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Abstract Single nucleotide polymorphism (SNP) interactions are the key to improving polygenic risk scores. Previous studies reported several significant SNP–SNP interaction pairs that shared a common SNP to form a cluster, but some identified pairs might be false positives. This study aims to identify factors associated with the cluster effect of false positivity and develop strategies to enhance the accuracy of SNP–SNP interactions. The results showed the cluster effect is a major cause of false-positive findings of SNP–SNP interactions. This cluster effect is due to high correlations between a causal pair and null pairs in a cluster. The clusters with a hub SNP with a significant main effect and a large minor allele frequency (MAF) tended to have a higher false-positive rate. In addition, peripheral null SNPs in a cluster with a small MAF tended to enhance false positivity. We also demonstrated that using the modified significance criterion based on the 3 p-value rules and the bootstrap approach (3pRule + bootstrap) can reduce false positivity and maintain high true positivity. In addition, our results also showed that a pair without a significant main effect tends to have weak or no interaction. This study identified the cluster effect and suggested using the 3pRule + bootstrap approach to enhance SNP–SNP interaction detection accuracy.

Abstract Introduction Men with African ancestry have the highest incidence and mortality rates of prostate cancer (PCa) worldwide. Methods This study aimed to identify differentially methylated genes between tumor vs. adjacent normal and aggressive vs. indolent PCa in 121 African American patients. Epigenome‐wide DNA methylation patterns in tumor DNA were assessed using the human Illumina Methylation EPIC V1 array. Results Around 5,139 differentially methylated CpG‐sites (q 0.2) were identified when comparing normal vs. tumor, with an overall trend of hypermethylation in prostate tumors. Multiple representative differentially methylated regions (DMRs), including immune‐related genes, such as CD40, Galectin3, OX40L, and STING, were detected in prostate tumors when compared to adjacent normal tissues. Based on an epigenetic clock model, we observed that tumors’ total number of stem cell divisions and the stem cell division rate were significantly higher than adjacent normal tissues. Regarding PCa aggressiveness, 2,061 differentially methylated CpG‐sites (q .05) were identified when the grade group (GG)1 was compared with GG4/5. Among these 2,061 CpG sites, 155 probes were consistently significant in more than one comparison. Among these genes, several immune system genes, such as COL18A1, S100A2, ITGA4, HLA‐C, and ADCYAP1, have previously been linked to tumor progression in PCa. Conclusion Several differentially methylated genes involved in immune‐oncologic pathways associated with disease risk or aggressiveness were identified. In addition, 261 African American‐specific differentially methylated genes related to the risk of PCa were identified. These results can shedlight on potential mechanisms contributing to PCa disparities in the African American Population.

Despite advances in screening, diagnosis, and treatment for prostate cancer (PCa), Black men tend to be diagnosed at younger ages, have higher mortality rates, and are at increased risk of recurrence or metastasis compared to their White counterparts. PCa disparities among Black men are caused by a complex interaction of social, behavioral, and biological factors across the public policy, community, organizational, interpersonal, and individual levels. Key contributing factors include mistrust in the health care system, poor communication between patients and providers, low awareness of screening guidelines, and high medical costs. These disparities are further exacerbated by the low representation of Black men in clinical trials, which limits access to high-quality cancer care and generalizability for PCa treatments. In this narrative review of the existing literature, we examined the epidemiology and identified contributing factors, and propose multi-level strategies to address and mitigate disparities among Black men with PCa.

Summary: Background: Tumour-promoting inflammation is a “hallmark” of cancer and conventional epidemiological studies have reported links between various inflammatory markers and cancer risk. The causal nature of these relationships and, thus, the suitability of these markers as intervention targets for cancer prevention is unclear. Methods: We meta-analysed 6 genome-wide association studies of circulating inflammatory markers comprising 59,969 participants of European ancestry. We then used combined cis-Mendelian randomization and colocalisation analysis to evaluate the causal role of 66 circulating inflammatory markers in risk of 30 adult cancers in 338,294 cancer cases and up to 1,238,345 controls. Genetic instruments for inflammatory markers were constructed using genome-wide significant (P 70% was employed to indicate support for shared causal variants across inflammatory markers and cancer outcomes. Findings were replicated in the FinnGen study and then pooled using meta-analysis. Findings: We found strong evidence to support an association of genetically-proxied circulating pro-adrenomedullin concentrations with increased breast cancer risk (OR: 1.19, 95% CI: 1.10–1.29, q-value = 0.033, PPH4 = 84.3%) and suggestive evidence to support associations of interleukin-23 receptor concentrations with increased pancreatic cancer risk (OR: 1.42, 95% CI: 1.20–1.69, q-value = 0.055, PPH4 = 73.9%), prothrombin concentrations with decreased basal cell carcinoma risk (OR: 0.66, 95% CI: 0.53–0.81, q-value = 0.067, PPH4 = 81.8%), and interleukin-1 receptor-like 1 concentrations with decreased triple-negative breast cancer risk (OR: 0.92, 95% CI: 0.88–0.97, q-value = 0.15, PPH4 = 85.6%). These findings were replicated in pooled analyses with the FinnGen study. Though suggestive evidence was found to support an association of macrophage migration inhibitory factor concentrations with increased bladder cancer risk (OR: 2.46, 95% CI: 1.48–4.10, q-value = 0.072, PPH4 = 76.1%), this finding was not replicated when pooled with the FinnGen study. For 22 of 30 cancer outcomes examined, there was little evidence (q-value ≥0.20) that any of the 66 circulating inflammatory markers examined were associated with cancer risk. Interpretation: Our comprehensive joint Mendelian randomization and colocalisation analysis of the role of circulating inflammatory markers in cancer risk identified potential roles for 4 circulating inflammatory markers in risk of 4 site-specific cancers. Contrary to reports from some prior conventional epidemiological studies, we found little evidence of association of circulating inflammatory markers with the majority of site-specific cancers evaluated. Funding: Cancer Research UK (C68933/A28534, C18281/A29019, PPRCPJT∖100005), World Cancer Research Fund (IIG_FULL_2020_022), National Institute for Health Research (NIHR202411, BRC-1215-20011), Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4), Academy of Finland Project 326291, European Union's Horizon 2020 grant agreement no. 848158 (EarlyCause), French National Cancer Institute (INCa SHSESP20, 2020-076), Versus Arthritis (21173, 21754, 21755), National Institutes of Health (U19 CA203654), National Cancer Institute (U19CA203654).

Abstract Background DNA methylation and gene expression are known to play important roles in the etiology of human diseases such as prostate cancer (PCa). However, it has not yet been possible to incorporate information of DNA methylation and gene expression into polygenic risk scores (PRSs). Here, we aimed to develop and validate an improved PRS for PCa risk by incorporating genetically predicted gene expression and DNA methylation, and other genomic information using an integrative method. Methods Using data from the PRACTICAL consortium, we derived multiple sets of genetic scores, including those based on available single‐nucleotide polymorphisms through widely used methods of pruning and thresholding, LDpred, LDpred‐funt, AnnoPred, and EBPRS, as well as PRS constructed using the genetically predicted gene expression and DNA methylation through a revised pruning and thresholding strategy. In the tuning step, using the UK Biobank data (1458 prevalent cases and 1467 controls), we selected PRSs with the best performance. Using an independent set of data from the UK Biobank, we developed an integrative PRS combining information from individual scores. Furthermore, in the testing step, we tested the performance of the integrative PRS in another independent set of UK Biobank data of incident cases and controls. Results Our constructed PRS had improved performance (C statistics: 76.1%) over PRSs constructed by individual benchmark methods (from 69.6% to 74.7%). Furthermore, our new PRS had much higher risk assessment power than family history. The overall net reclassification improvement was 69.0% by adding PRS to the baseline model compared with 12.5% by adding family history. Conclusions We developed and validated a new PRS which may improve the utility in predicting the risk of developing PCa. Our innovative method can also be applied to other human diseases to improve risk prediction across multiple outcomes.

A variety of anticancer drugs and targeted agents for lung cancer have been developed, but some patients do not respond to these medications as intended. Therefore, there is an urgent need to develop a tool for predicting the anticancer drug response of each patient. Patient-derived tumor organoids (PDOs) have emerged as reliable In vitro tools for developing precision medicine. Herein, we describe a case of a 50-year-old nonsmoking man who was diagnosed with non-small cell lung cancer. Initially, no clinical symptoms were found in this patient. Postoperative pathology confirmed a stage Ib tumor, and an epidermal growth factor receptor (EGFR) mutation (exon21p.L858R) was detected in the patient’s lung tumor specimen. The patient later showed intracranial relapse 17 months after complete resection. An organoid culture was established from the resected brain metastatic tissue and a drug sensitivity test showed, within 72 hours, that the organoids were resistant to gefitinib and osimertinib. Our results recapitulated the patient’s response to anticancer drugs, demonstrating the potential of PDOs for precision medicine.

Abstract Background Interactions of single nucleotide polymorphisms (SNPs) and environmental factors play an important role in understanding complex diseases' pathogenesis. A growing number of SNP-environment studies have been conducted in the past decade; however, the statistical methods for evaluating SNP-environment interactions are still underdeveloped. The conventional statistical approach with a full interaction model with an additive SNP mode tests one specific interaction type, so the full interaction model approach tends to lead to false-negative findings. To increase detection accuracy, developing a statistical tool to effectively detect various SNP-environment interaction patterns is necessary. Results SNPxE, a SNP-environment interaction pattern identifier, tests multiple interaction patterns associated with a phenotype for each SNP-environment pair. SNPxE evaluates 27 interaction patterns for an ordinal environment factor and 18 patterns for a categorical environment factor. For detecting SNP-environment interactions, SNPxE considers three major components: (1) model structure, (2) SNP’s inheritance mode, and (3) risk direction. Among the multiple testing patterns, the best interaction pattern will be identified based on the Bayesian information criterion or the smallest p-value of the interaction. Furthermore, the risk sub-groups based on the SNPs and environmental factors can be identified. SNPxE can be applied to both numeric and binary phenotypes. For better results interpretation, a heat-table of the outcome proportions can be generated for the sub-groups of a SNP-environment pair. Conclusions SNPxE is a valuable tool for intensively evaluate SNP-environment interactions, and the SNPxE findings can provide insights for solving the missing heritability issue. The R function of SNPxE is freely available for download at GitHub ( https://github.com/LinHuiyi/SIPI ).

High prostate-specific antigen (PSA) levels can indicate potential prostate problems and are a warning sign of prostate cancer. The impact of antioxidants on the PSA of generally healthy men is understudied. This study aims to evaluate 14 dietary and endogenous antioxidants associated with PSA levels for United States (US) men. We assessed 7398 men using the 2003–2010 US population-based National Health and Nutrition Examination Survey (NHANES). The PSA levels were categorized into three groups: Normal, borderline, and elevated levels. We performed analyses for middle-aged and older groups aged 40–64.9 and ≥65, respectively. The weighted multinomial regressions were performed to evaluate antioxidants associated with the PSA status. For results, 0.3% and 3.4% of middle-aged and older men, respectively, had elevated PSA (>10 ng/mL). Men with a higher serum albumin level had a lower risk of an elevated PSA, adjusting for age. The magnitude of albumin’s impact on PSA is larger in middle-aged men than in older men (OR of elevated PSA = 0.82 and 0.90, respectively, interaction p = 0.002). Other antioxidants are not associated with PSA. Our findings support men with low serum albumin tend to have an elevated PSA level, so related interventions can be considered to decrease PSA for maintaining prostate health.

Abstract Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP–SNP interactions in the four pathways (the angiogenesis-, mitochondria-, miRNA-, and androgen metabolism-related pathways) associated with PCa aggressiveness, we tested 8587 SNPs for 20,729 cases from the PCa consortium. We identified 3 KLK3 SNPs, and 1083 (P

A polygenic hazard score (PHS1) improves prostate cancer screening accuracy in European patients. Here, the authors test the performance of a version compatible with OncoArray genotypes (PHS2) in a multi-ethnic dataset and find that it risk-stratifies men for any, aggressive, and fatal prostate cancer.

Abstract Approximately 10%‐20% of patients with clinically localized clear cell renal cell carcinoma (ccRCC) at time of surgery will subsequently experience metastatic progression. Although considerable progression was seen in the systemic treatment of metastatic ccRCC in last 20 years, once ccRCC spreads beyond the confines of the kidney, 5‐year survival is less than 10%. Therefore, significant clinical advances are urgently needed to improve overall survival and patient care to manage the growing number of patients with localized ccRCC. We comprehensively evaluated expression of 388 candidate genes related with survival of ccRCC by using TCGA RNAseq (n = 515), Total Cancer Care (TCC) expression array data (n = 298), and a well characterized Moffitt RCC cohort (n = 248). We initially evaluated all 388 genes for association with overall survival using TCGA and TCC data. Eighty‐one genes were selected for further analysis and tested on Moffitt RCC cohort using NanoString expression analysis. Expression of nine genes (AURKA, AURKB, BIRC5, CCNE1, MK167, MMP9, PLOD2, SAA1, and TOP2A) was validated as being associated with poor survival. Survival prognostic models showed that expression of the nine genes and clinical factors predicted the survival in ccRCC patients with AUC value: 0.776, 0.821 and 0.873 for TCGA, TCC and Moffitt data set, respectively. Some of these genes have not been previously implicated in ccRCC survival and thus potentially offer insight into novel therapeutic targets. Future studies are warranted to validate these identified genes, determine their biological mechanisms and evaluate their therapeutic potential in preclinical studies.

Genome wide association studies have identified multiple loci associated with risk of developing prostate cancer but the functional significance of many of these are unknown. Here, after generating models to predict methylation, the authors identify CpG methylation sites associated with prostate cancer.

Polyphenon E (Poly E) is a standardized, caffeine-free green tea extract with defined polyphenol content. Poly E is reported to confer chemoprotective activity against prostate cancer (PCa) progression in the TRAMP model of human PCa, and has shown limited activity against human PCa in human trials. The molecular mechanisms of the observed Poly E chemopreventive activity against PCa are not fully understood. We hypothesized that Poly E treatment of PCa cells induces gene expression changes, which could underpin the molecular mechanisms of the limited Poly E chemoprevention activity against PCa. PC-3 cells were cultured in complete growth media supplemented with varied Poly E concentrations for 24 h, then RNA was isolated for comparative DNA microarray (0 vs. 200 mg/L Poly E) and subsequent TaqMan qRT-PCR analyses. Microarray data for 54,613 genes were filtered for >2-fold expression level changes, with 8319 genes increased and 6176 genes decreased. Eight genes involved in key signaling or regulatory pathways were selected for qRT-PCR. Two genes increased expression significantly, MXD1 (13.98-fold; p = 0.0003) and RGS4 (21.98-fold; p = 0.0011), by qRT-PCR. MXD1 and RGS4 significantly increased gene expression in Poly E-treated PC-3 cells, and the MXD1 gene expression increases were Poly E dose-dependent.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Abstract Background A hypoxic microenvironment leads to an increase in the invasiveness and the metastatic potential of cancer cells within tumors via the epithelial-mesenchymal transition (EMT) and cancer stemness acquisition. However, hypoxia-induced changes in the expression and function of candidate stem cell markers and their possible molecular mechanism is still not understood. Methods Lung cell lines were analyzed in normoxic or hypoxic conditions. For screening among the stem cell markers, a transcriptome analysis using next-generation sequencing was performed. For validation, the EMT and stem cell characteristics were analyzed. To determine whether an epigenetic mechanism was involved, the cell lines were treated with a DNA methyltransferase inhibitor (AZA), and methylation-specific PCR and bisulfite sequencing were performed. Results Next-generation sequencing revealed that the CXCR4 expression was significantly higher after the hypoxic condition, which functionally resulted in the EMT and cancer stemness acquisition. The acquisition of the EMT and stemness properties was inhibited by treatment with CXCR4 siRNA. The CXCR4 was activated by either the hypoxic condition or treatment with AZA. The methylation-specific PCR and bisulfite sequencing displayed a decreased CXCR4 promoter methylation in the hypoxic condition. Conclusions These results suggest that hypoxia-induced acquisition of cancer stem cell characteristics was associated with CXCR4 activation by its aberrant promoter demethylation.

Similarities in cancers can be studied to interrogate their etiology. Here, the authors use genome-wide association study summary statistics from six cancer types based on 296,215 cases and 301,319 controls of European ancestry, showing that solid tumours arising from different tissues share a degree of common germline genetic basis.

The original version of this Article contained an error in the spelling of the author Manuela Gago-Dominguez, which was incorrectly given as Manuela G. Dominguez. This has now been corrected in both the PDF and HTML versions of the Article.

Lung cancer, which remains a major cause of mortality worldwide, is a histologically diverse condition and demonstrates substantial phenotypic and genomic diversity among individual patients, manifesting as both intertumoral and intratumoral heterogeneity. This heterogeneity has made it difficult to develop lung cancer models. Two-dimensional (2D) cancer cell lines have been used to study genetic and molecular alterations in lung cancer. However, cancer cell lines have several disadvantages, including random genetic drift caused by long-term culture, a lack of annotated clinical data, and most importantly, the fact that only a subset of tumors shows 2D growth on plastic. Three-dimensional models of cancer have the potential to improve cancer research and drug development because they are more representative of cancer biology and its diverse pathophysiology. Herein, we present an integrated review of current information on preclinical lung cancer models and their limitations, including cancer cell line models, patient-derived xenografts, and lung cancer organoids, and discuss their possible therapeutic applications for drug discovery and screening to guide precision medicine in lung cancer research. Altogether, the success rate of generating lung cancer organoids must be improved, and a lung cancer organoid culture system is necessary to achieve the goal of designing an individualized therapeutic strategy for each lung cancer patient.

The number of cases of aggressive prostate cancer is increasing. Differentiating between aggressive and indolent cases has resulted in increased difficulty for the physician and patient to decide on the best treatment option. Due to this challenge, efforts are underway to profile genetic risk for prostate cancer aggressiveness, which may help physicians and patients at risk for developing aggressive prostate cancer to select an appropriate treatment option. This study explores patients’ interest in receiving genetic results, preference for how genetic risk information should be communicated, and willingness to share results with adult male first-degree relatives (FDRs). A nine-item survey was adapted to assess their beliefs and attitudes about genetic testing for prostate cancer aggressiveness. In addition, participants ( n = 50) responded to hypothetical scenarios and questions associated with perceived importance of risk disclosure, preferences for receiving genetic risk information, and sharing of results with FDRs. As the hypothetical risk estimate for aggressive prostate cancer increased, patients’ willingness to receive genetic risk information increased. This study found that most patients preferred receiving genetic risk education in the form of a DVD (76%), one-page informational sheet (75%), or educational booklet (70%). Almost all patients (98%) reported that they would be willing to share their test results with FDRs. The results of this study highlight prostate cancer patients’ desire to receive and share genetic risk information. Future research should focus on assessing the long-term benefits of receiving genetic information for prostate cancer patients and implications of sharing this information with FDRs.

Chromosome 8q24 is known to be a major susceptibility region for prostate cancer risk. Here the authors analyze genetic data across the 8q24 region from 71,535 prostate cancer patients identifying 12 risk loci, three previously unreported, highlighting the contribution of germline variation at this locus.

Prostate cancer (PrCa) involves a large heritable genetic component. Here, the authors perform multivariate fine-mapping of known PrCa GWAS loci, identifying variants enriched for biological function, explaining more familial relative risk, and with potential application in clinical risk profiling.

Abstract Significant racial disparities in prostate cancer (PCa) outcomes have been reported, with African‐American men (AAM) more likely to endure adverse oncologic outcomes. Despite efforts to dissipate racial disparities in PCa, a survival gap persists and it remains unclear to what extent this disparity can be explained by known clinicodemographic factors. In this study, we leveraged our large institutional database, spanning over 25 years, to investigate whether AAM continued to experience poor PCa outcomes and factors that may contribute to racial disparities in PCa. A total of 7307 patients diagnosed with PCa from 1989 through 2015 were included. Associations of race and clinicodemographic characteristics were analyzed using chi‐square for categorical and Mann–Whitney U‐test for continuous variables. Racial differences in prostate cancer outcomes were analyzed using competing risk analysis methods of Fine and Gray. Median follow‐up time was 106 months. There were 2304 deaths recorded, of which 432 resulted from PCa. AAM were more likely to be diagnosed at an earlier age (median 60 vs. 65 years, P = 60 years), racial differences in PCSM were more pronounced, with AAM experiencing higher rates of PCSM (HR, 2.05, 95% CI, 1.26–3.34, P = 0.003). After adjustment of clinicodemographic and potential risk factors, AAM continue to experience an increased risk of mortality from PCa, especially older AAM. Furthermore, AAM are more likely to be diagnosed at an early age and more likely to have higher comorbidity indices.

In 2021, approximately 248,530 new prostate cancer (PCa) cases are estimated in the United States. Hispanic/Latinos (H/L) are the second largest racial/ethnic group in the US. The objective of this study was to assess DNA methylation patterns between aggressive and indolent PCa along with ancestry proportions in 49 H/L men from Puerto Rico (PR). Prostate tumors were classified as aggressive (n = 17) and indolent (n = 32) based on the Gleason score. Genomic DNA samples were extracted by macro-dissection. DNA methylation patterns were assessed using the Illumina EPIC DNA methylation platform. We used ADMIXTURE to estimate global ancestry proportions. We identified 892 differentially methylated genes in prostate tumor tissues as compared with normal tissues. Based on an epigenetic clock model, we observed that the total number of stem cell divisions (TNSC) and stem cell division rate (SCDR) were significantly higher in tumor than adjacent normal tissues. Regarding PCa aggressiveness, 141 differentially methylated genes were identified. Ancestry proportions of PR men were estimated as African, European, and Indigenous American; these were 24.1%, 64.2%, and 11.7%, respectively. The identification of DNA methylation profiles associated with risk and aggressiveness of PCa in PR H/L men will shed light on potential mechanisms contributing to PCa disparities in PR population.

In 2020, approximately 191,930 new prostate cancer (PCa) cases are estimated in the United States (US). Hispanic/Latinos (H/L) are the second largest racial/ethnic group in the US. This study aims to assess methylation patterns between aggressive and indolent PCa including DNA repair genes along with ancestry proportions. Prostate tumors classified as aggressive (n = 11) and indolent (n = 13) on the basis of the Gleason score were collected. Tumor and adjacent normal tissue were annotated on H&E (Haemotoxylin and Eosin) slides and extracted by macro-dissection. Methylation patterns were assessed using the Illumina 850K DNA methylation platform. Raw data were processed using the Bioconductor package. Global ancestry proportions were estimated using ADMIXTURE (k = 3). One hundred eight genes including AOX1 were differentially methylated in tumor samples. Regarding the PCa aggressiveness, six hypermethylated genes (RREB1, FAM71F2, JMJD1C, COL5A3, RAE1, and GABRQ) and 11 hypomethylated genes (COL9A2, FAM179A, SLC17A2, PDE10A, PLEKHS1, TNNI2, OR51A4, RNF169, SPNS2, ADAMTSL5, and CYP4F12) were identified. Two significant differentially methylated DNA repair genes, JMJD1C and RNF169, were found. Ancestry proportion results for African, European, and Indigenous American were 24.1%, 64.2%, and 11.7%, respectively. The identification of DNA methylation patterns related to PCa in H/L men along with specific patterns related to aggressiveness and DNA repair constitutes a pivotal effort for the understanding of PCa in this population.

MicroRNAs (miRNAs) have been found to be dysregulated in prostate cancer (PCa). In this study, we investigated if miR-1207-3p is capable of distinguishing between indolent and aggressive PCa and if it contributes to explaining the disproportionate aggressiveness of PCa in men of African ancestry (moAA). A total of 404 patients with primary adenocarcinoma of the prostate were recruited between 1988 and 2003 at the Moffitt Cancer Center, Tampa, FL, USA. Patient clinicopathological features and demographic characteristics such as race were identified. RNA samples from 404 postprostatectomy prostate tumor tissue samples were analyzed by real-time quantitative reverse transcription polymerase chain reaction for the mRNA expression of miR-1207-3p. miR-1207-3p expression in PCa that resulted in overall death or PCa-specific death is significantly higher than in PCa cases that did not. The same positive correlation holds true for other clinical characteristics such as biochemical recurrence, Gleason score, clinical stage, and prostate-specific antigen level. Furthermore, miR-1207-3p expression was significantly less in moAA in comparison to Caucasian men. We also evaluated whether miR-1207-3p is associated with clinical outcomes adjusted for age at diagnosis and tumor stage in the modeling. Using competing risk regression, the PCa patients with a high miR-1207-3p expression (≥6 vs 3) had a high risk to develop PCa recurrence (hazard rate = 2.5, P < .001) adjusting for age at diagnosis and tumor stage. In conclusion, miR-1207-3p is a promising novel prognostic biomarker for PCa. Furthermore, miR-1207-3p may also be important in explaining the disproportionate aggressiveness of PCa in moAA.

Over one hundred loci have been identified to be associated with the familial risk of prostate cancer but the functional effects are poorly understood. Here the authors use single-nucleotide variant and epigentic data to show an underlying genetic architecture marked by histone modification.

Disparities between African American and Caucasian men in prostate cancer (PCa) diagnosis and treatment in the United States have been well established, with significant racial disparities documented at all stages of PCa management, from differences in the type of treatment offered to progression-free survival or death. These disparities appear to be complex in nature, involving biological determinants as well as socioeconomic and cultural aspects. We present a review of the literature on racial disparities in the diagnosis of PCa, treatment, survival, and genetic susceptibility. Significant differences were found among African Americans and whites in the incidence and mortality rates; namely, African Americans are diagnosed with PCa at younger ages than whites and usually with more advanced stages of the disease, and also undergo prostate-specific antigen testing less frequently. However, the determinants of the high rate of incidence and aggressiveness of PCa in African Americans remain unresolved. This pattern can be attributed to socioeconomic status, detection occurring at advanced stages of the disease, biological aggressiveness, family history, and differences in genetic susceptibility. Another risk factor for PCa is obesity. We found many discrepancies regarding treatment, including a tendency for more African American patients to be in watchful waiting than whites. Many factors are responsible for the higher incidence and mortality rates in African Americans. Better screening, improved access to health insurance and clinics, and more homogeneous forms of treatment will contribute to the reduction of disparities between African Americans and white men in PCa incidence and mortality.

Although the causes of prostate cancer are largely unknown, previous studies support the role of genetic factors in the development of prostate cancer. CHEK2 plays a critical role in DNA replication by responding to double-stranded breaks. In this review, we provide an overview of the current knowledge of the role of a genetic variant, 1100delC, of CHEK2 on prostate cancer risk and discuss the implication for potential translation of this knowledge into clinical practice. Currently, twelve articles that discussed CHEK2∗1100delC and its association with prostate cancer were identified. Of the twelve prostate cancer studies, five studies had independent data to draw conclusive evidence from. The pooled results of OR and 95% CI were 1.98 (1.23–3.18) for unselected cases and 3.39 (1.78–6.47) for familial cases, indicating that CHEK2∗1100delC mutation is associated with increased risk of prostate cancer. Screening for CHEK2∗1100delC should be considered in men with a familial history of prostate cancer.

Background. Molecular markers for prostate cancer (PCa) risks are currently lacking. Here we address the potential association of a dinucleotide polymorphism (DNP) in exon 2 of the p73 gene with PCa risk/progression and discern any disruption of p73 protein isoforms levels in cells harboring a p73 DNP allele. Methods. We investigated the association between p73 DNP genotype and PCa risk/aggressiveness and survival by fitting logistic regression models in 1,292 incident cases and 682 controls. Results. Although we detected no association between p73 DNP and PCa risk, a significant inverse relationship between p73 DNP and PCa aggressiveness (AT/AT + GC/AT versus GC/GC, OR = 0.55, 95%Cl = 0.31–0.99) was detected. Also, p73 DNP is marginally associated with overall death (dominant model, HR = 0.76, 95%Cl = 0.57–1.00, P=0.053) as well as PCa specific death (HR = 0.69, 95%Cl = 0.45–1.06, P=0.09). Western blot analyses for p73 protein isoforms indicate that cells heterozygous for the p73 DNP have lower levels of ∆Np73 relative to TAp73 (P

Prostate cancer (CaP) is the leading cancer among men of African descent in the USA, Caribbean, and Sub-Saharan Africa (SSA). The estimated number of CaP deaths in SSA during 2008 was more than five times that among African Americans and is expected to double in Africa by 2030. We summarize publicly available CaP data and collected data from the men of African descent and Carcinoma of the Prostate (MADCaP) Consortium and the African Caribbean Cancer Consortium (AC3) to evaluate CaP incidence and mortality in men of African descent worldwide. CaP incidence and mortality are highest in men of African descent in the USA and the Caribbean. Tumor stage and grade were highest in SSA. We report a higher proportion of T1 stage prostate tumors in countries with greater percent gross domestic product spent on health care and physicians per 100,000 persons. We also observed that regions with a higher proportion of advanced tumors reported lower mortality rates. This finding suggests that CaP is underdiagnosed and/or underreported in SSA men. Nonetheless, CaP incidence and mortality represent a significant public health problem in men of African descent around the world.

Background. Prostate cancer (PCa) racial disparity is multifactorial, involving biological, sociocultural, and lifestyle determinants. We investigated the association between selected potentially functional polymorphisms (SNPs) and prostate cancer (PCa) risk in Black (AAM) and White (EAM) men. We further explored if these associations varied by the body mass index (BMI) and height. Methods. Age-matched DNA samples from 259 AAM and 269 EAM were genotyped for 10 candidate SNPs in 7 genes using the TaqMan allelic differentiation analysis. The dominant, recessive, and additive age-adjusted unconditional logistic regression models were fitted. Results. Three SNPs showed statistically significant associations with PCa risk: in AAM, HNF1B rs7501939 (OR=2.42, P=0.0046) and rs4430796 (OR=0.57, P=0.0383); in EAM, CTBP2 rs4962416 (OR=1.52, P=0.0384). In addition, high BMI in AAM (OR=1.06, P=0.022) and height in EAM (OR=0.92, P=0.0434) showed significant associations. Interestingly, HNF1B rs7501939 was associated with PCa exclusively in obese AAM (OR=2.14, P=0.0103). Conclusion. Our results suggest that variation in the HNF1B may influence PCa risk in obese AAM.