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The aryl hydrocarbon receptor (AHR) is a nuclear receptor that modulates the response to environmental stimuli. It was recognized historically for its role in toxicology but, in recent decades, it has been increasingly recognized as an important modulator of disease-especially for its role in modulating immune and inflammatory responses. AHR has been implicated in many diseases that are driven by immune/inflammatory processes, including major depressive disorder, multiple sclerosis, rheumatoid arthritis, asthma, and allergic responses, among others. The mechanisms by which AHR has been suggested to impact immune/inflammatory diseases include targeted gene expression and altered immune differentiation. It has been suggested that single nucleotide polymorphisms (SNPs) that are near AHR-regulated genes may contribute to AHR-dependent disease mechanisms/pathways. Further, we have found that SNPs that are outside of nuclear receptor binding sites (i.e., outside of AHR response elements (AHREs)) may contribute to AHR-dependent gene regulation in a SNP- and ligand-dependent manner. This review will discuss the evidence and mechanisms of AHR contributions to immune/inflammatory diseases and will consider the possibility that SNPs that are outside of AHR binding sites might contribute to AHR ligand-dependent inter-individual variation in disease pathophysiology and response to pharmacotherapeutics.

Pharmacogenomics is the use of genomic and other “omic” information to individualize drug selection and drug use to avoid adverse drug reactions and to maximize drug efficacy. The science underlying pharmacogenomics has evolved rapidly over the 50 years since it was first suggested that genetics might influence drug response phenotypes. That process has occurred in parallel with advances in DNA sequencing and other molecular technologies, with striking increases in our understanding of the human genome. There are now many validated examples of the clinical utility of pharmacogenomics, and this type of clinical genomic information is increasingly being generated in clinical laboratories, incorporated into electronic health records, and used to “tailor” or individualize drug therapy. This review will survey the origins and development of pharmacogenomics; it will address some of the challenges associated with the clinical implementation of pharmacogenomics; and it will attempt to foresee future advances in this important genomic discipline, one that almost certainly will be among the earliest and most widely adopted aspects of clinical genomics.

Triple-negative breast cancer (TNBC) represents the most malignant subtype of breast cancer. The clinical application of PARP inhibitors (PARPi) is limited by the low frequency of BRCA1/2 mutations in TNBC. Here, we identified that MTAP deletion sensitized genotoxic agents in our clinical cohort of metastatic TNBC. Further study demonstrated that MTAP deficiency or inhibition rendered TNBC susceptibility to chemotherapeutic agents, particularly PARPi. Mechanistically, targeting MTAP that synergized with PARPi by disrupting the METTL16-MAT2A axis involved in methionine metabolism and depleting in vivo s-adenosylmethionine (SAM) levels. Exhausted SAM in turn impaired PARPi-induced DNA damage repair through attenuation of MRE11 recruitment and end resection by diminishing MRE11 methylation. Notably, brain metastatic TNBC markedly benefited from a lower dose of PARPi and MTAP deficiency/inhibition synergy due to the inherently limited methionine environment in the brain. Collectively, our findings revealed a feed-forward loop between methionine metabolism and DNA repair through SAM, highlighting a therapeutic strategy of PARPi combined with MTAP deficiency/inhibition for TNBC.

Background Our previous genome-wide association study using the MA.27 aromatase inhibitors adjuvant trial identified SNPs in the long noncoding RNA MIR2052HG associated with breast cancer-free interval. MIR2052HG maintained ERα both by promoting AKT/FOXO3-mediated ESR1 transcription and by limiting ubiquitin-mediated ERα degradation. Our goal was to further elucidate MIR2052HG’s mechanism of action. Methods RNA-binding protein immunoprecipitation assays were performed to demonstrate that the transcription factor, early growth response protein 1 (EGR1), worked together with MIR2052HG to regulate that lemur tyrosine kinase-3 (LMTK3) transcription in MCF7/AC1 and CAMA-1 cells. The location of EGR1 on the LMTK3 gene locus was mapped using chromatin immunoprecipitation assays. The co-localization of MIR2052HG RNA and the LMTK3 gene locus was determined using RNA-DNA dual fluorescent in situ hybridization. Single-nucleotide polymorphisms (SNP) effects were evaluated using a panel of human lymphoblastoid cell lines. Results MIR2052HG depletion in breast cancer cells results in a decrease in LMTK3 expression and cell growth. Mechanistically, MIR2052HG interacts with EGR1 and facilitates its recruitment to the LMTK3 promoter. LMTK3 sustains ERα levels by reducing protein kinase C (PKC) activity, resulting in increased ESR1 transcription mediated through AKT/FOXO3 and reduced ERα degradation mediated by the PKC/MEK/ERK/RSK1 pathway. MIR2052HG regulated LMTK3 in a SNP- and aromatase inhibitor-dependent fashion: the variant SNP increased EGR1 binding to LMTK3 promoter in response to androstenedione, relative to wild-type genotype, a pattern that can be reversed by aromatase inhibitor treatment. Finally, LMTK3 overexpression abolished the effect of MIR2052HG on PKC activity and ERα levels. Conclusions Our findings support a model in which the MIR2052HG regulates LMTK3 via EGR1, and LMTK3 regulates ERα stability via the PKC/MEK/ERK/RSK1 axis. These results reveal a direct role of MIR2052HG in LMTK3 regulation and raise the possibilities of targeting MIR2052HG or LMTK3 in ERα-positive breast cancer.

Inflammation is an important biological process which contributes to risk for depression, in part as a result of the production of proinflammatory cytokines and of alterations in glutamatergic neurotransmission. Ketamine has anti-inflammatory properties which might contribute to its antidepressant effects. This study was designed to clarify mechanisms of action for ketamine and its active metabolites, (2 )-hydroxynorketamine (HNK), which also appear to play a major role in ketamine's rapid antidepressant effects. An HMC3 human microglial cell line was used as a model system to test a possible role for ketamine in immune response regulation that might contribute to its antidepressant effects. Our results highlight the fact that ketamine and its two active metabolites can regulate the type I interferon pathway mediated, at least partially, through signal transducer and activation of transcription 3 (STAT3) which plays a major role in the immune response. Specifically, STAT3 downstream genes that were modulated by either ketamine or its active metabolites were enriched in the \"response to type I interferon\" pathway. Our data also suggest that STAT3 might play a role in ketamine's antidepressant effects, mediated, at least in part, through eukaryotic elongation factor 2 (EEF2), resulting in the augmentation of brain-derived neurotropic factor (BDNF) expression and promoting the synthesis of synaptic proteins postsynaptic density protein 95 (PSD95) and synapsin I (SYN1).

Bipolar disorder (BD) and obesity are highly comorbid. We previously performed a genome-wide association study (GWAS) for BD risk accounting for the effect of body mass index (BMI), which identified a genome-wide significant single-nucleotide polymorphism (SNP) in the gene encoding the transcription factor 7 like 2 (TCF7L2). However, the molecular function of TCF7L2 in the central nervous system (CNS) and its possible role in the BD and BMI interaction remained unclear. In the present study, we demonstrated by studying human induced pluripotent stem cell (hiPSC)-derived astrocytes, cells that highly express TCF7L2 in the CNS, that the BD-BMI GWAS risk SNP is associated with glucocorticoid-dependent repression of the expression of a previously uncharacterized TCF7L2 transcript variant. That transcript is a long non-coding RNA (lncRNA-TCF7L2) that is highly expressed in the CNS but not in peripheral tissues such as the liver and pancreas that are involved in metabolism. In astrocytes, knockdown of the lncRNA-TCF7L2 resulted in decreased expression of the parent gene, TCF7L2, as well as alterations in the expression of a series of genes involved in insulin signaling and diabetes. We also studied the function of TCF7L2 in hiPSC-derived astrocytes by integrating RNA sequencing data after TCF7L2 knockdown with TCF7L2 chromatin-immunoprecipitation sequencing (ChIP-seq) data. Those studies showed that TCF7L2 directly regulated a series of BD risk genes. In summary, these results support the existence of a CNS-based mechanism underlying BD-BMI genetic risk, a mechanism based on a glucocorticoid-dependent expression quantitative trait locus that regulates the expression of a novel TCF7L2 non-coding transcript.

We present Knowledge Engine for Genomics (KnowEnG), a free-to-use computational system for analysis of genomics data sets, designed to accelerate biomedical discovery. It includes tools for popular bioinformatics tasks such as gene prioritization, sample clustering, gene set analysis, and expression signature analysis. The system specializes in \"knowledge-guided\" data mining and machine learning algorithms, in which user-provided data are analyzed in light of prior information about genes, aggregated from numerous knowledge bases and encoded in a massive \"Knowledge Network.\" KnowEnG adheres to \"FAIR\" principles (findable, accessible, interoperable, and reuseable): its tools are easily portable to diverse computing environments, run on the cloud for scalable and cost-effective execution, and are interoperable with other computing platforms. The analysis tools are made available through multiple access modes, including a web portal with specialized visualization modules. We demonstrate the KnowEnG system's potential value in democratization of advanced tools for the modern genomics era through several case studies that use its tools to recreate and expand upon the published analysis of cancer data sets.

The cytochromes P450 (CYPs) represent a large gene superfamily that plays an important role in the metabolism of both exogenous and endogenous compounds. We have reported that the testis-specific Y-encoded-like proteins (TSPYLs) are novel CYP gene transcriptional regulators. However, little is known of mechanism(s) by which TSPYLs regulate CYP expression or the functional consequences of that regulation. The TSPYL gene family includes six members, TSPYL1 to TSPYL6 . However, TSPYL3 is a pseudogene, TSPYL5 is only known to regulates the expression of CYP19A1 , and TSPYL6 is expressed exclusively in the testis. Therefore, TSPYL 1, 2 and 4 were included in the present study. To better understand how TSPYL1, 2, and 4 might influence CYP expression, we performed a series of pull-downs and mass spectrometric analyses. Panther pathway analysis of the 2272 pulled down proteins for all 3 TSPYL isoforms showed that the top five pathways were the Wnt signaling pathway, the Integrin signaling pathway, the Gonadotropin releasing hormone receptor pathway, the Angiogenesis pathway and Inflammation mediated by chemokines and cytokines. Specifically, we observed that 177 Wnt signaling pathway proteins were pulled down with the TSPYLs. Subsequent luciferase assays showed that TSPYL1 knockdown had a greater effect on the activation of Wnt signaling than did TSPYL2 or TSPYL4 knockdown. Therefore, in subsequent experiments, we focused our attention on TSPYL1. HepaRG cell qRT-PCR showed that TSPYL1 regulated the expression of CYPs involved in cholesterol-metabolism such as CYP1B1 and CYP7A1. Furthermore, TSPYL1 and β-catenin regulated CYP1B1 expression in opposite directions and TSPYL1 appeared to regulate CYP1B1 expression by blocking β-catenin binding to the TCF7L2 transcription factor on the CYP1B1 promoter. In β-catenin and TSPYL1 double knockdown cells, CYP1B1 expression and the generation of CYP1B1 downstream metabolites such as 20-HETE could be restored. Finally, we observed that TSPYL1 expression was associated with plasma cholesterol levels and BMI during previous clinical studies of obesity. In conclusion, this series of experiments has revealed a novel mechanism for regulation of the expression of cholesterol-metabolizing CYPs, particularly CYP1B1, by TSPYL1 via Wnt/β-catenin signaling, raising the possibility that TSPYL1 might represent a molecular target for influencing cholesterol homeostasis.

Background Endocrine therapy is the most important treatment modality of breast cancer patients whose tumors express the estrogen receptor α (ERα). The androgen receptor (AR) is also expressed in the vast majority (80–90%) of ERα-positive tumors. AR-targeting drugs are not used in clinical practice, but have been evaluated in multiple trials and preclinical studies. Methods We performed a genome-wide study to identify hormone/drug-induced single nucleotide polymorphism (SNP) genotype - dependent gene-expression, known as PGx-eQTL, mediated by either an AR agonist (dihydrotestosterone) or a partial antagonist (enzalutamide), utilizing a previously well characterized lymphoblastic cell line panel. The association of the identified SNPs-gene pairs with breast cancer phenotypes were then examined using three genome-wide association (GWAS) studies that we have published and other studies from the GWAS catalog. Results We identified 13 DHT-mediated PGx-eQTL loci and 23 Enz-mediated PGx-eQTL loci that were associated with breast cancer outcomes post ER antagonist or aromatase inhibitors (AI) treatment, or with pharmacodynamic (PD) effects of AIs. An additional 30 loci were found to be associated with cancer risk and sex-hormone binding globulin levels. The top loci involved the genes IDH2 and TMEM9, the expression of which were suppressed by DHT in a PGx-eQTL SNP genotype-dependent manner. Both of these genes were overexpressed in breast cancer and were associated with a poorer prognosis. Therefore, suppression of these genes by AR agonists may benefit patients with minor allele genotypes for these SNPs. Conclusions We identified AR-related PGx-eQTL SNP-gene pairs that were associated with risks, outcomes and PD effects of endocrine therapy that may provide potential biomarkers for individualized treatment of breast cancer.