The inverse relationship between prostate specific antigen (PSA) and obesity

PSA, an outdated biomarker for prostate cancer: In search of a more specific biomarker, citrate takes the spotlight

The prevailing biomarker employed for prostate cancer (PCa) screening and diagnosis is the prostate-specific antigen (PSA). Despite excellent sensitivity, PSA lacks specificity, leading to false positives, unnecessary biopsies and overdiagnosis. Consequently, PSA is increasingly less used by clinicians, thus underscoring the imperative for the identification of new biomarkers. An emerging biomarker in this context is citrate, a molecule secreted by the normal prostate, which has been shown to be inversely correlated with PCa. Here, we discuss about PSA and its usage for PCa diagnosis, its lack of specificity, and the various conditions that can affect its levels. We then provide our vision about what we think would be a valuable addition to our PCa diagnosis toolkit, citrate. We describe the unique citrate metabolic program in the prostate and how this profile is reprogrammed during carcinogenesis. Finally, we summarize the evidence that supports the usage of citrate as a biomarker for PCa diagnosis, as it can be measured in various patient samples and be analyzed by several methods. The unique relationship between citrate and PCa, combined with the stability of citrate levels in other prostate-related conditions and the simplicity of its detection, further accentuates its potential as a biomarker.

Overweight-years and cancer risk: A prospective study of the association and comparison of predictive performance with body mass index (Atherosclerosis Risk in Communities Study)

Excess body mass index (BMI) is associated with a higher risk of at least 13 cancers, but it is usually measured at a single time point. We tested whether the overweight-years metric, which incorporates exposure time to BMI ≥25 kg/m2 , is associated with cancer risk and compared this with a single BMI measure. We used adulthood BMI readings in the Atherosclerosis Risk in Communities (ARIC) study to derive the overweight-years metric. We calculated associations between the metric and BMI and the risk of cancers using Cox proportional hazards models. Models that either included the metric or BMI were compared using Harrell's C-statistic. We included 13,463 participants, with 3,876 first primary cancers over a mean of 19 years (SD 7) of cancer follow-up. Hazard ratios for obesity-related cancers per standard deviation overweight-years were 1.15 (95% CI: 1.05-1.25) in men and 1.14 (95% CI: 1.08-1.20) in women. The difference in the C-statistic between models that incorporated BMI, or the overweight-years metric was non-significant in men and women. Overweight-years was associated with the risk of obesity-related cancers but did not outperform a single BMI measure in association performance characteristics.

Decoding the Influence of Obesity on Prostate Cancer and Its Transgenerational Impact

In recent decades, the escalating prevalence of metabolic disorders, notably obesity and being overweight, has emerged as a pressing concern in public health. Projections for the future indicate a continual upward trajectory in obesity rates, primarily attributable to unhealthy dietary patterns and sedentary lifestyles. The ramifications of obesity extend beyond its visible manifestations, intricately weaving a web of hormonal dysregulation, chronic inflammation, and oxidative stress. This nexus of factors holds particular significance in the context of carcinogenesis, notably in the case of prostate cancer (PCa), which is a pervasive malignancy and a leading cause of mortality among men. A compelling hypothesis arises from the perspective of transgenerational inheritance, wherein genetic and epigenetic imprints associated with obesity may wield influence over the development of PCa. This review proposes a comprehensive exploration of the nuanced mechanisms through which obesity disrupts prostate homeostasis and serves as a catalyst for PCa initiation. Additionally, it delves into the intriguing interplay between the transgenerational transmission of both obesity-related traits and the predisposition to PCa. Drawing insights from a spectrum of sources, ranging from in vitro and animal model research to human studies, this review endeavors to discuss the intricate connections between obesity and PCa. However, the landscape remains partially obscured as the current state of knowledge unveils only fragments of the complex mechanisms linking these phenomena. As research advances, unraveling the associated factors and underlying mechanisms promises to unveil novel avenues for understanding and potentially mitigating the nexus between obesity and the development of PCa.

Do Obesity-Related Traits Affect Prostate Cancer Risk through Serum Testosterone? A Mendelian Randomization Study

OBJECTIVE

This study aimed to investigate whether testosterone mediates or confounds the effect of obesity-related traits on prostate cancer (PCa) using Mendelian randomization (MR) analysis.

MATERIALS AND METHODS

Data of obesity-related traits (body mass index [BMI], waist-to-hip ratio [WHR], and waist-to-hip ratio adjusted for body mass index [WHRadjBMI]) were obtained from up to 806,834 people of European ancestry; data of testosterone (bioavailable testosterone [BT], total testosterone [TT], and sex hormone-binding globulin [SHBG]) were extracted from up to 194,453 participants in the UK Biobank; and the summary-level data of PCa (79,194 cases and 61,112 controls) were obtained from the PRACTICAL consortium.

RESULT

The results supported the causal relationship between higher BMI and a reduced risk of PCa (OR = 0.91, 95% confidence interval [CI]: 0.86-0.96). Furthermore, increased BT levels were associated with an elevated risk of PCa (OR = 1.15, 95% CI: 1.06-1.24). Importantly, our analysis revealed a unidirectional causal effect-higher BMI was linked to lower BT levels (beta = -0.27, 95% CI: -0.3--0.24), but not the other way around. This suggests that BT may mediate the effect of BMI on PCa rather than confound it. Our multivariable MR results further demonstrated that considering BT as a mediator led to the weakening of BMI's effect on PCa risk (OR = 0.97, 95% CI: 0.90-1.05), while the impact of BT on PCa remained unchanged when accounting for BMI. Moreover, we identified a significant indirect effect of BMI on PCa risk (OR = 0.96, 95% CI: 0.94-0.98).

CONCLUSION

Our study provided genetic evidence that serum BT can mediate the effect of BMI on the risk of PCa, indicating the possible mechanism by which obesity reduces PCa risk.

Hot Spots and Trends in the Relationship between Cancer and Obesity: A Systematic Review and Knowledge Graph Analysis

Cancer is one of the most difficult medical problems in today's world. There are many factors that induce cancer in humans, and obesity has become an important factor in inducing cancer. This study systematically and quantitatively describes the development trend, current situation and research hotspot of the relationship between cancer and obesity by using document statistics and knowledge graph visualization technology. Through the visualization technology analysis of knowledge graph in this study, the research hotspot and knowledge base source of the relationship between cancer and obesity in the last 20 years have been ascertained. Obesity-related factors, such as immunity, insulin, adiponectin, adipocytokines, nonalcoholic fatty liver and inflammatory reaction, may affect the occurrence of obesity and increase the risk of cancer. Obesity-related cancers include respiratory cancer, colorectal cancer, hepatocellular cancer, prostate cancer, gastric cancer, etc. Our research provides direction and basis for future research in this field, as well as technical and knowledge basis support for experts and researchers in related medical fields.

Development and validation of a multi-parameter nomogram for predicting prostate cancer: a retrospective analysis from Handan Central Hospital in China

Background

To explore the possible predicting factors related to prostate cancer and develop a validated nomogram for predicting the probability of patients with prostate cancer.

Method

Clinical data of 697 patients who underwent prostate biopsy in Handan Central Hospital from January 2014 to January 2020 were retrospectively collected. Cases were randomized into two groups: 80% (548 cases) as the development group, and 20% (149 cases) as the validation group. Univariate and multivariate logistic regression analyses were performed to determine the independent risk factors for prostate cancer. The nomogram prediction model was generated using the finalized independent risk factors. Decision curve analysis (DCA) and the area under receiver operating characteristics curve (ROC) of both development group and validation group were calculated and compared to validate the accuracy and efficiency of the nomogram prediction model. Clinical utility curve (CUC) helped to decide the desired cut-off value for the prediction model. The established nomogram with Prostate Cancer Prevention Trial Derived Cancer Risk Calculator (PCPT-CRC) and other domestic prediction models using the entire study population were compared.

Results

The independent risk factors determined through univariate and multivariate logistic regression analyses were: age, tPSA, fPSA, PV, DRE, TRUS and BMI. Nomogram prediction model was developed with the cut-off value of 0.31. The AUC of development group and validation group were 0.856 and 0.797 respectively. DCA exhibits consistent observations with the findings. Through validating our prediction model as well as other three domestic prediction models based on the entire study population of 697 cases, our prediction model demonstrated significantly higher predictive value than all the other models.

Conclusion

The nomogram for predicting prostate cancer can facilitate more accurate evaluation of the probability of having prostate cancer, and provide better ground for prostate biopsy.

Association between serum prostate-specific antigen concentrations and the risk of developing type 2 diabetes mellitus in Chinese men: A cohort study

AIMS/INTRODUCTION

The current literature suggests that men with diabetes have a lower prostate-specific antigen concentration than men without diabetes, but the causal association remains unclear. We aimed to investigate the association between serum prostate-specific antigen concentrations and the risk of type 2 diabetes mellitus in a cohort study of a Chinese population.

MATERIALS AND METHODS

We designed a cohort study that comprised 16,811 initially non-diabetic Chinese men who received annual health checkups between 2009 and 2016. The outcome of this study was type 2 diabetes mellitus, identified by medical diagnosis, self-reportage, medication use, fasting glucose, 2-h post oral glucose or glycated hemoglobin measurements. Cox proportional hazards models were carried out to evaluate the association.

RESULTS

During a median follow-up period of 3.8 years (interquartile range 1.91-5.73 years), 1,260 participants developed incident type 2 diabetes mellitus. The multivariable model, adjusted for various potential confounders, showed that serum prostate-specific antigen concentrations were inversely related to type 2 diabetes mellitus risk (P for trend = 0.014). Compared with the lowest quartile of serum prostate-specific antigen, the hazard ratio and 95% confidence intervals of type 2 diabetes mellitus risk for quartile 2-4 were 0.84 (0.66-1.07), 0.75 (0.59-0.94) and 0.77 (0.62-0.96), respectively. Subgroup analyses suggested the inverse relationship was more prominent in overweight or obese participants (P for interaction = 0.013).

CONCLUSIONS

High serum prostate-specific antigen concentration was associated with a low risk of type 2 diabetes mellitus in Chinese men. Future studies are required to confirm these findings and investigate underlying mechanisms.

PSA and obesity among men with localized prostate cancer: results of the ANDROCAN study

PURPOSE

PSA is known to be lowered in obese patients. There is a lack of data regarding patients with prostate cancer. Our objective was to prospectively assess the relationship PSA concentration, PSA mass and BMI in a cohort of patients with localized prostate cancer.

METHODS

A prospective, multicenter cohort study was conducted including patients undergoing radical prostatectomy. Clinical and biological data were collected for each patient before surgery.

RESULTS

A total of 1343 patients were analyzed. Mean age was 64.0 years. Mean weight was 82.2 kg and mean BMI was 26.8 kg/m². Mean PSA concentration was 8.7 ng/mL and mean PSA mass 29.3 ng. On univariate analysis, an association was found between PSA mass and either BMI, weight and waist circumference. No association was found between PSA concentration and each weight parameters. On multivariate analysis, obesity was not an independent predictor of PSA concentration (p = 0.73). Independent predictors of PSA concentration were cardiovascular disease (negative association, p = 0.034), predominant Gleason 4 (positive association, p < 0.001) and pT3a (positive association, p < 0.001). BMI was an independent predictor of PSA mass (positive association, p = 0.009). PSA mass was negatively associated with TT (p = 0.015) and cardiovascular disease (p = 0.003), and positively associated with BT (p = 0.032), Gleason grade ≥ 4 + 3 (p < 0.001) and pT3a (p < 0.001).

CONCLUSION

In this prospective study of patients with localized prostate cancer, higher BMI was associated with higher PSA mass but not with higher PSA concentration. Screening obese patients with a specific PSA method does not appear to be critical.

The prevalence and risk factors of prostatic calculi in Han Chinese: a cross-sectional study based on health examinations

PURPOSE

Prostatic calculi (PCal) are commonly present with prostate disease; we aim to map the incidence and associated clinical risk factors of PCal in Han Chinese.

MATERIAL AND METHODS

We retrospectively selected men who sought a medical check-up in 2018. Basic clinical items, including age, weight, height, prostate specific antigen (PSA), uric acid (UA), fasting blood glucose (FBG), urinalysis results, and transabdominal prostate ultrasound, were recorded. Univariate and logistic regression analyses were performed to evaluate whether these factors were associated with the presence of PCal.

RESULT

We recorded the parameters of laboratory tests and clinical information from 14,427 men; men with PCal comprised 51.65% of the total group and 76.61% of the subgroup of benign prostate hyperplasia (BPH) patients. All the enrolled parameters showed meaningful differences, but the logistic regression analysis only indicated significant effects related to age (OR = 1.044, 95% CI = 1.040-1.047, and p < .001), body mass index (BMI) (OR = 1.035, 95% CI = 1.022-1.048, and p < .001), UA (OR = 0.999, 95% CI = 0.999-1.000, and p = .029), BPH (OR = 2.923, 95% CI = 2.678-3.191, and p < .001), and prostate cysts (OR = 0.609, 95% CI = 0.471-0.788, and p < .001). The odds ratio of the predicted combined model is 1.068.

CONCLUSIONS

PCal was detected in 51.65% of men among healthy Han Chinese and in 76.61% of BPH patients. Age, BMI, UA, BPH, and prostate cysts were independent risk factors for the presence of PCal.

Relationship between body mass index and concentrations of prostate specific antigen: a cross-sectional study

The possible relationship between body mass index (BMI) and prostate-specific antigen (PSA) concentrations is controversial. The objective of this study was to assess the relationship between BMI and PSA concentrations in Chinese men. A total of 81,122 men who had undergone annual medical examinations at the First Affiliated Hospital of Army Medical University between 1 January 2011 and 31 December 2018 were included. Univariate and multivariate linear regression models were used to assess the relationship between BMI and PSA concentrations. The nonlinear relationship was analyzed using a generalized additive model with a spline smoothing function. Subsequently, a stratified linear regression model was used for subgroup analysis. The mean age and BMI of the participants were 45.91 ± 12.21 years and 24.79 ± 3.11 kg/m², respectively. After adjustment for age, waist circumference-hip circumference ratio, systolic blood pressure, diastolic blood pressure, fasting blood glucose, total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, alanine aminotransferase and aspartate aminotransferase, BMI was negatively related to PSA level (p < .001). A nonlinear relationship was detected, and different relationships between BMI and PSA concentrations were observed on each side of the inflection point (BMI = 23.11 kg/m²). Our study revealed an inverse, nonlinear relationship between BMI and PSA concentrations. Thus, this relationship may be a concern when establishing reference intervals or decision limits for PSA concentrations.

Clinical and metabolic implications of obesity in prostate cancer: is testosterone a missing link?

Objectives: To assess sex hormones in men with obesity and prostate cancer (PCa) and to study association between androgens and the pathogenesis biology of PCa in vitro. Subjects and methods: One hundred and eighty-one men older than 45 years selected from of a population attending to Urology departments screening for PCa, (78 participants without PCa and 103 patients with PCa). All participants were assessed for body mass index (BMI), age, Gleason score, and PSA. Endocrine profile was determined for LH, total testosterone (TT), 17β-estradiol (E2), prolactin and leptin. Biochemical profile (HbA1c, triacylglycerols and lipoproteins) was also determined. In vitro experiments were also performed, involving the study of 5α-dihydrotestosterone (DHT) and E2 in the presence of adipocyte-conditioned medium (aCM). Results: All variables were continuous and described a Gaussian distribution unless mentioned. To determine the relation of aggressiveness, variable were transformed into categories. Thus, PCa aggressiveness is associated with the increase of age and BMI (p < .0001) but with is decreased with TT and E2 (p < .05). Moreover, adipocyte-secreted molecules increase aggressiveness of PCa cells in vitro. Lastly, DTH but not E2 enables invasiveness in vitro. Conclusions: It was observed a coexistence of hormone axis profile alteration with sex hormones and BMI in PCa patients, in accordance with the new perspective of PCa pathogenesis.

Obesity at Diagnosis and Prostate Cancer Prognosis and Recurrence Risk Following Primary Treatment by Radical Prostatectomy

BACKGROUND

The association of obesity at diagnosis with prostate cancer progression is uncertain. This study aimed to examine the relationship between body mass index (BMI; 18.5-<25, 25-<30, 30-<35, ≥35 kg/m²) and prognostic risk at diagnosis, compare the concordance between prognostic risk assessed at diagnostic biopsy versus pathologic risk assessed at surgery across BMI categories, and investigate the association between obesity and prostate cancer recurrence and all-cause death.

METHODS

We examined men enrolled in CaPSURE who underwent radical prostatectomy between 1995 and 2017. Multiple imputation methods were used to handle missing data and reported along with complete case findings.

RESULTS

Participants (n = 5,200) were followed for a median of 4.5 years; 685 experienced recurrence. Obesity was associated with higher prognostic risk at time of diagnosis (OR_obese = 1.5; OR_{very obese} = 1.7) and upward reclassification of disease between biopsy and surgery, driven by change in tumor stage (OR_obese = 1.3; OR_{very obese} = 1.6). We observed an association between BMI and recurrence with adjustment for disease severity using diagnostic factors (HR_{very obese} = 1.7); this association disappeared when adjusting for disease severity factors obtained at surgery.

CONCLUSIONS

Our findings suggest that residual confounding may partially explain the conflicting evidence regarding obesity's influence on prostate cancer progression. Assessing T-stage via digital rectal exam may be complicated in larger men, potentially affecting clinical treatment decisions. A strong association with all-cause mortality demonstrates healthier BMI at diagnosis may still improve overall survival.

IMPACT

Patients with greater BMI are prone to more advanced disease at diagnosis and may be more likely to have their tumor stage underestimated at diagnosis.

Association between serum prostate-specific antigen level and diabetes, obesity, hypertension, and the laboratory parameters related to glucose tolerance, hepatic function, and lipid profile: implications for modification of prostate-specific antigen threshold

BACKGROUND

Previous studies indicated inverse relationships between body mass index (BMI), diabetes and prostate-specific antigen (PSA) concentration besides an established positive relationship between age and PSA. Other causal relationships between clinical parameters including hypertension, hepatic function, tests, lipid profile and PSA were also suggested. Thus, we incorporated these parameters all together into the analysis to identify possible determinants of PSA concentration to improve the accuracy of PSA tests.

METHODS

Associations between PSA and the above-mentioned clinical parameters were examined among 14,486 men who visited our hospital for a routine health checkup, using linear regression analyses.

RESULTS

Total of 1403 (9.7%) and 784 (5.4%) men were classified as diabetes and obesity, respectively. After adjusting age, significant PSA reductions were found in diabetic men, especially for men taking antidiabetics. Such association was seen when the diabetic status was represented by hemoglobin A1c (HbA1c) and fasting blood sugar (FBS) levels. That is, PSA levels were significantly reduced in men with higher HbA1c and FBS levels. Obesity was also associated with a reduction in PSA levels. Moreover, PSA levels were significantly decreased with increased ALT levels.

CONCLUSIONS

PSA test results should be carefully interpreted especially for men with diabetes and obesity, in whom a substantial reduction in PSA concentration is likely to occur.

An Ultra-Rapid Biosensory Point-of-Care (POC) Assay for Prostate-Specific Antigen (PSA) Detection in Human Serum

Prostate-specific antigen (PSA) is the established routine screening tool for the detection of early-stage prostate cancer. Given the laboratory-centric nature of the process, the development of a portable, ultra rapid high-throughput system for PSA screening is highly desirable. In this study, an advancedpoint-of-care system for PSA detection in human serum was developed based on a cellular biosensor where the cell membrane was modified by electroinserting a specific antibody against PSA. Thirty nine human serum samples were used for validation of this biosensory system for PSA detection. Samples were analyzed in parallel with a standard immunoradiometric assay (IRMA) and an established electrochemical immunoassay was used for comparison purposes. They were classified in three different PSA concentration ranges (0, <4 and ≥4 ng/mL). Cells membrane-engineered with 0.25 μg/mL anti-PSA antibody demonstrated a statistically lower response against the upper (≥4 ng/mL) PSA concentration range. In addition, the cell-based biosensor performed better than the immunosensor in terms of sensitivity and resolution against positive samples containing <4 ng/mL PSA. In spite of its preliminary, proof-of-concept stage of development, the cell-based biosensor could be used as aninitiative for the development of a fast, low-cost, and high-throughput POC screening system for PSA.

Metabolic deregulation in prostate cancer

Using RNAseq data from prostate cancer tissues we identified up to six metabolic subtypes of prostate cancer that show distinct disease-free and/or metastasis-free survival.