Systematic meta-analyses of gene-specific genetic association studies in prostate cancer

Leveraging Random Effects in Cistrome-Wide Association Studies for Decoding the Genetic Determinants of Prostate Cancer

Cistrome-wide association studies (CWAS) are pivotal for identifying genetic determinants of diseases by correlating genetically regulated cistrome states with phenotypes. Traditional CWAS typically develops a model based on cistrome and genotype data to associate predicted cistrome states with phenotypes. The random effect cistrome-wide association study (RECWAS), reevaluates the necessity of cistrome state prediction in CWAS. RECWAS utilizes either a linear model or marginal effect for initial feature selection, followed by kernel-based feature aggregation for association testing is introduced. Through simulations and analysis of prostate cancer data, a thorough evaluation of CWAS and RECWAS is conducted. The results suggest that RECWAS offers improved power compared to traditional CWAS, identifying additional genomic regions associated with prostate cancer. CWAS identified 102 significant regions, while RECWAS found 50 additional significant regions compared to CWAS, many of which are validated. Validation encompassed a range of biological evidence, including risk signals from the GWAS catalog, susceptibility genes from the DisGeNET database, and enhancer-domain scores. RECWAS consistently demonstrated improved performance over traditional CWAS in identifying genomic regions associated with prostate cancer. These findings demonstrate the benefits of incorporating kernel methods into CWAS and provide new insights for genetic discovery in complex diseases.

Genetic variants of antioxidant and xenobiotic metabolizing enzymes and their association with prostate cancer: A meta-analysis and functional in silico analysis

The development and progression of prostate cancer (PCa) depends on complex interactions between genetic, environmental and dietary factors that modulate the carcinogenesis process. Interactions between chemical exposures and genetic polymorphisms in genes encoding xenobiotic metabolizing enzymes (XME), antioxidant enzymes and DNA repair enzymes have been reported as the main drivers of cancer. Thus, a better understanding of the causal risk factors for PCa will provide avenues to identify men at increased risk and will contribute to develop effective detection and prevention methods. We performed a meta-analysis on 17,518 cases and 42,507 controls obtained from 42 studies to determine whether seven SNPs and one CNV pertaining to oxidative stress, xenobiotic detoxification and DNA repair enzymes are associated with the risk of PCa (GPX1 (rs1050450), XRCC1 (rs25487), PON1 (rs662), SOD2 (rs4880), CAT (rs1001179), GSTP1 (rs1695) and CNV GSTM1). A significant increased risk of PCa was found for SOD2 (rs4880) ORGG+GA vs. AA 1.08; 95%CI 1.01-1.15, CAT (rs1001179) ORTT vs. TC+CC 1.39; 95%CI 1.17-1.66, PON1 (rs662) ORCT vs. CC+TT 1.17; 95%CI 1.01-1.35, GSTP1 (rs1695) ORGG vs. GA+AA 1.20; 95%CI 1.05-1.38 and GSTM1 (dual null vs. functional genotype) ORN vs. NN1+NN2 1.34; 95%CI 1.10-1.64. The meta-analysis showed that the CNV GSTM1, and the SNPs GSTP1 (rs1695) and CAT (rs1001179) are strongly associated with a greater risk of PCa and, to a lesser extent, the genetic variants SOD2 (rs4880) and PON1 (rs662). Although several antioxidant enzymes and XME play an important role in the PCa development, other risk factors such as chemical exposures should also be considered to gain insight on PCa risk. The functional in silico analysis showed that the genetic variants studied had no clinical implication regarding malignancy, except for GPX1 (rs1050450) SNP.

Novel prostate cancer susceptibility gene SP6 predisposes patients to aggressive disease

Prostate cancer (PrCa) is one of the most common cancers in men, but little is known about factors affecting its clinical outcomes. Genome-wide association studies have identified more than 170 germline susceptibility loci, but most of them are not associated with aggressive disease. We performed a genome-wide analysis of 185,478 SNPs in Finnish samples (2738 cases, 2400 controls) from the international Collaborative Oncological Gene-Environment Study (iCOGS) to find underlying PrCa risk variants. We identified a total of 21 common, low-penetrance susceptibility loci, including 10 novel variants independently associated with PrCa risk. Novel risk loci were located in the 8q24 (CASC8 rs16902147, OR 1.86, padj = 3.53 × 10-8 and rs58809953, OR 1.71, padj = 4.00 × 10-6; intergenic rs79012498, OR 1.81, padj = 4.26 × 10-8), 17q21 (SP6 rs2074187, OR 1.66, padj = 3.75 × 10-5), 11q13 (rs12795301, OR 1.42, padj = 2.89 × 10-5) and 8p21 (rs995432, OR 1.38, padj = 3.00 × 10-11) regions. Here, we describe SP6, a transcription factor gene, as a new, potentially high-risk gene for PrCa. The intronic variant rs2074187 in SP6 was associated not only with overall susceptibility to PrCa (OR 1.66) but also with a higher odds ratio for aggressive PrCa (OR 1.89) and lower odds for non-aggressive PrCa (OR 1.43). Furthermore, the new intergenic variant rs79012498 at 8q24 conferred risk for aggressive PrCa. Our findings highlighted the power of a population-stratified approach to identify novel, clinically actionable germline PrCa risk loci and strongly suggested SP6 as a new PrCa candidate gene that may be involved in the pathogenesis of PrCa.

The protein inputs of an ultra-predictive aging clock represent viable anti-aging drug targets

Machine learning models capable of predicting age given a set of inputs are referred to as aging clocks. We recently developed an aging clock that utilizes 491 plasma protein inputs, has an exceptional accuracy, and is capable of measuring biological age. Here, we demonstrate that this clock is extremely predictive (r = 0.95) when used to measure age in a novel plasma proteomic dataset derived from 370 human subjects aged 18-69 years. Over-representation analyses of the proteins that make up this clock in the Gene Ontology and Reactome databases predominantly implicated innate and adaptive immune system processes. Immunological drugs and various age-related diseases were enriched in the DrugBank and GLAD4U databases. By performing an extensive literature review, we find that at least 269 (54.8 %) of these inputs regulate lifespan and/or induce changes relevant to age-related disease when manipulated in an animal model. We also show that, in a large plasma proteomic dataset, the majority (57.2 %) of measurable clock proteins significantly change their expression level with human age. Different subsets of proteins were overlapped with distinct epigenetic, transcriptomic, and proteomic aging clocks. These findings indicate that the inputs of this age predictor likely represent a rich source of anti-aging drug targets.

Genetic variations in microRNA-binding sites of solute carrier transporter genes as predictors of clinical outcome in colorectal cancer

One of the principal mechanisms of chemotherapy resistance in highly frequent solid tumors, such as colorectal cancer (CRC), is the decreased activity of drug transport into tumor cells due to low expression of important membrane proteins, such as solute carrier (SLC) transporters. Sequence complementarity is a major determinant for target gene recognition by microRNAs (miRNAs). Single-nucleotide polymorphisms (SNPs) in target sequences transcribed into messenger RNA may therefore alter miRNA binding to these regions by either creating a new site or destroying an existing one. miRSNPs may explain the modulation of expression levels in association with increased/decreased susceptibility to common diseases as well as in chemoresistance and the consequent inter-individual variability in drug response. In the present study, we investigated whether miRSNPs in SLC transporter genes may modulate CRC susceptibility and patient's survival. Using an in silico approach for functional predictions, we analyzed 26 miRSNPs in 9 SLC genes in a cohort of 1368 CRC cases and 698 controls from the Czech Republic. After correcting for multiple tests, we found several miRSNPs significantly associated with patient's survival. SNPs in SLCO3A1, SLC22A2 and SLC22A3 genes were defined as prognostic factors in the classification and regression tree analysis. In contrast, we did not observe any significant association between miRSNPs and CRC risk. To the best of our knowledge, this is the first study investigating miRSNPs potentially affecting miRNA binding to SLC transporter genes and their impact on CRC susceptibility or patient's prognosis.

The mechanism of activation of the actin binding protein EHBP1 by Rab8 family members

EHBP1 is an adaptor protein that regulates vesicular trafficking by recruiting Rab8 family members and Eps15-homology domain-containing proteins 1/2 (EHD1/2). It also links endosomes to the actin cytoskeleton. However, the underlying molecular mechanism of activation of EHBP1 actin-binding activity is unclear. Here, we show that both termini of EHBP1 have membrane targeting potential. EHBP1 associates with PI(3)P, PI(5)P, and phosphatidylserine via its N-terminal C2 domain. We show that in the absence of Rab8 family members, the C-terminal bivalent Mical/EHBP Rab binding (bMERB) domain forms an intramolecular complex with its central calponin homology (CH) domain and auto-inhibits actin binding. Rab8 binding to the bMERB domain relieves this inhibition. We have analyzed the CH:bMERB auto-inhibited complex and the active bMERB:Rab8 complex biochemically and structurally. Together with structure-based mutational studies, this explains how binding of Rab8 frees the CH domain and allows it to interact with the actin cytoskeleton, leading to membrane tubulation.

EHBP1 is an adaptor protein that regulates vesicular trafficking and links endosomes to the actin cytoskeleton. Here, authors show that both termini of EHBP1 have membrane targeting potential and that in the absence of its binding partner Rab8, the bMERB and CH domain of EHBP1 form an intramolecular complex which auto-inhibits actin binding.

The microbiome and cancer for clinicians

The human microbiome is an emerging target in cancer development and therapeutics. It may be directly oncogenic, through promotion of mucosal inflammation or systemic dysregulation, or may alter anti-cancer immunity/therapy. Microorganisms within, adjacent to and distant from tumors may affect cancer progression, and interactions and differences between these populations can influence the course of disease. Here we review the microbiome as it pertains to cancer for clinicians. The microbiota of cancers including colorectal, pancreas, breast and prostate are discussed. We examine "omics" technologies, microbiota associated with tumor tissue and tumor-site fluids such as feces and urine, as well as indirect effects of the gut microbiome. We describe roles of the microbiome in immunotherapy, and how it can be modulated to improve cancer therapeutics. While research is still at an early stage, there is potential to exploit the microbiome, as modulation may increase efficacy of treatments, reduce toxicities and prevent carcinogenesis.

Unraveling the Function of Lemur Tyrosine Kinase 2 Network

Lemur Tyrosine Kinase 2 (LMTK2) is a recently cloned transmembrane protein, actually a serine/threonine kinase named after the Madagascar primate lemur due to the long intracellular C-terminal tail. LMTK2 is relatively little known, compared to other kinases but its role has been increasingly recognized. Published data show that LMTK2 regulates key cellular events, including endocytic trafficking, nerve growth factor signaling, apoptosis, and Cl^- transport. Abnormalities in the expression and function of LMTK2 are associated with human disease, such as neurodegeneration, cancer and infertility. We summarized the current state of knowledge on LMTK2 structure, regulation, interactome, intracellular localization, and tissue expression and point out future research directions to better understand the role of LMTK2.

Association Between the Asp312Asn, Lys751Gln, and Arg156Arg Polymorphisms in XPD and the Risk of Prostate Cancer

Prostate cancer is the most common solid cancer and genetic factors play important roles in its pathogenesis. XPD is one of the 8 core genes involved in the nucleotide excision repair pathway. The relationship between Asp312Asn, Lys751Gln, and Arg156Arg polymorphisms in XPD and prostate cancer risk is a controversial topic. Therefore, we conducted a meta-analysis to explore the relationship between these 3 polymorphisms and the risk of developing prostate cancer. We searched the electronic literature in PubMed and Google Scholar for all relevant studies (last updated January 1, 2017). The pooled odds ratios and 95% confidence intervals for the associations between the Asp312Asn, Lys751Gln, or Arg156Arg polymorphisms in XPD and prostate cancer risk were calculated. To evaluate the effects of specific study characteristics on the association of these 3 polymorphisms and prostate cancer risk, we performed subgroup analysis if 2 or more studies were available. After an extensive literature review, 7 publications regarding Asp312Asn genotype distribution with 8 case–controls, 9 publications regarding Lys751Gln genotype distribution with 10 case–controls, and 3 publications regarding Arg156Arg genotype distribution with 4 case–controls were selected. The results showed that Asp312Asn (odds ratio = 1.34, 95% confidence interval: 0.96-1.87, P = .000), Lys751Gln (odds ratio = 0.98, 95% confidence interval: 0.89-1.08, P = .986), and Arg156Arg (odds ratio = 1.05, 95% confidence interval: 0.91-1.22, P = .57) polymorphisms do not increase the risk of prostate cancer in the dominant model. Further, in the subgroup analysis by ethnicity, no relationships were observed between Lys751Gln and Arg156Arg polymorphisms and prostate cancer risk. However, stratified analysis by ethnicity revealed that Asp312Asn affects African (odds ratio = 1.57, 95% confidence interval: 1.06-2.33, P = .382) and Asian populations (odds ratio = 2.09, 95% confidence interval: 1.39-3.14, P = .396) in homozygote comparison. In conclusion, this meta-analysis suggests that there is no general association between the Asp312Asn, Lys751Gln, and Arg156Arg polymorphisms in XPD and prostate cancer susceptibility.

A spatiotemporal hypothesis for the regulation, role, and targeting of AMPK in prostate cancer

The 5'-AMP-activated protein kinase (AMPK) is a master regulator of cellular homeostasis. Despite AMPK's known function in physiology, its role in pathological processes such as prostate cancer is enigmatic. However, emerging evidence is now beginning to decode the paradoxical role of AMPK in cancer and, therefore, inform clinicians if - and how - AMPK could be therapeutically targeted. Spatiotemporal regulation of AMPK complexes could be one of the mechanisms that governs this kinase's role in cancer. We hypothesize that different upstream stimuli will activate select subcellular AMPK complexes. This hypothesis is supported by the distinct subcellular locations of the various AMPK subunits. Each of these unique AMPK complexes regulates discrete downstream processes that can be tumour suppressive or oncogenic. AMPK's final biological output is then determined by the weighted net function of these downstream signalling events, influenced by additional prostate-specific signalling.

Genetic risk factors for ovarian cancer and their role for endometriosis risk

OBJECTIVE

Several genetic variants have been validated as risk factors for ovarian cancer. Endometriosis has also been described as a risk factor for ovarian cancer. Identifying genetic risk factors that are common to the two diseases might help improve our understanding of the molecular pathogenesis potentially linking the two conditions.

METHODS

In a hospital-based case-control analysis, 12 single nucleotide polymorphisms (SNPs), validated by the Ovarian Cancer Association Consortium (OCAC) and the Collaborative Oncological Gene-environment Study (COGS) project, were genotyped using TaqMan® OpenArray™ analysis. The cases consisted of patients with endometriosis, and the controls were healthy individuals without endometriosis. A total of 385 cases and 484 controls were analyzed. Odds ratios and P values were obtained using simple logistic regression models, as well as from multiple logistic regression models with adjustment for clinical predictors.

RESULTS

rs11651755 in HNF1B was found to be associated with endometriosis in this case-control study. The OR was 0.66 (95% CI, 0.51 to 0.84) and the P value after correction for multiple testing was 0.01. None of the other genotypes was associated with a risk for endometriosis.

CONCLUSIONS

As rs11651755 in HNF1B modified both the ovarian cancer risk and also the risk for endometriosis, HNF1B may be causally involved in the pathogenetic pathway leading from endometriosis to ovarian cancer.