Gene regulatory mechanisms underpinning prostate cancer susceptibility

Androgen receptor enhancer usage and the chromatin regulatory landscape in human prostate cancers

The androgen receptor (AR) is commonly known as a key transcription factor in prostate cancer development, progression and therapy resistance. Genome-wide chromatin association studies revealed that transcriptional regulation by AR mainly depends on binding to distal regulatory enhancer elements that control gene expression through chromatin looping to gene promoters. Changes in the chromatin epigenetic landscape and DNA sequence can locally alter AR-DNA-binding capacity and consequently impact transcriptional output and disease outcome. The vast majority of reports describing AR chromatin interactions have been limited to cell lines, identifying numerous other factors and interacting transcription factors that impact AR chromatin interactions. Do these factors also impact AR cistromics - the genome-wide chromatin-binding landscape of AR - in vivo? Recent technological advances now enable researchers to identify AR chromatin-binding sites and their target genes in human specimens. In this review, we provide an overview of the different factors that influence AR chromatin binding in prostate cancer specimens, which is complemented with knowledge from cell line studies. Finally, we discuss novel perspectives on studying AR cistromics in clinical samples.

Upregulation of MicroRNA-21 promotes tumorigenesis of prostate cancer cells by targeting KLF5

Prostate cancer (PCa) is the second frequently newly diagnosed cancer in men. Androgen deprivation therapy has been widely used to inhibit PCa growth but eventually fails in many patients. Androgen receptor and its downstream molecules like microRNAs could be promising therapeutic targets. We aimed to investigate the involvement of miR-21 in PCa tumorigenesis. We found that miR-21 was an unfavorable factor and correlated positively with tumor grade in PCa patients from TCGA database. MiR-21 was more highly expressed in androgen-independent PCa cells than in androgen-dependent PCa cells. Overexpression of miR-21 promoted androgen-dependent and -independent PCa cell proliferation, migration, invasion, and resistance to apoptosis. Furthermore, increased miR-21 expression promoted mouse xenograft growth. We identified nine genes differentially expressed in PCa tumors and normal tissue which could be potential targets of miR-21 by bioinformatic analyses. We demonstrate that miR-21 directly targeted KLF5 and inhibited KLF5 mRNA and protein levels in PCa. STRING and functional enrichment analysis results suggest that GSK3B might be regulated by KLF5. Our findings demonstrate that miR-21 promotes the tumorigenesis of PCa cells by directly targeting KLF5. These biological effects are mediated through upregulation of GSK3B and activation of the AKT signaling pathway.

The Role of HOX Transcription Factors in Cancer Predisposition and Progression

Homeobox (HOX) transcription factors, encoded by a subset of homeodomain superfamily genes, play pivotal roles in many aspects of cellular physiology, embryonic development, and tissue homeostasis. Findings over the past decade have revealed that mutations in HOX genes can lead to increased cancer predisposition, and HOX genes might mediate the effect of many other cancer susceptibility factors by recognizing or executing altered genetic information. Remarkably, several lines of evidence highlight the interplays between HOX transcription factors and cancer risk loci discovered by genome-wide association studies, thereby gaining molecular and biological insight into cancer etiology. In addition, deregulated HOX gene expression impacts various aspects of cancer progression, including tumor angiogenesis, cell autophagy, proliferation, apoptosis, tumor cell migration, and metabolism. In this review, we will discuss the fundamental roles of HOX genes in cancer susceptibility and progression, highlighting multiple molecular mechanisms of HOX involved gene misregulation, as well as their potential implications in clinical practice.

HOXB13 networking with ABCG1/EZH2/Slug mediates metastasis and confers resistance to cisplatin in lung adenocarcinoma patients

Rationale: Distant metastasis and chemoresistance are the major causes of short survival after initial chemotherapy in lung adenocarcinoma patients. However, the underlying mechanisms remain elusive. Our pilot study identified high expression of the homeodomain transcription factor HOXB13 in chemoresistant lung adenocarcinomas. We aimed to investigate the role of HOXB13 in mediating lung adenocarcinoma chemoresistance.

Methods: Immunohistochemistry assays were employed to assess HOXB13 protein levels in 148 non-small cell lung cancer patients. The role of HOXB13 in lung adenocarcinoma progression and resistance to cisplatin therapy was analyzed in cells, xenografted mice, and patient-derived xenografts. Needle biopsies from 15 lung adenocarcinoma patients who were resistant to cisplatin and paclitaxel therapies were analyzed for HOXB13 and EZH2 protein levels using immunohistochemistry.

Results: High expression of HOXB13 observed in 17.8% of the lung adenocarcinoma patients in this study promoted cancer progression and predicted poor prognosis. HOXB13 upregulated an array of metastasis- and drug-resistance-related genes, including ABCG1, EZH2, and Slug, by directly binding to their promoters. Cisplatin induced HOXB13 expression in lung adenocarcinoma cells, and patient-derived xenografts and depletion of ABCG1 enhanced the sensitivity of lung adenocarcinoma cells to cisplatin therapy. Our results suggest that determining the combined expression of HOXB13 and its target genes can predict patient outcomes.

Conclusions: A cisplatin-HOXB13-ABCG1/EZH2/Slug network may account for a novel mechanism underlying cisplatin resistance and metastasis after chemotherapy. Determining the levels of HOXB13 and its target genes from needle biopsy specimens may help predict the sensitivity of lung adenocarcinoma patients to platinum-based chemotherapy and patient outcomes.

Functional genomics reveal gene regulatory mechanisms underlying schizophrenia risk

Genome-wide association studies (GWASs) have identified over 180 independent schizophrenia risk loci. Nevertheless, how the risk variants in the reported loci confer schizophrenia susceptibility remains largely unknown. Here we systematically investigate the gene regulatory mechanisms underpinning schizophrenia risk through integrating data from functional genomics (including 30 ChIP-Seq experiments) and position weight matrix (PWM). We identify 132 risk single nucleotide polymorphisms (SNPs) that disrupt transcription factor binding and we find that 97 of the 132 TF binding-disrupting SNPs are associated with gene expression in human brain tissues. We validate the regulatory effect of some TF binding-disrupting SNPs with reporter gene assays (9 SNPs) and allele-specific expression analysis (10 SNPs). Our study reveals gene regulatory mechanisms affected by schizophrenia risk SNPs (including widespread disruption of POLR2A and CTCF binding) and identifies target genes for mechanistic studies and drug development. Our results can be accessed and visualized at SZDB database ( http://www.szdb.org/ ).

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.

Cancer-specific expression quantitative loci are affected by expression dysregulation

Expression quantitative trait loci (eQTLs) have been touted as the missing piece that can bridge the gap between genetic variants and phenotypes. Over the past decade, we have witnessed a sharp rise of effort in the identification and application of eQTLs. The successful application of eQTLs relies heavily on their reproducibility. The current eQTL databases such as Genotype-Tissue Expression (GTEx) were populated primarily with eQTLs deriving from germline single nucleotide polymorphisms and normal tissue gene expression. The novel scenarios that employ eQTL models for prediction purposes often involve disease phenotypes characterized by altered gene expressions. To evaluate eQTL reproducibility across diverse data sources and the effect of disease-specific gene expression alteration on eQTL identification, we conducted an eQTL study using 5178 samples from The Cancer Genome Atlas (TCGA). We found that the reproducibility of eQTLs between normal and tumor tissues was low in terms of the number of shared eQTLs. However, among the shared eQTLs, the effect directions were generally concordant. This suggests that the source of the gene expression (normal or tumor tissue) has a strong effect on the detectable eQTLs and the effect direction of the eQTLs. Additional analyses demonstrated good directional concordance of eQTLs between GTEx and TCGA. Furthermore, we found that multi-tissue eQTLs may exert opposite effects across multiple tissue types. In summary, our results suggest that eQTL prediction models need to carefully address tissue and disease dependency of eQTLs. Tissue-disease-specific eQTL databases can afford more accurate prediction models for future studies.

ZFX Mediates Non-canonical Oncogenic Functions of the Androgen Receptor Splice Variant 7 in Castrate-Resistant Prostate Cancer

Androgen receptor splice variant 7 (AR-V7) is crucial for prostate cancer progression and therapeutic resistance. We show that, independent of ligand, AR-V7 binds both androgen-responsive elements (AREs) and non-canonical sites distinct from full-length AR (AR-FL) targets. Consequently, AR-V7 not only recapitulates AR-FL's partial functions but also regulates an additional gene expression program uniquely via binding to gene promoters rather than ARE enhancers. AR-V7 binding and AR-V7-mediated activation at these unique targets do not require FOXA1 but rely on ZFX and BRD4. Knockdown of ZFX or select unique targets of AR-V7/ZFX, or BRD4 inhibition, suppresses growth of castration-resistant prostate cancer cells. We also define an AR-V7 direct target gene signature that correlates with AR-V7 expression in primary tumors, differentiates metastatic prostate cancer from normal, and predicts poor prognosis. Thus, AR-V7 has both ARE/FOXA1 canonical and ZFX-directed non-canonical regulatory functions in the evolution of anti-androgen therapeutic resistance, providing information to guide effective therapeutic strategies.

Large-scale transcriptome-wide association study identifies new prostate cancer risk regions

Although genome-wide association studies (GWAS) for prostate cancer (PrCa) have identified more than 100 risk regions, most of the risk genes at these regions remain largely unknown. Here we integrate the largest PrCa GWAS (N = 142,392) with gene expression measured in 45 tissues (N = 4458), including normal and tumor prostate, to perform a multi-tissue transcriptome-wide association study (TWAS) for PrCa. We identify 217 genes at 84 independent 1 Mb regions associated with PrCa risk, 9 of which are regions with no genome-wide significant SNP within 2 Mb. 23 genes are significant in TWAS only for alternative splicing models in prostate tumor thus supporting the hypothesis of splicing driving risk for continued oncogenesis. Finally, we use a Bayesian probabilistic approach to estimate credible sets of genes containing the causal gene at a pre-defined level; this reduced the list of 217 associations to 109 genes in the 90% credible set. Overall, our findings highlight the power of integrating expression with PrCa GWAS to identify novel risk loci and prioritize putative causal genes at known risk loci.

Detecting genome-wide directional effects of transcription factor binding on polygenic disease risk

Biological interpretation of genome-wide association study data frequently involves assessing whether SNPs linked to a biological process, for example, binding of a transcription factor, show unsigned enrichment for disease signal. However, signed annotations quantifying whether each SNP allele promotes or hinders the biological process can enable stronger statements about disease mechanism. We introduce a method, signed linkage disequilibrium profile regression, for detecting genome-wide directional effects of signed functional annotations on disease risk. We validate the method via simulations and application to molecular quantitative trait loci in blood, recovering known transcriptional regulators. We apply the method to expression quantitative trait loci in 48 Genotype-Tissue Expression tissues, identifying 651 transcription factor-tissue associations including 30 with robust evidence of tissue specificity. We apply the method to 46 diseases and complex traits (average n = 290 K), identifying 77 annotation-trait associations representing 12 independent transcription factor-trait associations, and characterize the underlying transcriptional programs using gene-set enrichment analyses. Our results implicate new causal disease genes and new disease mechanisms.

ANO7 is associated with aggressive prostate cancer

Prostate cancer is one of the most common and heritable human cancers. Our aim was to find germline biomarkers that can predict disease outcome. We previously detected predisposing signals at 2q37, the location of the prostate specific ANO7 gene. To investigate, in detail, the associations between the ANO7 gene and PrCa risk and disease aggressiveness, ANO7 was sequenced in castration resistant tumors together with samples from unselected PrCa patients and unaffected males. Two pathogenic variants were discovered and genotyped in 1769 patients and 1711 unaffected males. Expression of ANO7 vs. PrCa aggressiveness was investigated. Different databases along with Swedish and Norwegian cohorts were used for validation. Case–control and aggressive vs. nonaggressive association analyses were performed against risk and/or cancer aggressiveness. The ANO7 mRNA level and patient survival were analyzed using expression data from databases. Variant rs77559646 showed both risk (OR 1.40; p = 0.009, 95% CI 1.09–1.78) and association with aggressive PrCa (Genotype test p = 0.04). It was found to be an eQTL for ANO7 (Linear model p‐values for Finnish patients p = 0.009; Camcap prostate tumor p = 2.53E‐06; Stockholm prostate tumor cohort p = 1.53E‐13). rs148609049 was not associated with risk, but was related to shorter survival (HR 1.56; 95% CI 1.03–2.36). High ANO7 expression was independently linked to poor survival (HR 18.4; 95% CI 1.43–237). ANO7 genotypes correlate with expression and biochemical relapse, suggesting that ANO7 is a potential PrCa susceptibility gene and that its elevated expression correlates with disease severity and outcome.

What's new?

The discovery of germline biomarkers to predict outcome in prostate cancer could greatly aid disease management. One such marker of particular interest in this regard is the prostate‐specific gene ANO7, which previous studies have associated with high‐grade prostate cancer. Here, specific germline ANO7 genotypes were associated with increased prostate cancer risk. In patients, ANO7 expression correlated with disease severity, with elevated expression associated with decreased overall survival. The data suggest that ANO7 is a susceptibility marker in prostate cancer and, with further characterization, could be used to inform patient selection strategies and therapeutic approaches.

Oncogenic regulatory circuits driven by 19q13 rs11672691 underlies prostate cancer aggressiveness

The 19q13 allele rs11672691 has been reproducibly found in association with aggressive form of prostate cancer, yet the underlying mechanism remains totally unknown. We have recently uncovered a mechanism by which rs11672691 influenced a novel oncogenic regulatory circuit, including HOXA2, PCAT19 and CEACAM21, thereby contributing to prostate cancer aggressiveness.

Functional Silencing of HSD17B2 in Prostate Cancer Promotes Disease Progression

PURPOSE

Steroidogenic enzymes are essential for prostate cancer development. Enzymes inactivating potent androgens were not investigated thoroughly, which leads to limited interference strategies for prostate cancer therapy. Here we characterized the clinical relevance, significance, and regulation mechanism of enzyme HSD17B2 in prostate cancer development.

EXPERIMENTAL DESIGN

HSD17B2 expression was detected with patient specimens and prostate cancer cell lines. Function of HSD17B2 in steroidogenesis, androgen receptor (AR) signaling, and tumor growth was investigated with prostate cancer cell lines and a xenograft model. DNA methylation and mRNA alternative splicing were investigated to unveil the mechanisms of HSD17B2 regulation.

RESULTS

HSD17B2 expression was reduced as prostate cancer progressed. 17βHSD2 decreased potent androgen production by converting testosterone (T) or dihydrotestosterone (DHT) to each of their upstream precursors. HSD17B2 overexpression suppressed androgen-induced cell proliferation and xenograft growth. Multiple mechanisms were involved in HSD17B2 functional silencing including DNA methylation and mRNA alternative splicing. DNA methylation decreased the HSD17B2 mRNA level. Two new catalytic-deficient isoforms, generated by alternative splicing, bound to wild-type 17βHSD2 and promoted its degradation. Splicing factors SRSF1 and SRSF5 participated in the generation of new isoforms.

CONCLUSIONS

Our findings provide evidence of the clinical relevance, significance, and regulation of HSD17B2 in prostate cancer progression, which might provide new strategies for clinical management by targeting the functional silencing mechanisms of HSD17B2.See related commentary by Mostaghel, p. 1139.

Cancer expression quantitative trait loci (eQTLs) can be determined from heterogeneous tumor gene expression data by modeling variation in tumor purity

Expression quantitative trait loci (eQTLs) identified using tumor gene expression data could affect gene expression in cancer cells, tumor-associated normal cells, or both. Here, we have demonstrated a method to identify eQTLs affecting expression in cancer cells by modeling the statistical interaction between genotype and tumor purity. Only one third of breast cancer risk variants, identified as eQTLs from a conventional analysis, could be confidently attributed to cancer cells. The remaining variants could affect cells of the tumor microenvironment, such as immune cells and fibroblasts. Deconvolution of tumor eQTLs will help determine how inherited polymorphisms influence cancer risk, development, and treatment response.

Biology and Clinical Implications of the 19q13 Aggressive Prostate Cancer Susceptibility Locus

Genome-wide association studies (GWAS) have identified rs11672691 at 19q13 associated with aggressive prostate cancer (PCa). Here, we independently confirmed the finding in a cohort of 2,738 PCa patients and discovered the biological mechanism underlying this association. We found an association of the aggressive PCa-associated allele G of rs11672691 with elevated transcript levels of two biologically plausible candidate genes, PCAT19 and CEACAM21, implicated in PCa cell growth and tumor progression. Mechanistically, rs11672691 resides in an enhancer element and alters the binding site of HOXA2, a novel oncogenic transcription factor with prognostic potential in PCa. Remarkably, CRISPR/Cas9-mediated single-nucleotide editing showed the direct effect of rs11672691 on PCAT19 and CEACAM21 expression and PCa cellular aggressive phenotype. Clinical data demonstrated synergistic effects of rs11672691 genotype and PCAT19/CEACAM21 gene expression on PCa prognosis. These results provide a plausible mechanism for rs11672691 associated with aggressive PCa and thus lay the ground work for translating this finding to the clinic.

ATR inhibition controls aggressive prostate tumors deficient in Y-linked histone demethylase KDM5D

Epigenetic modifications control cancer development and clonal evolution in various cancer types. Here, we show that loss of the male-specific histone demethylase lysine-specific demethylase 5D (KDM5D) encoded on the Y chromosome epigenetically modifies histone methylation marks and alters gene expression, resulting in aggressive prostate cancer. Fluorescent in situ hybridization demonstrated that segmental or total deletion of the Y chromosome in prostate cancer cells is one of the causes of decreased KDM5D mRNA expression. The result of ChIP-sequencing analysis revealed that KDM5D preferably binds to promoter regions with coenrichment of the motifs of crucial transcription factors that regulate the cell cycle. Loss of KDM5D expression with dysregulated H3K4me3 transcriptional marks was associated with acceleration of the cell cycle and mitotic entry, leading to increased DNA-replication stress. Analysis of multiple clinical data sets reproducibly showed that loss of expression of KDM5D confers a poorer prognosis. Notably, we also found stress-induced DNA damage on the serine/threonine protein kinase ATR with loss of KDM5D. In KDM5D-deficient cells, blocking ATR activity with an ATR inhibitor enhanced DNA damage, which led to subsequent apoptosis. These data start to elucidate the biological characteristics resulting from loss of KDM5D and also provide clues for a potential novel therapeutic approach for this subset of aggressive prostate cancer.

Putative bovine topological association domains and CTCF binding motifs can reduce the search space for causative regulatory variants of complex traits

BACKGROUND

Topological association domains (TADs) are chromosomal domains characterised by frequent internal DNA-DNA interactions. The transcription factor CTCF binds to conserved DNA sequence patterns called CTCF binding motifs to either prohibit or facilitate chromosomal interactions. TADs and CTCF binding motifs control gene expression, but they are not yet well defined in the bovine genome. In this paper, we sought to improve the annotation of bovine TADs and CTCF binding motifs, and assess whether the new annotation can reduce the search space for cis-regulatory variants.

RESULTS

We used genomic synteny to map TADs and CTCF binding motifs from humans, mice, dogs and macaques to the bovine genome. We found that our mapped TADs exhibited the same hallmark properties of those sourced from experimental data, such as housekeeping genes, transfer RNA genes, CTCF binding motifs, short interspersed elements, H3K4me3 and H3K27ac. We showed that runs of genes with the same pattern of allele-specific expression (ASE) (either favouring paternal or maternal allele) were often located in the same TAD or between the same conserved CTCF binding motifs. Analyses of variance showed that when averaged across all bovine tissues tested, TADs explained 14% of ASE variation (standard deviation, SD: 0.056), while CTCF explained 27% (SD: 0.078). Furthermore, we showed that the quantitative trait loci (QTLs) associated with gene expression variation (eQTLs) or ASE variation (aseQTLs), which were identified from mRNA transcripts from 141 lactating cows' white blood and milk cells, were highly enriched at putative bovine CTCF binding motifs. The linearly-furthermost, and most-significant aseQTL and eQTL for each genic target were located within the same TAD as the gene more often than expected (Chi-Squared test P-value < 0.001).

CONCLUSIONS

Our results suggest that genomic synteny can be used to functionally annotate conserved transcriptional components, and provides a tool to reduce the search space for causative regulatory variants in the bovine genome.

High-throughput screening of prostate cancer risk loci by single nucleotide polymorphisms sequencing

Functional characterization of disease-causing variants at risk loci has been a significant challenge. Here we report a high-throughput single-nucleotide polymorphisms sequencing (SNPs-seq) technology to simultaneously screen hundreds to thousands of SNPs for their allele-dependent protein-binding differences. This technology takes advantage of higher retention rate of protein-bound DNA oligos in protein purification column to quantitatively sequence these SNP-containing oligos. We apply this technology to test prostate cancer-risk loci and observe differential allelic protein binding in a significant number of selected SNPs. We also test a unique application of self-transcribing active regulatory region sequencing (STARR-seq) in characterizing allele-dependent transcriptional regulation and provide detailed functional analysis at two risk loci (RGS17 and ASCL2). Together, we introduce a powerful high-throughput pipeline for large-scale screening of functional SNPs at disease risk loci.

Functional characterization of disease-causing variants at risk loci in cancer is challenging. Here, in prostate cancer the authors report a pipeline for high-throughput single-nucleotide polymorphisms sequencing (SNPs-seq) for large scale screening of functional SNPs at disease risk loci.

The Heterogeneity of Prostate Cancer: A Practical Approach

Prostate cancer is a paradigm tumor model for heterogeneity in almost every sense. Its clinical, spatial, and morphological heterogeneity divided by the high-level molecular genetic diversity outline the complexity of this disease in the clinical and research settings. In this review, we summarize the main aspects of prostate cancer heterogeneity at different levels, with special attention given to the spatial heterogeneity within the prostate, and to the standard morphological heterogeneity, with respect to tumor grading and modern classifications. We also cover the complex issue of molecular genetic heterogeneity, discussing it in the context of the current evidence of the genetic characterization of prostate carcinoma; the interpatient, intertumoral (multifocal disease), and intratumoral heterogeneity; tumor clonality; and metastatic disease. Clinical and research implications are summarized and serve to address the most pertinent problems stemming from the extreme heterogeneity of prostate cancer.

A Prostate Cancer Risk Element Functions as a Repressive Loop that Regulates HOXA13

Prostate cancer (PCa) is the leading cancer among men in the United States, with genetic factors contributing to ∼42% of the susceptibility to PCa. We analyzed a PCa risk region located at 7p15.2 to gain insight into the mechanisms by which this noncoding region may affect gene regulation and contribute to PCa risk. We performed Hi-C analysis and demonstrated that this region has long-range interactions with the HOXA locus, located ∼873 kb away. Using the CRISPR/Cas9 system, we deleted a 4-kb region encompassing several PCa risk-associated SNPs and performed RNA-seq to investigate transcriptomic changes in prostate cells lacking the regulatory element. Our results suggest that the risk element affects the expression of HOXA13 and HOTTIP, but not other genes in the HOXA locus, via a repressive loop. Forced expression of HOXA13 was performed to gain further insight into the mechanisms by which this risk element affects PCa risk.

Systematic identification of regulatory variants associated with cancer risk

Background

Most cancer risk-associated single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) are noncoding and it is challenging to assess their functional impacts. To systematically identify the SNPs that affect gene expression by modulating activities of distal regulatory elements, we adapt the self-transcribing active regulatory region sequencing (STARR-seq) strategy, a high-throughput technique to functionally quantify enhancer activities.

Results

From 10,673 SNPs linked with 996 cancer risk-associated SNPs identified in previous GWAS studies, we identify 575 SNPs in the fragments that positively regulate gene expression, and 758 SNPs in the fragments with negative regulatory activities. Among them, 70 variants are regulatory variants for which the two alleles confer different regulatory activities. We analyze in depth two regulatory variants—breast cancer risk SNP rs11055880 and leukemia risk-associated SNP rs12142375—and demonstrate their endogenous regulatory activities on expression of ATF7IP and PDE4B genes, respectively, using a CRISPR-Cas9 approach.

Conclusions

By identifying regulatory variants associated with cancer susceptibility and studying their molecular functions, we hope to help the interpretation of GWAS results and provide improved information for cancer risk assessment.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1322-z) contains supplementary material, which is available to authorized users.

Network-directed cis-mediator analysis of normal prostate tissue expression profiles reveals downstream regulatory associations of prostate cancer susceptibility loci

Large-scale genome-wide association studies have identified multiple single-nucleotide polymorphisms associated with risk of prostate cancer. Many of these genetic variants are presumed to be regulatory in nature; however, follow-up expression quantitative trait loci (eQTL) association studies have to-date been restricted largely to cis-acting associations due to study limitations. While trans-eQTL scans suffer from high testing dimensionality, recent evidence indicates most trans-eQTL associations are mediated by cis-regulated genes, such as transcription factors. Leveraging a data-driven gene co-expression network, we conducted a comprehensive cis-mediator analysis using RNA-Seq data from 471 normal prostate tissue samples to identify downstream regulatory associations of previously identified prostate cancer risk variants. We discovered multiple trans-eQTL associations that were significantly mediated by cis-regulated transcripts, four of which involved risk locus 17q12, proximal transcription factor HNF1B, and target trans-genes with known HNF response elements (MIA2, SRC, SEMA6A, KIF12). We additionally identified evidence of cis-acting down-regulation of MSMB via rs10993994 corresponding to reduced co-expression of NDRG1. The majority of these cis-mediator relationships demonstrated trans-eQTL replicability in 87 prostate tissue samples from the Gene-Tissue Expression Project. These findings provide further biological context to known risk loci and outline new hypotheses for investigation into the etiology of prostate cancer.

Rationale for the development of alternative forms of androgen deprivation therapy

With few exceptions, the almost 30,000 prostate cancer deaths annually in the United States are due to failure of androgen deprivation therapy. Androgen deprivation therapy prevents ligand-activation of the androgen receptor. Despite initial remission after androgen deprivation therapy, prostate cancer almost invariably progresses while continuing to rely on androgen receptor action. Androgen receptor's transcriptional output, which ultimately controls prostate cancer behavior, is an alternative therapeutic target, but its molecular regulation is poorly understood. Recent insights in the molecular mechanisms by which the androgen receptor controls transcription of its target genes are uncovering gene specificity as well as context-dependency. Heterogeneity in the androgen receptor's transcriptional output is reflected both in its recruitment to diverse cognate DNA binding motifs and in its preferential interaction with associated pioneering factors, other secondary transcription factors and coregulators at those sites. This variability suggests that multiple, distinct modes of androgen receptor action that regulate diverse aspects of prostate cancer biology and contribute differentially to prostate cancer's clinical progression are active simultaneously in prostate cancer cells. Recent progress in the development of peptidomimetics and small molecules, and application of Chem-Seq approaches indicate the feasibility for selective disruption of critical protein-protein and protein-DNA interactions in transcriptional complexes. Here, we review the recent literature on the different molecular mechanisms by which the androgen receptor transcriptionally controls prostate cancer progression, and we explore the potential to translate these insights into novel, more selective forms of therapies that may bypass prostate cancer's resistance to conventional androgen deprivation therapy.

Impact of novel miR-145-3p regulatory networks on survival in patients with castration-resistant prostate cancer

BACKGROUND

Despite recent advancements, metastatic castration-resistant prostate cancer (CRPC) is not considered curative. Novel approaches for identification of therapeutic targets of CRPC are needed.

METHODS

Next-generation sequencing revealed 945-1248 miRNAs from each lethal mCRPC sample. We constructed miRNA expression signatures of CRPC by comparing the expression of miRNAs between CRPC and normal prostate tissue or hormone-sensitive prostate cancer (HSPC). Genome-wide gene expression studies and in silico analyses were carried out to predict miRNA regulation and investigate the functional significance and clinical utility of the novel oncogenic pathways regulated by these miRNAs in prostate cancer (PCa).

RESULTS

Based on the novel miRNA expression signature of CRPC, miR-145-5p and miR-145-3p were downregulated in CRPC. By focusing on miR-145-3p, which is a passenger strand and has not been well studied in previous reports, we showed that miR-145-3p targeted 4 key molecules, i.e., MELK, NCAPG, BUB1, and CDK1, in CPRC. These 4 genes significantly predicted survival in patients with PCa.

CONCLUSIONS

Small RNA sequencing for lethal CRPC and in silico analyses provided novel therapeutic targets for CRPC.

Genetic association analysis of the RTK/ERK pathway with aggressive prostate cancer highlights the potential role of CCND2 in disease progression

The RTK/ERK signaling pathway has been implicated in prostate cancer progression. However, the genetic relevance of this pathway to aggressive prostate cancer at the SNP level remains undefined. Here we performed a SNP and gene-based association analysis of the RTK/ERK pathway with aggressive prostate cancer in a cohort comprising 956 aggressive and 347 non-aggressive cases. We identified several loci including rs3217869/CCND2 within the pathway shown to be significantly associated with aggressive prostate cancer. Our functional analysis revealed a statistically significant relationship between rs3217869 risk genotype and decreased CCND2 expression levels in a collection of 119 prostate cancer patient samples. Reduced expression of CCND2 promoted cell proliferation and its overexpression inhibited cell growth of prostate cancer. Strikingly, CCND2 downregulation was consistently observed in the advanced prostate cancer in 18 available clinical data sets with a total amount of 1,095 prostate samples. Furthermore, the lower expression levels of CCND2 markedly correlated with prostate tumor progression to high Gleason score and elevated PSA levels, and served as an independent predictor of biochemical relapse and overall survival in a large cohort of prostate cancer patients. Together, we have identified an association of genetic variants and genes in the RTK/ERK pathway with prostate cancer aggressiveness, and highlighted the potential importance of CCND2 in prostate cancer susceptibility and tumor progression to metastasis.

Genomic Insight into the Role of lncRNA in Cancer Susceptibility

With the development of advanced genomic methods, a large amount of long non-coding RNAs (lncRNAs) has been found to be important for cancer initiation and progression. Given that most of the genome-wide association study (GWAS)-identified cancer risk SNPs are located in the noncoding region, the expression and function of lncRNAs are more likely to be affected by the SNPs. The SNPs may affect the expression of lncRNAs directly through disrupting the binding of transcription factors or indirectly by affecting the expression of regulatory factors. Moreover, SNPs may disrupt the interaction between lncRNAs and other RNAs or proteins. Unveiling the relationship of lncRNA, protein-coding genes, transcription factors and miRNAs from the angle of genomics will improve the accuracy of disease prediction and help find new therapeutic targets.

Identifying subtype-specific associations between gene expression and DNA methylation profiles in breast cancer

BACKGROUND

Breast cancer is a complex disease in which different genomic patterns exists depending on different subtypes. Recent researches present that multiple subtypes of breast cancer occur at different rates, and play a crucial role in planning treatment. To better understand underlying biological mechanisms on breast cancer subtypes, investigating the specific gene regulatory system via different subtypes is desirable.

METHODS

Gene expression, as an intermediate phenotype, is estimated based on methylation profiles to identify the impact of epigenomic features on transcriptomic changes in breast cancer. We propose a kernel weighted l1-regularized regression model to incorporate tumor subtype information and further reveal gene regulations affected by different breast cancer subtypes. For the proper control of subtype-specific estimation, samples from different breast cancer subtype are learned at different rate based on target estimates. Kolmogorov Smirnov test is conducted to determine learning rate of each sample from different subtype.

RESULTS

It is observed that genes that might be sensitive to breast cancer subtype show prediction improvement when estimated using our proposed method. Comparing to a standard method, overall performance is also enhanced by incorporating tumor subtypes. In addition, we identified subtype-specific network structures based on the associations between gene expression and DNA methylation.

CONCLUSIONS

In this study, kernel weighted lasso model is proposed for identifying subtype-specific associations between gene expressions and DNA methylation profiles. Identification of subtype-specific gene expression associated with epigenomic changes might be helpful for better planning treatment and developing new therapies.

An Integrative Genomics Approach for Associating Genome-Wide Association Studies Information With Localized and Metastatic Prostate Cancer Phenotypes

High-throughput genotyping has enabled discovery of genetic variants associated with an increased risk of developing prostate cancer using genome-wide association studies (GWAS). The goal of this study was to associate GWAS information of patients with primary organ–confined and metastatic prostate cancer using gene expression data and to identify molecular networks and biological pathways enriched for genetic susceptibility variants involved in the 2 disease states. The analysis revealed gene signatures for the 2 disease states and a gene signature distinguishing the 2 patient groups. In addition, the analysis revealed molecular networks and biological pathways enriched for genetic susceptibility variants. The discovered pathways include the androgen, apoptosis, and insulinlike growth factor signaling pathways. This analysis established putative functional bridges between GWAS discoveries and the biological pathways involved in primary organ–confined and metastatic prostate cancer.

Bromodomain protein 4 discriminates tissue-specific super-enhancers containing disease-specific susceptibility loci in prostate and breast cancer

BACKGROUND

Epigenetic information can be used to identify clinically relevant genomic variants single nucleotide polymorphisms (SNPs) of functional importance in cancer development. Super-enhancers are cell-specific DNA elements, acting to determine tissue or cell identity and driving tumor progression. Although previous approaches have been tried to explain risk associated with SNPs in regulatory DNA elements, so far epigenetic readers such as bromodomain containing protein 4 (BRD4) and super-enhancers have not been used to annotate SNPs. In prostate cancer (PC), androgen receptor (AR) binding sites to chromatin have been used to inform functional annotations of SNPs.

RESULTS

Here we establish criteria for enhancer mapping which are applicable to other diseases and traits to achieve the optimal tissue-specific enrichment of PC risk SNPs. We used stratified Q-Q plots and Fisher test to assess the differential enrichment of SNPs mapping to specific categories of enhancers. We find that BRD4 is the key discriminant of tissue-specific enhancers, showing that it is more powerful than AR binding information to capture PC specific risk loci, and can be used with similar effect in breast cancer (BC) and applied to other diseases such as schizophrenia.

CONCLUSIONS

This is the first study to evaluate the enrichment of epigenetic readers in genome-wide associations studies for SNPs within enhancers, and provides a powerful tool for enriching and prioritizing PC and BC genetic risk loci. Our study represents a proof of principle applicable to other diseases and traits that can be used to redefine molecular mechanisms of human phenotypic variation.

Foxa1 gene and protein in developing rat eccrine sweat glands

To investigate the development of eccrine sweat glands and the expression of Foxa1 genes and proteins in the course of development, the footpads from E15.5 to E21.5, P1-P12, P14, P21, P28 and P56 rats were subjected to immunofluorescence staining of FoxA1 and double immunofluorescence staining of K14/α-SMA, FoxA1/K7 and FoxA1/α-SMA, and were processed for Foxa1 gene detection by RT-qPCR. The results showed that rat eccrine sweat gland germs was first observed emerging from the basal layer of epidermis at E19.5, and then elongated downward into the dermis, forming straight ducts by E21.5. Early development of the secretory segments appeared at P1. The Foxa1 gene was not expressed in rat footpads until P2, but from P2 to P5, its expression up-regulated sharply, and thereafter maintained at a high level until adulthood. FoxA1 protein was first observed at P6 in eccrine sweat glands, four days after initial detection of Foxa1 gene transcripts. In skin, FoxA1-positive cells were present exclusively in secretory coils, with 95% being K7-positive secretory cells and 5% being α-SMA-positive myoepithelial cells. We conclude that Foxa1 can be used as a marker of eccrine sweat glands in skin and also as a marker of secretory coils, and Foxa1 is related to the development of secretory coils.

Association of Family History of Type 2 Diabetes with Prostate Cancer: A National Cohort Study

Background

Personal history of type 2 diabetes mellitus (T2DM) is associated with a lower incidence of prostate cancer, but the underlying mechanisms are largely unknown. We hypothesized that genetic factors that are involved in the development of T2DM might protect against prostate cancer.

Methods

We used a few Swedish registers, including the Swedish Multigeneration Register and the Cancer Register, to examine the risk of prostate cancer among men with a family history of T2DM. Standardized incidence ratios were used to calculate the relative risk.

Results

The overall risk of prostate cancer among men with a familial history of T2DM was 0.87 (95% CI: 0.86–0.89) as compared to matched controls. The risk was even lower for those multiple affected relatives with T2DM, and it was 0.86 for those with two affected relatives and 0.67 for those with three and more affected relatives.

Conclusion

Family history of T2DM was associated with a lower incidence of prostate cancer, and the risk was even lower for those with more than one affected relative. Our study strongly suggests that genetic factors or shared familial factors, such as obesity, that contributed to T2DM may protect against prostate cancer.