Examination of potential novel biochemical factors in relation to prostate cancer incidence and mortality in UK Biobank

Long-term exposure to ambient air pollutants and risk of prostate cancer: A prospective cohort study

BACKGROUND

Air pollution has been hypothesized as a potential risk factor for prostate cancer, while previous studies on the topic mainly focused on single pollutant and the results were inconsistent. This study aimed to investigate the association between long-term exposure to multiple air pollutants and the risk of prostate cancer and their joint effect.

METHODS

This study included 210,722 men free of prostate cancer at baseline from the UK Biobank. Data on ambient air pollutants, including particulate matter with diameters ≤2.5 μm (PM2.5), ≤10 μm (PM10), nitrogen oxides (NO2 and NOx), sulfur dioxide (SO2), benzene, and ozone (O3) were collected from the UKs Department for Environment, Food and Rural Affair during 2003-2021.

RESULTS

During a median follow-up of 10.9 years, a total of 10,841 incident prostate cancer occurred. The hazard ratios (95% confidence intervals) of prostate cancer for each interquartile range increase in PM2.5, PM10, NO2, NOx, SO2, benzene and O3 were 1.120 (1.084-1.158), 1.121 (1.089-1.155), 1.040 (1.009-1.071), 1.040 (1.012-1.069), 0.983 (0.958-1.009), 1.080 (1.050-1.111), and 1.080 (1.050-1.111), respectively. The joint effect of PM2.5, PM10, NO2, NOx, SO2, and benzene was 1.039 (1.012-1.067). with the greatest contribution from NOx, PM10, benzene, and PM2.5. The impact of PM2.5, PM10, NO2, NOx and benzene on prostate cancer risk was weakened by a higher percentage of greenness at the home location buffer.

CONCLUSIONS

Long-term exposure to air pollutants may be positively associated with an elevated risk of prostate cancer, particularly for NOx, PM10, benzene, and PM2.5. This study highlights the potential role of comprehensively assessing and controlling various air pollutants in prevention of prostate cancer.

NCAPD3-mediated AKT activation regulates prostate cancer progression

Despite therapeutic improvements in prostate cancer treatment, the recurrence and mortality rates are still high, and the underlying mechanisms still need further study. Non-SMC Condensin II Complex Subunit D3 (NCAPD3) is a subunit of condensin II complex, mainly involved in the mitotic chromosome condensation of cells. This study aimed to figure out the detailed mechanisms by which NCAPD3 contributed to prostate cancer development. Clinical samples and cell lines were used to measure the expression of genes by quantitative real-time RT-PCR (qRT-PCR), Western-blot assay (WB), immunohistochemistry (IHC), and immunofluorescence (IF). Chromatin immunoprecipitation quantitative PCR (ChIP-qPCR) and dual-luciferase reporter assays were examined to explore the interplays between molecules. CCK8, transwell, and wound-healing assays were applied to perform cell proliferation and migration. A subcutaneous tumor xenograft model was constructed by injecting DU145-Lv-NCAPD3 cells and control cells into male BALB/c nude mice to confirm the result derived from in vitro assay. NCAPD3 increased STAT3 expression and phosphorylation in PCa cells, thereby enhancing STAT3 transcriptional activity to improve the levels of JAK2 and EZH2. This led to an increase in phosphorylation of AKT at Thr 308 and Ser 473 through JAK2/PI3K and EZH2/NSD2/mTORC2 pathways, respectively. Moreover, there was a positive mutual activation between STAT3 and JAK2, further enhanced by NCAPD3 to promote PCa progression. NCAPD3, as an oncogene, promoted PCa progression by phosphorylating and activating AKT, which suggests a novel functional pathway of NCAPD3 in promoting PCa progression.

Understanding the role of metabolic syndrome in prostate cancer risk: A UK Biobank prospective cohort study

Predictive value of metabolic syndrome for prostate cancer risk is not clear. We aimed to assess the association between metabolic syndrome and its components with prostate cancer incidence. The primary outcome was prostate cancer incidence, i.e., incidence rate ratios and adjusted cumulative incidence curves derived from flexible parametric survival models. Adjusted cumulative incidence curves were derived using a flexible survival parametrical modeling framework. We analysed UK Biobank data including 242,349 adult males, recruited during 2006-2010 and followed up until 2021, during which 6,467 (2.7%) participants were diagnosed with prostate cancer. Our findings indicate that metabolic syndrome, as a whole, was not associated with prostate cancer risk (incidence rate ratios, 1.07; 95% confidence interval, 0.94-1.22). However, specific components such as hypertension and obesity increased the risk (incidence rate ratios, 1.22; 95% confidence interval, 1.03-1.44 and incidence rate ratios, 1.24; 95% confidence interval, 1.05-1.46, respectively). Other components, such as prediabetes/diabetes and low cholesterol, were associated with a reduced risk (incidence rate ratios, 0.80; 95% confidence interval, 0.67-0.94 and incidence rate ratios, 0.82; 95% confidence interval, 0.69-0.97, respectively), while hyperlipidaemia showed no significant effect (incidence rate ratios, 1.07; 95% confidence interval, 0.93-1.24). Further research is needed to understand the underlying mechanisms behind these relationships. Prostate cancer prevention strategies might benefit from targeting modifiable risk factors, particularly hypertension and obesity.

Severe obesity, high inflammation, insulin resistance with risks of all-cause mortality and all-site cancers, and potential modification by healthy lifestyles

Severe obesity is often associated with inflammation and insulin resistance (IR), which expected to increase the risks of mortality and cancers. However, this relationship remains controversial, and it's unclear whether healthy lifestyles can mitigate these risks. The independent and joint associations of severe obesity (body mass index ≥ 35 m/kg2), inflammation (C-reactive protein > 10 mg/L and systemic inflammation markers > 9th decile), and IR surrogates with the risks of all-cause mortality and all-site cancers, were evaluated in 163,008 participants from the UK Biobank cohort. Further analyses were conducted to investigate how these associations were modified by lifestyle. During a median follow-up of 11.0 years, we identified 8844 deaths and 20,944 cancer cases. Severe obesity, inflammation and IR were each independently associated with increased risks of all-cause mortality [HRs(95%CIs) 1.24(1.17-1.30), 1.63(1.55-1.72) and 1.11(1.05-1.17)] and all-site cancers [1.06(1.02-1.10), 1.14(1.10-1.19) and 1.02(0.99-1.06)]. Joint analyses revealed significantly elevated risks of all-cause mortality and all-site cancers due to interaction between severe obesity, inflammation and IR, with the highest HRs(95%CIs) of 1.88(1.67-2.11) and 1.20(1.08-1.34), respectively. Further analyses showed stronger interaction between severe obesity, inflammation, IR and lifestyles, with similar associations observed in both males and females. Additionally, compared with unfavorable lifestyles, favorable lifestyles attenuated the risks of both all-cause mortality [the highest HRs(95%CIs) 2.35(1.75-3.15) vs. 3.72(2.86-4.84) for favorable vs. unfavorable lifestyles] and all-site cancers [1.16(0.89-1.53) vs. 1.63(1.26-2.10)]. Severe obesity interacts with inflammation and IR to exacerbate the risks of all-cause mortality and all-site cancers. Nonetheless, adherence to healthy lifestyles is recommended to mitigate these increased risks.

Investigating causal relationships of blood and urine biomarkers with urological cancer risks: a mendelian randomization study and colocalization analyses

Background: Establishing the causal links between biomarkers and cancer enhances understanding of risk factors and facilitates the discovery of therapeutic targets. To this end, we used Mendelian randomization (MR) and colocalization analysis to explore the causal relationship of blood and urinary biomarkers (BUBs) with urological cancers (UCs). Methods: First, we used a two-sample MR study to explore the causal relationship between 33 BUBs and 4 UCs, while we performed reverse Mendelian randomization. After Bonferroni correction, for BUB and UC with significant causality we confirmed the direct causality by multivariate MR adjusting for relevant risk factors. We also applied two-step MR analysis to further explore the possible mediators between BUB and UC with significant causality, while colocalization analysis was performed for BUB, UC and possible mediators. Sensitivity analysis were performed to assess the robustness of the results. Results: A two-sample MR study found that there were 8 BUBs of CA, IGF-1, LPA, TP, CRE, BILD, TBIL and NAP with potential causality with some UCs (p<0.05), but after Bonferroni correction only IGF-1 had a significant causality with PCa (OR = 1.14, 95% CI: 1.06-1.23; p=0.0006<0.05/33). Moreover, the causal relationship between IGF-1 and PCa remained significant (P<0.05) after adjusting for relevant risk factors in the multivariate MR study. The two-step MR study found SHBG to be a mediator between IGF-1 and PCa, and the colocalization analysis found that there was a common causal variant (nearby gene TNS3) between IGF-1 and SHBG (PPH4=93.21%), which further confirmed the mediating effect of SHBG. Conclusion: Strong evidence from our study suggests that IGF-1 increases the risk of PCa by decreasing SHBG levels, and in addition some BUBs were found to have a potential causal relationship with UCs.

Validation of candidate protein biomarkers previously identified by genetic instruments for prostate cancer risk: A prospective cohort analysis of directly measured protein levels in the ARIC study

BACKGROUND

Multiple novel protein biomarkers have been shown to be associated with prostate cancer risk using genetic instruments. This study aimed to externally validate the associations of 30 genetically predicted candidate proteins with prostate cancer risk using aptamer-based levels in US Black and White men in the Atherosclerosis Risk in Communities (ARIC) study. Plasma protein levels were previously measured by SomaScan® using the blood collected in 1990-1992.

METHODS

Among 4864 eligible participants, we ascertained 667 first primary prostate cancer cases through 2015. Hazard ratios (HRs) of prostate cancer and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression for tertiles of each protein. We adjusted for age, race, and other risk factors.

RESULTS

Of the 30 proteins and considering a nominal p trend < 0.05, two were positively associated with prostate cancer risk-RF1ML (tertile 3 vs. 1: HR = 1.23; 95% CI 1.02-1.48; p trend = 0.037) and TPST1 (1.28, 95% CI 1.06-1.55; p trend = 0.0087); two were inversely associated-ATF6A (HR = 0.80, 95% CI 0.65-0.98; p trend = 0.028) and SPINT2 (HR = 0.74, 95% CI 0.61-0.90; p trend = 0.0025). One protein, KDEL2, which was nonlinearly associated (test-for-linearity: p < 0.01) showed a statistically significant lower risk in the second tertile (HR = 0.79, 95% CI 0.65-0.95). Of these five, four proteins-ATF6A, KDEL2, RF1ML, and TPST1-were consistent in the direction of association with the discovery studies.

CONCLUSION

This study validated some pre-diagnostic protein biomarkers of the risk of prostate cancer.

Stacked neural network for predicting polygenic risk score

In recent years, the utility of polygenic risk scores (PRS) in forecasting disease susceptibility from genome-wide association studies (GWAS) results has been widely recognised. Yet, these models face limitations due to overfitting and the potential overestimation of effect sizes in correlated variants. To surmount these obstacles, we devised the Stacked Neural Network Polygenic Risk Score (SNPRS). This novel approach synthesises outputs from multiple neural network models, each calibrated using genetic variants chosen based on diverse p-value thresholds. By doing so, SNPRS captures a broader array of genetic variants, enabling a more nuanced interpretation of the combined effects of these variants. We assessed the efficacy of SNPRS using the UK Biobank data, focusing on the genetic risks associated with breast and prostate cancers, as well as quantitative traits like height and BMI. We also extended our analysis to the Korea Genome and Epidemiology Study (KoGES) dataset. Impressively, our results indicate that SNPRS surpasses traditional PRS models and an isolated deep neural network in terms of accuracy, highlighting its promise in refining the efficacy and relevance of PRS in genetic studies.

Joint association of biological aging and lifestyle with risks of cancer incidence and mortality: A cohort study in the UK Biobank

BACKGROUND

Aging is a risk factor for cancer incidence and mortality. Biological aging can reflect the aging degree of the body better than chronological age and can be aggravated by unhealthy lifestyle factors. We aimed to assess the joint effect of biological aging and lifestyle with risks of cancer incidence and mortality.

METHODS

This study included a total of 281,889 participants aged 37 to 73 from the UK Biobank database. Biological age was derived from chronological age and 9 clinical blood indicators, and lifestyle score was constructed by body mass index, smoking status, alcohol consumption, physical activity, and diet. Multivariate Cox hazard proportional regression model was used to analyze the independent and joint association of biological aging and lifestyle with risks of cancer incidence and mortality, respectively.

RESULTS

Over a median follow-up period of 12.3 years, we found that older biological age was associated with increased risks of overall cancer, digestive system cancers, lung, breast and renal cancers incidence and mortality (HRs: 1.12-2.25). In the joint analysis of biological aging and lifestyle with risks of cancer incidence and mortality, compared with unhealthy lifestyle and younger biological age, individuals with healthy lifestyle and older biological age had decreased risks of incidence (8% ∼ 60%) and mortality (20% ∼ 63%) for overall, esophageal, colorectal, pancreatic and lung cancers.

CONCLUSIONS

Biological aging may be an important risk factor for cancer morbidity and mortality. A healthier lifestyle is more likely to mitigate the adverse effects of biological aging on overall cancer and some site-specific cancers.

Associations of serum cystatin C concentrations with total mortality and mortality of 12 site-specific cancers

Purpose

Cystatin C (CysC), beyond its biomarker role of renal function, has been implicated in various physical and pathological activities. However, the impact of serum CysC on cancer mortality in a general population remains unknown. We aimed to examine the associations of serum CysC concentrations with total mortality and mortality of 12 site-specific cancers.

Methods

We included 241,008 participants of the UK Biobank cohort with CysC measurements who had normal creatinine-based estimated glomerular filtration rates and were free of cancer and renal diseases at baseline (2006-2010). Death information was obtained from the National Health Service death records through 28 February 2021. Multivariable Cox proportional hazards models were used to compute hazard ratios (HR) per one standard deviation increase in log-transformed CysC concentrations and 95% confidence intervals (95% CI) for mortality.

Results

Over a median follow-up of 12.1 (interquartile range, 11.3-12.8) years, 5,744 cancer deaths occurred. We observed a positive association between serum CysC concentrations and total cancer mortality (HR = 1.16, 95% CI: 1.12-1.20). Specifically, participants with higher serum CysC concentrations had increased mortality due to lung cancer (HR = 1.12, 95% CI: 1.05-1.20), blood cancer (HR = 1.29, 95% CI: 1.16-1.44), brain cancer (HR = 1.19, 95% CI: 1.04-1.36), esophageal cancer (HR = 1.20, 95% CI: 1.05-1.37), breast cancer (HR = 1.18, 95% CI: 1.03-1.36), and liver cancer (HR = 1.49, 95% CI: 1.31-1.69).

Conclusion

Our findings indicate that higher CysC concentrations are associated with increased mortality due to lung, blood, brain, esophageal, breast, and liver cancers. Future studies are necessary to clarify underlying mechanisms.

Blood Lipid Metabolic Profiles and Causal Links to Site-Specific Cancer Risks: A Mendelian Randomization Study

Observational and Mendelian randomization (MR) studies have established links between dyslipidemia and select cancer susceptibilities. However, there is a lack of comprehensive exploration of causal relationships spanning diverse cancer types. Here, we conducted a two-sample MR analysis to elucidate the causative connections between 9 blood lipid metabolic profiles (namely, adiponectin, leptin, lipoprotein A, apolipoprotein A1, apolipoprotein B, cholesterol, triglycerides, LDL-cholesterol, and HDL-cholesterol) and 21 site-specific cancer risks. Our findings reveal genetically predicted adiponectin levels to be associated with a reduced ovarian cancer risk, while genetically determined leptin increases bladder cancer risk but decreases prostate cancer risk. Lipoprotein A elevates risk of prostate cancer while diminishing risk of endometrial cancer, while apolipoprotein A1 heightens risks of breast and cervical cancers. Furthermore, elevated levels of cholesterol are positively correlated with kidney cancer, and triglycerides demonstrate a positive association with non-melanoma skin cancer but a negative association with breast cancer. Protective effects of genetically predicted LDL-cholesterol on endometrial cancer and adverse effects of HDL-cholesterol on breast cancer are also observed. Our study conclusively establishes that blood lipid metabolic profiles exert causal effects on cancer susceptibility, providing more robust evidence for cancer prevention and prompting contemplation regarding the future health of the human populace.

Plasma total cholesterol concentration and risk of higher-grade prostate cancer: A nested case-control study and a dose-response meta-analysis

Our previous publication found an increased risk of higher-grade (Gleason sum ≥7) prostate cancer for men with high total cholesterol concentration (≥200 mg/dl) in the Health Professionals Follow-up Study (HPFS). With additional 568 prostate cancer cases, we are now able to investigate this association in more detail. For the nested case-control study, we included 1260 men newly diagnosed with prostate cancer between 1993 and 2004, and 1328 controls. For the meta-analyses, 23 articles studied the relationship between total cholesterol level and prostate cancer incidence were included. Logistic regression models and dose-response meta-analysis were performed. An increased risk of higher-grade (Gleason sum ≥4 + 3) prostate cancer for high vs low quartile of total cholesterol level was observed in the HPFS (ORmultivariable  = 1.56; 95% CI = 1.01-2.40). This finding was compatible with the association noted in the meta-analysis of highest vs lowest group of total cholesterol level, which suggested a moderately increased risk of higher-grade prostate cancer (Pooled RR =1.21; 95%CI: 1.11-1.32). Moreover, the dose-response meta-analysis indicated that an increased risk of higher-grade prostate cancer occurred primarily at total cholesterol levels ≥200 mg/dl, where the RR was 1.04 (95%CI: 1.01-1.08) per 20 mg/dl increase in total cholesterol level. However, total cholesterol concentration was not associated with the risk of prostate cancer overall either in the HPFS or in the meta-analysis. Our primary finding, as well as the result of the meta-analysis suggested a modest increased risk of higher-grade prostate cancer, at total cholesterol concentrations exceeding 200 mg/dl.

Liver Fibrosis Scores and Prostate Cancer Risk and Mortality in the Atherosclerosis Risk in Communities Study

Subclinical liver impairment due to fibrosis could influence the development and detectability of prostate cancer. To investigate the association between liver fibrosis and prostate cancer incidence and mortality, we included 5,284 men (mean age: 57.6 years, 20.1% Black) without cancer or liver disease at Visit 2 in the Atherosclerosis Risk in Communities study. Liver fibrosis was assessed using the aspartate aminotransferase to platelet ratio index, fibrosis 4 index (FIB-4), and nonalcoholic fatty liver disease fibrosis score (NFS). Over 25 years, 215 Black and 511 White men were diagnosed with prostate cancer, and 26 Black and 51 White men died from the disease. We estimated HRs for total and fatal prostate cancer using Cox regression. FIB-4 [quintile 5 vs. 1: HR = 0.47, 95% confidence interval (CI): 0.29-0.77, Ptrend = 0.004] and NFS (HR = 0.56, 95% CI: 0.33-0.97, Ptrend = 0.03) were inversely associated with prostate cancer risk in Black men. Compared with no abnormal score, men with ≥1 abnormal score had a lower prostate cancer risk if they were Black (HR = 0.46, 95% CI: 0.24-0.89), but not White (HR = 1.04, 95% CI: 0.69-1.58). Liver fibrosis scores did not appear to be associated with fatal prostate cancer in Black or White men. Among men without a clinical diagnosis of liver disease, higher liver fibrosis scores were associated with lower incidence of prostate cancer in Black men, but not in White men, and not with fatal prostate cancer in either race. Further research is needed to understand the influence of subclinical liver disease on prostate cancer development versus detectability and the racial differences observed.

PREVENTION RELEVANCE

Investigating the link between liver fibrosis and prostate cancer risk and mortality, our study reveals the potential influence of liver health on prostate cancer development and on detection using PSA test, urging further research to understand the differential findings by race and to optimize prevention and intervention strategies.

Clinical biomarker-based biological aging and risk of cancer in the UK Biobank

BACKGROUND

Despite a clear link between aging and cancer, there has been inconclusive evidence on how biological age (BA) may be associated with cancer incidence.

METHODS

We studied 308,156 UK Biobank participants with no history of cancer at enrolment. Using 18 age-associated clinical biomarkers, we computed three BA measures (Klemera-Doubal method [KDM], PhenoAge, homeostatic dysregulation [HD]) and assessed their associations with incidence of any cancer and five common cancers (breast, prostate, lung, colorectal, and melanoma) using Cox proportional-hazards models.

RESULTS

A total of 35,426 incident cancers were documented during a median follow-up of 10.9 years. Adjusting for common cancer risk factors, 1-standard deviation (SD) increment in the age-adjusted KDM (hazard ratio = 1.04, 95% confidence interval = 1.03-1.05), age-adjusted PhenoAge (1.09, 1.07-1.10), and HD (1.02, 1.01-1.03) was significantly associated with a higher risk of any cancer. All BA measures were also associated with increased risks of lung and colorectal cancers, but only PhenoAge was associated with breast cancer risk. Furthermore, we observed an inverse association between BA measures and prostate cancer, although it was attenuated after removing glycated hemoglobin and serum glucose from the BA algorithms.

CONCLUSIONS

Advanced BA quantified by clinical biomarkers is associated with increased risks of any cancer, lung cancer, and colorectal cancer.

Total-, LDL-, and HDL-cholesterol, apolipoproteins, and triglycerides with risk of total and fatal prostate cancer in Black and White men in the ARIC study

BACKGROUND

Cholesterol reduction is considered a mechanism through which cholesterol-lowering drugs including statins are associated with a reduced aggressive prostate cancer risk. While prior cohort studies found positive associations between total cholesterol and more advanced stage and grade in White men, whether associations for total cholesterol, low (LDL)- and high (HDL)-density lipoprotein cholesterol, apolipoprotein B (LDL particle) and A1 (HDL particle), and triglycerides are similar for fatal prostate cancer and in Black men, who experience a disproportionate burden of total and fatal prostate cancer, is unknown.

METHODS

We conducted a prospective study of 1553 Black and 5071 White cancer-free men attending visit 1 (1987-1989) of the Atherosclerosis Risk in Communities Study. A total of 885 incident prostate cancer cases were ascertained through 2015, and 128 prostate cancer deaths through 2018. We estimated multivariable-adjusted hazard ratios (HRs) of total and fatal prostate cancer per 1-standard deviation increments and for tertiles (T1-T3) of time-updated lipid biomarkers overall and in Black and White men.

RESULTS

Greater total cholesterol concentration (HR per-1 SD = 1.25; 95% CI = 1.00-1.58) and LDL cholesterol (HR per-1 SD = 1.26; 95% CI = 0.99-1.60) were associated with higher fatal prostate cancer risk in White men only. Apolipoprotein B was nonlinearly associated with fatal prostate cancer overall (T2 vs. T1: HR = 1.66; 95% CI = 1.05-2.64) and in Black men (HR = 3.59; 95% CI = 1.53-8.40) but not White men (HR = 1.13; 95% CI = 0.65-1.97). Tests for interaction by race were not statistically significant.

CONCLUSIONS

These findings may improve the understanding of lipid metabolism in prostate carcinogenesis by disease aggressiveness, and by race while emphasizing the importance of cholesterol control.

Circulating lipoprotein (a) and all-cause and cause-specific mortality: a systematic review and dose-response meta-analysis

AIMS

To investigate the association between circulating lipoprotein(a) (Lp(a)) and risk of all-cause and cause-specific mortality in the general population and in patients with chronic diseases, and to elucidate the dose-response relations.

METHODS AND RESULTS

We searched literature to find prospective studies reporting adjusted risk estimates on the association of Lp(a) and mortality outcomes. Forty-three publications, reporting on 75 studies (957,253 participants), were included. The hazard ratios (HRs) and 95% confidence intervals (95%CI ) for the top versus bottom tertile of Lp(a) levels and risk of all-cause mortality were 1.09 (95%CI: 1.01-1.18, I2: 75.34%, n = 19) in the general population and 1.18 (95%CI: 1.04-1.34, I2: 52.5%, n = 12) in patients with cardiovascular diseases (CVD). The HRs for CVD mortality were 1.33 (95%CI: 1.11-1.58, I2: 82.8%, n = 31) in the general population, 1.25 (95%CI: 1.10-1.43, I2: 54.3%, n = 17) in patients with CVD and 2.53 (95%CI: 1.13-5.64, I2: 66%, n = 4) in patients with diabetes mellitus. Linear dose-response analyses revealed that each 50 mg/dL increase in Lp(a) levels was associated with 31% and 15% greater risk of CVD death in the general population and in patients with CVD. No non-linear dose-response association was observed between Lp(a) levels and risk of all-cause or CVD mortality in the general population or in patients with CVD (Pnonlinearity > 0.05).

CONCLUSION

This study provides further evidence that higher Lp(a) levels are associated with higher risk of all-cause mortality and CVD-death in the general population and in patients with CVD. These findings support the ESC/EAS Guidelines that recommend Lp(a) should be measured at least once in each adult person's lifetime, since our study suggests those with higher Lp(a) might also have higher risk of mortality.

Prebiopsy bpMRI and hematological parameter-based risk scoring model for predicting outcomes in biopsy-naive men with PSA 4-20 ng/mL

Excessive prostate biopsy is a common problem for clinicians. Although some hematological and bi-parametric magnetic resonance imaging (bpMRI) parameters might help increase the rate of positive prostate biopsies, there is a lack of studies on whether their combination can further improve clinical detection efficiency. We retrospectively enrolled 394 patients with PSA levels of 4-20 ng/mL who underwent prebiopsy bpMRI during 2010-2021. Based on bpMRI and hematological indicators, six models and a nomogram were constructed to predict the outcomes of biopsy. Furthermore, we constructed and evaluated a risk scoring model based on the nomogram. Age, prostate-specific antigen (PSA) density (PSAD), systemic immune-inflammation index, cystatin C level, and the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 score were significant predictors of prostate cancer (PCa) on multivariable logistic regression analyses (P < 0.05) and the five parameters were used to construct the XYFY nomogram. The area under the receiver operating characteristic (ROC) curve (AUC) of the nomogram was 0.916. Based on the nomogram, a risk scoring model (XYFY risk model) was constructed and then we divided the patients into low-(XYFY score: < 95), medium-(XYFY score: 95-150), and, high-risk (XYFY score: > 150) groups. The predictive values for diagnosis of PCa and clinically-significant PCa among the three risk groups were 3.0%(6/201), 41.8%(51/122), 91.5%(65/71); 0.5%(1/201), 19.7%(24/122), 60.6%(43/71), respectively. In conclusion, in this study, we used hematological and bpMRI parameters to establish and internally validate a XYFY risk scoring model for predicting the biopsy outcomes for patients with PSA levels of 4-20 ng/mL and this risk model would support clinical decision-making and reduce excessive biopsies.

Circulating phosphorus concentration and risk of prostate cancer: a Mendelian randomization study

BACKGROUND

Recent observational studies have suggested that circulating phosphorus concentrations are positively associated with the risk of prostate cancer. However, little is known about the causal direction of the association.

OBJECTIVES

To explore the potential causal relation between circulating phosphorus and risk of prostate cancer, we conducted a Mendelian randomization (MR) study.

METHODS

Summary statistics of prostate cancer were obtained from a meta-analysis of genome-wide association studies (GWASs) consisting of 79,148 cases and 61,106 controls. Single-nucleotide polymorphisms (SNPs) associated with serum phosphorus concentration were selected from a GWAS of 291,408 individuals from the UK Biobank. MR analysis was performed using the inverse variance weighted (IVW) method, supplemented with simple median method, weighted median method, maximum likelihood-based method, MR-Egger regression, and the MR pleiotropy residual sum and outlier test. We also performed a meta-analysis of observational studies to assess the associations of dietary phosphorus intake and serum phosphorus concentration with risk of prostate cancer.

RESULTS

In the MR analysis, a total of 125 independent SNPs associated with serum phosphorus concentrations were used as instrumental variables. Genetically predicted serum phosphorus concentrations were associated with a 19% increased risk of prostate cancer (95% CI: 9%, 31%) per 1-SD increment of serum phosphorus by IVW (P = 1.82 × 10-4). Sensitivity analyses using alternative MR methods produced similar positive associations, and no evidence of pleiotropy was detected by MR-Egger regression (P = 0.422). For meta-analysis, 8 studies for dietary phosphorus intake and 4 for serum phosphorus concentrations were included involving a total of 669,080 participants. Consistently, high dietary phosphorus intake and serum phosphorus concentrations were associated with an 8% (95% CI: 4%, 12%) and 7% (95% CI: 1%, 14%) increase in prostate cancer risk, respectively.

CONCLUSIONS

Our study suggested a potential causal relation between circulating phosphorus and risk of prostate cancer. Further studies are warranted to elucidate the underlying mechanism of phosphorus in the development of prostate cancer.

The relationship between lipoprotein A and other lipids with prostate cancer risk: A multivariable Mendelian randomisation study

BACKGROUND

Numerous epidemiological studies have investigated the role of blood lipids in prostate cancer (PCa) risk, though findings remain inconclusive to date. The ongoing research has mainly involved observational studies, which are often prone to confounding. This study aimed to identify the relationship between genetically predicted blood lipid concentrations and PCa.

METHODS AND FINDINGS

Data for low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides (TG), apolipoprotein A (apoA) and B (apoB), lipoprotein A (Lp(a)), and PCa were acquired from genome-wide association studies in UK Biobank and the PRACTICAL consortium, respectively. We used a two-sample summary-level Mendelian randomisation (MR) approach with both univariable and multivariable (MVMR) models and utilised a variety of robust methods and sensitivity analyses to assess the possibility of MR assumptions violation. No association was observed between genetically predicted concentrations of HDL, TG, apoA and apoB, and PCa risk. Genetically predicted LDL concentration was positively associated with total PCa in the univariable analysis, but adjustment for HDL, TG, and Lp(a) led to a null association. Genetically predicted concentration of Lp(a) was associated with higher total PCa risk in the univariable (ORweighted median per standard deviation (SD) = 1.091; 95% CI 1.028 to 1.157; P = 0.004) and MVMR analyses after adjustment for the other lipid traits (ORIVW per SD = 1.068; 95% CI 1.005 to 1.134; P = 0.034). Genetically predicted Lp(a) was also associated with advanced (MVMR ORIVW per SD = 1.078; 95% CI 0.999 to 1.163; P = 0.055) and early age onset PCa (MVMR ORIVW per SD = 1.150; 95% CI 1.015,1.303; P = 0.028). Although multiple estimation methods were utilised to minimise the effect of pleiotropy, the presence of any unmeasured pleiotropy cannot be excluded and may limit our findings.

CONCLUSIONS

We observed that genetically predicted Lp(a) concentrations were associated with an increased PCa risk. Future studies are required to understand the underlying biological pathways of this finding, as it may inform PCa prevention through Lp(a)-lowering strategies.

Role of cystatin C in urogenital malignancy

Urogenital malignancy accounts for one of the major causes of cancer-related deaths globally. Numerous studies have investigated novel molecular markers in the blood circulation, tumor tissue, or urine in order to assist in the clinical identification of tumors at early stages, predict the response of therapeutic strategies, and give accurate prognosis assessment. As an endogenous inhibitor of lysosomal cysteine proteinases, cystatin C plays an integral role in diverse processes. A substantial number of studies have indicated that it may be such a potential promising biomarker. Therefore, this review was intended to provide a detailed overview of the role of cystatin C in urogenital malignancy.

Oversupply of Limiting Cell Resources and the Evolution of Cancer Cells: A Review

Cancer prevention is superior to cancer treatment—indeed, understanding and controlling cancer risk is a key question in the fields of applied ecology and evolutionary oncology. Ecological cancer risk models offer the dual benefit of being generalizable across cancer types, and unveiling common mechanisms underlying cancer development and spread. Understanding the biological mechanisms of cancer risk may also guide the design of interventions to prevent cancer. Ecological considerations are central to many of these mechanisms; as one example, the ecologically-based hypothesis of metabolic cancer suppression posits that restricted vascular supply of limiting resources to somatic tissues normally suppresses the evolution of somatic cells toward cancer. Here we present a critical review of published evidence relevant to this hypothesis, and we conclude that there is substantial evidence that cancer risk does increase with an abnormal excess of limiting cell resources, including both dietary macronutrients as well as certain micronutrients.