Improving the diagnosis of prostate cancer by telomerase-positive circulating tumor cells: A prospective pilot study

Liquid biopsy: An arsenal for tumour screening and early diagnosis

Cancer has become the second leading cause of death in the world, and more than 50% of cancer patients are diagnosed at an advanced stage. Early diagnosis of tumours is the key to improving patient quality of life and survival time and reducing the socioeconomic burden. However, there is still a lack of reliable early diagnosis methods in clinical practice. In recent years, liquid biopsy technology has developed rapidly. It has the advantages of noninvasiveness, easy access to sample sources, and reproducibility. It has become the main focus of research on the early diagnosis methods of tumours. This review summarises the research progress of existing liquid biopsy markers, such as circulating tumour DNA, circulating viral DNA, DNA methylation, circulating tumour cells, circulating RNA, exosomes, and tumour education platelets in early diagnosis of tumours, and analyses the current advantages and limitations of various markers, providing a direction for the application and transformation of liquid biopsy research in early diagnosis of clinical tumours.

Developing a diagnostic model for predicting prostate cancer: a retrospective study based on Chinese multicenter clinical data

The overdiagnosis of prostate cancer (PCa) caused by nonspecific elevation serum prostate-specific antigen (PSA) and the overtreatment of indolent PCa have become a global problem that needs to be solved urgently. We aimed to construct a prediction model and provide a risk stratification system to reduce unnecessary biopsies. In this retrospective study, clinical data of 1807 patients from three Chinese hospitals were used. The final model was built using stepwise logistic regression analysis. The apparent performance of the model was assessed by receiver operating characteristic curves, calibration plots, and decision curve analysis. Finally, a risk stratification system of clinically significant prostate cancer (csPCa) was created, and diagnosis-free survival analyses were performed. Following multivariable screening and evaluation of the diagnostic performances, a final diagnostic model comprised of the PSA density and Prostate Imaging-Reporting and Data System (PI-RADS) score was established. Model validation in the development cohort and two external cohorts showed excellent discrimination and calibration. Finally, we created a risk stratification system using risk thresholds of 0.05 and 0.60 as the cut-off values. The follow-up results indicated that the diagnosis-free survival rate for csPCa at 12 months and 24 months postoperatively was 99.7% and 99.4%, respectively, for patients with a risk threshold below 0.05 after the initial negative prostate biopsy, which was significantly better than patients with higher risk. Our diagnostic model and risk stratification system can achieve a personalized risk calculation of csPCa. It provides a standardized tool for Chinese patients and physicians when considering the necessity of prostate biopsy.

Polyploid Giant Cancer Cells Are Frequently Found in the Urine of Prostate Cancer Patients

Prostate cancer is the third cause of cancer-related deaths in men. Its early and reliable diagnosis is still a public health issue, generating many useless prostate biopsies. Prostate cancer cells detected in urine could be the target of a powerful test but they are considered too rare. By using an approach targeting rare cells, we have analyzed urine from 45 patients with prostate cancer and 43 healthy subjects under 50 y.o. We observed a relevant number of giant cells in patients with cancer. Giant cells, named Polyploid Giant Cancer Cells (PGCC), are thought to be involved in tumorigenesis and treatment resistance. We thus performed immune-morphological studies with cancer-related markers such as α-methylacyl-CoA racemase (AMACR), prostate-specific membrane antigen (PSMA), and telomerase reverse transcriptase (TERT) to understand if the giant cells we found are PGCC or other urinary cells. We found PGCC in the urine of 22 patients, including those with early-stage prostate cancer, and one healthy subject. Although these results are preliminary, they provide, for the first time, clinical evidence that prostate cancers release PGCC into the urine. They are expected to stimulate further studies aimed at understanding the role of urinary PGCC and their possible use as a diagnostic tool and therapeutic target.

Feasibility study of expressing epcam + /vimentin + CTC in prostate cancer diagnosis

PURPOSE

Prostate cancer (PCa) is one of the most common malignancies in men and one of the leading causes of cancer-related deaths; circulating tumor cells (CTC) are malignant cells that have broken off from original tumor or metastatic sites and extravasated into the blood vessels either naturally or maybe as a consequence of surgical procedures. This study aims to explore the feasibility of liquid biopsy technique to diagnose prostate cancer.

METHOD

We constructed an assay platform integrating magnetic separation and fluorescence in situ hybridization (FISH) to effectively capture prostate cancer CTCs and evaluate the distribution between healthy volunteers and prostate cancer patients, respectively.

RESULTS

There was a significant difference in the number of CTCs between the healthy population and prostate cancer patients (P < 0.001). The results of the study showed that the CTCs capture identification system has good sensitivity and specificity in identifying prostate cancer patients.

CONCLUSION

The CTCs test allows us to accurately identify patients who are at high risk for prostate cancer, allowing for early intervention and treating patients effectively.

Biomarkers of Aggressive Prostate Cancer at Diagnosis

In the United States, prostate cancer (CaP) remains the second leading cause of cancer deaths in men. CaP is predominantly indolent at diagnosis, with a small fraction (25-30%) representing an aggressive subtype (Gleason score 7-10) that is prone to metastatic progression. This fact, coupled with the criticism surrounding the role of prostate specific antigen in prostate cancer screening, demonstrates the current need for a biomarker(s) that can identify clinically significant CaP and avoid unnecessary biopsy procedures and psychological implications of being diagnosed with low-risk prostate cancer. Although several diagnostic biomarkers are available to clinicians, very few comparative trials have been performed to assess the clinical effectiveness of these biomarkers. It is of note, however, that a majority of these clinical trials have been over-represented by men of Caucasian origin, despite the fact that African American men have a 1.7 times higher incidence and 2.1 times higher rate of mortality from prostate cancer. Biomarkers for CaP diagnosis based on the tissue of origin include urine-based gene expression assays (PCA3, Select MDx, ExoDx Prostate IntelliScore, Mi-Prostate Score, PCA3-PCGEM1 gene panel), blood-based protein biomarkers (4K, PHI), and tissue-based DNA biomarker (Confirm MDx). Another potential direction that has emerged to aid in the CaP diagnosis include multi-parametric magnetic resonance imaging (mpMRI) and bi-parametric magnetic resonance imaging (bpMRI), which in conjunction with clinically validated biomarkers may provide a better approach to predict clinically significant CaP at diagnosis. In this review, we discuss some of the adjunctive biomarker tests along with newer imaging modalities that are currently available to help clinicians decide which patients are at risk of having high-grade CaP on prostate biopsy with the emphasis on clinical utility of the tests across African American (AA) and Caucasian (CA) men.

HSP27/Menin Expression as New Prognostic Serum Biomarkers of Prostate Cancer Aggressiveness Independent of PSA

The screening of PCa is based on two tests, the total PSA test and the rectal examination. However, PSA is not specific for PCa stage confirmation, leading in false positive result and involving PCa over-diagnosis and over-treatment. HSP27 and Menin have been found to be overexpressed in a wide range of human cancers. Recent studies showed how HSP27 interacts with and stabilizes Menin to lead PCa progression and treatment resistance. The purpose of our study was to evaluate the correlation of HSP27 and Menin molecular expression, and their prognosis value in PCa with respect to clinicopathological features. Elisa was employed to measure serum HSP27 and Menin concentrations in 73 PCa patients and 80 healthy individuals. Immunohistochemistry (IHC) was used to determine HSP27 and Menin tissue expression in 57 tumors and 4 Benign Prostatic Hyperplasia (BPH) tissues. Serum HSP27 expression correlated with its tissue expression in all PCa patients, whereas serum Menin expression correlated only with tissue expression in aggressive PCa patients. Moreover, the results showed a positive correlation between HSP27 and Menin either in serum (r = 0.269; p = 0.021) or in tissue (r = 0.561; p < 0.0001). In aggressive PCa, serum expression of HSP27 and Menin was positively correlated (r = 0.664; R = 0.441; p = 0.001). The correlation between HSP27 and Menin expression in tissue was found only in patients with aggressive PCa (r = 0.606; R = 0.367; p = 0.004). Statistical analysis showed that the expression of both biomarkers was positively correlated with the hormone resistance or sensitivity, tumor aggressiveness, metastasis, Gleason Score, death and did not significantly correlate with age and PSA. Survival was illustrated by Kaplan−Meier curves; increased HSP27 and Menin expression correlated with shorter survival of PCa patients (p = 0.001 and p < 0.0001, respectively). Accuracy in predicting aggressiveness was quantified by the Area Under the Curve (AUC) of Receiver Operating Characteristic (ROC). We demonstrated that the combination of HSP27/Menin was statistically greater than PSA; it achieved an AUC of 0.824 (95% CI, 0.730−0.918; p < 0.0001). However, HSP27/Menin/PSA combination decreased the diagnostic value with an AUC of 0.569 (95% CI, 0.428−0.710; p = 0.645). Our work suggests the potential role of HSP27/Menin as diagnostic and prognostic biomarkers.

Expression Analysis of miRNAs and Their Potential Role as Biomarkers for Prostate Cancer Detection

Prostate cancer (PCa) is the second most frequent cancer diagnosed in men worldwide. The detection methods for PCa are either unreliable, like prostate-specific antigen (PSA), or extremely invasive, such as in the case of biopsies. Therefore, there is an urgent necessity for reliable and less invasive detection procedures that can differentiate between patients with benign diseases and those with cancer. In this matter, microRNAs (miRNAs) are suggested as potential biomarkers for cancer. MiRNAs have been found to be dysregulated in several different cancers, and these genetic alterations may present specific signatures for a given malignancy. Here, we examined the expression of miR141-3p, miR145-5p, miR146a-5p, and miR148b-3p in human tissue samples of PCa (n = 41) and benign prostatic diseases (BPD) (n = 30) using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). We combined the expression results with patient clinicopathological characteristics in logistic regression models to create accurate PCa predictive models. A model including information of miR148b-3p and patient age showed relevant prediction results (area under the curve [AUC] = 0.818, precision = 0.763, specificity = 0.762, and accuracy = 0.762). A model including all four miRNAs and patient age presented outstanding prediction results (AUC = 0.918, precision = 0.861, specificity = 0.861, and accuracy = 0.857). Our results represent a potential novel procedure based on logistic regression models that utilize miRNA expressions and patient age to assist with PCa diagnosis.

Insights into Circulating Tumor Cell Clusters: A Barometer for Treatment Effects and Prognosis for Prostate Cancer Patients

Simple Summary

Circulating tumor cells (CTCs) are a promising biomarker for the risk of prostate cancer aggressiveness and metastasis and play a role in the processes of tumor migration and metastasis. CTC clusters, which have different physical and biological properties from individual CTCs, are collections of tumor cells and non-malignant cells, resulting in greater metastatic potential. Therefore, this review aims to summarize the current knowledge of CTC clusters in metastasis as well as related biological properties and to suggest possibilities for their usage in diagnostic and therapeutic practice.

Abstract

Prostate cancer (PCa) exhibits high cellular heterogeneity across patients. Therefore, there is an urgent need for more real-time and accurate detection methods, in both prognosis and treatment in clinical settings. Circulating tumor cell (CTC) clusters, a population of tumor cells and non-malignant cells in the blood of patients with tumors, are a promising non-invasive tool for screening PCa progression and identifying potential benefit groups. CTC clusters are associated with tumor metastasis and possess stem-like characteristics, which are likely attributable to epithelial–mesenchymal transition (EMT). Additionally, these biological properties of CTC clusters, particularly androgen receptor V7, have indicated the potential to reflect curative effects, guide treatment modalities, and predict prognosis in PCa patients. Here, we discuss the role of CTC clusters in the mechanisms underlying PCa metastasis and clinical applications, with the aim of informing more appropriate clinical decisions, and ultimately, improving the overall survival of PCa patients.