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Most patients with metastatic prostate cancer eventually develop resistance to primary androgen deprivation therapy. To identify predictive biomarker for Abiraterone acetate/prednisone resistance, we screened alternative splice variants between responders and non-responders from the PROMOTE clinical study and pinned down the most significant variant, CENPK-delta8. Through preclinical patient-derived mouse xenograft (PDX) and 3D organoids obtained from responders and non-responders, as well as in vitro models, aberrant CENPK-delta8 expression was determined to link to drug resistance via enhanced migration and proliferation. The FLNA and FLOT1 were observed to specifically bind to CENK-delta8 rather than wild-type CENPK, underscoring the role of CENPK-delta8 in cytoskeleton organization and cell migration. Our study, leveraging data from the PROMOTE study, TCGA, and TCGA SpliceReq databases, highlights the important function of alternative splice variants in drug response and their potential to be prognostic biomarkers for improving individual therapeutic outcomes in precision medicine.

Acamprosate is a Food and Drug Administration (FDA) approved medication for the treatment of alcohol use disorder (AUD). However, only a subset of patients achieves optimal treatment outcomes. Currently, no biological measures are utilized to predict response to acamprosate treatment. We applied our established pharmaco-omics informed genomics strategy to identify potential biomarkers associated with acamprosate treatment response. Specifically, our previous open-label acamprosate clinical trial recruited 442 patients with AUD who were treated with acamprosate for three months. We first performed proteomics using baseline plasma samples to identify potential biomarkers associated with acamprosate treatment outcomes. Next, we applied our established "proteomics-informed genome-wide association study (GWAS)" research strategy, and identified 12 proteins, including interleukin-17 receptor B (IL17RB), associated with acamprosate treatment response.​ A GWAS for IL17RB concentrations identified several genome-wide significant signals. Specifically, the top hit single nucleotide polymorphism (SNP) rs6801605 with a minor allele frequency of 38% in the European American population mapped 4 kilobase (Kb) upstream of IL17RB, and intron 1 of the choline dehydrogenase (CHDH) gene on chromosome 3 (p: 4.8E-20). The variant genotype (AA) for the SNP rs6801605 was associated with lower IL17RB protein expression. In addition, we identified a series of genetic variants in IL17RB that were associated with acamprosate treatment outcomes. Furthermore, the variantgenotypes for all of those IL17RB SNPs were protective for alcohol relapse. Finally, we demonstrated that the basal level of mRNA expression of IL17RB was inversely correlated with those of nuclear factor-κB (NF-κB) subunits, and a significantly higher expression of NF-κB subunits was observed in AUD patients who relapsed to alcohol use. In summary, this study illustrates that IL17RB genetic variants might contribute to acamprosate treatment outcomes. This series of studies represents an important step toward generating functional hypotheses that could be tested to gain insight into mechanisms underlying acamprosate treatment response phenotypes. (The ClinicalTrials.gov Identifier: NCT00662571)., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

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., (© 2024. The Author(s).)

The opioid epidemic represents a national crisis. Oxycodone is one of the most prescribed opioid medications in the United States, whereas buprenorphine is currently the most prescribed medication for opioid use disorder (OUD) pharmacotherapy. Given the extensive use of prescription opioids and the global opioid epidemic, it is essential to understand how opioids modulate brain cell type function at the single-cell level. We performed single nucleus RNA-seq (snRNA-seq) using iPSC-derived forebrain organoids from three male OUD subjects in response to oxycodone, buprenorphine, or vehicle for seven days. We utilized the snRNA-seq data to identify differentially expressed genes following drug treatment using the Seurat integrative analysis pipeline. We utilized iPSC-derived forebrain organoids and single-cell sequencing technology as an unbiased tool to study cell-type-specific and drug-specific transcriptional responses. After quality control filtering, we analyzed 25787 cells and identified sixteen clusters using unsupervised clustering analysis. Our results reveal distinct transcriptional responses to oxycodone and buprenorphine by iPSC-derived brain organoids from patients with OUD. Specifically, buprenorphine displayed a significant influence on transcription regulation in glial cells. However, oxycodone induced type I interferon signaling in many cell types, including neural cells in brain organoids. Finally, we demonstrate that oxycodone, but not buprenorphine activated STAT1 and induced the type I interferon signaling in patients with OUD. These data suggest that elevation of STAT1 expression associated with OUD might play a role in transcriptional regulation in response to oxycodone. In summary, our results provide novel mechanistic insight into drug action at single-cell resolution., (© 2022. The Author(s).)

Background: Antidepressants are among the most prescribed medications in the United States. The aim of this study was to explore the prevalence of antidepressant prescriptions and investigate sex differences and age-sex interactions in adults enrolled in the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment (RIGHT) study. Materials and Methods: We conducted a retrospective analysis of the RIGHT study. Using electronic prescriptions, we assessed 12-month prevalence of antidepressant treatment. Sex differences and age-sex interactions were evaluated using multivariable logistic regression and flexible recursive smoothing splines. Results: The sample consisted of 11,087 participants (60% women). Antidepressant prescription prevalence was 22.24% (27.96% women, 13.58% men). After adjusting for age and enrollment year, women had significantly greater odds of antidepressant prescription (odds ratio = 2.29; 95% confidence interval = 2.07, 2.54). Furthermore, selective serotonin reuptake inhibitors (SSRIs) had a significant age-sex interaction. While SSRI prescriptions in men showed a sustained decrease with age, there was no such decline for women until after reaching ∼50 years of age. There are important limitations to consider in this study. Electronic prescription data were cross-sectional; information on treatment duration or adherence was not collected; this cohort is not nationally representative; and enrollment occurred over a broad period, introducing confounding by changes in temporal prescribing practices. Conclusions: Underscored by the significant interaction between age and sex on odds of SSRI prescription, our results warrant age to be incorporated as a mediator when investigating sex differences in mental illness, especially mood disorders and their treatment.

Objective: Fibroblast growth factor 21 (FGF21) analogs have been tested as potential therapeutics for substance use disorders. Prior research suggests that FGF21 administration might affect alcohol consumption and reward behaviors. Our recent report showed that plasma FGF21 levels were positively correlated with alcohol use in patients with alcohol use disorder (AUD). FGF21 has a short half-life (0.5-2 h) and crosses the blood-brain barrier. Therefore, we set out to identify molecular mechanisms for both the naïve form of FGF21 and a long-acting FGF21 molecule (PF-05231023) in induced pluripotent stem cell (iPSC)-derived forebrain neurons., Methods: We performed RNA-seq in iPSC-derived forebrain neurons treated with naïve FGF21 or PF-05231023 at physiologically relevant concentrations. We obtained plasma levels of FGF21 and GABA from our previous AUD clinical trial (n = 442). We performed ELISA for FGF21 in both iPSC-derived forebrain neurons and forebrain organoids. We determined protein interactions using co-immunoprecipitation. Finally, we applied ChIP assays to confirm the occupancy of REST, EZH2 and H3K27me3 by FGF21 using iPSC-derived forebrain neurons with and without drug exposure., Results: We identified 4701 and 1956 differentially expressed genes in response to naïve FGF21 or PF-05231023, respectively (FDR < 0.05). Notably, 974 differentially expressed genes overlapped between treatment with naïve FGF21 and PF-05231023. REST was the most important upstream regulator of differentially expressed genes. The GABAergic synapse pathway was the most significant pathway identified using the overlapping genes. We also observed a significant positive correlation between plasma FGF21 and GABA concentrations in AUD patients. In parallel, FGF21 and PF-05231023 significantly induced GABA levels in iPSC-derived neurons. Finally, functional genomics studies showed a drug-dependent occupancy of REST, EZH2, and H3K27me3 in the promoter regions of genes involved in GABA catabolism which resulted in transcriptional repression., Conclusions: Our results highlight a significant role in the epigenetic regulation of genes involved in GABA catabolism related to FGF21 action. (The ClinicalTrials.gov Identifier: NCT00662571)., (Copyright © 2023 The Author(s). Published by Elsevier GmbH.. All rights reserved.)

Background: Dilated cardiomyopathy (DCM) is a major cause of heart failure and carries a high mortality rate. Myocardial recovery in DCM-related heart failure patients is highly variable, with some patients having little or no response to standard drug therapy. A genome-wide association study may agnostically identify biomarkers and provide novel insight into the biology of myocardial recovery in DCM., Methods: A genome-wide association study for change in left ventricular ejection fraction was performed in 686 White subjects with recent-onset DCM who received standard pharmacotherapy. Genome-wide association study signals were subsequently functionally validated and studied in relevant cellular models to understand molecular mechanisms that may have contributed to the change in left ventricular ejection fraction., Results: The genome-wide association study identified a highly suggestive locus that mapped to the 5'-flanking region of the CDCP1 (CUB [complement C1r/C1s, Uegf, and Bmp1] domain containing protein 1) gene (rs6773435; P =7.12×10 -7 ). The variant allele was associated with improved cardiac function and decreased CDCP1 transcription. CDCP1 expression was significantly upregulated in human cardiac fibroblasts (HCFs) in response to the PDGF (platelet-derived growth factor) signaling, and knockdown of CDCP1 significantly repressed HCF proliferation and decreased AKT (protein kinase B) phosphorylation. Transcriptomic profiling after CDCP1 knockdown in HCFs supported the conclusion that CDCP1 regulates HCF proliferation and mitosis. In addition, CDCP1 knockdown in HCFs resulted in significantly decreased expression of soluble ST2 (suppression of tumorigenicity-2), a prognostic biomarker for heart failure and inductor of cardiac fibrosis., Conclusions: CDCP1 may play an important role in myocardial recovery in recent-onset DCM and mediates its effect primarily by attenuating cardiac fibrosis., Competing Interests: Disclosures R.M. Weinshilboum is a cofounder of and stockholder in OneOme, LLC. The other authors report no conflicts.

Objective: Elevated serum chromogranin A (CGA) is associated with intrinsic or treatment-related neuroendocrine differentiation (NED) in men with metastatic castration-resistant prostate cancer (mCRPC). Fluctuations in serum CGA during treatment of mCRPC have had conflicting results. We analyzed the impact of (i) rising serum CGA and (ii) baseline CGA/PSA ratio during treatment to identify associations with abiraterone acetate (AA) therapy., Methods: Between June 2013 and August 2015, 92 men with mCRPC were enrolled in a prospective trial with uniform serum CGA processing performed before initiating abiraterone acetate/prednisone (AA/P) and serially after 12 weeks of AA/P treatments. Serum CGA was measured using a homogenous automated immunofluorescent assay. Patients receiving proton pump inhibitors or with abnormal renal function were excluded due to possible false elevations of serum CGA (n = 21 excluded), therefore 71 patients were analyzed. All patients underwent a composite response assessment at 12-weeks. Kaplan-Meier estimates and Cox Regression models were used to calculate the association with time-to-treatment failure analyses and overall survival., Results: An increase in chromogranin was associated with a lower risk of treatment failure (hazard ratio [HR]: 0.52, p = 0.0181). The median CGA/PSA ratio was 7.8 (2.6-16.0) and an elevated pretreatment CGA/PSA ratio above the median was associated with a lower risk of treatment failure (HR: 0.54 p value = 0.0185). An increase in CGA was not found to be associated with OS (HR: 0.71, 95% CI: 0.42-1.21, p = 0.207). An elevated baseline CGA/PSA ratio was not associated with OS (HR: 0.62, 95% CI: 0.37-1.03, p = 0.062). An increase in PSA after 12 weeks of treatment was associated with an increased risk of treatment failure (HR: 4.14, CI: 2.21-7.73, p = < 0.0001) and worse OS (HR: 2.93, CI: 1.57-4.45, p = < 0.0001)., Conclusions: We show that an increasing chromogranin on AA/P and an elevated baseline CGA/PSA in patients with mCRPC were associated with a favorable response to AA/P with no changes in survival. There may be limited clinical utility in serum CGA testing to evaluate for lethal NED as AA/P did not induce lethal NED in this cohort. This highlights that not all patients with an increasing CGA have a worse OS., (© 2023 Wiley Periodicals LLC.)

Androgen receptor (AR) is expressed in 80% to 90% of estrogen receptor α-positive (ER+) breast cancers. Accumulated evidence has shown that AR is a tumor suppressor and that its expression is associated with improved prognosis in ER+ breast cancer. However, both a selective AR agonist (RAD140) and an AR inhibitor (enzalutamide, ENZ) have shown a therapeutic effect on ER+ breast cancer, so the potential for clinical application of AR-targeting therapy for ER+ breast cancer is still in dispute. In this study, we evaluated the efficacy of ENZ and RAD140 in vivo and in vitro in AR+/ER+ breast cancer models, characterizing the relationship of AR and ER levels to response to AR-targeting drugs and investigating the alterations of global gene expression and chromatin binding of AR and ERα after ENZ treatment. In the AR-low setting, ENZ directly functioned as an ERα antagonist. Cell growth inhibition by ENZ in breast cancer with low AR expression was independent of AR and instead dependent on ER. In AR-high breast cancer models, AR repressed ERα signaling and ENZ promoted ERα signaling by antagonizing AR. In contrast, RAD140 activated AR signaling and suppressed AR-high tumor growth by deregulating ERα expression and blocking ERα function. Overall, analysis of the dynamic efficacies and outcomes of AR agonist, and antagonist in the presence of different AR and ERα levels reveals regulators of response and supports the clinical investigation of ENZ in selected ER+ tumors with a low AR/ER ratio and AR agonists in tumors with a high AR/ER ratio., Significance: The ratio of androgen receptor to estrogen receptor in breast cancer dictates the response to AR-targeted therapies, providing guidelines for developing AR-directed treatment strategies for patients with breast cancer., (©2022 The Authors; Published by the American Association for Cancer Research.)

Cytochrome P450s ( CYPs ) display significant inter-individual variation in expression, much of which remains unexplained by known CYP single-nucleotide polymorphisms (SNPs). Testis-specific Y-encoded-like proteins ( TSPYL s) are transcriptional regulators for several drug-metabolizing CYPs including CYP3A4 However, transcription factors (TFs) that might influence CYP expression through an effect on TSPYL expression are unknown. Therefore, we studied regulators of TSPYL expression in hepatic cell lines and their possible SNP-dependent variation. Specifically, we identified candidate TFs that might influence TSPYL expression using the ENCODE ChIPseq database. Subsequently, the expression of TSPYL1/2/4 as well as that of selected CYP targets for TSPYL regulation were assayed in hepatic cell lines before and after knockdown of TFs that might influence CYP expression through TSPYL-dependent mechanisms. Those results were confirmed by studies of TF binding to TSPYL1/2/4 gene promoter regions. In hepatic cell lines, knockdown of the REST and ZBTB7A TFs resulted in decreased TSPYL1 and TSPYL4 expression and increased CYP3A4 expression, changes reversed by TSPYL1/4 overexpression. Potential binding sites for REST and ZBTB7A on the promoters of TSPYL1 and TSPYL4 were confirmed by chromatin immunoprecipitation. Finally, common SNP variants in upstream binding sites on the TSPYL1/4 promoters were identified and luciferase reporter constructs confirmed SNP-dependent modulation of TSPYL1/4 gene transcription. In summary, we identified REST and ZBTB7A as regulators of the expression of TSPYL genes which themselves can contribute to regulation of CYP expression and-potentially-of drug metabolism. SNP-dependent modulation of TSPYL transcription may contribute to individual variation in both CYP expression and-downstream-drug response phenotypes. SIGNIFICANCE STATEMENT: Testis-specific Y-encoded-like proteins ( TSPYL s) are transcriptional regulators of cytochrome P450 ( CYP ) gene expression. Here, we report that variation in TSPYL expression as a result of the effects of genetically regulated TSPYL transcription factors is an additional factor that could result in downstream variation in CYP expression and potentially, as a result, variation in drug biotransformation., (Copyright © 2022 by The Author(s).)

We identified resistance mechanisms to abiraterone acetate/prednisone (AA/P) in patients with metastatic castration-resistant prostate cancer (mCRPC) in the Prostate Cancer Medically Optimized Genome-Enhanced Therapy (PROMOTE) study., We analyzed whole-exome sequencing (WES) and RNA-sequencing data from 83 patients with metastatic biopsies before (V1) and after 12 weeks of AA/P treatment (V2). Resistance was determined by time to treatment change (TTTC)., At V2, 18 and 11 of 58 patients had either short-term (median 3.6 months; range 1.4-4.5) or long-term (median 29 months; range 23.5-41.7) responses, respectively. Nonresponders had low expression of TGFBR3 and increased activation of the Wnt pathway, cell cycle, upregulation of AR variants, both pre- and posttreatment, with further deletion of AR inhibitor CDK11B posttreatment. Deletion of androgen processing genes, HSD17B11, CYP19A1 were observed in nonresponders posttreatment. Genes involved in cell cycle, DNA repair, Wnt-signaling, and Aurora kinase pathways were differentially expressed between the responder and non-responder at V2. Activation of Wnt signaling in nonresponder and deactivation of MYC or its target genes in responders was detected via SCN loss, somatic mutations, and transcriptomics. Upregulation of genes in the AURKA pathway are consistent with the activation of MYC regulated genes in nonresponders. Several genes in the AKT1 axis had increased mutation rate in nonresponders. We also found evidence of resistance via PDCD1 overexpression in responders., Implications: Finally, we identified candidates drugs to reverse AA/P resistance: topoisomerase inhibitors and drugs targeting the cell cycle via the MYC/AURKA/AURKB/TOP2A and/or PI3K&#95;AKT&#95;MTOR pathways., (©2022 The Authors; Published by the American Association for Cancer Research.)

Poly(ADP-ribose) (PAR) polymerase inhibitors (PARPi) either have been approved or being tested in the clinic for the treatment of a variety of cancers with homologous recombination deficiency (HRD). However, cancer cells can develop resistance to PARPi drugs through various mechanisms, and new biomarkers and combination therapeutic strategies need to be developed to support personalized treatment. In this study, a genome-wide CRISPR screen was performed in a prostate cancer cell line with 3D culture condition which identified novel signals involved in DNA repair pathways. One of these genes, TBL1XR1, regulates sensitivity to PARPi in prostate cancer cells. Mechanistically, we show that TBL1XR1 interacts with and stabilizes SMC3 on chromatin and promotes γH2AX spreading along the chromatin of the cells under DNA replication stress. TBL1XR1-SMC3 double knockdown (knockout) cells have comparable sensitivity to PARPi compared to SMC3 knockdown or TBL1XR1 knockout cells, and more sensitivity than WT cells. Our findings provide new insights into mechanisms underlying response to PARPi or platin compounds in the treatment of malignancies., Competing Interests: LWa and RW are cofounders and stock holders of OneOme LLC. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhang, Gao, Gu, John, Wei, Huang, Yu, Adeosun, Weinshilboum and Wang.)

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhu, Gao, Qin, Liu, Cairns, Gu, Yu, Weinshilboum and Wang.)

Understanding the function of non-coding genomic sequence variants represents a challenge for biomedicine. Many diseases are products of gene-by-environment interactions with complex mechanisms. This study addresses these themes by mechanistic characterization of non-coding variants that influence gene expression only after drug or hormone exposure. Using glucocorticoid signaling as a model system, we integrated genomic, transcriptomic, and epigenomic approaches to unravel mechanisms by which variant function could be revealed by hormones or drugs. Specifically, we identified cis-regulatory elements and 3D interactions underlying ligand-dependent associations between variants and gene expression. One-quarter of the glucocorticoid-modulated variants that we identified had already been associated with clinical phenotypes. However, their affected genes were 'unmasked' only after glucocorticoid exposure and often with function relevant to the disease phenotypes. These diseases involved glucocorticoids as risk factors or therapeutic agents and included autoimmunity, metabolic and mood disorders, osteoporosis and cancer. For example, we identified a novel breast cancer risk gene, MAST4, with expression that was repressed by glucocorticoids in cells carrying the risk genotype, repression that correlated with MAST4 expression in breast cancer and treatment outcomes. These observations provide a mechanistic framework for understanding non-coding genetic variant-chemical environment interactions and their role in disease risk and drug response., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Alternative polyadenylation (APA) is a common genetic regulatory mechanism that generates distinct 3' ends for RNA transcripts. Changes in APA have been associated with multiple biological processes and disease phenotypes. However, the role of hormones and their drug analogs in APA remains largely unknown. In this study, we investigated transcriptome-wide the impact of glucocorticoids on APA in 30 human B-lymphoblastoid cell lines. We found that glucocorticoids could regulate APA for a subset of genes, possibly by changing the expression of 142 RNA-binding proteins, some with known APA-regulating properties. Interestingly, genes with glucocorticoid-mediated APA were enriched in viral translation-related pathways, while genes with glucocorticoid-mediated expression were enriched in interferon and interleukin pathways, suggesting that glucocorticoid-mediated APA might result in functional consequences distinct from gene expression. For example, glucocorticoids, a pharmacotherapy for severe COVID-19, were found to change the APA but not the expression of LY6E, an important antiviral inhibitor in coronavirus diseases. Glucocorticoid-mediated APA was also cell-type-specific, suggesting an action of glucocorticoids that may be unique to immune regulation. We also observed evidence for genotype-dependent glucocorticoid-mediated APA (referred to as pharmacogenomic-alterative polyadenylation quantitative trait loci), providing potential functional mechanisms for a series of common genetic variants that had previously been associated with immune disorders, but without a clear mechanism. In summary, this study reports a series of observations regarding the impact of glucocorticoids on APA, raising the possibility that this mechanism might have implications for both disease pathophysiology and drug therapy., (© 2022 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Background: The treatment of depression in children and adolescents is a substantial public health challenge. This study examined artificial intelligence tools for the prediction of early outcomes in depressed children and adolescents treated with fluoxetine, duloxetine, or placebo., Methods: The study samples included training datasets (N = 271) from patients with major depressive disorder (MDD) treated with fluoxetine and testing datasets from patients with MDD treated with duloxetine (N = 255) or placebo (N = 265). Treatment trajectories were generated using probabilistic graphical models (PGMs). Unsupervised machine learning identified specific depressive symptom profiles and related thresholds of improvement during acute treatment., Results: Variation in six depressive symptoms (difficulty having fun, social withdrawal, excessive fatigue, irritability, low self-esteem, and depressed feelings) assessed with the Children's Depression Rating Scale-Revised at 4-6 weeks predicted treatment outcomes with fluoxetine at 10-12 weeks with an average accuracy of 73% in the training dataset. The same six symptoms predicted 10-12 week outcomes at 4-6 weeks in (a) duloxetine testing datasets with an average accuracy of 76% and (b) placebo-treated patients with accuracies of 67%. In placebo-treated patients, the accuracies of predicting response and remission were similar to antidepressants. Accuracies for predicting nonresponse to placebo treatment were significantly lower than antidepressants., Conclusions: PGMs provided clinically meaningful predictions in samples of depressed children and adolescents treated with fluoxetine or duloxetine. Future work should augment PGMs with biological data for refined predictions to guide the selection of pharmacological and psychotherapeutic treatment in children and adolescents with depression., (© 2022 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.)

Acamprosate is an anti-craving drug used in alcohol use disorder (AUD) pharmacotherapy. However, only a subset of patients achieves optimal treatment outcomes. The identification of predictive biomarkers of acamprosate treatment response in patients with AUD would be a substantial advance in addiction medicine. We designed this study to use proteomics data as a quantitative biological trait as a step toward identifying inflammatory modulators that might be associated with acamprosate treatment outcomes. The NIAAA-funded Mayo Clinic Center for the Individualized Treatment of Alcoholism study had previously recruited 442 AUD patients who received 3 months of acamprosate treatment. However, only 267 subjects returned for the 3-month follow-up visit and, as a result, had treatment outcome information available. Baseline alcohol craving intensity was the most significant predictor of acamprosate treatment outcomes. We performed plasma proteomics using the Olink target 96 inflammation panel and identified that baseline plasma TNF superfamily member 10 (TNFSF10) concentration was associated with alcohol craving intensity and variation in acamprosate treatment outcomes among AUD patients. We also performed RNA sequencing using baseline peripheral blood mononuclear cells from AUD patients with known acamprosate treatment outcomes which revealed that inflammation-related pathways were highly associated with relapse to alcohol use during the 3 months of acamprosate treatment. These observations represent an important step toward advancing our understanding of the pathophysiology of AUD and molecular mechanisms associated with acamprosate treatment response. In conclusion, applying omics-based approaches may be a practical approach for identifying biologic markers that could potentially predict alcohol craving intensity and acamprosate treatment response., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Ho, Zhang, Moon, Coombes, Biernacka, Skime, Choi, Croarkin, Frye, Ngo, Skillon, Oesterle, Karpyak, Li and Weinshilboum.)

Purpose: To identify molecular predictors of grade 3/4 neutropenic or leukopenic events (NLE) after chemotherapy using a genome-wide association study (GWAS)., Experimental Design: A GWAS was performed on patients in the phase III chemotherapy study SUCCESS-A (n = 3,322). Genotyping was done using the Illumina HumanOmniExpress-12v1 array. Findings were functionally validated with cell culture models and the genotypes and gene expression of possible causative genes were correlated with clinical treatment response and prognostic outcomes., Results: One locus on chromosome 16 (rs4784750; NLRC5; P = 1.56E-8) and another locus on chromosome 13 (rs16972207; TNFSF13B; P = 3.42E-8) were identified at a genome-wide significance level. Functional validation revealed that expression of these two genes is altered by genotype-dependent and chemotherapy-dependent activity of two transcription factors. Genotypes also showed an association with disease-free survival in patients with an NLE., Conclusions: Two loci in NLRC5 and TNFSF13B are associated with NLEs. The involvement of the MHC I regulator NLRC5 implies the possible involvement of immuno-oncological pathways., (©2022 American Association for Cancer Research.)

The HER2 receptor modulates downstream signaling by forming homodimers and heterodimers with other members of the HER family. For patients with HER2-positive breast cancer, Trastuzumab, an anti-HER2 monoclonal antibody as first-line therapy has shown significant survival benefits. However, the development of acquired resistance to Trastuzumab continues to be a significant obstacle. TNF receptor-associated factor 4 (TRAF4) upregulation was discovered to be associated with a worse clinical outcome. Here we identified TRAF4 overexpression as one of the putative mechanisms for HER2-positive breast cancer cells to maintain HER2 signaling during Trastuzumab treatment, while TRAF4 knockdown reduced HER2 stability and improved Trastuzumab sensitivity. Mechanistically, TRAF4 regulates HER2 level through its impact on SMAD specific E3 ubiquitin protein ligase protein 2 (SMURF2). The development of a membrane-associated protein complex containing HER2, TRAF4, and SMURF2 has been observed. SMURF2 bound to the HER2 cytoplasmic domain, and directly ubiquitinated it leading to HER2 degradation, whereas TRAF4 stabilized HER2 by degrading SMURF2 and inhibiting the binding of SMURF2 to HER2. Moreover, downregulation of TRAF4 has decreased the AKT/mTOR signaling. In conclusion, we discovered a new HER2 signaling regulation that involves the TRAF4-SMURF2 complex, a possible mechanism that might contribute to anti-HER2 resistance, making TRAF4 a viable target for treating HER2 + breast cancer., (© 2022. The Author(s).)

Background and Purpose: Acamprosate is an anti-craving drug used for the pharmacotherapy of alcohol use disorder (AUD). However, only some patients achieve optimal therapeutic outcomes. This study was designed to explore differences in metabolomic profiles between patients who maintained sobriety and those who relapsed, to determine whether those differences provide insight into variation in acamprosate treatment response phenotypes., Experimental Approach: We previously conducted an acamprosate trial involving 442 AUD patients, and 267 of these subjects presented themselves for a 3-month follow-up. The primary outcome was abstinence. Clinical information, genomic data and metabolomics data were collected. Baseline plasma samples were assayed using targeted metabolomics., Key Results: Baseline plasma arginine, threonine, α-aminoadipic acid and ethanolamine concentrations were associated with acamprosate treatment outcomes and baseline craving intensity, a measure that has been associated with acamprosate treatment response. We next applied a pharmacometabolomics-informed genome-wide association study (GWAS) strategy to identify genetic variants that might contribute to variations in plasma metabolomic profiles that were associated with craving and/or acamprosate treatment outcome. Gene expression data for induced pluripotent stem cell-derived forebrain astrocytes showed that a series of genes identified during the metabolomics-informed GWAS were ethanol responsive. Furthermore, a large number of those genes could be regulated by acamprosate. Finally, we identified a series of single nucleotide polymorphisms that were associated with acamprosate treatment outcomes., Conclusion and Implications: These results serve as an important step towards advancing our understanding of disease pathophysiology and drug action responsible for variation in acamprosate response and alcohol craving in AUD patients., (© 2022 The Authors. British Journal of Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype with low overall survival rates and high molecular heterogeneity; therefore, few targeted therapies are available. The luminal androgen receptor (LAR) is the most consistently identified TNBC subtype, but the clinical utility has yet to be established. Here, we constructed a novel genomic classifier, LAR-Sig, that distinguishes the LAR subtype from other TNBC subtypes and provide evidence that it is a clinically distinct disease. A meta-analysis of seven TNBC datasets ( n = 1086 samples) from neoadjuvant clinical trials demonstrated that LAR patients have significantly reduced response (pCR) rates than non-LAR TNBC patients (odds ratio = 2.11, 95% CI: 1.33, 2.89). Moreover, deconvolution of the tumor microenvironment confirmed an enrichment of luminal epithelium corresponding with a decrease in basal and myoepithelium in LAR TNBC tumors. Increased immunosuppression in LAR patients may lead to a decreased presence of cycling T-cells and plasma cells. While, an increased presence of myofibroblast-like cancer-associated cells may impede drug delivery and treatment. In summary, the lower levels of tumor infiltrating lymphocytes (TILs), reduced immune activity in the micro-environment, and lower pCR rates after NAC, suggest that new therapeutic strategies for the LAR TNBC subtype need to be developed., (© The Author(s) 2022. Published by Oxford University Press on behalf of NAR Cancer.)

Objective: To test the ability of machine learning (ML) approaches with clinical and genomic biomarkers to predict methotrexate treatment response in patients with early rheumatoid arthritis (RA)., Methods: Demographic, clinical, and genomic data from 643 patients of European ancestry with early RA (mean age 54 years; 70% female) subdivided into a training (n = 336) and validation cohort (n = 307) were used. The genomic data comprised 160 single-nucleotide polymorphisms (SNPs) previously associated with RA or methotrexate metabolism. Response to methotrexate monotherapy was defined as good or moderate by the European Alliance of Associations for Rheumatology (EULAR) response criteria at the 3-month follow-up. Supervised ML methods were trained with 5 repeats and 10-fold cross-validation using the training cohort. Prediction performance was validated in the independent validation cohort., Results: Supervised ML methods combining age, sex, smoking, rheumatoid factor, baseline Disease Activity Score in 28 joints (DAS28) scores and 160 SNPs predicted EULAR response at 3 months with the area under the receiver operating curve of 0.84 (P = 0.05) in the training cohort and achieved a prediction accuracy of 76% (P = 0.05) in the validation cohort (sensitivity 72%, specificity 77%). Intergenic SNPs rs12446816, rs13385025, rs113798271, and ATIC (rs2372536) had variable importance above 60.0 and along with baseline DAS28 scores were among the top predictors of methotrexate response., Conclusion: Pharmacogenomic biomarkers combined with baseline DAS28 scores can be useful in predicting response to methotrexate in patients with early RA. Applying ML to predict treatment response holds promise for guiding effective RA treatment choices, including timely escalation of RA therapies., (© 2021 American College of Rheumatology.)

Approximately one-third of patients with metastatic castration-resistant prostate cancer (CRPC) exhibited primary abiraterone resistance. To identify alternative treatment for abiraterone nonresponders, we performed drug discovery analyses using the L1000 database using differentially expressed genes identified in tumor biopsies and patient-derived xenograft (PDX) tumors between abiraterone responders and nonresponders enrolled in PROMOTE trial. This approach identified 3 drugs, including topoisomerase II (TOP2) inhibitor mitoxantrone, CDK4/6 inhibitor palbociclib, and pan-CDK inhibitor PHA-793887. These drugs significantly suppressed the growth of abiraterone-resistant cell lines and PDX models. Moreover, we identified 11 genes targeted by all 3 drugs that were associated with worse outcomes in both the PROMOTE and Stand Up To Cancer cohorts. This 11-gene panel might also function as biomarkers to select the 3 alternative therapies for this subgroup of patients with CRPC, warranting further clinical investigation., (© 2022 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Purpose: Cardiac toxicity is a serious potential complication of HER2-directed therapies and anthracyclines. HER2 codon 655 and SLC28A3 gene polymorphisms have been reported to be associated with cardiac toxicity from anti-HER2 and anthracycline therapy, respectively. Association of the polymorphism at HER2 codon 655 with prognosis has also been reported., Experimental Design: Whole blood samples from patients treated on a randomized adjuvant breast cancer trial (BCIRG-006) that compared chemotherapy with or without trastuzumab plus either anthracycline or nonanthracycline chemotherapy were tested for genetic polymorphisms in HER2 codon 655 and SLC28A3. Genotypes were correlated with cardiac function and disease-free survival (DFS) outcomes., Results: Of 3,222 patients enrolled in BCIRG-006, 662 patient samples were successfully genotyped for the rs1136201 allele in HER2 (codon 655): 424 (64%) were AA, 30 (4.5%) were GG, and 208 (31%) were AG genotype. In addition, 665 patient samples were successfully genotyped for the rs7853758 allele in the SLC28A3 gene: 19 (3%) were AA, 475 (71%) were GG, and 171 (26%) were AG genotype. Follow-up time was 10 years. No correlation between DFS, cardiac event rate, or mean left ventricular ejection fraction (LVEF) and rs1136201 genotype was seen in the trastuzumab-treated or non-trastuzumab-treated patients. Moreover, mean LVEF and cardiac event rates were similar in all rs7853758 genotype groups treated with anthracycline-based therapy., Conclusions: In the largest study to date to evaluate whether two polymorphisms are associated with DFS and/or cardiac toxicity in HER2-positive breast cancer treated with trastuzumab and/or anthracyclines, we observed no correlation., (©2022 American Association for Cancer Research.)

Purpose: The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping., Methods: Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response-related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug-gene pairs, were deposited preemptively in the Mayo electronic health record., Results: For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping., Conclusion: Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources., Competing Interests: Conflict of Interest Liewei Wang, John Logan Black III, and Richard M. Weinshilboum are cofounders of and stockholders in OneOme, LLC, which was used only to return results to the study participants. Additionally, John Logan Black III and Mayo Clinic Ventures have applied for a patent on the CNVAR software cited in this study as well as the methodology upon which the software is based. All other authors declare no conflicts of interest., (Copyright © 2022 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Clinical pharmacogenomic testing typically uses targeted genotyping, which only detects variants included in the test design and may vary among laboratories. To evaluate the potential patient impact of genotyping compared with sequencing, which can detect common and rare variants, an in silico targeted genotyping panel was developed based on the variants most commonly included in clinical tests and applied to a cohort of 10,030 participants who underwent sequencing for CYP1A2, CYP2C19, CYP2C9, CYP2D6, CYP3A4, CYP3A5, DPYD, SLCO1B1, TPMT, UGT1A1, and VKORC1. The results of in silico targeted genotyping were compared with the clinically reported sequencing results. Of the 10,030 participants, 2780 (28%) had at least one potentially clinically relevant variant/allele identified by sequencing that would not have been detected in a standard targeted genotyping panel. The genes with the largest number of participants with variants only detected by sequencing were SLCO1B1, DPYD, and CYP2D6, which affected 13%, 6.3%, and 3.5% of participants, respectively. DPYD (112 variants) and CYP2D6 (103 variants) had the largest number of unique variants detected only by sequencing. Although targeted genotyping detects most clinically significant pharmacogenomic variants, sequencing-based approaches are necessary to detect rare variants that collectively affect many patients. However, efforts to establish pharmacogenomic variant classification systems and nomenclature to accommodate rare variants will be required to adopt sequencing-based pharmacogenomics., (Copyright © 2022 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Our previous matched case-control study of postmenopausal women with resected early-stage breast cancer revealed that only anastrozole, but not exemestane or letrozole, showed a significant association between the 6-month estrogen concentrations and risk of breast cancer. Anastrozole, but not exemestane or letrozole, is a ligand for estrogen receptor α. The mechanisms of endocrine resistance are heterogenous and with the new mechanism of anastrozole, we have found that treatment of anastrozole maintains fatty acid synthase (FASN) protein level by limiting the ubiquitin-mediated FASN degradation, leading to increased breast cancer cell growth. Mechanistically, anastrozole decreases the guided entry of tail-anchored proteins factor 4 (GET4) expression, resulting in decreased BCL2-associated athanogene cochaperone 6 (BAG6) complex activity, which in turn, prevents RNF126-mediated degradation of FASN. Increased FASN protein level can induce a negative feedback loop mediated by the MAPK pathway. High levels of FASN are associated with poor outcome only in patients with anastrozole-treated breast cancer, but not in patients treated with exemestane or letrozole. Repressing FASN causes regression of breast cancer cell growth. The anastrozole-FASN signaling pathway is eminently targetable in endocrine-resistant breast cancer., (©2021 American Association for Cancer Research.)

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., (© 2021. The Author(s).)

Aromatase inhibitors (AIs) are the treatment of choice for hormone receptor-positive early breast cancer in postmenopausal women. None of the third-generation AIs are superior to the others in terms of efficacy. We attempted to identify genetic factors that could differentiate between the effectiveness of adjuvant anastrozole and exemestane by examining single-nucleotide polymorphism (SNP)-treatment interaction in 4,465 patients. A group of SNPs were found to be differentially associated between anastrozole and exemestane regarding outcomes. However, they showed no association with outcome in the combined analysis. We followed up common SNPs near LY75 and GPR160 that could differentiate anastrozole from exemestane efficacy. LY75 and GPR160 participate in epithelial-to-mesenchymal transition and growth pathways, in both cases with SNP-dependent variation in regulation. Collectively, these studies identified SNPs that differentiate the efficacy of anastrozole and exemestane and they suggest additional genetic biomarkers for possible use in selecting an AI for a given patient., (© 2021 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Antiepileptic mood stabilizers (AED-MS) are often used to treat bipolar disorder (BD). Similar to other mood disorder medications, AED-MS treatment response varies between patients. Identification of biomarkers associated with treatment response may ultimately help with the delivery of individualized treatment and lead to improved treatment efficacy. Here, we conducted a narrative review of the current knowledge of the pharmacogenomics of AED-MS (valproic acid, lamotrigine and carbamazepine) treatment response in BD, including genetic contributions to AED-MS pharmacokinetics. Genes involved in neurotransmitter systems and drug transport have been shown to be associated with AED-MS treatment response. As more studies are conducted, and experimental and analytical methods advance, knowledge of AED-MS pharmacogenomics is expected to grow and contribute to precision medicine in BD.

Objectives: We previously discovered that the single nucleotide polymorphisms (SNP) rs9940645 in the ZNF423 gene regulate ZNF423 expression and serve as a potential biomarker for response to selective estrogen receptor modulators (SERMs). Here we explored pathways involved in ZNF423-mediated SERMs response and drugs that potentially sensitize SERMs., Methods: RNA sequencing and label-free quantitative proteomics were performed to identify genes and pathways that are regulated by ZNF423 and the ZNF423 SNP. Both cultured cells and mouse xenograft models with different ZNF423 SNP genotypes were used to study the cellular responses to metformin., Results: We identified ribosome and AMP-activated protein kinase (AMPK) signaling as potential pathways regulated by ZNF423 or ZNF423 rs9940645 SNP. Moreover, using clustered regularly interspaced short palindromic repeats/Cas9-engineered ZR75-1 breast cancer cells with different ZNF423 SNP genotypes, striking differences in cellular responses to metformin, either alone or in the combination of tamoxifen, were observed in both cell culture and the mouse xenograft model., Conclusions: We found that AMPK signaling is modulated by the ZNF423 rs9940645 SNP in estrogen and SERM-dependent fashion. The ZNF423 rs9940645 SNP affects metformin response in breast cancer and could be a potential biomarker for tailoring the metformin treatment., (Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc.)

The application of patient-derived xenografts (PDX) in drug screening and testing is a costly and time-consuming endeavor. While cell lines permit extensive mechanistic studies, many human breast cancer cell lines lack patient characteristics and clinical treatment information. Establishing cell lines that retain patient's genetic and drug response information would enable greater drug screening and mechanistic studies. Therefore, we utilized breast cancer PDX from the Mayo Breast Cancer Genome Guided Therapy Study (BEAUTY) to establish two immortalized, genomically unique breast cancer cell lines. Through extensive genetic and therapeutic testing, the cell lines were found to retain the same clinical subtype, major somatic alterations, and drug response phenotypes as their corresponding PDX and patient tumor. Our findings demonstrate PDX can be utilized to develop immortalized breast cancer cell lines and provide a valuable tool for understanding the molecular mechanism of drug resistance and exploring novel treatment strategies.

Selective serotonin reuptake inhibitors (SSRIs) are standard of care for major depressive disorder (MDD) pharmacotherapy, but only approximately half of these patients remit on SSRI therapy. Our previous genome-wide association study identified a single-nucleotide polymorphism (SNP) signal across the glutamate-rich 3 (ERICH3) gene that was nearly genome-wide significantly associated with plasma serotonin (5-HT) concentrations, which were themselves associated with SSRI response for MDD patients enrolled in the Mayo Clinic PGRN-AMPS SSRI trial. In this study, we performed a meta-analysis which demonstrated that those SNPs were significantly associated with SSRI treatment outcomes in four independent MDD trials. However, the function of ERICH3 and molecular mechanism(s) by which it might be associated with plasma 5-HT concentrations and SSRI clinical response remained unclear. Therefore, we characterized the human ERICH3 gene functionally and identified ERICH3 mRNA transcripts and protein isoforms that are highly expressed in central nervous system cells. Coimmunoprecipitation identified a series of ERICH3 interacting proteins including clathrin heavy chain which are known to play a role in vesicular function. Immunofluorescence showed ERICH3 colocalization with 5-HT in vesicle-like structures, and ERICH3 knock-out dramatically decreased 5-HT staining in SK-N-SH cells as well as 5-HT concentrations in the culture media and cell lysates without changing the expression of 5-HT synthesizing or metabolizing enzymes. Finally, immunofluorescence also showed ERICH3 colocalization with dopamine in human iPSC-derived neurons. These results suggest that ERICH3 may play a significant role in vesicular function in serotonergic and other neuronal cell types, which might help explain its association with antidepressant treatment response., (© 2020. The Author(s).)

Heterogeneity in the clinical presentation of major depressive disorder and response to antidepressants limits clinicians' ability to accurately predict a specific patient's eventual response to therapy. Validated depressive symptom profiles may be an important tool for identifying poor outcomes early in the course of treatment. To derive these symptom profiles, we first examined data from 947 depressed subjects treated with selective serotonin reuptake inhibitors (SSRIs) to delineate the heterogeneity of antidepressant response using probabilistic graphical models (PGMs). We then used unsupervised machine learning to identify specific depressive symptoms and thresholds of improvement that were predictive of antidepressant response by 4 weeks for a patient to achieve remission, response, or nonresponse by 8 weeks. Four depressive symptoms (depressed mood, guilt feelings and delusion, work and activities and psychic anxiety) and specific thresholds of change in each at 4 weeks predicted eventual outcome at 8 weeks to SSRI therapy with an average accuracy of 77% (p = 5.5E-08). The same four symptoms and prognostic thresholds derived from patients treated with SSRIs correctly predicted outcomes in 72% (p = 1.25E-05) of 1996 patients treated with other antidepressants in both inpatient and outpatient settings in independent publicly-available datasets. These predictive accuracies were higher than the accuracy of 53% for predicting SSRI response achieved using approaches that (i) incorporated only baseline clinical and sociodemographic factors, or (ii) used 4-week nonresponse status to predict likely outcomes at 8 weeks. The present findings suggest that PGMs providing interpretable predictions have the potential to enhance clinical treatment of depression and reduce the time burden associated with trials of ineffective antidepressants. Prospective trials examining this approach are forthcoming.

SLCO1B1 ( solute carrier organic anion transporter family member 1B1 ) is an important transmembrane hepatic uptake transporter. Genetic variants in the SLCO1B1 gene have been associated with altered protein folding, resulting in protein degradation and decreased transporter activity. Next-generation sequencing (NGS) of pharmacogenes is being applied increasingly to associate variation in drug response with genetic sequence variants. However, it is difficult to link variants of unknown significance with functional phenotypes using "one-at-a-time" functional systems. Deep mutational scanning (DMS) using a "landing pad cell-based system" is a high-throughput technique designed to analyze hundreds of gene open reading frame (ORF) missense variants in a parallel and scalable fashion. We have applied DMS to analyze 137 missense variants in the SLCO1B1 ORF obtained from the Exome Aggregation Consortium project. ORFs containing these variants were fused to green fluorescent protein and were integrated into "landing pad" cells. Florescence-activated cell sorting was performed to separate the cells into four groups based on fluorescence readout indicating protein expression at the single cell level. NGS was then performed and SLCO1B1 variant frequencies were used to determine protein abundance. We found that six variants not previously characterized functionally displayed less than 25% and another 12 displayed approximately 50% of wild-type protein expression. These results were then functionally validated by transporter studies. Severely damaging variants identified by DMS may have clinical relevance for SLCO1B1- dependent drug transport, but we need to exercise caution since the relatively small number of severely damaging variants identified raise questions with regard to the application of DMS to intrinsic membrane proteins such as organic anion transporter protein 1B1. SIGNIFICANCE STATEMENT: The functional implications of a large numbers of open reading frame (ORF) "variants of unknown significance" (VUS) in transporter genes have not been characterized. This study applied deep mutational scanning to determine the functional effects of VUS that have been observed in the ORF of SLCO1B1 ( s olute carrier organic anion transporter family member 1B1 ). Several severely damaging variants were identified, studied, and validated. These observations have implications for both the application of deep mutational scanning to intrinsic membrane proteins and for the clinical effect of drugs and endogenous compounds transported by SLCO1B1 ., (Copyright © 2021 by The Author(s).)

Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), yet their mechanisms of action are not fully understood and their therapeutic benefit varies among individuals. We used a targeted metabolomics approach utilizing a panel of 180 metabolites to gain insights into mechanisms of action and response to citalopram/escitalopram. Plasma samples from 136 participants with MDD enrolled into the Mayo Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) were profiled at baseline and after 8 weeks of treatment. After treatment, we saw increased levels of short-chain acylcarnitines and decreased levels of medium-chain and long-chain acylcarnitines, suggesting an SSRI effect on β-oxidation and mitochondrial function. Amines-including arginine, proline, and methionine sulfoxide-were upregulated while serotonin and sarcosine were downregulated, suggesting an SSRI effect on urea cycle, one-carbon metabolism, and serotonin uptake. Eighteen lipids within the phosphatidylcholine (PC aa and ae) classes were upregulated. Changes in several lipid and amine levels correlated with changes in 17-item Hamilton Rating Scale for Depression scores (HRSD 17 ). Differences in metabolic profiles at baseline and post-treatment were noted between participants who remitted (HRSD 17  ≤ 7) and those who gained no meaningful benefits (<30% reduction in HRSD 17 ). Remitters exhibited (a) higher baseline levels of C3, C5, alpha-aminoadipic acid, sarcosine, and serotonin; and (b) higher week-8 levels of PC aa C34:1, PC aa C34:2, PC aa C36:2, and PC aa C36:4. These findings suggest that mitochondrial energetics-including acylcarnitine metabolism, transport, and its link to β-oxidation-and lipid membrane remodeling may play roles in SSRI treatment response.

Objectives: Based on our previous findings that postmenopausal women with estrone (E1) and estradiol (E2) concentrations at or above 1.3 pg/ml and 0.5 pg/ml, respectively, after 6 months of adjuvant anastrozole therapy had a three-fold risk of recurrence, we aimed to identify a single-nucleotide polymorphism (SNP)-based model that would predict elevated E1 and E2 and then validate it in an independent dataset., Patients and Methods: The test set consisted of 322 women from the M3 study and the validation set consisted of 152 patients from MA.27. All patients were treated with adjuvant anastrozole, had on-anastrozole E1 and E2 concentrations and genome-wide genotyping., Results: SNPs were identified from the M3 genome-wide association study. The best model to predict the E1-E2 phenotype with high balanced accuracy was a support vector machine model using clinical factors plus 46 SNPs. We did not have an independent cohort that is similar to the M3 study with clinical, E1-E2 phenotypes and genotype data to test our model. Hence, we chose a nested matched case-control cohort (MA.27 study) for testing. Our E1-E2 model was not validated but we found the MA.27 validation cohort was both clinically and genomically different., Conclusions: We identified a SNP-based model that had excellent performance characteristics for predicting the phenotype of elevated E1 and E2 in women treated with anastrozole. This model was not validated in an independent dataset but that dataset was clinically and genomically substantially different. The model will need validation in a prospective study.

Several antiepileptic drugs (AEDs) have US Food and Drug Administration (FDA) approval for use as mood stabilizers in bipolar disorder (BD), but not all BD patients respond to these AED mood stabilizers (AED-MSs). To identify genetic polymorphisms that contribute to the variability in AED-MS response, we performed a discovery genome-wide association study (GWAS) of 199 BD patients from the Mayo Clinic Bipolar Disorder Biobank. Most of these patients had been treated with the AED-MS valproate/divalproex and/or lamotrigine. AED-MS response was assessed using the Alda scale, which quantifies clinical improvement while accounting for potential confounding factors. We identified two genome-wide significant single-nucleotide polymorphism (SNP) signals that mapped to the THSD7A (rs78835388, P = 7.1E-09) and SLC35F3 (rs114872993, P = 3.2E-08) genes. We also identified two genes with statistically significant gene-level associations: ABCC1 (P = 6.7E-07; top SNP rs875740, P = 2.0E-6), and DISP1 (P = 8.9E-07; top SNP rs34701716, P = 8.9E-07). THSD7A SNPs were previously found to be associated with risk for several psychiatric disorders, including BD. Both THSD7A and SLC35F3 are expressed in excitatory/glutamatergic and inhibitory/γ-aminobutyric acidergic (GABAergic) neurons, which are targets of AED-MSs. ABCC1 is involved in the transport of valproate and lamotrigine metabolites, and the SNPs in ABCC1 and DISP1 with the strongest evidence of association in our GWAS are strong splicing quantitative trait loci in the human gut, suggesting a possible influence on drug absorption. In conclusion, our pharmacogenomic study identified novel genetic loci that appear to contribute to AED-MS treatment response, and may facilitate precision medicine in BD., (© 2020 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Pulsatilla Decoction (Bai-Tou-Weng-Tang) has been used medically in China for thousands of years for the treatment of diseases caused by bacteria. In recent decades, Pulsatilla Decoction is becoming a well-known formula prescription used for the treatment of ulcerative colitis in traditional Chinese medicine. Pulsatilla chinensis is the chief herbal source of Pulsatilla Decoction, and it is rich in triterpenoid saponins, such as anemoside B4, anemoside A3, and 23-hydroxybetulinic acid. Anemoside B4 is the most abundant of that group and has been used as a quality control marker for Pulsatilla chinensis. As the major active component of Pulsatilla chinensis, anemoside B4 has also received attention as a pure compound for its therapeutic potential. In this review, we systematically analyze the findings on triterpenoid saponins, especially anemoside B4, anemoside A3 and 23-hydroxybetulinic acid, included in Pulsatilla chinensis and Pulsatilla Decoction. We discuss the pharmacokinetics and tissue distribution of these triterpenoid saponins as well as their biological activities. We also summarize the pharmacological effects of anemoside B4 and its two possible metabolites, anemoside A3 and 23-hydroxybetulinic acid, as pure compounds. In summary, this review sketches a profile of the state of existing knowledge with regard to the pharmacological effects of anemoside B4, especially its anti-inflammatory and immunomodulatory effects. These findings point to the possibility that anemoside B4 has potential to be studied further as a natural compound-originated immunomodulatory agent for the treatment of inflammatory diseases such as ulcerative colitis and thus, may represent one of the most important active components of Pulsatilla Decoction responsible for its anti-ulcerative colitis efficacy., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Aromatase inhibitors (AIs) reduce breast cancer recurrence and prolong survival, but up to 30% of patients exhibit recurrence. Using a genome-wide association study of patients entered on MA.27, a phase III randomized trial of anastrozole versus exemestane, we identified a single nucleotide polymorphism (SNP) in CUB And Sushi multiple domains 1 (CSMD1) associated with breast cancer-free interval, with the variant allele associated with fewer distant recurrences. Mechanistically, CSMD1 regulates CYP19 expression in an SNP- and drug-dependent fashion, and this regulation is different among 3 AIs: anastrozole, exemestane, and letrozole. Overexpression of CSMD1 sensitized AI-resistant cells to anastrozole but not to the other 2 AIs. The SNP in CSMD1 that was associated with increased CSMD1 and CYP19 expression levels increased anastrozole sensitivity, but not letrozole or exemestane sensitivity. Anastrozole degrades estrogen receptor α (ERα), especially in the presence of estradiol (E2). ER+ breast cancer organoids and AI- or fulvestrant-resistant breast cancer cells were more sensitive to anastrozole plus E2 than to AI alone. Our findings suggest that the CSMD1 SNP might help to predict AI response, and anastrozole plus E2 serves as a potential new therapeutic strategy for patients with AI- or fulvestrant-resistant breast cancers.

Purpose: To determine if the degree of estrogen suppression with aromatase inhibitors (AI: anastrozole, exemestane, letrozole) is associated with efficacy in early-stage breast cancer, and to examine for differences in the mechanism of action between the three AIs., Experimental Design: Matched case-control studies [247 matched sets from MA.27 (anastrozole vs. exemestane) and PreFace (letrozole) trials] were undertaken to assess whether estrone (E1) or estradiol (E2) concentrations after 6 months of adjuvant therapy were associated with risk of an early breast cancer event (EBCE). Preclinical laboratory studies included luciferase activity, cell proliferation, radio-labeled ligand estrogen receptor binding, surface plasmon resonance ligand receptor binding, and nuclear magnetic resonance assays., Results: Women with E1 ≥1.3 pg/mL and E2 ≥0.5 pg/mL after 6 months of AI treatment had a 2.2-fold increase in risk ( P = 0.0005) of an EBCE, and in the anastrozole subgroup, the increase in risk of an EBCE was 3.0-fold ( P = 0.001). Preclinical laboratory studies examined mechanisms of action in addition to aromatase inhibition and showed that only anastrozole could directly bind to estrogen receptor α (ERα), activate estrogen response element-dependent transcription, and stimulate growth of an aromatase-deficient CYP19A1 -/- T47D breast cancer cell line., Conclusions: This matched case-control clinical study revealed that levels of estrone and estradiol above identified thresholds after 6 months of adjuvant anastrozole treatment were associated with increased risk of an EBCE. Preclinical laboratory studies revealed that anastrozole, but not exemestane or letrozole, is a ligand for ERα. These findings represent potential steps towards individualized anastrozole therapy., (©2020 American Association for Cancer Research.)

Background: Acylcarnitines have important functions in mitochondrial energetics and β-oxidation, and have been implicated to play a significant role in metabolic functions of the brain. This retrospective study examined whether plasma acylcarnitine profiles can help biochemically distinguish the three phenotypic subtypes of major depressive disorder (MDD): core depression (CD+), anxious depression (ANX+), and neurovegetative symptoms of melancholia (NVSM+)., Methods: Depressed outpatients (n = 240) from the Mayo Clinic Pharmacogenomics Research Network were treated with citalopram or escitalopram for eight weeks. Plasma samples collected at baseline and after eight weeks of treatment with citalopram or escitalopram were profiled for short-, medium- and long-chain acylcarnitine levels using AbsoluteIDQ®p180-Kit and LC-MS. Linear mixed effects models were used to examine whether acylcarnitine levels discriminated the clinical phenotypes at baseline or eight weeks post-treatment, and whether temporal changes in acylcarnitine profiles differed between groups., Results: Compared to ANX+, CD+ and NVSM+ had significantly lower concentrations of short- and long-chain acylcarnitines at both baseline and week 8. In NVSM+, the medium- and long-chain acylcarnitines were also significantly lower in NVSM+ compared to ANX+. Short-chain acylcarnitine levels increased significantly from baseline to week 8 in CD+ and ANX+, whereas medium- and long-chain acylcarnitines significantly decreased in CD+ and NVSM+., Conclusions: In depressed patients treated with SSRIs, β-oxidation and mitochondrial energetics as evaluated by levels and changes in acylcarnitines may provide the biochemical basis of the clinical heterogeneity of MDD, especially when combined with clinical characteristics., Competing Interests: Declaration of Competing Interest Richard Weinshilboum is a co-founder and stockholder in OneOme, LLC, a pharmacogenomic clinical decision support company. Dr. Kaddurah-Daouk is an inventor on patents related to metabolomics applications in the study of CNS diseases and holds equity in Metabolon, Inc., a biotechnology company that provides metabolic profiling capabilities. Dr. A. John Rush has received: consulting fees from Akili, Brain Resource Inc., Compass Inc., Curbstone Consultant LLC., Emmes Corp., Johnson and Johnson (Janssen), Liva-Nova, Mind Linc., Sunovion; speaking fees from Janssen and Liva-Nova; and royalties from Guilford Press and the University of Texas Southwestern Medical Center, Dallas, TX (for the Inventory of Depressive Symptoms and its derivatives). Dr. Rush is also named co-inventor on two patents: U.S. Patent No. 7795,033: Methods to Predict the Outcome of Treatment with Antidepressant Medication and U.S. Patent No. 7906,283: Methods to Identify Patients at Risk of Developing Adverse Events During Treatment with Antidepressant Medication. Drew Neavin's stipend has been supported in part by NIH T32 GM072474 and the Mayo Graduate School. Ahmed Ahmed's research was supported by National Institute of General Medical Sciences of the National Institutes of Health under award number T32 GM008685. Dr. Matthias Arnold was supported by National Institute on Aging [R01AG057452, RF1AG051550, R01AG046171], National Institute of Mental Health [R01MH108348], and Qatar National Research Fund [NPRP8-061–3–011]. The funders listed above had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or the decision to submit the manuscript for publication. Dr. Dunlop has received research support from Acadia, Axsome, Janssen, Takeda and he serves as a consultant to Assurex Health and Aptinyx Inc. dr. Craighead is a board member of Hugarheill ehf, an Icelandic company dedicated to the prevention of depression, and he receives book royalties from John Wiley & Sons; his research is also supported by the Mary and John Brock Foundation and the Fuqua family foundations; he is a consultant to the George West Mental Health Foundation and is a member of the scientific advisory boards of the AIM for Mental Health Foundation and the Anxiety Disorders Association of America. dr. Bobo's research has been supported by the NIMH, AHRQ, Mayo Foundation for Medical Education and Research; he has contributed chapters to UpToDate on the treatment of bipolar disorders. Additional support was received from PHS Grant UL1 RR025008 from the Clinical and Translational Science Award program, National Institutes of Health, National Center for Research Resources, PHS Grant M01 RR0039 from the General Clinical Research Center program, and K23 MH086690 (BWD)., (Copyright © 2019. Published by Elsevier B.V.)

We previously reported that testis-specific Y-encoded-like protein (TSPYLs) are transcription regulators for CYP3A4, CYP2C9, and CYP2C19. Here, we observed dual roles for TSPYLs in mediating serotonin transport and the metabolism of selective serotonin reuptake inhibitors (SSRIs) in patients with major depressive disorder (MDD). The widely prescribed SSRIs, citalopram, and escitalopram are metabolized mainly by CYP2C19. The TSPYL1 rs3828743 single nucleotide polymorphism (SNP), which decreases its suppression of CYP2C19 expression, was associated with rapid escitalopram metabolism and worse treatment response in the Mayo PGRN-AMPS clinical trial. We also found that TSPYLs can regulate expression of the serotonin transporter protein, SLC6A4, and, in turn, serotonin transport into cells. The SNPs in tight linkage disequilibrium with the TSPYL1 rs10223646 SNP were significantly correlated with baseline severity of depression in patients with MDD in the Sequenced Treatment Alternatives to Relieve Depression and International SSRI Pharmacogenomics Consortium clinical trials. Our findings suggest that genetic variation in TSPYL genes may be novel indicators for baseline severity of depression and SSRI poor response., (© 2019 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.)

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., Competing Interests: The authors have declared that no competing interests exist.