Pharm Res DOI 10.1007/s11095-017-2200-9
RESEARCH PAPER
Targeted Metabolomics Identifies Pharmacodynamic Biomarkers for BIO 300 Mitigation of Radiation-Induced Lung Injury Jace W. Jones 1 & Isabel L. Jackson 2 & Zeljko Vujaskovic 2 & Michael D. Kaytor 3 & Maureen A. Kane 1
Received: 17 March 2017 / Accepted: 30 May 2017 # Springer Science+Business Media New York 2017
ABSTRACT Purpose Biomarkers serve a number of purposes during drug development including defining the natural history of injury/ disease, serving as a secondary endpoint or trigger for intervention, and/or aiding in the selection of an effective dose in humans. BIO 300 is a patent-protected pharmaceutical formulation of nanoparticles of synthetic genistein being developed by Humanetics Corporation. The primary goal of this metabolomic discovery experiment was to identify biomarkers that correlate with radiation-induced lung injury and BIO 300 efficacy for mitigating tissue damage based upon the primary endpoint of survival. Methods High-throughput targeted metabolomics of lung tissue from male C57L/J mice exposed to 12.5 Gy whole thorax lung irradiation, treated daily with 400 mg/kg BIO 300 for either 2 weeks or 6 weeks starting 24 h post radiation exposure, were assayed at 180 d post-radiation to identify potential biomarkers. Results A panel of lung metabolites that are responsive to radiation and able to distinguish an efficacious treatment schedule of BIO 300 from a non-efficacious treatment schedule in terms of 180 d survival were identified. Electronic supplementary material The online version of this article (doi:10.1007/s11095-017-2200-9) contains supplementary material, which is available to authorized users. * Maureen A. Kane
[email protected] 1
School of Pharmacy, Department of Pharmaceutical Sciences, University of Maryland, 20 N. Pine Street, Baltimore, Maryland 21201, USA
2
School of Medicine, Division of Translational Radiation Sciences Department of Radiation Oncology, University of Maryland, Baltimore 21201 Maryland, USA
3
Humanetics Corporation, Edina 55435, Minnesota, USA
Conclusions These metabolites represent potential biomarkers that could be further validated for use in drug development of BIO 300 and in the translation of dose from animal to human.
KEY WORDS biomarkers . genistein . lung injury . metabolomics . radiation
ABBREVIATIONS ARS CID DEARE FDA FDR FIA H&E HDMSE HPLC LC LD MCM MRM NMDA PC PCa PCA PCe PCho PE PLS-DA PUFA sem SFA SM TIC UPLC
Acute radiation syndrome Collision-induced dissociation Delayed effects of acute radiation exposure Federal Drug Administration False discovery rate Flow injection analysis Hematoxylin and eosin High definition mass spectrometry High-performance liquid chromatography Liquid chromatography Lethal dose Medical countermeasure Multiple reaction monitoring N-methyl-D-aspartate Glycerophosphatidylcholine Diacyl glycerophosphatidylcholine Principal component analysis Ether glycerophosphatidylcholine Phosphocholine Glycerophosphoethanolamine Partial least squares-discriminate analysis Polyunsaturated fatty acid Standard error of the mean Saturated fatty acid Sphingomyelin Total ion chromatogram Ultra performance liquid chromatography
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XIC WTLI
Extracted ion chromatogram Whole thorax lung irradiation
INTRODUCTION Accidental or intentional exposure of individuals to high dose radiation results in acute radiation syndrome (ARS) of the hematopoietic and gastrointestinal systems (1,2). Delayed effects of acute radiation exposure (DEARE) are also significant including pulmonary pneumonitis and fibrosis (3,4). Pneumonitis is an inflammatory reaction that occurs 2 to 6 months post-exposure causing debilitating or lifethreatening respiratory complications. Chronic fibrosis of the lung develops months to years post-exposure resulting in diminished quality of life and loss of function (1,3). Accordingly, there is a need to develop therapeutics with the purpose of mitigating radiation-induced lung injury to preserve lung function of individuals exposed to high-dose radiation. Genistein, a natural component of soy, has been shown to significantly improve survival and reduce lung damage following total body irradiation or organ specific irradiation in rodents (5–7). BIO 300 is a nanosuspension pharmaceutical formulation of synthetic genistein being developed by Humanetics Corporation as a medical countermeasure (MCM) to mitigate radiation-induced pulmonary damage and dysfunction. BIO 300 is wet-nanomilled to reduce mean particle size and improve bioavailability over non-nano formulations which suffer from poor solubility and limited bioavailability (7). BIO 300 has demonstrated efficacy for preventing radiation-induced lung injury when given prophylactically or for mitigating radiation-induced lung injury when given as a post-exposure therapeutic (8,9). A recent study shows that 4 or 6 week daily treatment with 400 mg/kg BIO 300 reduces morbidity/mortality associated with radiationinduced lung injury in a mouse model by improving lung function and reducing morphological damage and airway loss due to edema, congestion, and fibrotic scarring (9,10). As radiation injuries represent a condition for which clinical trials cannot be ethically conducted in humans, drug development must be conducted under the Federal Drug Administration (FDA) Animal Rule (11). Drug development under the FDA Animal Rule relies upon well-defined animal models and biomarkers where the potential uses of biomarkers include defining the natural history of the injury/disease, serving as a secondary endpoint or trigger for intervention, and/ or aiding in the selection of an effective dose in humans (11–13). Whereas there have been numerous reports of molecules that are changed in response to various radiation exposures (14–17), as of yet, there are no FDA qualified biomarkers for any radiation-induced injury and/or for the response to therapeutics used to mitigate radiation-induced injury (18). FDA qualified biomarkers can be used as drug development
tools to produce analytically valid measurements that can be relied upon to have a specific use and interpretable meaning during drug development (12). Ionizing radiation induces DNA damage, oxidative stress, hypoxia, and inflammation which causes the dysregulation of cellular molecules including proteins, metabolites, and lipids (19,20). Endogenous metabolism can serve as an effective readout of altered biochemical pathways that contribute to radiation-induced lung injury (17). Metabolites are small molecules that are intermediates and end products of cellular processes; metabolomic responses are more immediately related to the phenotype as compared to proteomic or genomic readouts. Consequently, metabolomics provides a powerful platform for identifying molecular signatures resulting from biological response to radiation insult. Quantification of individual species can then be used systematically to assess the ability of metabolites to inform on the incidence, severity, latency and progression of radiation-induced lung injury as well as the extent of mitigation of injury by candidate MCMs. Here we used high-throughput targeted metabolomics to identify potential biomarkers for radiation-induced lung injury that could also have utility in the further development of BIO 300.
MATERIALS AND METHODS Whole Thorax Lung Irradiation (WTLI) Mouse Model The animal model used in this study has been described in detail elsewhere (9,10). Briefly, age matched male C57L/J mice that were 10–14 weeks old on irradiation day were irradiated with WTLI at 12.5 Gy (~LD90/180) and then administered 400 mg/kg BIO 300 (Humanetics Corporation) by daily oral gavage starting at 24 h post-irradiation for either 2 weeks (2 w) or 6 weeks (6 w). For WTLI, animals were anesthetized with 80–100 mg/kg ketamine and 10–15 mg/ kg xylazine and placed in the prone position. Animals were exposed to 0 Gy (sham radiation) or 12.5 Gy of 320 kV x-rays (1.25 Gy min−1; HVL = 1 mm Cu; XRAD320, Precision XRay, North Branford, CT). Sham irradiated mice are noted as Bsham^ and mice irradiated with 12.5 Gy WTLI but untreated with BIO 300 are notated as B0 w^ (both are vehicle only). Vehicle, BIO 300 nanosuspension minus the active pharmaceutical ingredient, was provided by Humanetics. Animals were monitored daily and euthanized according to predefined criteria (9). The primary end point of the study from which these samples were derived was defined as a significant improvement in survival time in the BIO 300 treated animals as compared to the control group. The secondary end points for that study were defined as reductions in major morbidity including differences in latency, incidence, severity, and duration of radiation-induced lung injury after WTLI (9). All
Pharmacodynamic biomarkers for BIO 300
animal work adhered to the BPrinciples of Laboratory Animal Care^ (NIH publication #85–23, revised in 1985). All experiments were performed in compliance with the animal use protocol approved by the University of Maryland Institutional Animal Care and Use Committee. Histology At the time of euthanasia, a bilateral thoracotomy was performed. Gross morphology of the heart and lungs was assessed and documented. Pleural effusions were measured after which the lungs and heart were removed. Lungs were separated into left and right lobes and individually weighed. Heart weights were documented. The left lung was rinsed in PBS and inflated with 10% neutral buffered formalin and placed in 10% formalin for fixation. The right lung was snap frozen in liquid nitrogen and stored at −80°C for future analysis. Five-micron thick tissue sections were stained with hematoxylin and eosin (H&E) for assessment of tissue damage and Masson’s Trichrome for assessment of fibrosis. Brightfield acquisition of lung tissue was obtained using the tile function of Zeiss software ZEN 2011 and a Zeiss Imager.M2 AXIO microscope. Pictures were taken using a 10x Zeiss Plan-Apochromat objective. The entire region of interest was scanned with numerous focus points. Multiple images were then processed using the fuse function in Zen 2011. A typical image of a lung section would be a fusion of up to 180 high resolution images corresponding to a .czi file of approximately 1.5 GB. High Throughput, Targeted Metabolomics Targeted, quantitative metabolomics was performed using Biocrates AbsoluteIDQ p180 kit (Biocrates, Life Science AG, Innsbruck, Austria). The AbsoluteIDQ p180 kit was prepared as described by the manufacturer. The kit is a combined flow injection analysis (FIA) and liquid chromatography (LC) tandem mass spectrometry assay. The assay quantifies up to 188 metabolites from five metabolite classes: acylcarnitines, amino acids, biogenic amines, glycerophospholipids, sphingolipids, and hexose. Internal standards, analyte derivatization and metabolite extraction are integrated into a 96well plate kit. Metabolite detection is done via pre-selected multiple reaction monitoring (MRM) transitions. Briefly, lung tissue was snap frozen at the time of euthanasia and stored at -80°C until analysis. Tissue was homogenized in 85:15 (methanol:ethanol, v/v) with 5 mM PBS at a ratio of 5 mg/mL. After centrifugation, 20 μL was loaded onto the 96 well kit plate and dried under a stream of nitrogen. A 5% solution of phenylisothiocyanate in ethanol:water:pyridine (1:1:1, v/v/v) was added for derivatization of biogenic amines and amino acids. Metabolite extraction was then achieved with 5 mM ammonium acetate in methanol. The FIA and LC tandem mass spectrometry platform consisted of a
Shimadzu Prominence UFLC XR high-performance liquid chromatograph (HPLC) (Shimadzu, Columbia, MD) coupled to an AB Sciex QTRAP® 5500 hybrid tandem quadrupole/ linear ion trap mass spectrometer (AB Sciex, Framingham, MA). The MetIQ software (Biocrates) controlled the assay workflow including sample registration, calculation of metabolite concentrations, and assay validation.
Lipid Structure Confirmation Diacyl and ether glycerophosphatidylcholine (PCa and PCe, respectively) structures were confirmed via ultra performance liquid chromatography (UPLC) tandem mass spectrometry. Total lipid extracts from fresh mouse lung samples were prepared using a modified Bligh/Dyer protocol (21). The extracted lipids were re-suspended in methanol/chloroform (1:1, v/v) and further diluted with isopropanol/acetonitrile/water (2:1:1, v/v/v) for analysis. UPLC was performed on a Waters ACQUITY UPLC system (Milford, MA). The separation was achieved using a C18 CSH (1.7 μm; 2.1 x 100 mm) column (Waters, Milford, MA). Mobile phase A was 10 mM ammonium formate with 0.1% formic acid in water/ acetonitrile (40:60, v/v) and mobile phase B was 10 mM ammonium formate with 0.1% formic acid in acetonitrile/ isopropanol (10:90, v/v). The gradient was ramped from 40% to 43% B in 2 min, ramped to 50% in 0.1 min, ramped to 54% B in 9.9 min, ramped to 70% in 0.1 min, and ramped to 99% B in 5.9 min. The gradient was returned to initial conditions in 0.5 min and held for 1.9 min for column equilibration. The flow rate was 0.4 mL/min. The column was maintained at 55°C and the auto-sampler was kept at 5°C. A 2 μL injection was used for all samples. The tandem mass spectrometry experiments were performed on a Waters SYNAPT G2-S traveling wave ion-mobility enabled hybrid quadrupole time-of-flight mass spectrometer (Milford, MA). The instrument was operated in positive and negative ion mode electrospray. The capillary voltage was 2.0 kV and sampling cone voltage was 30 V. Nitrogen at a flow of 650 L/h was used as the desolvation gas with a constant desolvation temperature of 400°C. The source temperature was set at 125°C. Data were acquired over the m/z range of 100–1200. The mass spectrometer was operated in ionmobility data independent mode (HDMSE) with alternating low- and high-collision energies. The first scan was set at lowcollision energy (4 eV) and used to collect precursor ion spectra. The second scan was set at high-collision energy and ramped from 30–55 eV which was used for generation of product ion spectra. Argon gas was used for collisioninduced dissociation (CID). Leucine Enkephalin was used as the lock-mass to ensure high mass accuracy data acquisition. Data were acquired and analyzed with Waters MassLynx v4.1 and MSE Data Viewer v1.2.
Jones et al.
Statistical Analysis Statistical analysis of the targeted metabolomics data was performed with the MetaboAnalyst web-based statistical package (22) and GraphPad Prism (v 6.03; La Jolla, CA). Mouse lungs were assigned to one of four cohorts based on irradiation and length of BIO 300 administration. The cohorts were sham (n = 4), 0 w (n = 3), 2 w (n = 3), and 6 w (n = 5).
RESULTS The primary goal of this metabolomic discovery experiment was to identify biomarkers that correlate with radiationinduced lung injury and BIO 300 efficacy for mitigating radiation-induced lung injury based upon the primary endpoint of survival. In the study from which these samples were derived, mice were irradiated with 12.5 Gy WTLI and then treated with 400 mg/kg BIO 300 daily, starting 24 h post irradiation, for varying durations: 0 w (vehicle only), 2 w, or 6 w (9). Figure 1 shows the Kaplan Meier survival curves for 180 day survival for each treatment group. In this study, the 0 w and 2 w BIO 300 treatment groups both yielded 13% survival while the 6 w BIO 300 treatment group yielded a statistically significant, 34% increase in survival (9). Fig. S1 shows the histopathological lung tissue damage in treated and untreated mice at 180 days post-12.5 Gy WTLI, where the 6 w BIO 300 treatment displayed less overall damage than either the 2 w or 0 w cohort. Lung tissue from surviving animals at 180 d from each of the cohorts was subjected to high throughput, targeted metabolomics followed by statistical processing (multivariate, univariate, and hierarchical clustering data analysis) to identify metabolites that were responsive to MCM efficacy. The metabolites quantified are listed in Supporting Information (SI) Table S1. A total of 188 metabolites are included in the kit. Metabolites (18 in total) designated with an * in Table S1 were removed from the data analysis for quality control purposes (e.g., internal standard was not detected, calibration curve was unacceptable). In addition to the listed metabolites, a series of ratios and sums of individual metabolite concentrations representing additional clinical or pathophysiological information were included. In some cases, using ratios and sums of metabolite concentrations offers the potential advantage for reduced biological and/or analytical variability and improved specificity. In total, there were 208 individual components which included 169 metabolites and 39 metabolite combinations that were used for data processing. Multivariate analysis of the metabolite concentrations for the four cohorts as individual groups (sham, 0 w, 2 w, and 6 w) did not result in clear discrimination between the groups. Fig. S2 shows the principal component analysis (PCA) and
Fig. 1 Kaplan Meier mouse survival curves for 180 day survival following 12.5 Gy WTLI with and without administration of BIO 300. Four survival curves are shown: Sham WTLI (blue), 100% survival; mice exposed to 12.5 Gy WTLI with no BIO 300 treatment (red), 13% survival; mice exposed to 12.5 Gy WTLI with 2 week daily administration of 400 mg/kg BIO 300 (green), 13% survival; mice exposed to 12.5 Gy WTLI with 6 week daily administration of 400 mg/kg BIO 300 (purple), 47% survival. Daily BIO 300 administration was initiated starting 24 h post-WTLI.
partial least squares-discriminate analysis (PLS-DA) plots with these groups as individual cohorts. However, hierarchical clustering analysis via the use of a dendrogram demonstrated that samples from 6 w and sham clustered similarly and likewise 0 w and 2 w samples clustered together (Fig. S3). This clearly indicated that the metabolomic profile for lung tissue from the 6 w treatment schedule was statistically similar to sham lung tissue and both 6 w and sham metabolomics profiles were statistically different from the other two treatment schedules (0 w and 2 w) which were statistically similar to each other. With this knowledge and the goal of identifying metabolites that distinguished the difference in BIO 300 efficacy towards survival according to treatment schedule, samples from the 6 w BIO 300 treatment group with improved survival and the sham group were combined and samples from the 0 w and the 2 w BIO 300 treatment group that had no effect on survival were combined for data analysis. The PLS-DA plot of these groupings robustly discriminated the 6 w / sham cohort from the 0 w / 2 w cohort (Q2 = 0.70), with the tight clustering of the 6 w / sham group further emphasizing the similarity of the metabolomic profiles of the 6 w and sham samples (Fig. 2a). Additional statistical analysis in the form of hierarchical clustering (heatmap; Fig. 2b) and univariate analysis (volcano plot; Fig. 2c) highlighted individual metabolites that were differentially expressed between the two cohorts. There were a total of 117 metabolites and metabolite combinations that reached statistical significance when comparing the two groupings (p < 0.05; false discovery rate (FDR) < 5%; Table S2). A number of amino acid, glycerophosphatidylcholine (PC), and sphingomyelin (SM) metabolites and metabolite combinations according to treatment schedule are represented in Figs. 3, 4 and 5. These particular metabolites and metabolite combinations were selected according to statistical significance when comparing 6 w / sham grouping to 0 w / 2 w grouping. Bars representing the individual treatment groups are shown in each figure to highlight the individual effects of the 2 w and
Pharmacodynamic biomarkers for BIO 300
Fig. 2
Multivariate analysis, hierarchical clustering and univariate analysis displaying statistical metabolite differences between 6 w / sham and 0 w / 2 w. (a) PLS-DA plot comparing 6 w / sham grouping (green) to 2 w / 0 w grouping (red); R2 = 0.88, Q2 = 0.70. The 95% confidence interval is indicated by the elliptical pattern per group. (b) Heatmap displaying the top 20 metabolites based on t-test/ANOVA, Pearson distancing and Ward clustering. (c) Volcano plot highlighting metabolites (red) that had a p-value 0.05 except for Met-SO/ Met) and were systematically elevated when compared to 2 w and 0 w. Graphical representation of individual PC, SM species, and combinations thereof are displayed in Figs. 4 and 5. Figure 4a shows four individual PC species including diacyl (PCa32:0, PCa34:1) and ether PC (PCe32:1, PCe36:5). Figure 4b shows the trends for total diacyl PC (Total PCa) and total ether PC (Total PCe) as well as the ratio of polyunsaturated fatty acid PC to saturated fatty acid PC (PUFA/SFA). Figure 5a highlights four individual sphingolipid species including two SM (SM16:0, SM24:0) and two hydroxylated SM (SM(OH)16:1, SM(OH)24:1). Figure 5b shows the trends for total sphingomyelins (Total SM), the ratio of total SM to total PC (Total SM/Total PC), and for total hydroxylated SM (Total SM(OH)). These metabolites or metabolite combinations showed statistically similar levels for 6 w and sham (p > 0.05 for comparison of 6 w to sham). All individual concentrations and combinations, excluding the combination of polyunsaturated PCs to fully saturated PCs (PUFA/SFA), for 6 w and sham samples had greater levels when compared to 2 w and 0 w samples. Lipid structure impacts biological function. Structure confirmation for the diacyl and ether PC presented in Fig. 4 was pursued in order to gain insight into what acyl chains were present including the presence of alkyl and/or vinyl ethers.
Jones et al. Fig. 3 Concentrations of selected amino acids (a) and amino acid combinations (b) for lung tissue from 0 w, 2 w, 6 w, and sham groups. Concentrations are in pmol/mg of tissue and presented as mean ± standard error of mean (sem). Significance (t-test with FDR < 5%) was calculated by grouping 2 w and 0 w together and comparing those values to the grouping of 6 w and sham. * p < 0.05, ** p < 0.01, *** p < 0.005, **** p < 0.0001.
Structure confirmation was a result of the following criteria: 1.) chromatographic retention time on a C18 column, 2.) accurate mass (
