validation (LOOCV). The metrics derived from the receiver operating characteristic curve were used to assess model performance. In the whole prostate segmentation, combining the ANOVA algorithm as the feature selector withRandom Forest (RF) and Extra Trees (ET) classifiers resulted in the highest performance among the models, with an AUC of 0.78 and 083, respectively. In the lesion-based segmentation, the highest AUC was achieved byMRMR feature selector + Linear Discriminant Analysis (LDA) andLogistic Regression (LR) classifiers (0.76 and 0.79, respectively). The LOOCV results revealed that both the RF_ANOVA and ET_ANOVA models showed high levels of accuracy and generalizability across different centers, with an average AUC value of 0.87 for the ET_ANOVA combination. Machine learning-based analysis of radiomics features extracted from 68Ga-PSMA-11 PET/CT scans can accurately classify prostate tumors into low-risk and intermediate- to high-risk groups.

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 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.

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.

Radiogenomic analysis of ultrasound phenotypic features coupled to proteomes predicts metastatic risk in primary prostate cancer

BackgroundPrimary prostate cancer with metastasis has a poor prognosis, so assessing its risk of metastasis is essential.MethodsThis study combined comprehensive ultrasound features with tissue proteomic analysis to obtain biomarkers and practical diagnostic image features that signify prostate cancer metastasis.ResultsIn this study, 17 ultrasound image features of benign prostatic hyperplasia (BPH), primary prostate cancer without metastasis (PPCWOM), and primary prostate cancer with metastasis (PPCWM) were comprehensively analyzed and combined with the corresponding tissue proteome data to perform weighted gene co-expression network analysis (WGCNA), which resulted in two modules highly correlated with the ultrasound phenotype. We screened proteins with temporal expression trends based on the progression of the disease from BPH to PPCWOM and ultimately to PPCWM from two modules and obtained a protein that can promote prostate cancer metastasis. Subsequently, four ultrasound image features significantly associated with the metastatic biomarker HNRNPC (Heterogeneous nuclear ribonucleoprotein C) were identified by analyzing the correlation between the protein and ultrasound image features. The biomarker HNRNPC showed a significant difference in the five-year survival rate of prostate cancer patients (p < 0.0053). On the other hand, we validated the diagnostic efficiency of the four ultrasound image features in clinical data from 112 patients with PPCWOM and 150 patients with PPCWM, obtaining a combined diagnostic AUC of 0.904. In summary, using ultrasound imaging features for predicting whether prostate cancer is metastatic has many applications.ConclusionThe above study reveals noninvasive ultrasound image biomarkers and their underlying biological significance, which provide a basis for early diagnosis, treatment, and prognosis of primary prostate cancer with metastasis.

Ratio fluorescence/colorimetric dual mode aptasensor and smartphones-assisted miniaturized device for early diagnosis of prostate cancer

Prostate specific antigen (PSA) is the most common tumor biomarker for prostate cancer (PCa), and its precise determination is essential to improving survival rate and reducing treatment cost of cancer patient. Here, we have proposed a novel ratio fluorescence/colorimetric dual mode aptasensor based on CdTe-apt + B-CDs + ZrFe MOF system for PSA determination. Specifically, as-prepared ZrFe MOF with good peroxidase like activity can quench the fluorescence of B-CDs + CdTe-apt system via inner filter effect (IFE), while the existence of PSA can restore fluorescence of CdTe-apt but virtually unchanged fluorescence of B-CDs due to specific identification between PSA and aptamer. Similarly, the addition of PSA can recover the peroxidase like activity of ZrFe MOF which is significantly suppressed by PSA aptamer. Based on this, the proposed ratio fluorescence/colorimetric dual mode aptasensor has achieved satisfactory results in PSA analysis of serum specimens. Valuably, an inexpensive, portable but credible smartphones-assisted miniaturized device is expected to be exploited for the early diagnosis of PCa, inspiring the design and construction of advanced portable devices for self-monitoring and home screening of various cancers.

Phage Display's Prospects for Early Diagnosis of Prostate Cancer.

Prostate cancer (PC) is the second most diagnosed cancer among men. It was observed that early diagnosis of disease is highly beneficial for the survival of cancer patients. Therefore, the extension and increasing quality of life of PC patients can be achieved by broadening the cancer screening programs that are aimed at the identification of cancer manifestation in patients at earlier stages, before they demonstrate well-understood signs of the disease. Therefore, there is an urgent need for standard, sensitive, robust, and commonly available screening and diagnosis tools for the identification of early signs of cancer pathologies. In this respect, the "Holy Grail" of cancer researchers and bioengineers for decades has been molecular sensing probes that would allow for the diagnosis, prognosis, and monitoring of cancer diseases via their interaction with cell-secreted and cell-associated PC biomarkers, e.g., PSA and PSMA, respectively. At present, most PSA tests are performed at centralized laboratories using high-throughput total PSA immune analyzers, which are suitable for dedicated laboratories and are not readily available for broad health screenings. Therefore, the current trend in the detection of PC is the development of portable biosensors for mobile laboratories and individual use. Phage display, since its conception by George Smith in 1985, has emerged as a premier tool in molecular biology with widespread application. This review describes the role of the molecular evolution and phage display paradigm in revolutionizing the methods for the early diagnosis and monitoring of PC.

Diagnostic value comparison of the combination of prostate-specific membrane antigen-body positron emission tomography/magnetic resonance imaging and prostate health index with each alone in early diagnosis of prostate cancer

ObjectiveThis study aimed to figure out whether the combination of prostate health index (PHI) and prostate-specific membrane antigen (PSMA)-positron emission tomography/magnetic resonance imaging (PET/MR) could improve the diagnostic accuracy for prostate cancer (PCa) than that of each individual method used alone. MethodsIn this prospective, observational study, 41 patients who underwent systematic prostate biopsy between June 2019 and September 2022 were enrolled. Both the PHI test and 18F-PSMA-1007-PET/MR were performed prior to biopsies. The diagnostic accuracy of different models was compared by logistic regression, area under the curves (AUC) of the receiver operating characteristic and net reclassification improvement (NRI) index. ResultsAmong the 41 patients, 14 (34.1%) were pathologically diagnosed with PCa. PHI in PCa group was significantly higher than that in benign group (44.4 vs. 35.0, p=0.048). Similarly, all the patients in PCa group received the positive results of 18F-PSMA-1007-PET/MR, of which the positive rate was significantly higher than those in bengin group (100% vs. 62.96%, p<0.05). The 18F-PSMA-1007-PET/MR provided additional diagnostic value to PHI (AUC: 0.802 vs. 0.692, p=0.025). However, there was no significant difference between the combination model and the 18F-PSMA-1007-PET/MR alone (AUC 0.802 vs. 0.685, p=0.071). The optimal PHI cutoff of the combination model is 32, with which the model could significantly reduce unnecessary biopsy (NRI: 22.22%, 95% confidence interval: 6.54–37.90, p=0.005). But among patients with PHI≥43.5, there was no significant difference between the combination model and PHI alone (NRI: 11.11%, 95% confidence interval: −0.74–22.97, p=0.066). ConclusionThe combination of PHI and 18F-PSMA-1007-PET/MR outperforms PHI alone for predicting PCa, especially in avoiding unnecessary biopsy. However, for patients with PHI≥43.5, the addition of 18F-PSMA-1007-PET/MR to PHI does not yield additional benefits.

Intracellular MicroRNA Imaging and Specific Discrimination of Prostate Cancer Circulating Tumor Cells Using Multifunctional Gold Nanoprobe-Based Thermophoretic Assay.

Circulating tumor cells (CTCs) have emerged as powerful biomarkers for diagnosis of prostate cancer. However, the effective identification and concurrently accurate imaging of CTCs for early screening of prostate cancer have been rarely explored. Herein, we reported a multifunctional gold nanoprobe-based thermophoretic assay for simultaneous specific distinguishing of prostate cancer CTCs and sensitive imaging of intracellular microRNA (miR-21), achieving the rapid and precise detection of prostate cancer. The multifunctional gold nanoprobe (GNP-DNA/Ab) was modified by two types of prostate-specific antibodies, anti-PSMA and anti-EpCAM, which could effectively recognize the targeting CTCs, and meanwhile linked double-stranded DNA for further visually imaging intracellular miR-21. Upon the specific internalization of GNP-DNA/Ab by PC-3 cells, target aberrant miR-21 could displace the signal strand to recover the fluorescence signal for sensitive detection at the single-cell level, achieving single PC-3 cell imaging benefiting from the thermophoresis-mediated signal amplification procedure. Taking advantage of the sensitive miR-21 imaging performance, GNP-DNA/Ab could be employed to discriminate the PC-3 and Jurkat cells because of the different expression levels of miR-21. Notably, PC-3 cells were efficiently recognized from white blood cells, exhibiting promising potential for the early diagnosis of prostate cancer. Furthermore, GNP-DNA/Ab possessed good biocompatibility and stability. Therefore, this work provides a great tool for aberrant miRNA-related detection and specific discrimination of CTCs, achieving the early and accurate diagnosis of prostate cancer.

Development of a highly sensitive fluorescent probe using Delonix regia (Gulmohar) tree pod shell for precise sarcosine detection in human urine samples: advancing prostate cancer diagnosis

We designed a highly sensitive fluorescent sensor for the early detection of sarcosine, a potential biomarker for prostate cancer. This sensor was based on surface-cobalt-doped fluorescent carbon quantum dots (Co-CD) using a FRET-based photoluminescent sensing platform. Blue luminescent carbon quantum dots (CQD) were synthesised through a hydrothermal approach, utilizing Delonix regia tree pod shells. Cobalt was employed to functionalize the CQD, enhancing the quantum-entrapped effects and minimizing surface flaws. To optimize Co-CD preparation, we employed a Box-Behnken design (BBD), and response surface methodology (RSM) based on single-factor experiments. The Co-CD was then used as a fluorescent probe for selective Cu2+ detection, with Cu2+ quenching Co-CD fluorescence through an energy transfer process, referred to as ‘turn-off’. When sarcosine was introduced, the fluorescence intensity of Co-CD was restored, creating a ‘turn-on’ response. The sensor exhibited a Cu2+ detection limit (LOD) of 2.4 µM with a linear range of 0 μM to 10 µM. The sarcosine detection in phosphate buffer saline (PBS, pH 7.4) resulted in an LOD of 1.54 μM and a linear range of 0 to 10 µM. Importantly, the sensor demonstrated its suitability for clinical analysis by detecting sarcosine in human urine. In summary, our rapid and highly sensitive sensor offers a novel approach for the detection of sarcosine in real samples, facilitating early prostate cancer diagnosis. Communicated by Ramaswamy H. Sarma

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.