In silico functional pathway annotation of 86 established prostate cancer risk variants

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.

Overexpression of GATA5 Inhibits Prostate Cancer Progression by Regulating PLAGL2 via the FAK/PI3K/AKT Pathway

Simple Summary

Prostate cancer (PCa) has the highest incidence of malignant tumors and is the second-ranked tumor-causing death of men. GATA binding protein 5 (GATA5) belongs to the GATA gene family and we found that GATA5 was downregulated in PCa tissues, but the function of GATA5 in PCa remains elusive. We found overexpression GATA5 inhibited tumor proliferation, migration, invasion and the process of epithelial–mesenchymal transition (EMT), and upregulation of GATA5 promoted PCa cell apoptosis. In addition, we disclosed that GATA5 could interact with pleomorphic adenoma gene-like-2 (PLAGL2) to regulate PCa cell growth via FAK/PI3K/AKT signaling pathway. Hence, these findings suggested that GATA5 could serve as a new therapeutic target in the future.

Abstract

Background: Prostate cancer (PCa) is a malignancy with high incidence and the principal cause of cancer deaths in men. GATA binding protein 5 (GATA5) belongs to the GATA gene family. GATA5 has a close association with carcinogenesis, but the role of GATA5 in PCa remains poorly understood. The aim of our present study was to probe into the effect of GATA5 on PCa progression and to elucidate the involved mechanism. Methods: The expression of GATA5 was detected in both PCa samples and PCa cell lines. GATA5 overexpression, PLAGL2 knockdown, and overexpression cell models were generated, then Western blotting experiments were utilized to validate the efficiency of transfection. The effects of GATA5 on PCa cell proliferation, metastasis, apoptosis, cell cycle progression, and EMT were detected in vitro or in vivo. Furthermore, the mechanism by which GATA5 inhibits prostate cancer progression through regulating PLAGL2 via the FAK/PI3K/AKT pathway was also explored. Results: GATA5 expression was downregulated in PCa samples and cell lines. GATA5 overexpression inhibited PCa cell proliferation and metastasis but increased the rate of apoptosis. In addition, we confirmed that GATA5 inhibited prostate cancer progression, including EMT, by regulating PLAGL2 via the FAK/PI3K/AKT pathway. Conclusion: We demonstrated that GATA5, as a tumor suppressor in PCa, inhibits PCa progression by regulating PLAGL2. These results showed that the GATA5/PLAGL2/FAK/PI3K/AKT pathway may become a new therapeutic direction for the treatment of PCa.

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.

Innovative strategies for annotating the "relationSNP" between variants and molecular phenotypes

Characterizing how variation at the level of individual nucleotides contributes to traits and diseases has been an area of growing interest since the completion of sequencing the first human genome. Our understanding of how a single nucleotide polymorphism (SNP) leads to a pathogenic phenotype on a genome-wide scale is a fruitful endeavor for anyone interested in developing diagnostic tests, therapeutics, or simply wanting to understand the etiology of a disease or trait. To this end, many datasets and algorithms have been developed as resources/tools to annotate SNPs. One of the most common practices is to annotate coding SNPs that affect the protein sequence. Synonymous variants are often grouped as one type of variant, however there are in fact many tools available to dissect their effects on gene expression. More recently, large consortiums like ENCODE and GTEx have made it possible to annotate non-coding regions. Although annotating variants is a common technique among human geneticists, the constant advances in tools and biology surrounding SNPs requires an updated summary of what is known and the trajectory of the field. This review will discuss the history behind SNP annotation, commonly used tools, and newer strategies for SNP annotation. Additionally, we will comment on the caveats that distinguish approaches from one another, along with gaps in the current state of knowledge, and potential future directions. We do not intend for this to be a comprehensive review for any specific area of SNP annotation, but rather it will be an excellent resource for those unfamiliar with computational tools used to functionally characterize SNPs. In summary, this review will help illustrate how each SNP annotation method impacts the way in which the genetic and molecular etiology of a disease is explored in-silico.

Post-GWAS in prostate cancer: from genetic association to biological contribution

Genome-wide association studies (GWAS) have been successful in deciphering the genetic component of predisposition to many human complex diseases including prostate cancer. Germline variants identified by GWAS progressively unravelled the substantial knowledge gap concerning prostate cancer heritability. With the beginning of the post-GWAS era, more and more studies reveal that, in addition to their value as risk markers, germline variants can exert active roles in prostate oncogenesis. Consequently, current research efforts focus on exploring the biological mechanisms underlying specific susceptibility loci known as causal variants by applying novel and precise analytical methods to available GWAS data. Results obtained from these post-GWAS analyses have highlighted the potential of exploiting prostate cancer risk-associated germline variants to identify new gene networks and signalling pathways involved in prostate tumorigenesis. In this Review, we describe the molecular basis of several important prostate cancer-causal variants with an emphasis on using post-GWAS analysis to gain insight into cancer aetiology. In addition to discussing the current status of post-GWAS studies, we also summarize the main molecular mechanisms of potential causal variants at prostate cancer risk loci and explore the major challenges in moving from association to functional studies and their implication in clinical translation.

Predictive single nucleotide polymorphism markers for acute oral mucositis in patients with nasopharyngeal carcinoma treated with radiotherapy

The aim of this study was to investigate the association between the susceptibility of severe oral mucositis (OM) in Chinese nasopharyngeal carcinoma (NPC) patients treated with radiotherapy and single nucleotide polymorphisms (SNPs) across the whole genome. SNPs were screened in a total of 24 patients with NPC and an additional 6 were subjected to mRNA expression analysis. Patients were subdivided into CTC 0-2 (CTC toxicity grade 0, 1, and 2) and CTC 3+ (CTC toxicity grade 3 and above) groups according to their CTC (common toxicity criteria) scores. The GTEx dataset was used to performed eQTL analyses and in-vitro functional assays were performed for eQTL-associated genes. Our data identified 7 functional SNPs associated with the development of OM. We observed that rs11081899-A, located in the 5′-UTR of the ZNF24 gene, was significantly correlated with a higher risk of severe mucositis (OR = 14.631, 95% CI = 2.61-105.46, p = 1.2 × 10⁻⁴), and positively associated with ZNF24 mRNA expression (p = 4.1 × 10⁻⁶) from GTEx dataset. In addition, high ZNF24 mRNA expression was associated with severe OM in patients with NPC (p = 0.02). Further functional assays revealed that ZNF24 knockdown reduced p65 expression and suppressed TNF-α-induced NF-κB activation and pro-inflammatory cytokines release. These findings suggested that rs11081899-A may be a genetic susceptibility factor for radiation-induced OM in patients with NPC, although its value in clinical application needs to be further verified in a large cohort. Also, we suggested that downregulation of ZNF24 may attenuate the development of mucositis by suppressing NF-κB activation.

Downstream targets of GWAS-detected genes for breast, lung, and prostate and colon cancer converge to G1/S transition pathway

Genome-wide association studies (GWASs) identified over 500 single nucleotide polymorphisms (SNPs) influencing cancer risk. It is logical to expect the cancer-associated genes to cluster in pathways directly involved in carcinogenesis, e.g. cell cycle. Nevertheless, analyses of the GWAS-detected cancer risk genes usually show no or weak enrichment by known cancer genes.We hypothesized that GWAS-detected cancer risk-associated genes function as upstream regulators of the genes directly involved in carcinogenesis. We have analyzed four common cancers: breast, colon, lung, and prostate. To identify downstream targets of GWAS-detected cancer risk genes we used MedScan, which is a text mining tool offered by PathwayStudio. We also used data on protein/protein interactions reported by BioGRID database. Among all identified targets we have selected common downstream targets. A gene was considered a common downstream target if it was a downstream target for at least three GWAS-detected genes for a given cancer type. Common downstream targets were identified separately for each cancer type. We found that common downstream targets for all four cancer types were enriched by cell cycle genes, more specifically, the genes involved in G1/S transition. Common downstream targets for bipolar disorder, Crohn's disease, and type 2 diabetes did not show G1/S transition enrichment.The results of this analysis suggest that many cancer risk genes function as upstream regulators of the genes directly involved in G1/S transition and exert their risk effects by reducing threshold for G1/S transition, elevating the background level of cell proliferation and cancer risk.

Functional genomics of candidate genes derived from genome-wide association studies for five common neurological diseases

AIM

Recent genome-wide association studies (GWAS) are identifying novel candidate genes for several neurological diseases (NDs). However, a global functional analysis of those genes derived from GWAS for NDs is missing. We explored the genomic and functional features of novel candidate genes for five common NDs: Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, stroke and migraine.

MATERIALS AND METHODS

A functional enrichment analysis was performed for GWAS-derived genes, for categories such as Kyoto Encyclopedia of Genes and Genomes pathways, gene expression, InterPro domains, transcription factor binding sites, gene ontology (GO) terms and microRNA (miRNA) targets. An analysis of protein-protein interactions was carried out.

RESULTS

Six hundred and forty-two unique single nucleotide polymorphisms (SNPs) were identified for the five NDs and 2.3% of them were non-synonymous SNPs. There were no common SNPs for all five NDs and eight genes were associated with more than one ND. The enrichment analysis showed significant values for several GO categories, such as cell-cell adhesion and location in neurites and for expression in prefrontal cortex. An analysis of protein-protein interactions showed the evidence of a large component. Fifty-one of these GWAS-derived genes are known to be potentially druggable and twelve are known to harbor mutations for neuropsychiatric disorders.

CONCLUSIONS

Our results suggest that there is little overlap between the genes identified in GWAS for the five common NDs. Identification of functional categories in the GWAS-derived candidate genes for common NDs could lead to a better understanding of their functional consequences and could be useful for the future discovery of additional genetic risk factors for those diseases.