Prostate cancer aggressiveness and age: Impact of p53, BCL-2 and microvessel density

Prostate-specific Antigen Density as a Proxy for Predicting Prostate Cancer Severity: Is There Any Difference between Systematic and Targeted Biopsy?

Background

Prostate cancer screening with prostate-specific antigen (PSA) can result in unnecessary biopsies and overdiagnosis. Alternately, PSA density (PSAD) calculation may help support biopsy decisions; however, evidence of its usefulness is not concrete.

Objective

To evaluate the predictive value of PSAD for clinically significant prostate cancer detection by systematic and MRI-targeted biopsies.

Methods

This prospective study was conducted at two tertiary hospitals in Riyadh, Saudi Arabia, between December 2018 and November 2021. Patients suspected of prostate cancer were subjected to multi-parametric MRI, and for those with positive findings, systematic and targeted biopsies were performed. Clinically non-significant and significant prostate cancer cases were classified based on histopathology-defined ISUP grade or Gleason score. The PSAD was measured using the prostate volume determined by the MRI and categorized into ≤0.15, 0.16-0.20, and >0.20 ng/ml2 subgroups.

Results

Systematic and targeted biopsies were carried out for 284 patients. The discriminant ability of PSAD is higher in MRI-targeted biopsy compared with systematic biopsy (AUC: 0.77 vs. 0.73). The highest sensitivity (97%) and specificity (87%) were detected at 0.07 ng/ml2 in targeted biopsy. More than half of the clinically significant cases were detected in the >0.2 ng/ml2 PSAD category (systematic: 52.4%; targeted: 51.1%). The CHAID methodology found that the probability of having clinically significant cancer (CSC) in patients with PSAD >0.15 ng/ml2 was more than threefold than that in patients with PSAD ≤0.15 ng/ml2 (64% vs. 20.2%). When considered by age, in PSAD ≤0.15 ng/ml2 subgroup, the percentage of CSC detection rate increased from 20.2% to 24.6% in patients aged ≥60 years.

Conclusion

PSAD has good discriminant power for predicting clinically significant prostate cancer. A cutoff of 0.07 ng/ml2 should be adopted, but should be interpreted with caution and by considering other parameters such as age.

Global and regional quality of care index for prostate cancer: an analysis from the Global Burden of Disease study 1990-2019

BACKGROUND

Prostate cancer (PCa) is one of the most prevalent cancers worldwide, with a significant burden on societies and healthcare providers. We aimed to develop a metric for PCa quality of care that could demonstrate the disease's status in different countries and regions (e.g., socio-demographic index (SDI) quintiles) and assist in improving healthcare policies.

METHODS

Basic burden of disease indicators for various regions and age-groups were retrieved from Global Burden of Disease Study 1990-2019, which then were used to calculate four secondary indices: mortality to incidence ratio, DALYs to prevalence ratio, prevalence to incidence ratio, and YLLs to YLDs ratio. These four indices were combined through a principal component analysis (PCA), producing the quality of care index (QCI).

RESULTS

PCa's age-standardized incidence rate increased from 34.1 in 1990 to 38.6 in 2019, while the age-standardized death rate decreased in the same period (18.1 to 15.3). From 1990 to 2019, global QCI increased from 74 to 84. Developed regions (high SDI) had the highest PCa QCIs in 2019 (95.99), while the lowest QCIs belonged to low SDI countries (28.67), mainly from Africa. QCI peaked in age groups 50 to 54, 55 to 59, or 65 to 69, depending on the socio-demographic index.

CONCLUSIONS

Global PCa QCI stands at a relatively high value (84 in 2019). Low SDI countries are affected the most by PCa, mainly due to the lack of effective preventive and treatment methods in those regions. In many developed countries, QCI decreased or stopped rising after recommendations against routine PCa screening in the 2010-2012 period, highlighting the role of screening in reducing PCa burden.

Utility of Clinical-Radiomic Model to Identify Clinically Significant Prostate Cancer in Biparametric MRI PI-RADS V2.1 Category 3 Lesions

Purpose

To determine the predictive performance of the integrated model based on clinical factors and radiomic features for the accurate identification of clinically significant prostate cancer (csPCa) among Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions.

Materials and Methods

A retrospective study of 103 patients with PI-RADS 3 lesions who underwent pre-operative 3.0-T MRI was performed. Patients were randomly divided into the training set and the testing set at a ratio of 7:3. Radiomic features were extracted from axial T2WI, diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) images of each patient. The minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) feature selection methods were used to identify the radiomic features and construct a radiomic model for csPCa identification. Moreover, multivariable logistic regression analysis was used to integrate the clinical factors with radiomic feature model to further improve the accuracy of csPCa identification, and the two are presented in the form of normogram. The performance of the integrated model was compared with radiomic model and clinical model on testing set.

Results

A total of four radiomic features were selected and used for radiomic model construction producing a radiomic score (Radscore). Radscore was significantly different between the csPCa and the non-csPCa patients (training set: p < 0.001; testing set: p = 0.035). Multivariable logistic regression analysis showed that age and PSA could be used as independent predictors for csPCa identification. The clinical–radiomic model produced the receiver operating characteristic (ROC) curve (AUC) in the testing set was 0.88 (95%CI, 0.75–1.00), which was similar to clinical model (AUC = 0.85; 95%CI, 0.52–0.90) (p = 0.048) and higher than the radiomic model (AUC = 0.71; 95%CI, 0.68–1.00) (p < 0.001). The decision curve analysis implies that the clinical–radiomic model could be beneficial in identifying csPCa among PI-RADS 3 lesions.

Conclusion

The clinical–radiomic model could effectively identify csPCa among biparametric PI-RADS 3 lesions and thus could help avoid unnecessary biopsy and improve the life quality of patients.

Targeting Bcl-2 for cancer therapy

Apoptosis deficiency is one of the most important features observed in neoplastic diseases. The Bcl-2 family is composed of a subset of proteins that act as decisive apoptosis regulators. Research and clinical studies have both demonstrated that the hyperactivation of Bcl-2-related anti-apoptotic effects correlates with cancer occurrence, progression and prognosis, also having a role in facilitating the radio- and chemoresistance of various malignancies. Therefore, targeting Bcl-2 inactivation has provided some compelling therapeutic advantages by enhancing apoptotic sensitivity or reversing drug resistance. Therefore, this pharmacological route turned into one of the most promising routes for cancer treatment. This review discusses some of the well-defined and emerging roles of Bcl-2 as well as its potential clinical value in cancer therapeutics.

Association between prostate cancer characteristics and BRCA1/2-associated family cancer history in a Japanese cohort

In addition to breast, ovarian, and pancreatic cancers, BRCA1/2 genes have been associated with prostate cancer (PC). However, the role of BRCA1/2-associated family cancer history (FCH) has remained unexplored in treating these four cancer types as a homogenous pathophysiological group. We aimed to clarify the relationship between BRCA1/2-associated FCH and PC, and to assess its relationship with cancer aggressiveness. Patient characteristics, positive family history of BRCA1/2-associated cancer, and cancer characteristics (Gleason score, prostate specific antigen level at diagnosis, and clinical tumor stage) were analyzed. Among the 1,985 eligible candidates, 473 (23.83%) patients had adequately detailed FCH, obtained via questionnaire, and were thus included in the study. BRCA1/2-associated FCH was observed in 135 (28.54%) patients with PC (68, 14.38%), breast (44, 9.30%), pancreatic (31, 6.55%), or ovarian (8, 1.69%) cancers. BRCA1/2-associated FCH was not significantly associated with high Gleason score (≥ 8). Patients with BRCA-associated FCH were less likely to present with high clinical tumor stage, and no difference was observed in prostate-specific antigen level, presence of metastatic lesions at diagnosis, or likelihood of high-risk classification between patients with and without BRCA-associated FCH. This is the first report of BRCA1/2-associated FCH in Japanese men, indicating that family history did not affect the severity or aggressiveness of PC.

A CD24-p53 axis contributes to African American prostate cancer disparities

BACKGROUND

Using a functional analysis of prostate cancer cells, we found a CD24-dependent inactivation of mutant p53, but the clinical significance of this observation remained uncertain. Here, we validated these results with samples of human prostate cancer and explored the role of a CD24-p53 axis in racial disparities of prostate cancer.

METHODS

Samples of formalin-fixed, paraffin-embedded prostate cancer from 141 European Americans (EAs) and 147 African Americans (AAs) in two independent sample cohorts were assessed for protein expression of CD24, mutant p53, mouse double minute 2 human homolog (MDM2), and cyclin dependent kinase inhibitor 2A (ARF) using immunohistochemical analyses. All samples were analyzed for TP53^R175H and TP53^R273H .

RESULTS

CD24, mutant p53, MDM2, and ARF proteins were expressed in 55%, 24%, 39%, and 68% of prostate cancer samples, respectively. CD24 and mutant p53 were present more frequently in late-stage and metastatic prostate cancer. The presence of CD24 was associated with a greater than fourfold risk of metastasis, which included lymph node and distant metastases. H score analysis showed positive correlations of CD24 expression with mutant p53 (r = .308, P < .001) and MDM2 (r = .227, P = .004). There was a negative correlation for CD24 with ARF (r = -.280, P < .001). A racial disparity was evident for CD24 (AAs/EAs: 64% vs 47%; P = .004) but not for mutant p53 (AA/EA: 28% vs 21%; P = .152). In 32 CD24⁺ /mutant p53⁺ cases, a TP53^R273H mutation was found in five cases, but no TP53^R175H mutation was found.

CONCLUSION

The CD24-p53 axis may contribute to aggressive and metastatic prostate cancers, especially those of AAs. This observation enhances understanding of the pathogenesis of prostate cancer and its associated racial disparities.

Clinical Utility of Ghrelin-O-Acyltransferase (GOAT) Enzyme as a Diagnostic Tool and Potential Therapeutic Target in Prostate Cancer

Recent data suggested that plasma Ghrelin O-Acyl Transferase enzyme (GOAT) levels could represent a new diagnostic biomarker for prostate cancer (PCa). In this study, we aimed to explore the diagnostic and prognostic/aggressiveness capacity of GOAT in urine, as well as to interrogate its putative pathophysiological role in PCa. We analysed urine/plasma levels of GOAT in a cohort of 993 patients. In vitro (i.e., cell-proliferation) and in vivo (tumor-growth in a xenograft-model) approaches were performed in response to the modulation of GOAT expression/activity in PCa cells. Our results demonstrate that plasma and urine GOAT levels were significantly elevated in PCa patients compared to controls. Remarkably, GOAT significantly outperformed PSA in the diagnosis of PCa and significant PCa in patients with PSA levels ranging from 3 to 10 ng/mL (the so-called PSA grey-zone). Additionally, urine GOAT levels were associated to clinical (e.g., Gleason-score, PSA levels) and molecular (e.g., CDK2/CDK6/CDKN2A expression) aggressiveness parameters. Indeed, GOAT overexpression increased, while its silencing/blockade decreased cell-proliferation in PCa cells. Moreover, xenograft tumors derived from GOAT-overexpressing PCa (DU145) cells were significantly higher than those derived from the mock-overexpressing cells. Altogether, our results demonstrate that GOAT could be used as a diagnostic and aggressiveness marker in urine and a therapeutic target in PCa.