Modifiable risk factors for prostate cancer in low- and lower-middle-income countries: a systematic review and meta-analysis

Effect of smoking on prostate cancer: Results from the National Health and Nutrition Examination Survey 2003-2018 and Mendelian randomization analyses

INTRODUCTION

The controversial relationship between smoking and prostate cancer (PCa) risk prompted us to conduct a cross-sectional study using the National Health and Nutrition Examination Survey (NHANES) database and apply Mendelian randomization (MR) analyses in order to clarify the possible causal effect of smoking on PCa risk.

METHODS

Using univariate and multivariate logistic regression methods, a secondary analysis of the pooled 2003-2018 NHANES dataset was performed to explore the association between smoking and PCa risk. Propensity-score matching was used to reduce selection bias. Then, we conducted subsequent MR analysis study to investigate the potential causal effect of smoking on PCa risk, with genetic variants of four exposure factors including the lifetime smoking index, light smoking, smoking initiation, and the amount of smoking per day obtained from genome-wide association studies, and PCa summary statistics obtained from three database populations. Inverse-variance weighting was the primary analytical method, and weighted median and MR-Egger regression were used for sensitivity analyses. The MR results for the three PCa databases were combined using meta-analysis.

RESULTS

The study included 16073 NHANES subjects, comprising 554 with PCa and 15519 without PCa. Logistic regression before and after matching did not reveal any significant association. Meta-analysis of the MR results also did not support an association of PCa risk with lifetime smoking index (OR=0.95; 95% CI: 0.83-1.09), light smoking (OR=1.00; 95% CI: 0.95-1.06), smoking initiation (OR=0.99, 95% CI=0.99-1.00), or the amount of smoking per day (OR=1.00; 95% CI: 0.99-1.00) and PCa risk.

CONCLUSIONS

There was no evidence for an association between smoking and the risk of PCa. Further studies are needed to determine if there are any associations of other forms of smoking with the risk of PCa at different stages.

Exposure to environmental pollutants and genetic variants related to oxidative stress and xenobiotic metabolism-Association with prostate cancer

This study assessed whether genetic variants coding for certain enzymes involved in xenobiotic detoxification, antioxidant defences and DNA repair, along with exposure to environmental chemicals, were associated with an increased prostate cancer (PCa) risk. The study population consisted of 300 men (150 PCa cases and 150 controls) which underwent prostate biopsy as their serum prostate specific antigen (PSA) levels were greater than 4 ng/ml. Genetic variants in GSTM1, GSTP1, SOD2, CAT, GPX1, XRCC1 were determined and data for chemical exposures was obtained through a structured questionnaire and by biomonitoring in a subsample of cases and controls. High serum PSA levels were associated with a greater risk of PCa, while physical exercise appears to exert a protective effect against its development. In addition, elevated urinary levels of certain organic pollutants, such as benzo(a)pyrene (BaP), bisphenol A (BPA), and ethyl-paraben (EPB), were associated with an increased risk of PCa.

Transcending frontiers in prostate cancer: the role of oncometabolites on epigenetic regulation, CSCs, and tumor microenvironment to identify new therapeutic strategies

Prostate cancer, as one of the most prevalent malignancies in males, exhibits an approximate 5-year survival rate of 95% in advanced stages. A myriad of molecular events and mutations, including the accumulation of oncometabolites, underpin the genesis and progression of this cancer type. Despite growing research demonstrating the pivotal role of oncometabolites in supporting various cancers, including prostate cancer, the root causes of their accumulation, especially in the absence of enzymatic mutations, remain elusive. Consequently, identifying a tangible therapeutic target poses a formidable challenge. In this review, we aim to delve deeper into the implications of oncometabolite accumulation in prostate cancer. We center our focus on the consequential epigenetic alterations and impacts on cancer stem cells, with the ultimate goal of outlining novel therapeutic strategies.

Intake of the Total, Classes, and Subclasses of (Poly)Phenols and Risk of Prostate Cancer: A Prospective Analysis of the EPIC Study

Existing epidemiological evidence regarding the potential role of (poly)phenol intake in prostate cancer (PCa) risk is scarce and, in the case of flavonoids, it has been suggested that their intake may increase PCa risk. We investigated the associations between the intake of the total and individual classes and subclasses of (poly)phenols and the risk of PCa, including clinically relevant subtypes. The European Prospective Investigation into Cancer and Nutrition (EPIC) cohort included 131,425 adult men from seven European countries. (Poly)phenol intake at baseline was assessed by combining validated center/country-specific dietary questionnaires and the Phenol-Explorer database. Multivariable-adjusted Cox proportional hazards models were used to estimate the hazard ratios (HR) and 95% confidence intervals (CI). In total, 6939 incident PCa cases (including 3501 low-grade and 710 high-grade, 2446 localized and 1268 advanced, and 914 fatal Pca cases) were identified during a mean follow-up of 14 years. No associations were observed between the total intake of (poly)phenols and the risk of PCa, either overall (HRlog2 = 0.99, 95% CI 0.94-1.04) or according to PCa subtype. Null associations were also found between all classes (phenolic acids, flavonoids, lignans, and stilbenes) and subclasses of (poly)phenol intake and the risk of PCa, overall and according to PCa subtype. The results of the current large prospective cohort study do not support any association between (poly)phenol intake and PCa incidence.

2022 Update on Prostate Cancer Epidemiology and Risk Factors-A Systematic Review

CONTEXT

Prostate cancer (PCa) is one of the most common cancers worldwide. Understanding the epidemiology and risk factors of the disease is paramount to improve primary and secondary prevention strategies.

OBJECTIVE

To systematically review and summarize the current evidence on the descriptive epidemiology, large screening studies, diagnostic techniques, and risk factors of PCa.

EVIDENCE ACQUISITION

PCa incidence and mortality rates for 2020 were obtained from the GLOBOCAN database of the International Agency for Research on Cancer. A systematic search was performed in July 2022 using PubMed/MEDLINE and EMBASE biomedical databases. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines and was registered in PROSPERO (CRD42022359728).

EVIDENCE SYNTHESIS

Globally, PCa is the second most common cancer, with the highest incidence in North and South America, Europe, Australia, and the Caribbean. Risk factors include age, family history, and genetic predisposition. Additional factors may include smoking, diet, physical activity, specific medications, and occupational factors. As PCa screening has become more accepted, newer approaches such as magnetic resonance imaging (MRI) and biomarkers have been implemented to identify patients who are likely to harbor significant tumors. Limitations of this review include the evidence being derived from meta-analyses of mostly retrospective studies.

CONCLUSIONS

PCa remains the second most common cancer among men worldwide. PCa screening is gaining acceptance and will likely reduce PCa mortality at the cost of overdiagnosis and overtreatment. Increasing use of MRI and biomarkers for the detection of PCa may mitigate some of the negative consequences of screening.

PATIENT SUMMARY

Prostate cancer (PCa) remains the second most common cancer among men, and screening for PCa is likely to increase in the future. Improved diagnostic techniques can help reduce the number of men who need to be diagnosed and treated to save one life. Avoidable risk factors for PCa may include factors such as smoking, diet, physical activity, specific medications, and certain occupations.

Causal Effects of Modifiable Behaviors on Prostate Cancer in Europeans and East Asians: A Comprehensive Mendelian Randomization Study

OBJECTIVE

Early evidence is disputable for the effects of modifiable lifestyle behaviors on prostate cancer (PCa) risk. No research has yet appraised such causality in different ancestries using a Mendelian randomization (MR) approach.

METHODS

A two-sample univariable and multivariable MR analysis was performed. Genetic instruments associated with lifestyle behaviors were selected based on genome-wide association studies. Summary-level data for PCa were obtained from PRACTICAL and GAME-ON/ELLIPSE consortia for Europeans (79,148 PCa cases and 61,106 controls), and ChinaPCa consortium for East Asians (3343 cases and 3315 controls). Replication was performed using FinnGen (6311 cases and 88,902 controls) and BioBank Japan data (5408 cases and 103,939 controls).

RESULTS

Tobacco smoking was identified as increasing PCa risks in Europeans (odds ratio [OR]: 1.95, 95% confidence interval [CI]: 1.09-3.50, p = 0.027 per standard deviation increase in the lifetime smoking index). For East Asians, alcohol drinking (OR: 1.05, 95%CI: 1.01-1.09, p = 0.011) and delayed sexual initiation (OR: 1.04, 95%CI: 1.00-1.08, p = 0.029) were identified as risk factors, while cooked vegetable consumption (OR: 0.92, 95%CI: 0.88-0.96, p = 0.001) was a protective factor for PCa.

CONCLUSIONS

Our findings broaden the evidence base for the spectrum of PCa risk factors in different ethnicities, and provide insights into behavioral interventions for prostate cancer.

Let’s Go 3D! New Generation of Models for Evaluating Drug Response and Resistance in Prostate Cancer

Prostate cancer (PC) is the third most frequently diagnosed cancer worldwide and the second most frequent in men. Several risk factors can contribute to the development of PC, and those include age, family history, and specific genetic mutations. So far, drug testing in PC, as well as in cancer research in general, has been performed on 2D cell cultures. This is mainly because of the vast benefits these models provide, including simplicity and cost effectiveness. However, it is now known that these models are exposed to much higher stiffness; lose physiological extracellular matrix on artificial plastic surfaces; and show changes in differentiation, polarization, and cell–cell communication. This leads to the loss of crucial cellular signaling pathways and changes in cell responses to stimuli when compared to in vivo conditions. Here, we emphasize the importance of a diverse collection of 3D PC models and their benefits over 2D models in drug discovery and screening from the studies done so far, outlining their benefits and limitations. We highlight the differences between the diverse types of 3D models, with the focus on tumor–stroma interactions, cell populations, and extracellular matrix composition, and we summarize various standard and novel therapies tested on 3D models of PC for the purpose of raising awareness of the possibilities for a personalized approach in PC therapy.