Comprehensive functional annotation of 77 prostate cancer risk loci

Long Non-Coding RNA PCAT19 Suppresses Cell Proliferation and Angiogenesis in Coronary Artery Disease through Interaction with GCNT2

LncRNAs involvement in heart disease, however, the effect of lncRNA prostate cancer-associated transcript 19 (PCAT19) in coronary artery disease (CAD) remains unclear. In the current study, we aimed to verify the role of PCAT19 in CAD. We first investigated the differentially expressed lncRNAs in different Genes Expression Omnibus (GEO) database. We then detected lncRNAs expression in healthy volunteers and acute myocardial infarction (AMI) patients by qRT‑PCR. The correlation of PCAT19 and Glucosaminyl (N-Acetyl) Transferase 2 (GCNT2) was analyzed. Human coronary artery endothelial cells (HCAECs) was used to conduct cell hypoxia-reoxygenation (H/R) injury model to imitate AMI injury. CCK8, BrdU, tube formation assay were used to detect cell viability, proliferation, and angiogenesis. Immunofluorescence, western blotting were used to detect ki67, VEGFA, PCNA, CD31, and GCNT2 expression, respectively. We obtained six different lncRNAs from GEO database and identified PCAT19 high expression in AMI patients. PCAT19 was positive correlation to GCNT2. Further experiments presented that PCAT19 knockdown promoted cell viability, proliferation and angiogenesis, GCNT2 knockdown also promoted cell viability, proliferation, and angiogenesis. These results confirmed by the inhibition of Ki67 and VEGFA. Importantly, PCAT19 overexpression suppressed cell proliferation and angiogenesis, these results also confirmed by the inhibition of PCNA and CD31. However, the inhibitory effect of PCAT19 overexpression was reversed by GCNT2 knockdown. Our study indicated that PCAT19 plays an important role in the CAD disease, its effects was related to GCNT2. Our research provides a novel sight for the effect of PCAT19 on CAD.

Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions

To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5 × 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (p value <10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study.

Construction of lncRNA/Pseudogene-miRNA Network Based on In Silico Approaches for Glycolysis Pathway to Identify Prostate Adenocarcinoma-Related Potential Biomarkers

LncRNAs, pseudogenes, and miRNAs participate a fundamental function in tumorigenesis, metabolism, and invasion of cancer cells, although their regulation of tumor glycolysis in prostate adenocarcinoma (PRAD) is thoroughly not well studied. In this study, we applied transcriptomic, proteomic, and medical information to identify glycolysis-related key genes and modules associated with PRAD. Then, the glycolysis-related lncRNA/lncRNAs/pseudogenes-miRNA-mRNA network was constructed. Analysis of DNA methylation status and expression data determined a DNA methylation-dysregulated three-DE-mRNAs signature for predicting diagnosis, ANGPTL4, GNE, and HSPA in PRAD patients and healthy control. Several lncRNAs/pseudogenes, significantly correlated with the overall survival PVT1, CA5BP1, MIRLET7BHG, SNHG12, and ZNF37BP and disease-free survival status, MALAT1, GUSBP11, MIRLET7BHG, and SNHG1, of patients with PRAD were determined. The methylation profile of DE-lncRNA/pseudogenes was significantly proper for predicting PRAD prognostic model. The transcription level of 6 DE-mRNA ANGPTL4, QSOX1, BIK, CLDN3, DDIT4, and TFF3 was correlated with cancer-related fibroblast infiltration in PRAD. The mutated form of 7 mRNAs, COL5A1, IDH1, HK2, DDIT4, GNE, and QSOX1, was associated with PRAD. In addition to the glycolysis pathway, DE-RNAs play regulatory roles on several pathways, including DNA damage, RTK, cell cycle, RAS/MAPK, TSC/mTOR and PI3K/AKT, AR hormone, and EMT. Overall, our study improves our knowledge of the relation between lncRNAs/pseudogenes and miRNA related to glycolysis and PRAD pathogenesis.

Parkinson's disease risk enhancers in microglia

Genome-wide association studies have identified thousands of single nucleotide polymorphisms that associate with increased risk for Parkinson's disease (PD), but the functions of most of them are unknown. Using assay for transposase-accessible chromatin (ATAC) and H3K27ac chromatin immunoprecipitation (ChIP) sequencing data, we identified 73 regulatory elements in microglia that overlap PD risk SNPs. To determine the target genes of a "risk enhancer" within intron two of SNCA, we used CRISPR-Cas9 to delete the open chromatin region where two PD risk SNPs reside. The loss of the enhancer led to reduced expression of multiple genes including SNCA and the adjacent gene MMRN1. It also led to expression changes of genes involved in glucose metabolism, a process that is known to be altered in PD patients. Our work expands the role of SNCA in PD and provides a connection between PD-associated genetic variants and underlying biology that points to a risk mechanism in microglia.

Transcriptomics analysis reveals distinct mechanism of breast cancer stem cells regulation in mammospheres from MCF-7 and T47D cells

Luminal A breast cancer, constituting 70 % of breast cancer cases, presents a challenge due to the development of resistance and recurrence caused by breast cancer stem cells (BCSC). Luminal breast tumors are characterized by TP53 expression, a tumor suppressor gene involved in maintaining stem cell attributes in cancer. Although a previous study successfully developed mammospheres (MS) from MCF-7 (with wild-type TP53) and T47D (with mutant TP53) luminal breast cancer cells for BCSC enrichment, their transcriptomic profiles remain unclear. We aimed to elucidate the transcriptomic disparities between MS of MCF-7 and T47D cells using bioinformatics analyses of differentially expressed genes (DEGs), including the KEGG pathway, Gene Ontology (GO), drug-gene association, disease-gene association, Gene Set Enrichment Analysis (GSEA), DNA methylation analysis, correlation analysis of DEGs with immune cell infiltration, and association analysis of genes and small-molecule compounds via the Connectivity Map (CMap). Upregulated DEGs were enriched in metabolism-related KEGG pathways, whereas downregulated DEGs were enriched in the MAPK signaling pathway. Drug-gene association analysis revealed that both upregulated and downregulated DEGs were associated with fostamatinib. The KEGG pathway GSEA results indicated that the DEGs were enriched for oxidative phosphorylation, whereas the downregulated DEGs were negatively enriched for the p53 signaling pathway. Examination of DNA methylation revealed a noticeable disparity in the expression patterns of the PKM2, ERO1L, SLC6A6, EPAS1, APLP2, RPL10L, and NEDD4 genes when comparing cohorts with low- and high-risk breast cancer. Furthermore, a significant positive correlation was identified between SLC6A6 expression and macrophage presence, as well as MSN, and AKR1B1 expression and neutrophil and dentritic cell infiltration. CMap analysis unveiled SA-83851 as a potential candidate to counteract the effects of DEGs, specifically in cells harbouring mutant TP53. Further research, including in vitro and in vivo validations, is warranted to develop drugs targeting BCSCs.

Single nucleotide polymorphism within chromosome 8q24 is associated with prostate cancer development in Saudi Arabia

Objective

Genome-wide association studies have demonstrated that single nucleotide polymorphisms (SNPs) are important risk factors for the development of prostate cancer (PCa). Preliminary studies have suggested that the incidence of PCa in Saudi males is low but is probably familial or genetically related.

Methods

To identify any possible association of SNP with PCa development in Saudi patients, we investigated a group of SNPs in Saudi PCa patients (n=85) and compared the outcomes to healthy normal controls (n=115) and nodular hyperplasia patients (n=120). DNA was extracted from paraffin-embedded formalin fixed tissue or whole blood from both patients' groups and healthy control group. A total of thirteen SNPs were genotyped using TaqMan® minor groove binder polymerase chain reaction assay.

Results

The rs16901979A, s629242T and rs1447295A alleles were found at significantly higher frequency in PCa patients than controls (p<0.05). The rs16901979 CA genotype was found at significantly greater frequency in PCa patients than in healthy controls (43% vs. 14%, odds ratio=4.6, p=0.0001) and benign hyperplasia group (43% vs. 25%, odds ratio=2.2, p=0.009).

Conclusion

Our study has highlighted the association of rs16901979 SNP with PCa in Saudi males. Such findings have important implications in the PCa diagnosis and in screening unaffected family members of Saudi patients.

Dissecting transcription of the 8q24-MYC locus in prostate cancer recognizes the equilibration between androgen receptor direct and indirect dual-functions

BACKGROUND

Androgen receptor (AR) activation and repression dual-functionality only became known recently and still remains intriguing in prostate cancer (PCa). MYC is a prominent oncogene that functionally entangles with AR signaling in PCa. Further exploration of AR regulatory mechanisms on MYC gene transcription bears clinical and translation significance.

METHODS

Bioinformatics analysis of PCa cell line and clinical RNA-Seq and ChIP-Seq (chromatin immunoprecipitation-sequencing) datasets to anchor interactions of AR and MYC transcriptional networks. ChIP-qPCR and 3C (chromosome conformation capture) analyses to probe MYC distal regulation by AR binding sites (ABSs). CRISPR/Cas9-mediated genome-editing to specify functions of ABS within the 8q24-MYC locus on androgen-mediated MYC transcription. Global FoxA1 and HoxB13 distribution profiling to advance AR transcriptional mechanisms.

RESULTS

Here we recognize AR bi-directional transcription mechanisms by exploiting the prominent 8q24-MYC locus conferring androgen hyper-sensitivity. At ~ 25 Kb downstream of the MYC gene, we identified an undefined ABS, P10. By chromatin analyses, we validated androgen-dependent spatial interaction between P10 and MYC-Promoter (MYC-Pro) and temporal epigenetic repression of these MYC-proximal elements. We next designed a CRISPR/Cas9-mediated double genomic knock-out (KO) strategy to show that P10-KO slightly lessened androgen-elicited MYC transrepression in LNCaP-AR cells. In similar genomic editing assays, androgen-mediated MYC repression became slightly deepened upon KO of P11, an ABS in the PVT1 gene locus highly enriched in AR-binding motifs and peaks. We also investigated multiple ABSs in the established PCAT1 super-enhancer that distally interacts with MYC-Pro for transactivation, with each KO pool consistently shown to relieve androgen-elicited MYC repression. In the end, we systemically assessed androgen effects in the 8q24-MYC locus and along PCa genome to generalize H3K27ac and BRD4 re-distribution from pioneer factors (FoxA1 and HoxB13) to AR sites.

CONCLUSION

Together, we reconciled these observations by unifying AR dual-functions that are mechanistically coupled to and equilibrated by co-factor redistribution.

Hormone-induced enhancer assembly requires an optimal level of hormone receptor multivalent interactions

Transcription factors (TFs) activate enhancers to drive cell-specific gene programs in response to signals, but our understanding of enhancer assembly during signaling events is incomplete. Here, we show that androgen receptor (AR) forms condensates through multivalent interactions mediated by its N-terminal intrinsically disordered region (IDR) to orchestrate enhancer assembly in response to androgen signaling. AR IDR can be substituted by IDRs from selective proteins for AR condensation capacity and its function on enhancers. Expansion of the poly(Q) track within AR IDR results in a higher AR condensation propensity as measured by multiple methods, including live-cell single-molecule microscopy. Either weakening or strengthening AR condensation propensity impairs its heterotypic multivalent interactions with other enhancer components and diminishes its transcriptional activity. Our work reveals the requirement of an optimal level of AR condensation in mediating enhancer assembly and suggests that alteration of the fine-tuned multivalent IDR-IDR interactions might underlie AR-related human pathologies.

Associations of CTCF and FOXA1 with androgen and IGF pathways in men with localized prostate cancer

AIMS

To examine associations between the transcription factors CCCTC-binding factor (CTCF) and forkhead box protein A1 (FOXA1) and the androgen receptor (AR) and their association with components of the insulin-like growth factor (IGF)-pathway in a cohort of men with localized prostate cancer.

METHODS

Using prostate tissue samples collected during the Prostate cancer: Evidence of Exercise and Nutrition Trial (PrEvENT) trial (N = 70 to 92, depending on section availability), we assessed the abundance of CTCF, FOXA1, AR, IGFIR, p-mTOR, PTEN and IGFBP-2 proteins using a modified version of the Allred scoring system. Validation studies were performed using large, publicly available datasets (TCGA) (N = 489).

RESULTS

We identified a strong correlation between CTCF and AR staining with benign prostate tissue. CTCF also strongly associated with the IGFIR, with PTEN and with phospho-mTOR. FOXA1 was also correlated with staining for the IGF-IR, with IGFBP-2 and with staining for activated phosphor-mTOR. The staining for the IGF-IR was strongly correlated with the AR.

CONCLUSION

Our findings emphasise the close and complex links between the endocrine controls, well known to play an important role in prostate cancer, and the transcription factors implicated by the recent genetic evidence.

MYC reshapes CTCF-mediated chromatin architecture in prostate cancer

MYC is a well characterized oncogenic transcription factor in prostate cancer, and CTCF is the main architectural protein of three-dimensional genome organization. However, the functional link between the two master regulators has not been reported. In this study, we find that MYC rewires prostate cancer chromatin architecture by interacting with CTCF protein. Through combining the H3K27ac, AR and CTCF HiChIP profiles with CRISPR deletion of a CTCF site upstream of MYC gene, we show that MYC activation leads to profound changes of CTCF-mediated chromatin looping. Mechanistically, MYC colocalizes with CTCF at a subset of genomic sites, and enhances CTCF occupancy at these loci. Consequently, the CTCF-mediated chromatin looping is potentiated by MYC activation, resulting in the disruption of enhancer-promoter looping at neuroendocrine lineage plasticity genes. Collectively, our findings define the function of MYC as a CTCF co-factor in three-dimensional genome organization.

Optimized high-throughput screening of non-coding variants identified from genome-wide association studies

The vast majority of disease-associated single nucleotide polymorphisms (SNP) identified from genome-wide association studies (GWAS) are localized in non-coding regions. A significant fraction of these variants impact transcription factors binding to enhancer elements and alter gene expression. To functionally interrogate the activity of such variants we developed snpSTARRseq, a high-throughput experimental method that can interrogate the functional impact of hundreds to thousands of non-coding variants on enhancer activity. snpSTARRseq dramatically improves signal-to-noise by utilizing a novel sequencing and bioinformatic approach that increases both insert size and the number of variants tested per loci. Using this strategy, we interrogated known prostate cancer (PCa) risk-associated loci and demonstrated that 35% of them harbor SNPs that significantly altered enhancer activity. Combining these results with chromosomal looping data we could identify interacting genes and provide a mechanism of action for 20 PCa GWAS risk regions. When benchmarked to orthogonal methods, snpSTARRseq showed a strong correlation with in vivo experimental allelic-imbalance studies whereas there was no correlation with predictive in silico approaches. Overall, snpSTARRseq provides an integrated experimental and computational framework to functionally test non-coding genetic variants.

Extensive androgen receptor enhancer heterogeneity in primary prostate cancers underlies transcriptional diversity and metastatic potential

Androgen receptor (AR) drives prostate cancer (PCa) development and progression. AR chromatin binding profiles are highly plastic and form recurrent programmatic changes that differentiate disease stages, subtypes and patient outcomes. While prior studies focused on concordance between patient subgroups, inter-tumor heterogeneity of AR enhancer selectivity remains unexplored. Here we report high levels of AR chromatin binding heterogeneity in human primary prostate tumors, that overlap with heterogeneity observed in healthy prostate epithelium. Such heterogeneity has functional consequences, as somatic mutations converge on commonly-shared AR sites in primary over metastatic tissues. In contrast, less-frequently shared AR sites associate strongly with AR-driven gene expression, while such heterogeneous AR enhancer usage also distinguishes patients' outcome. These findings indicate that epigenetic heterogeneity in primary disease is directly informative for risk of biochemical relapse. Cumulatively, our results illustrate a high level of AR enhancer heterogeneity in primary PCa driving differential expression and clinical impact.

Associations between NKX2-5 gene polymorphisms and congenital heart disease in the Chinese Tibetan population

BACKGROUND

The pathogenesis of congenital heart disease (CHD) has not been fully elucidated, and this study considers the interaction between inheritance and the environment as the main cause of CHD. Previous studies have found that the incidence of CHD in the Tibetan plateau population is significantly higher than in low-altitude populations. Numerous reports have confirmed that NKX2-5 gene mutations can lead to coronary heart disease, but the relationship between NKX2-5 and Tibetan nationality has not yet been reported.

OBJECTIVE

To explore the relationship between NKX2-5 gene polymorphisms and CHD in Tibetan people.

METHODS

Blood samples were collected retrospectively from Tibetan patients diagnosed with CHD as well as healthy Tibetans, and the exons of NKX2-5 were sequenced. The MassARRAY technique was used to detect and genotype candidate tag single nucleotide polymorphisms (SNPs) in the non-coding regions of NKX2-5.

RESULTS

Exon sequencing revealed no difference in the coding regions of the NKX2-5 gene between the CHD and control groups. In the non-coding regions of NKX2-5, rs6882776 and rs2546741 differed significantly between the two groups. Strong linkage disequilibrium was found between the selected sites of NKX2-5.

CONCLUSIONS

The NKX2-5 exons do not associate with CHD in Tibetans. Rs6882776 and rs2546741 in the non-coding regions of NKX2-5 may protect against CHD in Tibetans. The NKX2-5 haplotype associated with CHD occurrence in the Tibetan population.

Assessment of genetic susceptibility to multiple primary cancers through whole-exome sequencing in two large multi-ancestry studies

BACKGROUND

Up to one of every six individuals diagnosed with one cancer will be diagnosed with a second primary cancer in their lifetime. Genetic factors contributing to the development of multiple primary cancers, beyond known cancer syndromes, have been underexplored.

METHODS

To characterize genetic susceptibility to multiple cancers, we conducted a pan-cancer, whole-exome sequencing study of individuals drawn from two large multi-ancestry populations (6429 cases, 165,853 controls). We created two groupings of individuals diagnosed with multiple primary cancers: (1) an overall combined set with at least two cancers across any of 36 organ sites and (2) cancer-specific sets defined by an index cancer at one of 16 organ sites with at least 50 cases from each study population. We then investigated whether variants identified from exome sequencing were associated with these sets of multiple cancer cases in comparison to individuals with one and, separately, no cancers.

RESULTS

We identified 22 variant-phenotype associations, 10 of which have not been previously discovered and were significantly overrepresented among individuals with multiple cancers, compared to those with a single cancer.

CONCLUSIONS

Overall, we describe variants and genes that may play a fundamental role in the development of multiple primary cancers and improve our understanding of shared mechanisms underlying carcinogenesis.

Dual contribution of the mTOR pathway and of the metabolism of amino acids in prostate cancer

BACKGROUND

Prostate cancer is the leading cause of cancer in men, and its incidence increases with age. Among other risk factors, pre-existing metabolic diseases have been recently linked with prostate cancer, and our current knowledge recognizes prostate cancer as a condition with important metabolic anomalies as well. In malignancies, metabolic disorders are commonly associated with aberrations in mTOR, which is the master regulator of protein synthesis and energetic homeostasis. Although there are reports demonstrating the high dependency of prostate cancer cells for lipid derivatives and even for carbohydrates, the understanding regarding amino acids, and the relationship with the mTOR pathway ultimately resulting in metabolic aberrations, is still scarce.

CONCLUSIONS AND PERSPECTIVES

In this review, we briefly provide evidence supporting prostate cancer as a metabolic disease, and discuss what is known about mTOR signaling and prostate cancer. Next, we emphasized on the amino acids glutamine, leucine, serine, glycine, sarcosine, proline and arginine, commonly related to prostate cancer, to explore the alterations in their regulatory pathways and to link them with the associated metabolic reprogramming events seen in prostate cancer. Finally, we display potential therapeutic strategies for targeting mTOR and the referred amino acids, as experimental approaches to selectively attack prostate cancer cells.

Genome-wide interaction analysis identified low-frequency variants with sex disparity in lung cancer risk

Differences by sex in lung cancer incidence and mortality have been reported which cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene-sex interaction analysis using genotypes from a lung cancer cohort including ~ 47 000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 [odds ratio (OR) = 0.71, P = 4.29×10-8); rs79942605 (OR = 2.17, P = 2.81×10-8) and rs208908 (OR = 0.70, P = 4.54×10-8) were identified with different risk effect of lung cancer between men and women. Further expression quantitative trait loci and functional annotation analysis suggested rs208908 affects lung cancer risk through differential regulation of Coxsackie virus and adenovirus receptor gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

XGBG: A Novel Method for Identifying Ovarian Carcinoma Susceptible Genes Based on Deep Learning

Ovarian carcinomas (OCs) represent a heterogeneous group of neoplasms consisting of several entities with pathogenesis, molecular profiles, multiple risk factors, and outcomes. OC has been regarded as the most lethal cancer among women all around the world. There are at least five main types of OCs classified by the fifth edition of the World Health Organization of tumors: high-/low-grade serous carcinoma, mucinous carcinoma, clear cell carcinoma, and endometrioid carcinoma. With the improved knowledge of genome-wide association study (GWAS) and expression quantitative trait locus (eQTL) analyses, the knowledge of genomic landscape of complex diseases has been uncovered in large measure. Moreover, pathway analyses also play an important role in exploring the underlying mechanism of complex diseases by providing curated pathway models and information about molecular dynamics and cellular processes. To investigate OCs deeper, we introduced a novel disease susceptible gene prediction method, XGBG, which could be used in identifying OC-related genes based on different omics data and deep learning methods. We first employed the graph convolutional network (GCN) to reconstruct the gene features based on both gene feature and network topological structure. Then, a boosting method is utilized to predict OC susceptible genes. As a result, our model achieved a high AUC of 0.7541 and an AUPR of 0.8051, which indicates the effectiveness of the XGPG. Based on the newly predicted OC susceptible genes, we gathered and researched related literatures to provide strong support to the results, which may help in understanding the pathogenesis and mechanisms of the disease.

The landscape of GWAS validation; systematic review identifying 309 validated non-coding variants across 130 human diseases

Background

The remarkable growth of genome-wide association studies (GWAS) has created a critical need to experimentally validate the disease-associated variants, 90% of which involve non-coding variants.

Methods

To determine how the field is addressing this urgent need, we performed a comprehensive literature review identifying 36,676 articles. These were reduced to 1454 articles through a set of filters using natural language processing and ontology-based text-mining. This was followed by manual curation and cross-referencing against the GWAS catalog, yielding a final set of 286 articles.

Results

We identified 309 experimentally validated non-coding GWAS variants, regulating 252 genes across 130 human disease traits. These variants covered a variety of regulatory mechanisms. Interestingly, 70% (215/309) acted through cis-regulatory elements, with the remaining through promoters (22%, 70/309) or non-coding RNAs (8%, 24/309). Several validation approaches were utilized in these studies, including gene expression (n = 272), transcription factor binding (n = 175), reporter assays (n = 171), in vivo models (n = 104), genome editing (n = 96) and chromatin interaction (n = 33).

Conclusions

This review of the literature is the first to systematically evaluate the status and the landscape of experimentation being used to validate non-coding GWAS-identified variants. Our results clearly underscore the multifaceted approach needed for experimental validation, have practical implications on variant prioritization and considerations of target gene nomination. While the field has a long way to go to validate the thousands of GWAS associations, we show that progress is being made and provide exemplars of validation studies covering a wide variety of mechanisms, target genes, and disease areas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01216-w.

A microRNA Transcriptome-wide Association Study of Prostate Cancer Risk

Large genome-wide association studies have identified hundreds of single-nucleotide polymorphisms associated with increased risk of prostate cancer (PrCa), and many of these risk loci is presumed to confer regulatory effects on gene expression. While eQTL studies of long RNAs has yielded many potential risk genes, the relationship between PrCa risk genetics and microRNA expression dysregulation is understudied. We performed an microRNA transcriptome-wide association study of PrCa risk using small RNA sequencing and genome-wide genotyping data from N = 441 normal prostate epithelium tissue samples along with N = 411 prostate adenocarcinoma tumor samples from the Cancer Genome Atlas (TCGA). Genetically regulated expression prediction models were trained for all expressed microRNAs using the FUSION TWAS software. TWAS for PrCa risk was performed with both sets of models using single-SNP summary statistics from the recent PRACTICAL consortium PrCa case-control OncoArray GWAS meta-analysis. A total of 613 and 571 distinct expressed microRNAs were identified in the normal and tumor tissue datasets, respectively (overlap: 480). Among these, 79 (13%) normal tissue microRNAs demonstrated significant cis-heritability (median cis-h2 = 0.15, range: 0.03–0.79) for model training. Similar results were obtained from TCGA tumor samples, with 48 (9%) microRNA expression models successfully trained (median cis-h2 = 0.14, range: 0.06–0.60). Using normal tissue models, we identified two significant TWAS microRNA associations with PrCa risk: over-expression of mir-941 family microRNAs (PTWAS = 2.9E-04) and reduced expression of miR-3617-5p (PTWAS = 1.0E-03). The TCGA tumor TWAS also identified a significant association with miR-941 overexpression (PTWAS = 9.7E-04). Subsequent finemapping of the TWAS results using a multi-tissue database indicated limited evidence of causal status for each microRNA with PrCa risk (posterior inclusion probabilities &lt;0.05). Future work will examine downstream regulatory effects of microRNA dysregulation as well as microRNA-mediated risk mechanisms via competing endogenous RNA relationships.

The mTOR chromatin-bound interactome in prostate cancer

A growing number of studies support a direct role for nuclear mTOR in gene regulation and chromatin structure. Still, the scarcity of known chromatin-bound mTOR partners limits our understanding of how nuclear mTOR controls transcription. Herein, comprehensive mapping of the mTOR chromatin-bound interactome in both androgen-dependent and -independent cellular models of prostate cancer (PCa) identifies a conserved 67-protein interaction network enriched for chromatin modifiers, transcription factors, and SUMOylation machinery. SUMO2/3 and nuclear pore protein NUP210 are among the strongest interactors, while the androgen receptor (AR) is the dominant androgen-inducible mTOR partner. Further investigation reveals that NUP210 facilitates mTOR nuclear trafficking, that mTOR and AR form a functional transcriptional module with the nucleosome remodeling and deacetylase (NuRD) complex, and that androgens specify mTOR-SUMO2/3 promoter-enhancer association. This work identifies a vast network of mTOR-associated nuclear complexes advocating innovative molecular strategies to modulate mTOR-dependent gene regulation with conceivable implications for PCa and other diseases.

Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure

Background

Numerous genome-wide association studies (GWAS) conducted to date revealed genetic variants associated with various diseases, including breast and prostate cancers. Despite the availability of these large-scale data, relatively few variants have been functionally characterized, mainly because the majority of single-nucleotide polymorphisms (SNPs) map to the non-coding regions of the human genome. The functional characterization of these non-coding variants and the identification of their target genes remain challenging.

Results

In this communication, we explore the potential functional mechanisms of non-coding SNPs by integrating GWAS with the high-resolution chromosome conformation capture (Hi-C) data for breast and prostate cancers. We show that more genetic variants map to regulatory elements through the 3D genome structure than the 1D linear genome lacking physical chromatin interactions. Importantly, the association of enhancers, transcription factors, and their target genes with breast and prostate cancers tends to be higher when these regulatory elements are mapped to high-risk SNPs through spatial interactions compared to simply using a linear proximity. Finally, we demonstrate that topologically associating domains (TADs) carrying high-risk SNPs also contain gene regulatory elements whose association with cancer is generally higher than those belonging to control TADs containing no high-risk variants.

Conclusions

Our results suggest that many SNPs may contribute to the cancer development by affecting the expression of certain tumor-related genes through long-range chromatin interactions with gene regulatory elements. Integrating large-scale genetic datasets with the 3D genome structure offers an attractive and unique approach to systematically investigate the functional mechanisms of genetic variants in disease risk and progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-01021-x.

OUP accepted manuscript

In the last years, many studies were able to identify associations between common genetic variants and complex diseases. However, the mechanistic biological links explaining these associations are still mostly unknown. Common variants are usually associated with a relatively small effect size, suggesting that interactions among multiple variants might be a major genetic component of complex diseases. Hence, elucidating the presence of functional relations among variants may be fundamental to identify putative variants’ interactions. To this aim, we developed Polympact, a web-based resource that allows to explore functional relations among human common variants by exploiting variants’ functional element landscape, their impact on transcription factor binding motifs, and their effect on transcript levels of protein-coding genes. Polympact characterizes over 18 million common variants and allows to explore putative relations by combining clustering analysis and innovative similarity and interaction network models. The properties of the network models were studied and the utility of Polympact was demonstrated by analysing the rich sets of Breast Cancer and Alzheimer's GWAS variants. We identified relations among multiple variants, suggesting putative interactions. Polympact is freely available at bcglab.cibio.unitn.it/polympact.

Mechanistic insights into genetic susceptibility to prostate cancer

Prostate cancer (PCa) is the second most common cancer in men and is a highly heritable disease that affects millions of individuals worldwide. Genome-wide association studies have to date discovered nearly 270 genetic loci harboring hundreds of single nucleotide polymorphisms (SNPs) that are associated with PCa susceptibility. In contrast, the functional characterization of the mechanisms underlying PCa risk association is still growing. Given that PCa risk-associated SNPs are highly enriched in noncoding cis-regulatory genomic regions, accumulating evidence suggests a widespread modulation of transcription factor chromatin binding and allelic enhancer activity by these noncoding SNPs, thereby dysregulating gene expression. Emerging studies have shown that a proportion of noncoding variants can modulate the formation of transcription factor complexes at enhancers and CTCF-mediated 3D genome architecture. Interestingly, DNA methylation-regulated CTCF binding could orchestrate a long-range chromatin interaction between PCa risk enhancer and causative genes. Additionally, one-causal-variant-two-risk genes or multiple-risk-variant-multiple-genes are prevalent in some PCa risk-associated loci. In this review, we will discuss the current understanding of the general principles of SNP-mediated gene regulation, experimental advances, and functional evidence supporting the mechanistic roles of several PCa genetic loci with potential clinical impact on disease prevention and treatment.

An Ovarian Cancer Susceptible Gene Prediction Method Based on Deep Learning Methods

Ovarian cancer (OC) is one of the most fatal diseases among women all around the world. It is highly lethal because it is usually diagnosed at an advanced stage which may reduce the survival rate greatly. Even though most of the patients are treated timely and effectively, the survival rate is still low due to the high recurrence rate of OC. With a large number of genome-wide association analysis (GWAS)-discovered risk regions of OC, expression quantitative trait locus (eQTL) analyses can explore candidate susceptible genes based on these risk loci. However, a large number of OC-related genes remain unknown. In this study, we proposed a novel gene prediction method based on different omics data and deep learning methods to identify OC causal genes. We first employed graph attention network (GAT) to obtain a compact gene feature representation, then a deep neural network (DNN) is utilized to predict OC-related genes. As a result, our model achieved a high AUC of 0.761 and AUPR of 0.788, which proved the accuracy and effectiveness of our proposed method. At last, we conducted a gene-set enrichment analysis to further explore the mechanism of OC. Finally, we predicted 245 novel OC causal genes and 10 top related KEGG pathways.

Regulatory SNPs: Altered Transcription Factor Binding Sites Implicated in Complex Traits and Diseases

The vast majority of the genetic variants (mainly SNPs) associated with various human traits and diseases map to a noncoding part of the genome and are enriched in its regulatory compartment, suggesting that many causal variants may affect gene expression. The leading mechanism of action of these SNPs consists in the alterations in the transcription factor binding via creation or disruption of transcription factor binding sites (TFBSs) or some change in the affinity of these regulatory proteins to their cognate sites. In this review, we first focus on the history of the discovery of regulatory SNPs (rSNPs) and systematized description of the existing methodical approaches to their study. Then, we brief the recent comprehensive examples of rSNPs studied from the discovery of the changes in the TFBS sequence as a result of a nucleotide substitution to identification of its effect on the target gene expression and, eventually, to phenotype. We also describe state-of-the-art genome-wide approaches to identification of regulatory variants, including both making molecular sense of genome-wide association studies (GWAS) and the alternative approaches the primary goal of which is to determine the functionality of genetic variants. Among these approaches, special attention is paid to expression quantitative trait loci (eQTLs) analysis and the search for allele-specific events in RNA-seq (ASE events) as well as in ChIP-seq, DNase-seq, and ATAC-seq (ASB events) data.

Functional mapping of androgen receptor enhancer activity

Background

Androgen receptor (AR) is critical to the initiation, growth, and progression of prostate cancer. Once activated, the AR binds to cis-regulatory enhancer elements on DNA that drive gene expression. Yet, there are 10–100× more binding sites than differentially expressed genes. It is unclear how or if these excess binding sites impact gene transcription.

Results

To characterize the regulatory logic of AR-mediated transcription, we generated a locus-specific map of enhancer activity by functionally testing all common clinical AR binding sites with Self-Transcribing Active Regulatory Regions sequencing (STARRseq). Only 7% of AR binding sites displayed androgen-dependent enhancer activity. Instead, the vast majority of AR binding sites were either inactive or constitutively active enhancers. These annotations strongly correlated with enhancer-associated features of both in vitro cell lines and clinical prostate cancer samples. Evaluating the effect of each enhancer class on transcription, we found that AR-regulated enhancers frequently interact with promoters and form central chromosomal loops that are required for transcription. Somatic mutations of these critical AR-regulated enhancers often impact enhancer activity.

Conclusions

Using a functional map of AR enhancer activity, we demonstrated that AR-regulated enhancers act as a regulatory hub that increases interactions with other AR binding sites and gene promoters.

TERT Genotype Polymorphism: A Glance of Change Egyptian MDS Outcomes

Background:

Myelodysplastic Syndromes (MDS)are clonal hematologic disorders characterized by genetic instability and ineffective hematopoiesis associated with telomere dysfunction. We aimed at investigating the association between the rs2242652 single nucleotide variant of the TERT gene and susceptibility for MDS, as well as its prognostic impact and relation to disease phenotype.

Methods:

Genotyping analysis was carried on 100 MDS patients recruited at Mansoura Oncology center, in addition to 100 healthy subjects for detection of rs2242652 variant of TERT gene on chromosome 5 by real time PCR following the protocol of Custom TaqMan^® SNP Genotyping.

Results:

The rs2242652 TERT genetic polymorphism was associated with an increased risk of MDS (odds ratios 2.6 for genotype GA, 6.4 for genotype AA). The majority of AA homozygous mutant variant were associated pancytopenia (88%), poor risk cytogenetics (92%) and High/very high IPSS-R score (88%). At the end of follow-up (median 30 months), 14% of the cases transformed to secondary AML. The rate of leukemic transformation was significantly associated with the mutant AA genotype (93% of transformed cases, 52% of AA genotype cases; P< 0.0001). Survival outcome was inferior in AA mutant genotype (median 14 months, 95% CI: 12-16 months) to the GA genotype (median 30 months, 95% CI: 26-33 months) and those of the GG genotype (median not reached), P<0.001.

Conclusion:

Our study shows an intriguing and previously unrecognized association between rs2242652 TERT mutation and MDS risk. The presence of rs2242652 mutation defines a subgroup of patients with aggressive disease phenotype and dismal outcome. Further research is recommended to elucidate underlying pathologic mechanisms and to define an efficient therapeutic target.

CRISPRi screens reveal a DNA methylation-mediated 3D genome dependent causal mechanism in prostate cancer

Prostate cancer (PCa) risk-associated SNPs are enriched in noncoding cis-regulatory elements (rCREs), yet their modi operandi and clinical impact remain elusive. Here, we perform CRISPRi screens of 260 rCREs in PCa cell lines. We find that rCREs harboring high risk SNPs are more essential for cell proliferation and H3K27ac occupancy is a strong indicator of essentiality. We also show that cell-line-specific essential rCREs are enriched in the 8q24.21 region, with the rs11986220-containing rCRE regulating MYC and PVT1 expression, cell proliferation and tumorigenesis in a cell-line-specific manner, depending on DNA methylation-orchestrated occupancy of a CTCF binding site in between this rCRE and the MYC promoter. We demonstrate that CTCF deposition at this site as measured by DNA methylation level is highly variable in prostate specimens, and observe the MYC eQTL in the 8q24.21 locus in individuals with low CTCF binding. Together our findings highlight a causal mechanism synergistically driven by a risk SNP and DNA methylation-mediated 3D genome architecture, advocating for the integration of genetics and epigenetics in assessing risks conferred by genetic predispositions.

Identification of Germline Genetic Variants that Increase Prostate Cancer Risk and Influence Development of Aggressive Disease

Prostate cancer (PrCa) is a heterogeneous disease, which presents in individual patients across a diverse phenotypic spectrum ranging from indolent to fatal forms. No robust biomarkers are currently available to enable routine screening for PrCa or to distinguish clinically significant forms, therefore late stage identification of advanced disease and overdiagnosis plus overtreatment of insignificant disease both remain areas of concern in healthcare provision. PrCa has a substantial heritable component, and technological advances since the completion of the Human Genome Project have facilitated improved identification of inherited genetic factors influencing susceptibility to development of the disease within families and populations. These genetic markers hold promise to enable improved understanding of the biological mechanisms underpinning PrCa development, facilitate genetically informed PrCa screening programmes and guide appropriate treatment provision. However, insight remains largely lacking regarding many aspects of their manifestation; especially in relation to genes associated with aggressive phenotypes, risk factors in non-European populations and appropriate approaches to enable accurate stratification of higher and lower risk individuals. This review discusses the methodology used in the elucidation of genetic loci, genes and individual causal variants responsible for modulating PrCa susceptibility; the current state of understanding of the allelic spectrum contributing to PrCa risk; and prospective future translational applications of these discoveries in the developing eras of genomics and personalised medicine.

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, p_adj = 3.53 × 10^-8 and rs58809953, OR 1.71, p_adj = 4.00 × 10^-6; intergenic rs79012498, OR 1.81, p_adj = 4.26 × 10^-8), 17q21 (SP6 rs2074187, OR 1.66, p_adj = 3.75 × 10^-5), 11q13 (rs12795301, OR 1.42, p_adj = 2.89 × 10^-5) and 8p21 (rs995432, OR 1.38, p_adj = 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.

rs2274911 polymorphism in GPRC6A associated with serum E2 and PSA in a Southern Chinese male population

BACKGROUND

rs2274911 (Pro91Ser, G > A) is a missense mutation located on the second exon of the GPRC6A gene. Increasing evidence revealed a significant association between the A allele of rs2274911 and male diseases, such as oligospermia, cryptorchidism, and prostate tumor. However, the function of rs2274911 in healthy males is unclear.

SUBJECTS AND METHODS

A total of 1742 healthy men were selected from the Fangchenggang Area Male Health and Examination Survey (FAMHES). The association between rs2274911 and phenotype was evaluated. The cell characteristics of rs2274911 mutation (mu), wild-type GPRC6A (WT), and RFP control in human embryonic kidney (293T) and human prostate cancer (PC3) cells were analyzed. RNA sequencing was performed on PC3 cells.

RESULTS

E2 and PSA serum levels increased with the accumulation of the A allele (E2: G vs. A, -0.029 [-0.050, -0.008], P < 0.01, P trend = 0.027; PSA: G vs. A, -0.040 [-0.079, 0.000], P < 0.05, P trend = 0.048). rs2274911 enhanced the proliferation and invasion ability of PC3 or 293T cells and activated the ERK pathway. The genes were identified as rs2274911 mu-affected genes through RNA sequential analysis of rs2274911 mu, GPRC6A WT, and RFP control of PC3 cells. Most of these genes were related to cancer development processes, cAMP, and the ERK cell signaling pathway.

CONCLUSION

This project represents that rs2274911 is associated with E2 and PSA serum levels in Southern Chinese men. Rs2274991 mutation promotes 293T and PC3 cell proliferation in vitro. These results suggest that rs2274911 is a functional variant of GPRC6A.

Transcriptional network modulated by the prognostic signature transcription factors and their long noncoding RNA partners in primary prostate cancer

Background

Transcriptional regulators are seminal players in the onset and progression of prostate cancer. However, clarification of their underlying regulatory circuits and mechanisms demands considerable effort.

Methods

Integrated analyses were performed on genomic, transcriptomic, and clinicopathological profiles of primary prostate cancer and transcription factor-binding profiles, which included estimating transcription factor activity, identifying transcription factors of prognostic values, and discovering cis- and trans-regulations by long noncoding RNAs. Interactions between transcription factors and long noncoding RNAs were validated by RNA immunoprecipitation quantitative PCR. RNA interference assays were performed to explore roles of the selected transcription regulators.

Findings

Sixteen transcription factors, namely, ETS1, ARID4B, KLF12, GMEB1, HBP1, MXI1, MYC, MAX, PGR, BCL11A, AR, KLF4, SRF, HIF1A, EHF, and ATOH1, were jointly identified as a prognostic signature. Candidate long noncoding RNAs interplaying with the prognostic signature constituent transcription factors were further discovered. Their interactions were randomly checked, and many of them were experimentally proved. Transcription regulation by MYC and its long noncoding RNA partner AL590617.2 was further validated on their candidate targets. Moreover, the regulatory network governed by the transcription factors and their interacting long noncoding RNA partners is illustrated and stored in our LNCTRN database (https://navy.shinyapps.io/lnctrn).

Interpretation

The prognostic signature constituent transcription factors and their interacting long noncoding RNAs may represent promising biomarkers and/or therapeutic targets for prostate cancer. Furthermore, the computational framework proposed in the present study can be utilized to explore critical transcriptional regulators in other types of cancer.

Funding

This work was supported by National Natural Science Foundation of China and Fudan University.

Transcription factors in epithelial ovarian cancer: histotype-specific drivers and novel therapeutic targets

Transcription factors (TFs) are major contributors to cancer risk and somatic development. In preclinical and clinical studies, direct or indirect inhibition of TF-mediated oncogenic gene expression profiles have proven to be effective in many tumor types, highlighting this group of proteins as valuable therapeutic targets. In spite of this, our understanding of TFs in epithelial ovarian cancer (EOC) is relatively limited. EOC is a heterogeneous disease composed of five major histologic subtypes; high-grade serous, low-grade serous, endometrioid, clear cell and mucinous. Each histology is associated with unique clinical etiologies, sensitivity to therapies, and molecular signatures - including diverse transcriptional regulatory programs. While some TFs are shared across EOC subtypes, a set of TFs are expressed in a histotype-specific manner and likely explain part of the histologic diversity of EOC subtypes. Targeting TFs present with unique opportunities for development of novel precision medicine strategies for ovarian cancer. This article reviews the critical TFs in EOC subtypes and highlights the potential of exploiting TFs as biomarkers and therapeutic targets.

Validation of prostate cancer risk variants rs10993994 and rs7098889 by CRISPR/Cas9 mediated genome editing

GWAS have identified numerous SNPs associated with prostate cancer risk. One such SNP is rs10993994. It is located in the β-microseminoprotein (MSMB) promoter region, mediates MSMB prostate secretion levels, and is linked to mRNA expression changes in both MSMB and the adjacent gene NCOA4. In addition, our previous work showed a second SNP, rs7098889, is in positive linkage disequilibrium with rs10993994 and associated with MSMB expression independent of rs10993994. Here, we generate a series of clones with single alleles removed by double guide RNA (gRNA) mediated CRISPR/Cas9 deletions, through which we demonstrate that each of these SNPs independently and greatly alters MSMB expression in an allele-specific manner. We further show that these SNPs have no substantial effect on the expression of NCOA4. These data demonstrate that a single SNP can have a large effect on gene expression and illustrate the importance of functional validation studies to deconvolute observed correlations. The method we have developed is generally applicable to test any SNP for which a relevant heterozygous cell line is available. AUTHOR SUMMARY: In pursuing the underlying biological mechanism of prostate cancer pathogenesis, scientists utilized the existence of common single nucleotide polymorphisms (SNPs) in the human genome as genetic markers to perform large scale genome wide association studies (GWAS) and have so far identified more than a hundred prostate cancer risk variants. Such variants provide an unbiased and systematic new venue to study the disease mechanism, and the next big challenge is to translate these genetic associations to the causal role of altered gene function in oncogenesis. The majority of these variants are waiting to be studied and lots of them may act in oncogenesis through gene expression regulation. To prove the concept, we took rs10993994 and its linked rs7098889 as an example and engineered single cell clones by allelic-specific CRISPR/Cas9 deletion to separate the effect of each allele. We observed that a single nucleotide difference would lead to surprisingly high level of MSMB gene expression change in a gene specific and cell-type specific manner. Our study strongly supports the notion that differential level of gene expression caused by risk variants and their associated genetic locus play a major role in oncogenesis and also highlights the importance of studying the function of MSMB encoded β-MSP in prostate cancer pathogenesis.

Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure.. [DOI: 10.1101/2020.10.06.328567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Numerous genome-wide association studies (GWAS) conducted to date revealed genetic variants associated with various diseases, including breast and prostate cancers. Despite the availability of these large-scale data, relatively few variants have been functionally characterized, mainly because the majority of single-nucleotide polymorphisms (SNPs) map to the non-coding regions of the human genome. The functional characterization of these non-coding variants and the identification of their target genes remain challenging. In this communication, we explore the potential functional mechanisms of non-coding SNPs by integrating GWAS with the high-resolution chromosome conformation capture (Hi-C) data for breast and prostate cancers. We show that more genetic variants map to regulatory elements through the 3D genome structure than the 1D linear genome lacking physical chromatin interactions. Importantly, the association of enhancers, transcription factors, and their target genes with breast and prostate cancers tends to be higher when these regulatory elements are mapped to high-risk SNPs through spatial interactions compared to simply using a linear proximity. Finally, we demonstrate that topologically associating domains (TADs) carrying high-risk SNPs also contain gene regulatory elements whose association with cancer is generally higher than those belonging to control TADs containing no high-risk variants. Our results suggest that many SNPs may contribute to the cancer development by affecting the expression of certain tumor-related genes through long-range chromatin interactions with gene regulatory elements. Integrating large-scale genetic datasets with the 3D genome structure offers an attractive and unique approach to systematically investigate the functional mechanisms of genetic variants in disease risk and progression.

Ovarian Cancer Risk Variants Are Enriched in Histotype-Specific Enhancers and Disrupt Transcription Factor Binding Sites

Quantifying the functional effects of complex disease risk variants can provide insights into mechanisms underlying disease biology. Genome-wide association studies have identified 39 regions associated with risk of epithelial ovarian cancer (EOC). The vast majority of these variants lie in the non-coding genome, where they likely function through interaction with gene regulatory elements. In this study we first estimated the heritability explained by known common low penetrance risk alleles for EOC. The narrow sense heritability (hg2) of EOC overall and high-grade serous ovarian cancer (HGSOCs) were estimated to be 5%-6%. Partitioned SNP heritability across broad functional categories indicated a significant contribution of regulatory elements to EOC heritability. We collated epigenomic profiling data for 77 cell and tissue types from Roadmap Epigenomics and ENCODE, and from H3K27Ac ChIP-seq data generated in 26 ovarian cancer and precursor-related cell and tissue types. We identified significant enrichment of risk single-nucleotide polymorphisms (SNPs) in active regulatory elements marked by H3K27Ac in HGSOCs. To further investigate how risk SNPs in active regulatory elements influence predisposition to ovarian cancer, we used motifbreakR to predict the disruption of transcription factor binding sites. We identified 469 candidate causal risk variants in H3K27Ac peaks that are predicted to significantly break transcription factor (TF) motifs. The most frequently broken motif was REST (p value = 0.0028), which has been reported as both a tumor suppressor and an oncogene. Overall, these systematic functional annotations with epigenomic data improve interpretation of EOC risk variants and shed light on likely cells of origin.

Analysis of GPRC6A variants in different pancreatitis etiologies

BACKGROUND

The G-protein-coupled receptor Class C Group 6 Member A (GPRC6A) is activated by multiple ligands and is important for the regulation of calcium homeostasis. Extracellular calcium is capable to increase NLRP3 inflammasome activity of the innate immune system and deletion of this proinflammatory pathway mitigated pancreatitis severity in vivo. As such this pathway and the GPRC6A receptor is a reasonable candidate gene for pancreatitis. Here we investigated the prevalence of sequence variants in the GPRC6A locus in different pancreatitis aetiologies.

METHODS

We selected 6 tagging SNPs with the SNPinfo LD TAG SNP Selection tool and the functional relevant SNP rs6907580 for genotyping. Cohorts from Germany, further European countries and China with up to 1,124 patients and 1,999 controls were screened for single SNPs with melting curve analysis.

RESULTS

We identified an association of rs1606365(G) with alcoholic chronic pancreatitis in a German (odds ratio (OR) 0.76, 95% confidence interval (CI) 0.65-0.89, p = 8 × 10^-5) and a Chinese cohort (OR 0.78, 95% CI 0.64-0.96, p = 0.02). However, this association was not replicated in a combined cohort of European patients (OR 1.18, 95% CI 0.99-1.41, p = 0.07). Finally, no association was found with acute and non-alcoholic chronic pancreatitis.

CONCLUSIONS

Our results support a potential role of calcium sensing receptors and inflammasome activation in alcoholic chronic pancreatitis development. As the functional consequence of the associated variant is unclear, further investigations might elucidate the relevant mechanisms.

BRD4 promotes metastatic potential in oral squamous cell carcinoma through the epigenetic regulation of the MMP2 gene

BACKGROUND

Oral squamous cell carcinoma (OSCC) has increased morbidity, and its high metastatic potential affects patient survival. Bromodomain containing 4 (BRD4) is a chromatin protein that associates with acetylated histone lysines and facilitates transcription. BRD4 has been implicated in cell proliferation, metastasis, and prognosis in several types of cancer. However, the role of BRD4 in OSCC remains to be elucidated.

METHODS

We investigated the role of BRD4 and its potential utility as a therapeutic target in OSCC.

RESULTS

JQ1, the BRD4 inhibitor, suppressed the cell proliferation, migration, and invasion in the OSCC cell lines and in vivo. JQ1 reduced the expression levels of 15 metastasis genes in OSCC, including matrix metallopeptidase 2 (MMP2). Our chromatin immunoprecipitation assay showed that JQ1 reduced the BRD4 binding to the histone H3 lysine 27 acetylation-enriched sites in the MMP2 locus. Analyses of biopsy specimens from OSCC patients revealed that the BRD4 and MMP2 expression levels were correlated in the cancerous regions, and both were highly expressed in lymph node metastasis cases, including delayed metastasis.

CONCLUSIONS

BRD4 contributes to metastasis in OSCC, through the epigenetic regulation of the MMP2 gene, and thus BRD4 may represent a therapeutic target and a novel prediction indicator for metastasis.

TFAP2B, AP-1 and JAZF1 Expression in Tissues of Papillary Thyroid Carcinoma Patients; Clinical, Pathological and Prognostic Values

OBJECTIVE

Transcription factor activating protein 2 B (TFAP2 B) is a transcription factor that regulates many steps of embryogenesis, cell growth, apoptosis and recently oncogenesis and cancer progression. AP-1 is a transcription factor that is a downstream molecule of the MAPK signaling pathway. Juxtaposed with zinc finger gene 1 (JAZF1) is a recently detected transforming growth factor which has a role in carcinogenesis. Hence the present study aimed to assess those markers expression in tissues from patients with such cancer correlation their expression with clinic-pathological findings of the tumor and prognostic and follow-up findings of patients.

METHODS

We have collected tissue samples from papillary thyroid cancer patients and adjacent non-neoplastic tissues from 80 patients. We assessed the expression of TFAP2B, AP-1 and JAZF1 using immunohistochemistry.

RESULTS

Expression of TFAP2B was positively associated with lymph nodes metastases (p=0.003), distant metastases (p=0.002), recurrence of the tumor (p=0.002), unfavourable disease-free survival rate (p=0.003). AP-1 expression is positively associated with advanced stage (p=0.002), presence of extra-thyroid invasion (p=0.005), recurrence of the tumor (p=0.005), unfavorable disease-free survival rate (p=0.01). JAZF1 expression is negatively associated with huge tumor size (0.023), vascular invasion (p=0.007) and unfavorable overall survival rate (p=.030).

CONCLUSION

High expression levels of TFAP2B and AP-1 and low expression levels of JAZF1 were associated with unfavourable pathological, prognostic parameters and dismal patient's outcome.<br />.

Beyond the coding genome: non-coding mutations and cancer

Latest advancements in genomics involving individuals from different races and geographical locations has led to the identification of thousands of common as well as rare genetic variants and copy number variations (CNVs). These studies have surprisingly revealed that the majority of genetic variation is not present within the coding region but rather in the non-coding region of the genome, which is also termed as "Medical Genome". This short review describes how mutations/variations within; regulatory sequences, architectural proteins and transcriptional regulators give rise to the aberrant gene expression profiles that drives cellular transformations and malignancies.

Pathway Analysis of Genes Identified through Post-GWAS to Underpin Prostate Cancer Aetiology

Understanding the functional role of risk regions identified by genome-wide association studies (GWAS) has made considerable recent progress and is referred to as the post-GWAS era. Annotation of functional variants to the genes, including cis or trans and understanding their biological pathway/gene network enrichments, is expected to give rich dividends by elucidating the mechanisms underlying prostate cancer. To this aim, we compiled and analysed currently available post-GWAS data that is validated through further studies in prostate cancer, to investigate molecular biological pathways enriched for assigned functional genes. In total, about 100 canonical pathways were significantly, at false discovery rate (FDR) < 0.05), enriched in assigned genes using different algorithms. The results have highlighted some well-known cancer signalling pathways, antigen presentation processes and enrichment in cell growth and development gene networks, suggesting risk loci may exert their functional effect on prostate cancer by acting through multiple gene sets and pathways. Additional upstream analysis of the involved genes identified critical transcription factors such as HDAC1 and STAT5A. We also investigated the common genes between post-GWAS and three well-annotated gene expression datasets to endeavour to uncover the main genes involved in prostate cancer development/progression. Post-GWAS generated knowledge of gene networks and pathways, although continuously evolving, if analysed further and targeted appropriately, will have an important impact on clinical management of the disease.

Transcription Factor Enrichment Analysis in Enhancers Identifies EZH2 as a Susceptibility Gene for Osteoporosis

PURPOSE

Genome-wide association studies (GWASs) have identified hundreds of single nucleotide polymorphisms (SNPs) associated with osteoporosis. Most of these SNPs are noncoding variants and could be mapped to enhancers. Transcription factors (TFs) play important roles in gene regulation via enhancers harboring these SNPs; thus, we aimed to identify common regulatory TFs binding to enhancers associated with osteoporosis.

METHODS

We first annotated all the osteoporosis-related SNPs identified by GWASs to enhancers and conducted TF enrichment analyses to identify common TFs binding to osteoporosis-associated enhancers. We further conducted genetic association analyses between the identified TFs and bone mineral density (BMD) in a Han Chinese population.

RESULTS

After functional annotation, a total of 5081 osteoporosis-related SNPs were mapped to enhancers. TF enrichment analyses identified 2 significant TFs after multiple testing adjustments, which are EZH2 (Padj = .028) and NRSF (Padj = .038). We also found 1 SNP, rs111851041, in EZH2 was significantly associated with BMD both at the hip and spine after multiple testing adjustments (hip BMD: P = 4.32 × 10-4; spine BMD: P = 2.72 × 10-3). The expression of EZH2 decreased significantly from 12 to 48 hours of osteogenic differentiation. And functional validation showed that EZH2 was associated with osteoporosis-related phenotypes in knockout mice.

CONCLUSIONS

By conducting TF enrichment analyses, we identified EZH2 as a common TF binding to osteoporosis-associated enhancers, and EZH2 was also associated with BMD in a Chinese population. EZH2 is functionally related to bone phenotypes. The identified gene could provide new insight into osteoporosis pathophysiology and highlight opportunities for future clinical and pharmacological research on osteoporosis.

Risk of Prostate Cancer Associated With Familial and Hereditary Cancer Syndromes

PURPOSE

Recently developed clinical guidelines suggest that men in families with specific cancer syndromes, such as hereditary breast and ovarian cancer (HBOC), consider genetic testing, especially in the setting of aggressive disease. However, although a family history (FH) of the same disease among close relatives is an established risk factor for prostate cancer (PC), a direct comparison of PC risk for men with each syndrome in a single population is needed.

METHODS

The Utah Population Database was used to identify 619,630 men, age ≥ 40 years, who were members of a pedigree that included at least 3 consecutive generations. Each man was evaluated for FH of hereditary PC (HPC), HBOC, and Lynch syndrome (LS) and for his own PC status. PC occurrences (N = 36,360) were classified into one or more subtypes: early onset (EO), lethal, and/or clinically significant. Relative risks (RRs) associated with each subtype, adjusted for important covariables, were calculated in STATA using a modified Poisson regression with robust error variances to obtain corresponding RR CIs for each FH definition.

RESULTS

An FH of HPC conveyed the greatest relative risk for all PC subtypes combined (RR, 2.30; 95% CI, 2.22 to 2.40), followed by HBOC and LS (both with 1 < RR < 2 and statistically significant). The strongest risks associated with FH were observed for EO disease in all pedigree types, consistent with the contribution of genetic factors to disease occurrence.

CONCLUSION

In this large, population-based, family database, the risk of PC varied by cancer FH and was most strongly associated with EO disease. These results are critically valuable in understanding and targeting high-risk populations that would benefit from genetic screening and enhanced surveillance.

Long non-coding RNA MANCR is a target of BET bromodomain protein BRD4 and plays a critical role in cellular migration and invasion abilities of prostate cancer

Androgen receptor (AR)-negative castration-resistant prostate cancer (CRPC) is highly aggressive and is resistant to most of the current therapies. Bromodomain and extra terminal domain (BET) protein BRD4 binds to super-enhancers (SEs) that drive high expression of oncogenes in many cancers. A BET inhibitor, JQ1, has been found to suppress the malignant phenotypes of prostate cancer cells, however, the target genes of JQ1 remain largely unknown. Here we show that SE-associated genes specific for AR-negative CRPC PC3 cells include genes involved in migration and invasion, and that JQ1 impairs migration and invasion of PC3 cells. We identified a long non-coding RNA, MANCR, which was markedly down-regulated by JQ1, and found that BRD4 binds to the MANCR locus. MANCR knockdown led to a significant decrease in migration and invasion of PC3 cells. Furthermore, RNA sequencing analysis revealed that expression of the genes involved in migration and invasion was altered by MANCR knockdown. In summary, our data demonstrate that MANCR plays a critical role in migration and invasion of PC3 cells.

Germline genetics in localized prostate cancer

PURPOSE OF REVIEW

To provide the reader an understanding of the importance and limitations of prostate cancer (PCa) screening, the heritable component of PCa and the role that germline genetic markers can play in risk-adapted screening and treatment.

RECENT FINDINGS

Despite strong science supporting the association of germline genetic change with PCa risk and outcome, there has been a reluctance to pursue practical application of these technologies. Recent findings suggest that actionable information may now be garnered from this form of testing, which can help men at risk for and with PCa.

SUMMARY

This is an exciting time whereby germline genetic markers can help overcome some of the shortcomings of current PCa screening and treatment paradigms. Understanding their benefit and limitations while keeping the patient's best interest in mind will be the key for the responsible application of these exciting technologies.

Integrative prediction of gene expression with chromatin accessibility and conformation data

BACKGROUND

Enhancers play a fundamental role in orchestrating cell state and development. Although several methods have been developed to identify enhancers, linking them to their target genes is still an open problem. Several theories have been proposed on the functional mechanisms of enhancers, which triggered the development of various methods to infer promoter-enhancer interactions (PEIs). The advancement of high-throughput techniques describing the three-dimensional organization of the chromatin, paved the way to pinpoint long-range PEIs. Here we investigated whether including PEIs in computational models for the prediction of gene expression improves performance and interpretability.

RESULTS

We have extended our [Formula: see text] framework to include DNA contacts deduced from chromatin conformation capture experiments and compared various methods to determine PEIs using predictive modelling of gene expression from chromatin accessibility data and predicted transcription factor (TF) motif data. We designed a novel machine learning approach that allows the prioritization of TFs binding to distal loop and promoter regions with respect to their importance for gene expression regulation. Our analysis revealed a set of core TFs that are part of enhancer-promoter loops involving YY1 in different cell lines.

CONCLUSION

We present a novel approach that can be used to prioritize TFs involved in distal and promoter-proximal regulatory events by integrating chromatin accessibility, conformation, and gene expression data. We show that the integration of chromatin conformation data can improve gene expression prediction and aids model interpretability.

JAZF1 Suppresses Papillary Thyroid Carcinoma Cell Proliferation and Facilitates Apoptosis via Regulating TAK1/NF-κB Pathways

Purpose

Juxtaposed with another zinc finger gene 1 (JAZF1) is involved in gluconeogenesis, insulin sensitivity, cell differentiation, lipid metabolism and inflammation, but its role in carcinoma remains inexplicit.

Patients and methods

We explored the JAZF1 expression in human papillary thyroid cancer (PTC) tissues, adjacent normal thyroid tissues and nodular goitre tissues, as well as Ki67 expression in PTC tissues, using immunohistochemistry staining. Western blotting and RT-qPCR were performed to explore the JAZF1 expression levels in Nthy-ori 3–1, BCPAP and TPC-1 cells. BCPAP cells overexpressing JAZF1 were constructed using an Adv-JAZF1-GFP recombinant adenovirus vector. Next, the cell proliferation assay, colony formation assay, cell cycle analysis, apoptosis and immunofluorescence were performed. The mRNA expression level of nuclear factor-κB p65 (NF-κB p65) was examined using RT-qPCR. The expression of Bcl-2, Bax, transforming growth factor beta-activated kinase 1 (TAK1), NF-κB p65 and NF-κB p-p65 were examined using Western blotting.

Results

The expression of JAZF1 in human PTC tissues was downregulated compared with adjacent thyroid tissues or nodular goitre. Additionally, JAZF1 expression was associated with the location and lymph node metastasis of PTC. The expression level of JAZF1 had a negative correlation with Ki67 labelling index (LI). Compared to Nthy-ori 3–1 cells and TPC-1 cells, BCPAP cells expressed the lowest JAZF1. JAZF1 overexpressed significantly inhibited proliferation, caused G0/G1 cell cycle arrest and promoted apoptosis in BCPAP cells. Furthermore, JAZF1 overexpressed in BCPAP cells clearly upregulated the expression level of Bax protein, whereas decreased the expression of Bcl-2, TAK1, NF-κB but did not affect the mRNA or protein expression level of NF-κB p65.

Conclusion

JAZF1 inhibits proliferation and induces apoptosis in BCPAP cells by suppressing the activation of TAK1/NF-κB signalling pathways, suggesting that JAZF1 may serve as a reliable molecular marker in PTC.

Germline genetic variation in prostate susceptibility does not predict outcomes in the chemoprevention trials PCPT and SELECT

Background

The development of prostate cancer can be influenced by genetic and environmental factors. Numerous germline SNPs influence prostate cancer susceptibility. The functional pathways in which these SNPs increase prostate cancer susceptibility are unknown. Finasteride is currently not being used routinely as a chemoprevention agent but the long term outcomes of the PCPT trial are awaited. The outcomes of the SELECT trial have not recommended the use of chemoprevention in preventing prostate cancer. This study investigated whether germline risk SNPs could be used to predict outcomes in the PCPT and SELECT trial.

Methods

Genotyping was performed in European men entered into the PCPT trial (n = 2434) and SELECT (n = 4885). Next generation genotyping was performed using Affymetrix® Eureka™ Genotyping protocols. Logistic regression models were used to test the association of risk scores and the outcomes in the PCPT and SELECT trials.

Results

Of the 100 SNPs, 98 designed successfully and genotyping was validated for samples genotyped on other platforms. A number of SNPs predicted for aggressive disease in both trials. Men with a higher polygenic score are more likely to develop prostate cancer in both trials, but the score did not predict for other outcomes in the trial.

Conclusion

Men with a higher polygenic risk score are more likely to develop prostate cancer. There were no interactions of these germline risk SNPs and the chemoprevention agents in the SELECT and PCPT trials.

Genome-wide germline correlates of the epigenetic landscape of prostate cancer

Oncogenesis is driven by germline, environmental and stochastic factors. It is unknown how these interact to produce the molecular phenotypes of tumors. We therefore quantified the influence of germline polymorphisms on the somatic epigenome of 589 localized prostate tumors. Predisposition risk loci influence a tumor's epigenome, uncovering a mechanism for cancer susceptibility. We identified and validated 1,178 loci associated with altered methylation in tumoral but not nonmalignant tissue. These tumor methylation quantitative trait loci influence chromatin structure, as well as RNA and protein abundance. One prominent tumor methylation quantitative trait locus is associated with AKT1 expression and is predictive of relapse after definitive local therapy in both discovery and validation cohorts. These data reveal intricate crosstalk between the germ line and the epigenome of primary tumors, which may help identify germline biomarkers of aggressive disease to aid patient triage and optimize the use of more invasive or expensive diagnostic assays.