Association of Antifolate Response Signature Status and Clinical Activity of Pemetrexed-Platinum Chemotherapy in Non-Small Cell Lung Cancer: The Piedmont Study

PURPOSE

The Piedmont study is a prospectively designed retrospective evaluation of a new 48-gene antifolate response signature (AF-PRS) in patients with locally advanced/metastatic nonsquamous (NS) non-small cell lung cancer (NSCLC) treated with pemetrexed-containing platinum doublet chemotherapy (PMX-PDC). The study tested the hypothesis that AF-PRS identifies patients with NS-NSCLC who have a higher likelihood of responding positively to PMX-PDC. The goal was to gather clinical evidence supporting AF-PRS as a potential diagnostic test.

EXPERIMENTAL DESIGN

Residual pretreatment FFPE tumor samples and clinical data were analyzed from 105 patients treated with first-line (1L) PMX-PDC. Ninety-five patients had sufficient RNA sequencing (RNA-seq) data quality and clinical annotation for inclusion in the analysis. Associations between AF-PRS status and associate genes and outcome measures including progression-free survival (PFS) and clinical response were evaluated.

RESULTS

Overall, 53% of patients were AF-PRS(+), which was associated with extended PFS, but not overall survival, versus AF-PRS(-) (16.6 months vs. 6.6 months; P = 0.025). In patients who were stage I to III patients at the time of treatment, PFS was further extended in AF-PRS(+) versus AF-PRS(-) (36.2 months vs. 9.3 months; P = 0.03). Complete response (CR) to therapy was noted in 14 of 95 patients. AF-PRS(+) preferentially selected a majority (79%) of CRs, which were evenly split between patients stage I to III (six of seven) and stage IV (five of seven) at the time of treatment.

CONCLUSIONS

AF-PRS identified a significant population of patients with extended PFS and/or clinical response following PMX-PDC treatment. AF-PRS may be a useful diagnostic test for patients indicated for systemic chemotherapy, especially when determining the optimal PDC regimen for locally advanced disease.

Abstract A002: Purity Independent Subtyping of Tumor (PurIST): Real-world data validation of a pancreatic ductal adenocarcinoma (PDAC) gene expression classifier and its prognostic implications

Background: PDAC is a highly morbid disease with no validated biomarkers for first-line (1L) treatment selection. The PurIST single-sample molecular subtyping gene signature, initially described by Rashid et al. (Clin. Cancer Res., 2020), classifies PDAC tumors as basal or classical. Prior work showed that these subtypes are associated with prognosis and that basal subtype patients have significantly lower objective response rate to FOLFIRINOX (FFX) compared to classical subtype patients. This suggests potential implications for treatment with FFX versus gemcitabine and nab-paclitaxel (GnP). Here, we retrospectively demonstrate the clinical validity of PurIST implemented as a laboratory developed test (LDT) on the Tempus Labs sequencing platform using a real-world dataset of advanced PDAC patients. Methods: De-identified PDAC patients were selected from the Tempus Oncology Data Ecosystem under an IRB-approved protocol according to the following inclusion criteria: no systemic treatment, surgically unresectable/metastatic, available RNA-sequencing data from primary or metastatic tissue, and FFX or GnP as 1L systemic therapy with available outcomes. Sequencing was performed by the CAP/CLIA validated Tempus xT assay. The PurIST model was applied to normalized RNA-sequence abundance files to compute a basal or classical subtype label. Predefined statistical analysis parameters included 12-month survival rate and median overall survival (OS) in FFX treated patients. OS was compared using Kaplan-Meier estimates, hazard ratios, and log-rank statistical tests. Results: 258 PDAC patients (64.9 +/- 9.9 yrs, 42% female), were identified for analysis with median OS of 11.7 months (95% CI: 10.6-13.7) and 12-month censorship rate of 12.8%. 151 patients were treated with FFX and 107 with GnP. 42 patients (28%) receiving FFX and 31 patients (29%) receiving GnP were classified as basal. Among FFX treated patients, median OS was 14.4 months (95% CI: 12.5-16.9) in classical patients vs. 9.4 months (95% CI: 8.3-14.5) in basal patients (HR = 1.72, 95% CI = 1.2-2.6, p=0.006). The 12-month survival rate was significantly lower in basal patients receiving FFX vs. classical patients (33.3% vs. 59.4%, p=0.011). In basal patients, no difference in OS was observed between FFX and GnP groups (p=0.6). Classical patients receiving FFX had a 14.4 months median OS vs. 10.8 months for patients receiving GnP (p=0.046). Conclusions: In this real-world cohort, we validate the association between PurIST subtypes and PDAC patient survival when administered FFX or GnP. Among FFX-treated patients, classical patients had significantly better outcomes compared to basal patients. Moreover, classical patients appeared to have improved outcomes with FFX vs. GnP. These findings represent underlying biological PDAC differences and demonstrate the clinical validity of PurIST as a prognostic marker in PDAC patients when performed as an LDT on the Tempus xT platform. Ongoing evaluation of PurIST performance will be continuously monitored through the Tempus Oncology Data ecosystem.

Citation Format: Stephane Wenric, James M. Davison, Yun E. Wang, Gregory M. Mayhew, Kirk Beebe, Hyunseok P. Kang, Michael V. Milburn, Vincent Chung, Tanios Bekaii-Saab, Charles M. Perou. Purity Independent Subtyping of Tumor (PurIST): Real-world data validation of a pancreatic ductal adenocarcinoma (PDAC) gene expression classifier and its prognostic implications [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr A002.

Distinct Predictive Immunogenomic Profiles of Response to Immune Checkpoint Inhibitors and IL2: A Real-world Evidence Study of Patients with Advanced Renal Cancer

Recombinant human high-dose IL2 (HD-IL2; aldesleukin) was one of the first approved immune-oncology agents based upon clinical activity in renal cell carcinoma (RCC) and metastatic melanoma but use was limited due to severe toxicity. Next-generation IL2 agents designed to improve tolerability are in development, increasing the need for future identification of genomic markers of clinical benefit and/or clinical response. In this retrospective study, we report clinical and tumor molecular profiling from patients with metastatic RCC (mRCC) treated with HD-IL2 and compare findings with patients with RCC treated with anti-PD-1 therapy. Genomic characteristics common and unique to IL2 and/or anti-PD-1 therapy response are presented, with insight into rational combination strategies for these agents. Residual pretreatment formalin-fixed paraffin embedded tumor samples from n = 36 patients with HD-IL2 mRCC underwent RNA-sequencing and corresponding clinical data were collected. A de novo 40-gene nearest centroid IL2 treatment response classifier and individual gene and/or immune marker signature differences were correlated to clinical response and placed into context with a separate dataset of n = 35 patients with anti-PD-1 mRCC. Immune signatures and genes, comprising suppressor and effector cells, were increased in patients with HD-IL2 clinical benefit. The 40-gene response classifier was also highly enriched for immune genes. While several effector immune signatures and genes were common between IL2 and anti-PD-1 treated patients, multiple inflammatory and/or immunosuppressive genes, previously reported to predict poor response to anti-PD-L1 immunotherapy, were only increased in IL2-responsive tumors. These findings suggest that common and distinct immune-related response markers for IL2 and anti-PD-1 therapy may help guide their use, either alone or in combination.

Significance

Next-generation IL2 agents, designed for improved tolerability over traditional HD-IL2 (aldesleukin), are in clinical development. Retrospective molecular tumor profiling of patients treated with HD-IL2 or anti-PD-1 therapy provides insights into genomic characteristics of therapy response. This study revealed common and distinct immune-related predictive response markers for IL2 and anti-PD-1 therapy which may play a role in therapy guidance, and rational combination strategies for these agents.

Genome-wide scan identifies novel genetic loci regulating salivary metabolite levels

Saliva, as a biofluid, is inexpensive and non-invasive to obtain, and provides a vital tool to investigate oral health and its interaction with systemic health conditions. There is growing interest in salivary biomarkers for systemic diseases, notably cardiovascular disease. Whereas hundreds of genetic loci have been shown to be involved in the regulation of blood metabolites, leading to significant insights into the pathogenesis of complex human diseases, little is known about the impact of host genetics on salivary metabolites. Here we report the first genome-wide association study exploring 476 salivary metabolites in 1419 subjects from the TwinsUK cohort (discovery phase), followed by replication in the Study of Health in Pomerania (SHIP-2) cohort. A total of 14 distinct locus-metabolite associations were identified in the discovery phase, most of which were replicated in SHIP-2. While only a limited number of the loci that are known to regulate blood metabolites were also associated with salivary metabolites in our study, we identified several novel saliva-specific locus-metabolite associations, including associations for the AGMAT (with the metabolites 4-guanidinobutanoate and beta-guanidinopropanoate), ATP13A5 (with the metabolite creatinine) and DPYS (with the metabolites 3-ureidopropionate and 3-ureidoisobutyrate) loci. Our study suggests that there may be regulatory pathways of particular relevance to the salivary metabolome. In addition, some of our findings may have clinical significance, such as the utility of the pyrimidine (uracil) degradation metabolites in predicting 5-fluorouracil toxicity and the role of the agmatine pathway metabolites as biomarkers of oral health.

Hypoxia-mediated impaired erythrocyte Lands' Cycle is pathogenic for sickle cell disease

Although Lands' cycle was discovered in 1958, its function and cellular regulation in membrane homeostasis under physiological and pathological conditions remain largely unknown. Nonbiased high throughput metabolomic profiling revealed that Lands' cycle was impaired leading to significantly elevated erythrocyte membrane lysophosphatidylcholine (LysoPC) content and circulating and erythrocyte arachidonic acid (AA) in mice with sickle cell disease (SCD), a prevalent hemolytic genetic disorder. Correcting imbalanced Lands' cycle by knockdown of phospholipase 2 (cPLA2) or overexpression of lysophosphatidycholine acyltransferase 1 (LPCAT1), two key enzymes of Lands' cycle in hematopoietic stem cells, reduced elevated erythrocyte membrane LysoPC content and circulating AA levels and attenuated sickling, inflammation and tissue damage in SCD chimeras. Human translational studies validated SCD mouse findings and further demonstrated that imbalanced Lands' cycle induced LysoPC production directly promotes sickling in cultured mouse and human SCD erythrocytes. Mechanistically, we revealed that hypoxia-mediated ERK activation underlies imbalanced Lands' cycle by preferentially inducing the activity of PLA2 but not LPCAT in human and mouse SCD erythrocytes. Overall, our studies have identified a pathological role of imbalanced Lands' cycle in SCD erythrocytes, novel molecular basis regulating Lands' cycle and therapeutic opportunities for the disease.

Untargeted metabolomic analysis for the clinical screening of inborn errors of metabolism

Global metabolic profiling currently achievable by untargeted mass spectrometry-based metabolomic platforms has great potential to advance our understanding of human disease states, including potential utility in the detection of novel and known inborn errors of metabolism (IEMs). There are few studies of the technical reproducibility, data analysis methods, and overall diagnostic capabilities when this technology is applied to clinical specimens for the diagnosis of IEMs. We explored the clinical utility of a metabolomic workflow capable of routinely generating semi-quantitative z-score values for ~900 unique compounds, including ~500 named human analytes, in a single analysis of human plasma. We tested the technical reproducibility of this platform and applied it to the retrospective diagnosis of 190 individual plasma samples, 120 of which were collected from patients with a confirmed IEM. Our results demonstrate high intra-assay precision and linear detection for the majority compounds tested. Individual metabolomic profiles provided excellent sensitivity and specificity for the detection of a wide range of metabolic disorders and identified novel biomarkers for some diseases. With this platform, it is possible to use one test to screen for dozens of IEMs that might otherwise require ordering multiple unique biochemical tests. However, this test may yield false negative results for certain disorders that would be detected by a more well-established quantitative test and in its current state should be considered a supplementary test. Our findings describe a novel approach to metabolomic analysis of clinical specimens and demonstrate the clinical utility of this technology for prospective screening of IEMs.

Bladder cancer biomarker discovery using global metabolomic profiling of urine

Bladder cancer (BCa) is a common malignancy worldwide and has a high probability of recurrence after initial diagnosis and treatment. As a result, recurrent surveillance, primarily involving repeated cystoscopies, is a critical component of post diagnosis patient management. Since cystoscopy is invasive, expensive and a possible deterrent to patient compliance with regular follow-up screening, new non-invasive technologies to aid in the detection of recurrent and/or primary bladder cancer are strongly needed. In this study, mass spectrometry based metabolomics was employed to identify biochemical signatures in human urine that differentiate bladder cancer from non-cancer controls. Over 1000 distinct compounds were measured including 587 named compounds of known chemical identity. Initial biomarker identification was conducted using a 332 subject sample set of retrospective urine samples (cohort 1), which included 66 BCa positive samples. A set of 25 candidate biomarkers was selected based on statistical significance, fold difference and metabolic pathway coverage. The 25 candidate biomarkers were tested against an independent urine sample set (cohort 2) using random forest analysis, with palmitoyl sphingomyelin, lactate, adenosine and succinate providing the strongest predictive power for differentiating cohort 2 cancer from non-cancer urines. Cohort 2 metabolite profiling revealed additional metabolites, including arachidonate, that were higher in cohort 2 cancer vs. non-cancer controls, but were below quantitation limits in the cohort 1 profiling. Metabolites related to lipid metabolism may be especially interesting biomarkers. The results suggest that urine metabolites may provide a much needed non-invasive adjunct diagnostic to cystoscopy for detection of bladder cancer and recurrent disease management.

Elevated sphingosine-1-phosphate promotes sickling and sickle cell disease progression

Sphingosine-1-phosphate (S1P) is a bioactive lipid that regulates multicellular functions through interactions with its receptors on cell surfaces. S1P is enriched and stored in erythrocytes; however, it is not clear whether alterations in S1P are involved in the prevalent and debilitating hemolytic disorder sickle cell disease (SCD). Here, using metabolomic screening, we found that S1P is highly elevated in the blood of mice and humans with SCD. In murine models of SCD, we demonstrated that elevated erythrocyte sphingosine kinase 1 (SPHK1) underlies sickling and disease progression by increasing S1P levels in the blood. Additionally, we observed elevated SPHK1 activity in erythrocytes and increased S1P in blood collected from patients with SCD and demonstrated a direct impact of elevated SPHK1-mediated production of S1P on sickling that was independent of S1P receptor activation in isolated erythrocytes. Together, our findings provide insights into erythrocyte pathophysiology, revealing that a SPHK1-mediated elevation of S1P contributes to sickling and promotes disease progression, and highlight potential therapeutic opportunities for SCD.

An atlas of genetic influences on human blood metabolites

Genome-wide association scans with high-throughput metabolic profiling provide unprecedented insights into how genetic variation influences metabolism and complex disease. Here we report the most comprehensive exploration of genetic loci influencing human metabolism to date, including 7,824 adult individuals from two European population studies. We report genome-wide significant associations at 145 metabolic loci and their biochemical connectivity regarding more than 400 metabolites in human blood. We extensively characterize the resulting in vivo blueprint of metabolism in human blood by integrating it with information regarding gene expression, heritability, overlap with known drug targets, previous association with complex disorders and inborn errors of metabolism. We further developed a database and web-based resources for data mining and results visualization. Our findings contribute to a greater understanding of the role of inherited variation in blood metabolic diversity, and identify potential new opportunities for pharmacologic development and disease understanding.

Serum metabolomics indicate altered cellular energy metabolism in children with cystic fibrosis

BACKGROUND

Cystic fibrosis (CF) is a multi-system disease affecting multiple organs and cells besides the respiratory system. Metabolomic profiling allows simultaneous detection of biochemicals originating from cells, organs, or exogenous origin that may be valuable for monitoring of disease severity or in diagnosis.

AIM

We hypothesized that metabolomics using serum from children would differentiate CF from non-CF lung disease subjects and would provide insight into metabolism in CF.

METHODS

Serum collected from children with CF (n = 31) and 31 age and gender matched children with other lung diseases was used for metabolomic profiling by gas- and liquid-chromatography. Relative concentration of metabolites was compared between the groups using partial least square discriminant analyses (PLS-DA) and linear modeling.

RESULTS

A clear separation of the two groups was seen in PLS-DA. Linear model found that among the 459 detected metabolites 92 differed between CF and non-CF. These included known biochemicals in lipid metabolism, oxidants, and markers consistent with abnormalities in bile acid processing. Bacterial metabolites were identified and differed between the groups indicating intestinal dysbiosis in CF. As a novel finding several pathways were markedly different in CF, which jointly point towards decreased activity in the β-oxidation of fatty acids. These pathways include low ketone bodies, low medium chain carnitines, elevated di-carboxylic acids and decreased 2-hydroxybutyrate from amino acid metabolism in CF compared to non-CF.

CONCLUSION

Serum metabolomics discriminated CF from non-CF and show altered cellular energy metabolism in CF potentially reflecting mitochondrial dysfunction. Future studies are indicated to examine their relation to the underlying CF defect and their use as biomarkers for disease severity or for cystic fibrosis transmembrane regulator (CFTR) function in an era of CFTR modifying drugs.

Metabolomic signatures in lipid-loaded HepaRGs reveal pathways involved in steatotic progression

OBJECTIVES

A spectrum of disorders including simple steatosis, nonalcoholic steatohepatitis, fibrosis, and cirrhosis is described by nonalcoholic fatty liver disease (NAFLD). With the increased prevalence of obesity, and consequently NAFLD, there is a need for novel therapeutics in this area. To facilitate this effort, a cellular model of hepatic steatosis was developed using HepaRG cells and the resulting biochemical alterations were determined.

DESIGN AND METHODS

Using global metabolomic profiling, by means of a novel metabolite extraction procedure, the metabolic profiles in response to the saturated fatty acid palmitate, and a mixture of saturated and unsaturated fatty acids, palmitate and oleate (1:2) were examined.

RESULTS

We observed elevated levels of the branched chain amino acids, tricarboxylic acid cycle intermediates, sphingosine and acylcarnitines, and reduced levels of carnitine in the steatotic HepaRG model with both palmitate and palmitate:oleate treatments. In addition, elevated levels of diacylglycerols and monoacylglycerols as well as altered bile acid metabolism were selectively displayed by palmitate-induced steatotic cells.

CONCLUSIONS

Biochemical changes in pathways important in the transition to hepatic steatosis including insulin resistance, altered mitochondrial metabolism, and oxidative stress are revealed by this global metabolomic approach. Moreover, the utility of this in vitro model for investigating the mechanisms of steatotic progression, insulin resistance, and lipotoxicity in NAFLD was demonstrated.

Metabolomic signatures of aggressive prostate cancer

BACKGROUND

Current diagnostic techniques have increased the detection of prostate cancer; however, these tools inadequately stratify patients to minimize mortality. Recent studies have identified a biochemical signature of prostate cancer metastasis, including increased sarcosine abundance. This study examined the association of tissue metabolites with other clinically significant findings.

METHODS

A state of the art metabolomics platform analyzed prostatectomy tissues (331 prostate tumor, 178 cancer-free prostate tissues) from two independent sites. Biochemicals were analyzed by gas chromatography-mass spectrometry and ultrahigh performance liquid chromatography-tandem mass spectrometry. Statistical analyses identified metabolites associated with cancer aggressiveness: Gleason score, extracapsular extension, and seminal vesicle and lymph node involvement.

RESULTS

Prostate tumors had significantly altered metabolite profiles compared to cancer-free prostate tissues, including biochemicals associated with cell growth, energetics, stress, and loss of prostate-specific biochemistry. Many metabolites were further associated with clinical findings of aggressive disease. Aggressiveness-associated metabolites stratified prostate tumor tissues with high abundances of compounds associated with normal prostate function (e.g., citrate and polyamines) from more clinically advanced prostate tumors. These aggressive prostate tumors were further subdivided by abundance profiles of metabolites including NAD+ and kynurenine. When added to multiparametric nomograms, metabolites improved prediction of organ confinement (AUROC from 0.53 to 0.62) and 5-year recurrence (AUROC from 0.53 to 0.64).

CONCLUSIONS

These findings support and extend earlier metabolomic studies in prostate cancer and studies where metabolic enzymes have been associated with carcinogenesis and/or outcome. Furthermore, these data suggest that panels of analytes may be valuable to translate metabolomic findings to clinically useful diagnostic tests.

Metabolomic profiles in individuals with negative affectivity and social inhibition: a population-based study of Type D personality

BACKGROUND

Individuals with negative affectivity who are inhibited in social situations are characterized as distressed, or Type D, and have an increased risk of cardiovascular disease (CVD). The underlying biomechanisms that link this psychological affect to a pathological state are not well understood. This study applied a metabolomic approach to explore biochemical pathways that may contribute to the Type D personality.

METHODS

Type D personality was determined by the Type D Scale-14. Small molecule biochemicals were measured using two complementary mass-spectrometry based metabolomics platforms. Metabolic profiles of Type D and non-Type D participants within a population-based study in Southern Germany were compared in cross-sectional regression analyses. The PHQ-9 and GAD-7 instruments were also used to assess symptoms of depression and anxiety, respectively, within this metabolomic study.

RESULTS

668 metabolites were identified in the serum of 1502 participants (age 32-77); 386 of these individuals were classified as Type D. While demographic and biomedical characteristics were equally distributed between the groups, a higher level of depression and anxiety was observed in Type D individuals. Significantly lower levels of the tryptophan metabolite kynurenine were associated with Type D (p-value corrected for multiple testing=0.042), while no significant associations could be found for depression and anxiety. A Gaussian graphical model analysis enabled the identification of four potentially interesting metabolite networks that are enriched in metabolites (androsterone sulfate, tyrosine, indoxyl sulfate or caffeine) that associate nominally with Type D personality.

CONCLUSIONS

This study identified novel biochemical pathways associated with Type D personality and demonstrates that the application of metabolomic approaches in population studies can reveal mechanisms that may contribute to psychological health and disease.

Application of metabolomics to diagnosis of insulin resistance

Metabolomics, the global interrogation of the biochemical components in a biological sample, has become an important complement to genomics and proteomics to aid in the understanding of pathophysiology. Major advantages of metabolomics are the size of the metabolome relative to the genome or proteome and the fact that it provides a view of the existing biochemical phenotype. As such, metabolomics is fast becoming an important discovery tool for new diagnostic and prognostic biomarkers. Although many methods exist for performing metabolomics, relatively few have led to successful development of new diagnostic tests. This review will aid the reader in understanding various metabolomic methods and their applications, as well as some of their inherent advantages and disadvantages. In addition, we present one example of the application of metabolomics to the identification of new fasting blood biomarkers for the diagnosis and monitoring of insulin resistance.

Early metabolic markers of the development of dysglycemia and type 2 diabetes and their physiological significance

Metabolomic screening of fasting plasma from nondiabetic subjects identified α-hydroxybutyrate (α-HB) and linoleoyl-glycerophosphocholine (L-GPC) as joint markers of insulin resistance (IR) and glucose intolerance. To test the predictivity of α-HB and L-GPC for incident dysglycemia, α-HB and L-GPC measurements were obtained in two observational cohorts, comprising 1,261 nondiabetic participants from the Relationship between Insulin Sensitivity and Cardiovascular Disease (RISC) study and 2,580 from the Botnia Prospective Study, with 3-year and 9.5-year follow-up data, respectively. In both cohorts, α-HB was a positive correlate and L-GPC a negative correlate of insulin sensitivity, with α-HB reciprocally related to indices of β-cell function derived from the oral glucose tolerance test (OGTT). In follow-up, α-HB was a positive predictor (adjusted odds ratios 1.25 [95% CI 1.00-1.60] and 1.26 [1.07-1.48], respectively, for each standard deviation of predictor), and L-GPC was a negative predictor (0.64 [0.48-0.85] and 0.67 [0.54-0.84]) of dysglycemia (RISC) or type 2 diabetes (Botnia), independent of familial diabetes, sex, age, BMI, and fasting glucose. Corresponding areas under the receiver operating characteristic curve were 0.791 (RISC) and 0.783 (Botnia), similar in accuracy when substituting α-HB and L-GPC with 2-h OGTT glucose concentrations. When their activity was examined, α-HB inhibited and L-GPC stimulated glucose-induced insulin release in INS-1e cells. α-HB and L-GPC are independent predictors of worsening glucose tolerance, physiologically consistent with a joint signature of IR and β-cell dysfunction.

Perturbation of bile acid homeostasis is an early pathogenesis event of drug induced liver injury in rats

Drug-induced liver injury (DILI) is a significant consideration for drug development. Current preclinical DILI assessment relying on histopathology and clinical chemistry has limitations in sensitivity and discordance with human. To gain insights on DILI pathogenesis and identify potential biomarkers for improved DILI detection, we performed untargeted metabolomic analyses on rats treated with thirteen known hepatotoxins causing various types of DILI: necrosis (acetaminophen, bendazac, cyclosporine A, carbon tetrachloride, ethionine), cholestasis (methapyrilene and naphthylisothiocyanate), steatosis (tetracycline and ticlopidine), and idiosyncratic (carbamazepine, chlorzoxasone, flutamide, and nimesulide) at two doses and two time points. Statistical analysis and pathway mapping of the nearly 1900 metabolites profiled in the plasma, urine, and liver revealed diverse time and dose dependent metabolic cascades leading to DILI by the hepatotoxins. The most consistent change induced by the hepatotoxins, detectable even at the early time point/low dose, was the significant elevations of a panel of bile acids in the plasma and urine, suggesting that DILI impaired hepatic bile acid uptake from the circulation. Furthermore, bile acid amidation in the hepatocytes was altered depending on the severity of the hepatotoxin-induced oxidative stress. The alteration of the bile acids was most evident by the necrosis and cholestasis hepatotoxins, with more subtle effects by the steatosis and idiosyncratic hepatotoxins. Taking together, our data suggest that the perturbation of bile acid homeostasis is an early event of DILI. Upon further validation, selected bile acids in the circulation could be potentially used as sensitive and early DILI preclinical biomarkers.

Mining the unknown: a systems approach to metabolite identification combining genetic and metabolic information

Recent genome-wide association studies (GWAS) with metabolomics data linked genetic variation in the human genome to differences in individual metabolite levels. A strong relevance of this metabolic individuality for biomedical and pharmaceutical research has been reported. However, a considerable amount of the molecules currently quantified by modern metabolomics techniques are chemically unidentified. The identification of these “unknown metabolites” is still a demanding and intricate task, limiting their usability as functional markers of metabolic processes. As a consequence, previous GWAS largely ignored unknown metabolites as metabolic traits for the analysis. Here we present a systems-level approach that combines genome-wide association analysis and Gaussian graphical modeling with metabolomics to predict the identity of the unknown metabolites. We apply our method to original data of 517 metabolic traits, of which 225 are unknowns, and genotyping information on 655,658 genetic variants, measured in 1,768 human blood samples. We report previously undescribed genotype–metabotype associations for six distinct gene loci (SLC22A2, COMT, CYP3A5, CYP2C18, GBA3, UGT3A1) and one locus not related to any known gene (rs12413935). Overlaying the inferred genetic associations, metabolic networks, and knowledge-based pathway information, we derive testable hypotheses on the biochemical identities of 106 unknown metabolites. As a proof of principle, we experimentally confirm nine concrete predictions. We demonstrate the benefit of our method for the functional interpretation of previous metabolomics biomarker studies on liver detoxification, hypertension, and insulin resistance. Our approach is generic in nature and can be directly transferred to metabolomics data from different experimental platforms.

Genome-wide association studies on metabolomics data have demonstrated that genetic variation in metabolic enzymes and transporters leads to concentration changes in the respective metabolite levels. The conventional goal of these studies is the detection of novel interactions between the genome and the metabolic system, providing valuable insights for both basic research as well as clinical applications. In this study, we borrow the metabolomics GWAS concept for a novel, entirely different purpose. Metabolite measurements frequently produce signals where a certain substance can be reliably detected in the sample, but it has not yet been elucidated which specific metabolite this signal actually represents. The concept is comparable to a fingerprint: each one is uniquely identifiable, but as long as it is not registered in a database one cannot tell to whom this fingerprint belongs. Obviously, this issue tremendously reduces the usability of a metabolomics analyses. The genetic associations of such an “unknown,” however, give us concrete evidence of the metabolic pathway this substance is most probably involved in. Moreover, we complement the approach with a specific measure of correlation between metabolites, providing further evidence of the metabolic processes of the unknown. For a number of cases, this even allows for a concrete identity prediction, which we then experimentally validate in the lab.

Cancer detection and biopsy classification using concurrent histopathological and metabolomic analysis of core biopsies

Background

Metabolomics, the non-targeted interrogation of small molecules in a biological sample, is an ideal technology for identifying diagnostic biomarkers. Current tissue extraction protocols involve sample destruction, precluding additional uses of the tissue. This is particularly problematic for high value samples with limited availability, such as clinical tumor biopsies that require structural preservation to histologically diagnose and gauge cancer aggressiveness. To overcome this limitation and increase the amount of information obtained from patient biopsies, we developed and characterized a workflow to perform metabolomic analysis and histological evaluation on the same biopsy sample.

Methods

Biopsies of ten human tissues (muscle, adrenal gland, colon, lung, pancreas, small intestine, spleen, stomach, prostate, kidney) were placed directly in a methanol solution to recover metabolites, precipitate proteins, and fix tissue. Following incubation, biopsies were removed from the solution and processed for histology. Kidney and prostate cancer tumor and benign biopsies were stained with hemotoxylin and eosin and prostate biopsies were subjected to PIN-4 immunohistochemistry. The methanolic extracts were analyzed for metabolites on GC/MS and LC/MS platforms. Raw mass spectrometry data files were automatically extracted using an informatics system that includes peak identification and metabolite identification software.

Results

Metabolites across all major biochemical classes (amino acids, peptides, carbohydrates, lipids, nucleotides, cofactors, xenobiotics) were measured. The number (ranging from 260 in prostate to 340 in colon) and identity of metabolites were comparable to results obtained with the current method requiring 30 mg ground tissue. Comparing relative levels of metabolites, cancer tumor from benign kidney and prostate biopsies could be distinguished. Successful histopathological analysis of biopsies by chemical staining (hematoxylin, eosin) and antibody binding (PIN-4, in prostate) showed cellular architecture and immunoreactivity were retained.

Conclusions

Concurrent metabolite extraction and histological analysis of intact biopsies is amenable to the clinical workflow. Methanol fixation effectively preserves a wide range of tissues and is compatible with chemical staining and immunohistochemistry. The method offers an opportunity to augment histopathological diagnosis and tumor classification with quantitative measures of biochemicals in the same tissue sample. Since certain biochemicals have been shown to correlate with disease aggressiveness, this method should prove valuable as an adjunct to differentiate cancer aggressiveness.

Biochemical alterations associated with ALS

Our objective was to identify metabolic pathways affected by ALS using non-targeted metabolomics in plasma, comparing samples from healthy volunteers to those from ALS patients. This discovery could become the basis for the identification of therapeutic targets and diagnostic biomarkers of ALS. Two distinct cross-sectional studies were conducted. Plasma was collected from 62 (Study 1) and 99 (Study 2) participants meeting El Escorial criteria for possible, probable, or definite ALS; 69 (Study 1) and 48 (Study 2) healthy controls samples were collected. Global metabolic profiling was used to detect and evaluate biochemical signatures of ALS. Twenty-three metabolites were significantly altered in plasma from ALS patients in both studies. These metabolites include biochemicals in pathways associated with neuronal change, hypermetabolism, oxidative damage, and mitochondrial dysfunction, all of which are proposed disease mechanisms in ALS. The data also suggest possible hepatic dysfunction associated with ALS. In conclusion, the data presented here provide insight into the pathophysiology of ALS while suggesting promising areas of focus for future studies. The metabolomics approach can generate novel hypotheses regarding ALS disease mechanisms with the potential to identify therapeutic targets and novel diagnostic biomarkers.

Human metabolic individuality in biomedical and pharmaceutical research

Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.

Assessment of the effects of dentifrice on periodontal disease biomarkers in gingival crevicular fluid

BACKGROUND

Periodontal disease has been studied primarily from clinical outcomes in lengthy human studies. Comprehensive biochemical profiling (metabolomics) has become a powerful tool for disease characterization and biomarker discovery. In a previous study, we performed a metabolomic analysis of gingival crevicular fluid collected from healthy, gingivitis, and periodontitis sites. Many metabolites associated with inflammation, oxidative stress, tissue degradation, and bacterial metabolism were found to be significantly induced by the diseases.

METHODS

A panel of 10 markers was selected from the previous metabolomic study based on their statistical significance. Thirty-nine chronic periodontitis subjects were randomly assigned to a toothpaste regimen: control dentifrice (n = 21) or triclosan-containing dentifrice ([CT] n = 18). Subjects were instructed to use their assigned dentifrice twice daily for 6 weeks. Gingival crevicular fluid samples from six healthy, six gingivitis, and three periodontitis sites were collected from each subject at baseline, 1 week, and 6 weeks. The relative levels of the markers in the samples were determined by mass spectrometry. One-sided matched-paired t tests were performed to compare data from healthy, gingivitis, and periodontitis sites.

RESULTS

Statistical analysis indicates that CT significantly decreased the levels of inosine, lysine, putrescine, and xanthine at the gingivitis sites as early as week 1. In contrast, control dentifrice had little effect.

CONCLUSIONS

This result provides biochemical confirmation for the therapeutic effects of CT on gingivitis. Biomarkers were significantly altered by CT before clinical changes were observed, suggesting that the markers have predicative value for disease state assessment.

Metabolic footprint of diabetes: a multiplatform metabolomics study in an epidemiological setting

BACKGROUND

Metabolomics is the rapidly evolving field of the comprehensive measurement of ideally all endogenous metabolites in a biological fluid. However, no single analytic technique covers the entire spectrum of the human metabolome. Here we present results from a multiplatform study, in which we investigate what kind of results can presently be obtained in the field of diabetes research when combining metabolomics data collected on a complementary set of analytical platforms in the framework of an epidemiological study.

METHODOLOGY/PRINCIPAL FINDINGS

40 individuals with self-reported diabetes and 60 controls (male, over 54 years) were randomly selected from the participants of the population-based KORA (Cooperative Health Research in the Region of Augsburg) study, representing an extensively phenotyped sample of the general German population. Concentrations of over 420 unique small molecules were determined in overnight-fasting blood using three different techniques, covering nuclear magnetic resonance and tandem mass spectrometry. Known biomarkers of diabetes could be replicated by this multiple metabolomic platform approach, including sugar metabolites (1,5-anhydroglucoitol), ketone bodies (3-hydroxybutyrate), and branched chain amino acids. In some cases, diabetes-related medication can be detected (pioglitazone, salicylic acid).

CONCLUSIONS/SIGNIFICANCE

Our study depicts the promising potential of metabolomics in diabetes research by identification of a series of known and also novel, deregulated metabolites that associate with diabetes. Key observations include perturbations of metabolic pathways linked to kidney dysfunction (3-indoxyl sulfate), lipid metabolism (glycerophospholipids, free fatty acids), and interaction with the gut microflora (bile acids). Our study suggests that metabolic markers hold the potential to detect diabetes-related complications already under sub-clinical conditions in the general population.

Metabolomic profiling reveals biochemical pathways and biomarkers associated with pathogenesis in cystic fibrosis cells

Cystic fibrosis (CF) is a life-shortening disease caused by a mutation in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. To gain an understanding of the epithelial dysfunction associated with CF mutations and discover biomarkers for therapeutics development, untargeted metabolomic analysis was performed on primary human airway epithelial cell cultures from three separate cohorts of CF patients and non-CF subjects. Statistical analysis revealed a set of reproducible and significant metabolic differences between the CF and non-CF cells. Aside from changes that were consistent with known CF effects, such as diminished cellular regulation against oxidative stress and osmotic stress, new observations on the cellular metabolism in the disease were generated. In the CF cells, the levels of various purine nucleotides, which may function to regulate cellular responses via purinergic signaling, were significantly decreased. Furthermore, CF cells exhibited reduced glucose metabolism in glycolysis, pentose phosphate pathway, and sorbitol pathway, which may further exacerbate oxidative stress and limit the epithelial cell response to environmental pressure. Taken together, these findings reveal novel metabolic abnormalities associated with the CF pathological process and identify a panel of potential biomarkers for therapeutic development using this model system.

Ethylene glycol monomethyl ether-induced toxicity is mediated through the inhibition of flavoprotein dehydrogenase enzyme family

Ethylene glycol monomethyl ether (EGME) is a widely used industrial solvent known to cause adverse effects to human and other mammals. Organs with high metabolism and rapid cell division, such as testes, are especially sensitive to its actions. In order to gain mechanistic understanding of EGME-induced toxicity, an untargeted metabolomic analysis was performed in rats. Male rats were administrated with EGME at 30 and 100 mg/kg/day. At days 1, 4, and 14, serum, urine, liver, and testes were collected for analysis. Testicular injury was observed at day 14 of the 100 mg/kg/day group only. Nearly 1900 metabolites across the four matrices were profiled using liquid chromatography-mass spectrometry/mass spectrometry and gas chromatography-mass spectrometry. Statistical analysis indicated that the most significant metabolic perturbations initiated from the early time points by EGME were the inhibition of choline oxidation, branched-chain amino acid catabolism, and fatty acid β-oxidation pathways, leading to the accumulation of sarcosine, dimethylglycine, and various carnitine- and glycine-conjugated metabolites. Pathway mapping of these altered metabolites revealed that all the disrupted steps were catalyzed by enzymes in the primary flavoprotein dehydrogenase family, suggesting that inhibition of flavoprotein dehydrogenase-catalyzed reactions may represent the mode of action for EGME-induced toxicity. Similar urinary and serum metabolite signatures are known to be the hallmarks of multiple acyl-coenzyme A dehydrogenase deficiency in humans, a genetic disorder because of defects in primary flavoprotein dehydrogenase reactions. We postulate that disruption of key biochemical pathways utilizing flavoprotein dehydrogenases in conjugation with downstream metabolic perturbations collectively result in the EGME-induced tissue damage.

alpha-hydroxybutyrate is an early biomarker of insulin resistance and glucose intolerance in a nondiabetic population

BACKGROUND

Insulin resistance is a risk factor for type 2 diabetes and cardiovascular disease progression. Current diagnostic tests, such as glycemic indicators, have limitations in the early detection of insulin resistant individuals. We searched for novel biomarkers identifying these at-risk subjects.

METHODS

Using mass spectrometry, non-targeted biochemical profiling was conducted in a cohort of 399 nondiabetic subjects representing a broad spectrum of insulin sensitivity and glucose tolerance (based on the hyperinsulinemic euglycemic clamp and oral glucose tolerance testing, respectively).

RESULTS

Random forest statistical analysis selected alpha-hydroxybutyrate (alpha-HB) as the top-ranked biochemical for separating insulin resistant (lower third of the clamp-derived M(FFM) = 33 [12] micromol x min(-1) x kg(FFM) (-1), median [interquartile range], n = 140) from insulin sensitive subjects (M(FFM) = 66 [23] micromol x min(-1) x kg(FFM) (-1)) with a 76% accuracy. By targeted isotope dilution assay, plasma alpha-HB concentrations were reciprocally related to M(FFM); and by partition analysis, an alpha-HB value of 5 microg/ml was found to best separate insulin resistant from insulin sensitive subjects. alpha-HB also separated subjects with normal glucose tolerance from those with impaired fasting glycemia or impaired glucose tolerance independently of, and in an additive fashion to, insulin resistance. These associations were also independent of sex, age and BMI. Other metabolites from this global analysis that significantly correlated to insulin sensitivity included certain organic acid, amino acid, lysophospholipid, acylcarnitine and fatty acid species. Several metabolites are intermediates related to alpha-HB metabolism and biosynthesis.

CONCLUSIONS

alpha-hydroxybutyrate is an early marker for both insulin resistance and impaired glucose regulation. The underlying biochemical mechanisms may involve increased lipid oxidation and oxidative stress.

Metabolomic profiling can predict which humans will develop liver dysfunction when deprived of dietary choline

Choline is an essential nutrient, and deficiency causes liver and muscle dysfunction. Common genetic variations alter the risk of developing organ dysfunction when choline deficient, probably by causing metabolic inefficiencies that should be detectable even while ingesting a normal choline-adequate diet. We determined whether metabolomic profiling of plasma at baseline could predict whether humans will develop liver dysfunction when deprived of dietary choline. Fifty-three participants were fed a diet containing 550 mg choline/70 kg/d for 10 d and then fed < 50 mg choline/70 kg/d for up to 42 d. Participants who developed organ dysfunction on this diet were repleted with a choline-adequate diet for > or = 3 d. Plasma samples, obtained at baseline, end of depletion, and end of repletion, were used for targeted and nontargeted metabolomic profiling. Liver fat was assessed using magnetic resonance spectroscopy. Metabolomic profiling and targeted biochemical analyses were highly correlated for the analytes assessed by both procedures. In addition, we report relative concentration changes of other small molecules detected by the nontargeted metabolomic analysis after choline depletion. Finally, we show that metabolomic profiles of participants when they were consuming a control baseline diet could predict whether they would develop liver dysfunction when deprived of dietary choline.

Acceleration of purine degradation by periodontal diseases

Periodontal diseases, such as gingivitis and periodontitis, are characterized by bacterial plaque accumulation around the gingival crevice and the subsequent inflammation and destruction of host tissues. To test the hypothesis that cellular metabolism is altered as a result of host-bacteria interaction, we performed an unbiased metabolomic profiling of gingival crevicular fluid (GCF) collected from healthy, gingivitis, and periodontitis sites in humans, by liquid and gas chromatography mass spectrometry. The purine degradation pathway, a major biochemical source for reactive oxygen species (ROS) production, was significantly accelerated at the disease sites. This suggests that periodontal-disease-induced oxidative stress and inflammation are mediated through this pathway. The complex host-bacterial interaction was further highlighted by depletion of anti-oxidants, degradation of host cellular components, and accumulation of bacterial products in GCF. These findings provide new mechanistic insights and a panel of comprehensive biomarkers for periodontal disease progression.

Untargeted metabolomic profiling as an evaluative tool of fenofibrate-induced toxicology in Fischer 344 male rats

Peroxisome proliferator-activated receptor-alpha (PPARalpha) agonists such as fenofibrate are used to treat dyslipidemia. Although fenofibrate is considered safe in humans, it is known to cause hepatocarcinogenesis in rodents. To evaluate untargeted metabolic profiling as a tool for gaining insight into the underlying pharmacology and hepatotoxicology, Fischer 344 male rats were dosed with 300 mg/kg/day of fenofibrate for 14 days and the urine and plasma were analyzed on days 2 and 14. A combination of liquid and gas chromatography mass spectrometry returned the profiles of 486 plasma and 932 urinary metabolites. Aside from known pharmacological effects, such as accelerated fatty acid beta-oxidation and reduced plasma cholesterol, new observations on the drug's impact on cellular metabolism were generated. Reductions in TCA cycle intermediates and biochemical evidence of lactic acidosis demonstrated that energy metabolism homeostasis was altered. Perturbation of the glutathione biosynthesis and elevation of oxidative stress markers were observed. Furthermore, tryptophan metabolism was up-regulated, resulting in accumulation of tryptophan metabolites associated with reactive oxygen species generation, suggesting the possibility of oxidative stress as a mechanism of nongenotoxic carcinogenesis. Finally, several metabolites related to liver function, kidney function, cell damage, and cell proliferation were altered by fenofibrate-induced toxicity at this dose.

Analysis of the adult human plasma metabolome

OBJECTIVE

It is well established that disease states are associated with biochemical changes (e.g., diabetes/glucose, cardiovascular disease/cholesterol), as are responses to chemical agents (e.g., medications, toxins, xenobiotics). Recently, nontargeted methods have been used to identify the small molecules (metabolites) in a biological sample to uncover many of the biochemical changes associated with a disease state or chemical response. Given that these experimental results may be influenced by the composition of the cohort, in the present study we assessed the effects of age, sex and race on the relative concentrations of small molecules (metabolites) in the blood of healthy adults.

METHODS

Using gas- and liquid-chromatography in combination with mass spectrometry, a nontargeted metabolomic analysis was performed on plasma collected from an age- and sex-balanced cohort of 269 individuals.

RESULTS

Of the more than 300 unique compounds that were detected, significant changes in the relative concentration of more than 100 metabolites were associated with age. Many fewer differences were associated with sex and fewer still with race. Changes in protein, energy and lipid metabolism, as well as oxidative stress, were observed with increasing age. Tricarboxylic acid intermediates, creatine, essential and nonessential amino acids, urea, ornithine, polyamines and oxidative stress markers (e.g., oxoproline, hippurate) increased with age. Compounds related to lipid metabolism, including fatty acids, carnitine, beta-hydroxybutyrate and cholesterol, were lower in the blood of younger individuals. By contrast, relative concentrations of dehydroepiandrosterone-sulfate (a proposed antiaging androgen) were lowest in the oldest age group. Certain xenobiotics (e.g., caffeine) were higher in older subjects, possibly reflecting decreases in hepatic cytochrome P450 activity.

CONCLUSIONS

Our nontargeted analytical approach detected a large number of metabolites, including those that were found to be statistically altered with age, sex or race. Age-associated changes were more pronounced than those related to differences in sex or race in the population group we studied. Age, sex and race can be confounding factors when comparing different groups in clinical studies. Future studies to determine the influence of diet, lifestyle and medication are also warranted.

The crystal structures of human steroidogenic factor-1 and liver receptor homologue-1

Steroidogenic factor-1 (SF-1) and liver receptor homologue-1 (LRH-1) belong to the fushi tarazu factor 1 subfamily of nuclear receptors. SF-1 is an essential factor for sex determination during development and regulates adrenal and gonadal steroidogenesis in the adult, whereas LRH-1 is a critical factor for development of endodermal tissues and regulates cholesterol and bile acid homeostasis. Regulatory ligands are unknown for SF-1 and LRH-1. A reported mouse LRH-1 structure revealed an empty pocket in a region commonly occupied by ligands in the structures of other nuclear receptors, and pocket-filling mutations did not alter the constitutive activity observed. Here we report the crystal structures of the putative ligand-binding domains of human SF-1 at 2.1-A resolution and human LRH-1 at 2.5-A resolution. Both structures bind a coactivator-derived peptide at the canonical activation-function surface, thus adopting the transcriptionally activating conformation. In human LRH-1, coactivator peptide binding also occurs to a second site. We discovered in both structures a phospholipid molecule bound in a pocket of the putative ligand-binding domain. MS analysis of the protein samples used for crystallization indicated that the two proteins associate with a range of phospholipids. Mutations of the pocket-lining residues reduced the transcriptional activities of SF-1 and LRH-1 in mammalian cell transfection assays without affecting their expression levels. These results suggest that human SF-1 and LRH-1 may be ligand-binding receptors, although it remains to be seen if phospholipids or possibly other molecules regulate SF-1 or LRH-1 under physiological conditions.

A family of phosphodiesterase inhibitors discovered by cocrystallography and scaffold-based drug design

Cyclic nucleotide phosphodiesterases (PDEs) comprise a large family of enzymes that regulate a variety of cellular processes. We describe a family of potent PDE4 inhibitors discovered using an efficient method for scaffold-based drug design. This method involves an iterative approach starting with low-affinity screening of compounds followed by high-throughput cocrystallography to reveal the molecular basis underlying the activity of the newly identified compounds. Through detailed structural analysis of the interaction of the initially discovered pyrazole carboxylic ester scaffold with PDE4D using X-ray crystallography, we identified three sites of chemical substitution and designed small selective libraries of scaffold derivatives with modifications at these sites. A 4,000-fold increase in the potency of this PDE4 inhibitor was achieved after only two rounds of chemical synthesis and the structural analysis of seven pyrazole derivatives bound to PDE4B or PDE4D, revealing the robustness of this approach for identifying new inhibitors that can be further developed into drug candidates.

Structural Basis for the Activity of Drugs that Inhibit Phosphodiesterases

Phosphodiesterases (PDEs) comprise a large family of enzymes that catalyze the hydrolysis of cAMP or cGMP and are implicated in various diseases. We describe the high-resolution crystal structures of the catalytic domains of PDE4B, PDE4D, and PDE5A with ten different inhibitors, including the drug candidates cilomilast and roflumilast, for respiratory diseases. These cocrystal structures reveal a common scheme of inhibitor binding to the PDEs: (i) a hydrophobic clamp formed by highly conserved hydrophobic residues that sandwich the inhibitor in the active site; (ii) hydrogen bonding to an invariant glutamine that controls the orientation of inhibitor binding. A scaffold can be readily identified for any given inhibitor based on the formation of these two types of conserved interactions. These structural insights will enable the design of isoform-selective inhibitors with improved binding affinity and should facilitate the discovery of more potent and selective PDE inhibitors for the treatment of a variety of diseases.

A glutamine switch mechanism for nucleotide selectivity by phosphodiesterases

Phosphodiesterases (PDEs) comprise a family of enzymes that modulate the immune response, inflammation, and memory, among many other functions. There are three types of PDEs: cAMP-specific, cGMP-specific, and dual-specific. Here we describe the mechanism of nucleotide selectivity on the basis of high-resolution co-crystal structures of the cAMP-specific PDE4B and PDE4D with AMP, the cGMP-specific PDE5A with GMP, and the apo-structure of the dual-specific PDE1B. These structures show that an invariant glutamine functions as the key specificity determinant by a "glutamine switch" mechanism for recognizing the purine moiety in cAMP or cGMP. The surrounding residues anchor the glutamine residue in different orientations for cAMP and for cGMP. The PDE1B structure shows that in dual-specific PDEs a key histidine residue may enable the invariant glutamine to toggle between cAMP and cGMP. The structural understanding of nucleotide binding enables the design of new PDE inhibitors that may treat diseases in which cyclic nucleotides play a critical role.

Structural basis for autorepression of retinoid X receptor by tetramer formation and the AF-2 helix

The 9-cis-retinoic acid receptors (RXRalpha, RXRbeta, and RXRgamma) are nuclear receptors that play key roles in multiple hormone-signaling pathways. Biochemical data indicate that, in the absence of ligand, RXR can exist as an inactive tetramer and that its dissociation, induced by ligand, is important for receptor activation. In this article we report the inactivated tetramer structures of the RXRalpha ligand-binding domain (LBD), either in the absence of or in the presence of a nonactivating ligand. These structures reveal that the RXR LBD tetramer forms a compact, disc-shaped complex, consisting of two symmetric dimers that are packed along helices 3 and 11. In each monomer, the AF-2 helix protrudes away from the core domain and spans into the coactivator binding site in the adjacent monomer of the symmetric dimer. In this configuration, the AF-2 helix physically excludes the binding of coactivators and suggests an autorepression mechanism that is mediated by the AF-2 helix within the tetramer. The RXR-tetramer interface is assembled from amino acids that are conserved across several closely related receptors, including the HNF4s and COUP transcription factors, and may therefore provide a model for understanding structure and regulation of this subfamily of nuclear receptors.

Atomic structure of PDE4: insights into phosphodiesterase mechanism and specificity

Cyclic nucleotides are second messengers that are essential in vision, muscle contraction, neurotransmission, exocytosis, cell growth, and differentiation. These molecules are degraded by a family of enzymes known as phosphodiesterases, which serve a critical function by regulating the intracellular concentration of cyclic nucleotides. We have determined the three-dimensional structure of the catalytic domain of phosphodiesterase 4B2B to 1.77 angstrom resolution. The active site has been identified and contains a cluster of two metal atoms. The structure suggests the mechanism of action and basis for specificity and will provide a framework for structure-assisted drug design for members of the phosphodiesterase family.

Crystallization of native and selenomethionyl yeast orotidine 5'-phosphate decarboxylase

Crystals of the Saccharomyces cerevisiae pyrimidine biosynthetic enzyme orotidine 5'-phosphate decarboxylase (ODCase) were grown by the hanging-drop vapor-diffusion technique at 277 K using polyethylene glycol 4000 as the precipitant. Crystals of native and selenomethionyl ODCase diffract to less than 2.2 A and belong to the orthorhombic space group P2(1)2(1)2(1), with unit-cell parameters a = 90.1, b = 116.2, c = 117.0 A. Crystals of ODCase grown in the presence of the postulated transition-state analog inhibitor 6-hydroxyuridine 5'--phosphate (BMP) diffract to less than 2.5 A and belong to space group P2(1), with unit-cell parameters a = 79.9, b = 80.0, c = 98.2 A, beta = 108.6 degrees.

Asymmetry in the PPARgamma/RXRalpha crystal structure reveals the molecular basis of heterodimerization among nuclear receptors

The nuclear receptor PPARgamma/RXRalpha heterodimer regulates glucose and lipid homeostasis and is the target for the antidiabetic drugs GI262570 and the thiazolidinediones (TZDs). We report the crystal structures of the PPARgamma and RXRalpha LBDs complexed to the RXR ligand 9-cis-retinoic acid (9cRA), the PPARgamma agonist rosiglitazone or GI262570, and coactivator peptides. The PPARgamma/RXRalpha heterodimer is asymmetric, with each LBD deviated approximately 10 degrees from the C2 symmetry, allowing the PPARgamma AF-2 helix to interact with helices 7 and 10 of RXRalpha. The heterodimer interface is composed of conserved motifs in PPARgamma and RXRalpha that form a coiled coil along helix 10 with additional charge interactions from helices 7 and 9. The structures provide a molecular understanding of the ability of RXR to heterodimerize with many nuclear receptors and of the permissive activation of the PPARgamma/RXRbeta heterodimer by 9cRA.

Anatomy of a proficient enzyme: the structure of orotidine 5'-monophosphate decarboxylase in the presence and absence of a potential transition state analog

Orotidine 5'-phosphate decarboxylase produces the largest rate enhancement that has been reported for any enzyme. The crystal structure of the recombinant Saccharomyces cerevisiae enzyme has been determined in the absence and presence of the proposed transition state analog 6-hydroxyuridine 5'-phosphate, at a resolution of 2.1 A and 2.4 A, respectively. Orotidine 5'-phosphate decarboxylase folds as a TIM-barrel with the ligand binding site near the open end of the barrel. The binding of 6-hydroxyuridine 5'-phosphate is accompanied by protein loop movements that envelop the ligand almost completely, forming numerous favorable interactions with the phosphoryl group, the ribofuranosyl group, and the pyrimidine ring. Lysine-93 appears to be anchored in such a way as to optimize electrostatic interactions with developing negative charge at C-6 of the pyrimidine ring, and to donate the proton that replaces the carboxylate group at C-6 of the product. In addition, H-bonds from the active site to O-2 and O-4 help to delocalize negative charge in the transition state. Interactions between the enzyme and the phosphoribosyl group anchor the pyrimidine within the active site, helping to explain the phosphoribosyl group's remarkably large contribution to catalysis despite its distance from the site of decarboxylation.

Molecular determinants of nuclear receptor-corepressor interaction

Retinoic acid and thyroid hormone receptors can act alternatively as ligand-independent repressors or ligand-dependent activators, based on an exchange of N-CoR or SMRT-containing corepressor complexes for coactivator complexes in response to ligands. We provide evidence that the molecular basis of N-CoR recruitment is similar to that of coactivator recruitment, involving cooperative binding of two helical interaction motifs within the N-CoR carboxyl terminus to both subunits of a RAR-RXR heterodimer. The N-CoR and SMRT nuclear receptor interaction motifs exhibit a consensus sequence of LXX I/H I XXX I/L, representing an extended helix compared to the coactivator LXXLL helix, which is able to interact with specific residues in the same receptor pocket required for coactivator binding. We propose a model in which discrimination of the different lengths of the coactivator and corepressor interaction helices by the nuclear receptor AF2 motif provides the molecular basis for the exchange of coactivators for corepressors, with ligand-dependent formation of the charge clamp that stabilizes LXXLL binding sterically inhibiting interaction of the extended corepressor helix.

The PPARs and PXRs: nuclear xenobiotic receptors that define novel hormone signaling pathways

Traditional pharmacologic approaches had identified several classes of xenobiotics that elicited characteristic biological effects in vivo but that lacked defined molecular mechanisms of action. Among these xenobiotics were the peroxisome proliferators, the thiazolidinediones (TZDs), and a set of compounds that induced the expression of cytochrome P450 (CYP) 3A genes and promoted the metabolism of other xenobiotics. All three classes of xenobiotics are now known to exert their actions through activation of orphan members of the nuclear receptor family of ligand-activated transcription factors. Peroxisome proliferators are a diverse group of amphipathic acids that include the fibrate class of triglyceride- and cholesterol-lowering drugs. TZDs sensitize tissues such as skeletal muscle, liver, and adipose to the actions of insulin and lower glucose and lipid levels in type 2 diabetics. The peroxisome proliferators and TZDs are now known to mediate their effects through the peroxisome proliferator-activated receptors (PPARs) alpha and gamma, respectively. The activities of these compounds established the PPARs as key regulators of glucose and lipid homeostasis. We and others have recently shown that various naturally occurring fatty acids and eicosanoids serve as PPAR ligands, suggesting a novel regulatory mechanism whereby dietary lipids and their metabolites can regulate gene transcription and impact overall energy balance. The third class of xenobiotics we have studied induces the expression of CYP3A genes, mono-oxygenases responsible for the metabolism of natural steroids as well as a variety of xenobiotics, including > 60% of all drugs. We have recently shown that compounds that induce CYP3A gene expression do so through activation of novel orphan receptors, termed the pregnane X receptors (PXRs). Many of the PXR activators are widely used drugs such as dexamethasone, lovastatin, and rifampicin, whose induction of CYP3A levels causes them to promote the metabolism of other drugs, often with adverse consequences. Thus, the finding that the PXRs regulate CYP3A gene expression provides a basis for the efficient identification and elimination of candidate drugs that will interact with other medicines. Searches for natural ligands have revealed that the PXRs are activated by C21 steroids, including pregnenolone and progesterone, suggesting that these orphan receptors define a novel steroid hormone signaling pathway. In sum, work from our laboratories and others has demonstrated that peroxisome proliferators, TZDs, and inducers of CYP3A gene expression exert their biological actions through the activation of orphan nuclear receptors. These findings provide insights into new endocrine signaling pathways and have important implications for the discovery of safer and more efficacious drugs for the treatment of a variety of diseases.

A peroxisome proliferator-activated receptor gamma ligand inhibits adipocyte differentiation

The peroxisome proliferator-activated receptors (PPARs) are nuclear hormone receptors that regulate glucose and lipid homeostasis. The PPARgamma subtype plays a central role in the regulation of adipogenesis and is the molecular target for the 2, 4-thiazolidinedione class of antidiabetic drugs. Structural studies have revealed that agonist ligands activate the PPARs through direct interactions with the C-terminal region of the ligand-binding domain, which includes the activation function 2 helix. GW0072 was identified as a high-affinity PPARgamma ligand that was a weak partial agonist of PPARgamma transactivation. X-ray crystallography revealed that GW0072 occupied the ligand-binding pocket by using different epitopes than the known PPAR agonists and did not interact with the activation function 2 helix. In cell culture, GW0072 was a potent antagonist of adipocyte differentiation. These results establish an approach to the design of PPAR ligands with modified biological activities.

Molecular recognition of fatty acids by peroxisome proliferator-activated receptors

The peroxisome proliferator-activated receptors (PPARs) are nuclear receptors for fatty acids (FAs) that regulate glucose and lipid homeostasis. We report the crystal structure of the PPAR delta ligand-binding domain (LBD) bound to either the FA eicosapentaenoic acid (EPA) or the synthetic fibrate GW2433. The carboxylic acids of EPA and GW2433 interact directly with the activation function 2 (AF-2) helix. The hydrophobic tail of EPA adopts two distinct conformations within the large hydrophobic cavity. GW2433 occupies essentially the same space as EPA bound in both conformations. These structures provide molecular insight into the propensity for PPARs to interact with a variety of synthetic and natural compounds, including FAs that vary in both chain length and degree of saturation.

Determinants of coactivator LXXLL motif specificity in nuclear receptor transcriptional activation

Ligand-dependent activation of gene transcription by nuclear receptors is dependent on the recruitment of coactivators, including a family of related NCoA/SRC factors, via a region containing three helical domains sharing an LXXLL core consensus sequence, referred to as LXDs. In this manuscript, we report receptor-specific differential utilization of LXXLL-containing motifs of the NCoA-1/SRC-1 coactivator. Whereas a single LXD is sufficient for activation by the estrogen receptor, different combinations of two, appropriately spaced, LXDs are required for actions of the thyroid hormone, retinoic acid, peroxisome proliferator-activated, or progesterone receptors. The specificity of LXD usage in the cell appears to be dictated, at least in part, by specific amino acids carboxy-terminal to the core LXXLL motif that may make differential contacts with helices 1 and 3 (or 3') in receptor ligand-binding domains. Intriguingly, distinct carboxy-terminal amino acids are required for PPARgamma activation in response to different ligands. Related LXXLL-containing motifs in NCoA-1/SRC-1 are also required for a functional interaction with CBP, potentially interacting with a hydrophobic binding pocket. Together, these data suggest that the LXXLL-containing motifs have evolved to serve overlapping roles that are likely to permit both receptor-specific and ligand-specific assembly of a coactivator complex, and that these recognition motifs underlie the recruitment of coactivator complexes required for nuclear receptor function.

Interactions controlling the assembly of nuclear-receptor heterodimers and co-activators

Retinoic-acid receptor-alpha (RAR-alpha) and peroxisome proliferator-activated receptor-gamma (PPAR-gamma) are members of the nuclear-receptor superfamily that bind to DNA as heterodimers with retinoid-X receptors (RXRs). PPAR-RXR heterodimers can be activated by PPAR or RXR ligands, whereas RAR-RXR heterodimers are selectively activated by RAR ligands only, because of allosteric inhibition of the binding of ligands to RXR by RAR. However, RXR ligands can potentiate the transcriptional effects of RAR ligands in cells. Transcriptional activation by nuclear receptors requires a carboxy-terminal helical region, termed activation function-2 (AF-2), that forms part of the ligand-binding pocket and undergoes a conformational change required for the recruitment of co-activator proteins, including NCoA-1/SRC-1. Here we show that allosteric inhibition of RXR results from a rotation of the RXR AF-2 helix that places it in contact with the RAR coactivator-binding site. Recruitment of an LXXLL motif of SRC-1 to RAR in response to ligand displaces the RXR AF-2 domain, allowing RXR ligands to bind and promote the binding of a second LXXLL motif from the same SRC-1 molecule. These results may partly explain the different responses of nuclear-receptor heterodimers to RXR-specific ligands.

Ligand binding and co-activator assembly of the peroxisome proliferator-activated receptor-gamma

The peroxisome proliferator-activated receptor-gamma (PPAR-gamma) is a ligand-dependent transcription factor that is important in adipocyte differentiation and glucose homeostasis and which depends on interactions with co-activators, including steroid receptor co-activating factor-1 (SRC-1). Here we present the X-ray crystal structure of the human apo-PPAR-gamma ligand-binding domain (LBD), at 2.2 A resolution; this structure reveals a large binding pocket, which may explain the diversity of ligands for PPAR-gamma. We also describe the ternary complex containing the PPAR-gamma LBD, the antidiabetic ligand rosiglitazone (BRL49653), and 88 amino acids of human SRC-1 at 2.3 A resolution. Glutamate and lysine residues that are highly conserved in LBDs of nuclear receptors form a 'charge clamp' that contacts backbone atoms of the LXXLL helices of SRC-1. These results, together with the observation that two consecutive LXXLL motifs of SRC-1 make identical contacts with both subunits of a PPAR-gamma homodimer, suggest a general mechanism for the assembly of nuclear receptors with co-activators.

Preliminary X-ray diffraction studies of recombinant 19 kDa human fibroblast collagenase

Crystals of the catalytic domain of human fibroblast collagenase have been grown in the presence and absence of an inhibitor. Crystals of the inhibitor complex grew from 0.2 M ammonium sulfate and 15 to 30% PEG 8000 at 22 degrees C as bipyramids in the space group P6(2) or P6(4). Crystals of the unligated enzyme grew as rods in the space group P4(1)2(1)2 or P4(3)2(1)2 from 1.0 to 2.0 M sodium formate at 4 degrees C. Both crystal forms grew quite slowly over a period of months, but ultimately yielded crystals that diffracted beyond 2.5 A. The collagenase samples used in these studies were heterogeneous at the amino terminus. Three major species (full length, N-1 and N-2) were identified by mass spectrometry and Edman sequencing. Analysis of dissolved crystals revealed the native crystal form selectively crystallized as the N-2 species; however, no selectivity of N-terminal forms was observed for crystals of the inhibitor complex.