Alterations in Polyamine Metabolism in Patients With Lymphangioleiomyomatosis and Tuberous Sclerosis Complex 2-Deficient Cells

Abstract

Background: Lymphangioleiomyomatosis (LAM), a destructive lung disease that affects primarily women, is caused by loss-of-function mutations in TSC1 or TSC2, leading to hyperactivation of mechanistic/mammalian target of rapamycin complex 1 (mTORC1). Rapamycin (sirolimus) treatment suppresses mTORC1 but also induces autophagy, which promotes the survival of TSC2-deficient cells. Based on the hypothesis that simultaneous inhibition of mTORC1 and autophagy would limit the availability of critical nutrients and inhibit LAM cells, we conducted a phase 1 clinical trial of sirolimus and hydroxychloroquine for LAM. Here, we report the analyses of plasma metabolomic profiles from the clinical trial.

Methods: We analyzed the plasma metabolome in samples obtained before, during, and after 6 months of treatment with sirolimus and hydroxychloroquine, using univariate statistical models and machine learning approaches. Metabolites and metabolic pathways were validated in TSC2-deficient cells derived from patients with LAM. Single-cell RNA-Seq was employed to assess metabolic enzymes in an early-passage culture from an LAM lung.

Results: Metabolomic profiling revealed changes in polyamine metabolism during treatment, with 5'-methylthioadenosine and arginine among the most highly upregulated metabolites. Similar findings were observed in TSC2-deficient cells derived from patients with LAM. Single-cell transcriptomic profiling of primary LAM cultured cells revealed that mTORC1 inhibition upregulated key enzymes in the polyamine metabolism pathway, including adenosylmethionine decarboxylase 1.

Conclusions: Our data demonstrate that polyamine metabolic pathways are targeted by the combination of rapamycin and hydroxychloroquine, leading to upregulation of 5'-methylthioadenosine and arginine in the plasma of patients with LAM and in TSC2-deficient cells derived from a patient with LAM upon treatment with this drug combination.

Trial registry: ClinicalTrials.gov; No.: NCT01687179; URL: www.clinicaltrials.gov. Partners Human Research Committee, protocol No. 2012P000669.

Keywords: 5′-methylthioadenosine; angiomyolipoma; arginine; autophagy; hydroxychloroquine; lymphangioleiomyomatosis; mechanistic/mammalian target of rapamycin complex 1; metabolomics; polyamines; rapamycin; single-cell transcriptomics; sirolimus; tuberous sclerosis.

Copyright © 2019 American College of Chest Physicians. All rights reserved.

Figures

Figure 1

Overview of data collection and analysis. A, Sample collection and analysis pipeline. Plasma samples were collected before treatment as baseline reference, during a 24-week treatment period consisting of four visits, and from the posttreatment observation period consisting of two visits. Metabolomic profiling was performed by liquid chromatography-mass spectrometry. Principal component analysis and a self-organizing map were used for global metabolomic profiles analysis. Differential analysis was used for identification of changes of metabolite levels caused by treatment. Three statistical models were employed for biomarker identification: partial least squares-discriminant analysis, empirical Bayes analysis of microarrays, and significance analysis of microarrays. Identified biomarkers and metabolic pathways were validated in a TSC2-deficient cell line (621-101) derived from a patient with lymphangioleiomyomatosis. B, Summary of sample collections. Thirteen subjects were enrolled in the study and provided baseline plasma samples. During the period of treatment, plasma samples were collected at up to four visits, resulting in a total of 47 samples. In total, 18 samples were collected at two posttreatment visits. BL = baseline; DA = differential analysis; DT = during treatment; EBAM = empirical Bayes analysis of microarrays; LAM = lymphangioleiomyomatosis; LC-MS = liquid chromatography-mass spectrometry; PCA = principal component analysis; PLS-DA = partial least squares-discriminant analysis; PT = posttreatment; SAM = significance analysis of microarrays; SOM = self-organizing map.

Figure 2

Differential analysis of metabolomic profiles across baseline (BL), during treatment (DT), and posttreatment (PT) identified upregulation of 5′-methylthioadenosine (MTA)-related polyamine metabolism by combinatorial treatment of rapamycin and hydroxychloroquine. A, Heatmap of significantly upregulated and downregulated metabolites (rows) DT and PT (columns). Total triacylglycerol (TAG), specific TAG species, and many metabolites in polyamine metabolism were upregulated DT (indicated as red bar on left side), including MTA, arginine, S-adenosyl-l-homocysteine, and acetylspermidine. B, MTA and arginine in polyamine metabolism showed the most significant upregulation DT compared with baseline. Five of 32 upregulated metabolites are intermediate metabolites in polyamine metabolism (green dots). Dots on the right sides represent upregulated metabolites during treatment, whereas dots on the left side represent downregulated metabolites during treatment. The x axis represents fold change; the y axis represents negative log10-transformed P values. The dashed red line indicates a false discovery rate (FDR) cutoff of 0.05. C, Arginine was significantly upregulated DT compared with BL and PT (***P < .001). The y axis represents normalized log2-transformed values. The DT samples from four visits (n = 47) were grouped for analysis, and PT samples from two visits (n = 18) were grouped for analysis. D, MTA was significantly upregulated DT compared with BL and PT (***P < .001). The y axis represents normalized log2-transformed values. E, MTA and arginine are among the most significant metabolites identified by partial least squares-discriminate analysis. The colored boxes on the right indicate the relative concentrations of the corresponding metabolite in BL and DT samples. The variable importance in projection (VIP) score is a weighted sum of squares of the partial least squares loadings. A full list of significant metabolites with VIP scores is provided in e-Table 4. F, MTA and arginine are the most significant biomarkers discriminating treatment group from BL identified by empirical Bayes analysis. The green circles represent metabolites that exceed the significance threshold (dotted line). MTA and arginine are labeled. All metabolites identified as biomarkers and their FDR values can be found in e-Table 5. EBAM = empirical Bayes analysis of microarrays; FA = fatty acid; LCER = lactosylceramide; LPC = lysophosphosphatidylcholine; LPE = lysophosphosphatidylethanolamine; PC = phosphatidylcholine; PE = phosphatidylethanolamine. See Figure 1 legend for expansion of other abbreviations.

Figure 2

Differential analysis of metabolomic profiles across baseline (BL), during treatment (DT), and posttreatment (PT) identified upregulation of 5′-methylthioadenosine (MTA)-related polyamine metabolism by combinatorial treatment of rapamycin and hydroxychloroquine. A, Heatmap of significantly upregulated and downregulated metabolites (rows) DT and PT (columns). Total triacylglycerol (TAG), specific TAG species, and many metabolites in polyamine metabolism were upregulated DT (indicated as red bar on left side), including MTA, arginine, S-adenosyl-l-homocysteine, and acetylspermidine. B, MTA and arginine in polyamine metabolism showed the most significant upregulation DT compared with baseline. Five of 32 upregulated metabolites are intermediate metabolites in polyamine metabolism (green dots). Dots on the right sides represent upregulated metabolites during treatment, whereas dots on the left side represent downregulated metabolites during treatment. The x axis represents fold change; the y axis represents negative log10-transformed P values. The dashed red line indicates a false discovery rate (FDR) cutoff of 0.05. C, Arginine was significantly upregulated DT compared with BL and PT (***P < .001). The y axis represents normalized log2-transformed values. The DT samples from four visits (n = 47) were grouped for analysis, and PT samples from two visits (n = 18) were grouped for analysis. D, MTA was significantly upregulated DT compared with BL and PT (***P < .001). The y axis represents normalized log2-transformed values. E, MTA and arginine are among the most significant metabolites identified by partial least squares-discriminate analysis. The colored boxes on the right indicate the relative concentrations of the corresponding metabolite in BL and DT samples. The variable importance in projection (VIP) score is a weighted sum of squares of the partial least squares loadings. A full list of significant metabolites with VIP scores is provided in e-Table 4. F, MTA and arginine are the most significant biomarkers discriminating treatment group from BL identified by empirical Bayes analysis. The green circles represent metabolites that exceed the significance threshold (dotted line). MTA and arginine are labeled. All metabolites identified as biomarkers and their FDR values can be found in e-Table 5. EBAM = empirical Bayes analysis of microarrays; FA = fatty acid; LCER = lactosylceramide; LPC = lysophosphosphatidylcholine; LPE = lysophosphosphatidylethanolamine; PC = phosphatidylcholine; PE = phosphatidylethanolamine. See Figure 1 legend for expansion of other abbreviations.

Figure 3

Plasma metabolomic profiling reveals metabolic pathways targeted by combinatorial treatment of sirolimus and hydroxychloroquine. A, Base representation of self-organizing maps. Clusters of metabolites of similar patterns were merged into bases, which resulted in 12 bases representing clusters of metabolites differentially regulated by the treatments. Each color represents metabolites that behave similarly among subjects and across treatment points. B, Heatmap of metabolites upregulated or downregulated during treatment and posttreatment in each base, color-coded to match (A). The color indicates the direction of change. For example, metabolites in base 1 (red, top) were downregulated during treatment. C, Enriched metabolism pathways representative of each base shown in (B). Metabolites in polyamine metabolism are included in arginine and proline metabolism in base 6. TCA = tricarboxylic acid. See Figure 1 legend for expansion of other abbreviations.

Figure 4

5′-Methylthioadenosine (MTA)-related polyamine metabolism was upregulated by combinatorial treatment of rapamycin and chloroquine in TSC2-deficient 621-101 cells derived from a patient with lymphangioleiomyomatosis. A, Heatmap of significantly upregulated or downregulated metabolites (rows) across treatment conditions (columns). 621-101 cells (passage 24) were treated for 24 hours with 20 nM rapamycin, 5 μM chloroquine, a combination of 20 nM rapamycin and 5 μM chloroquine, or dimethylsulfoxide (DMSO) control. Many intermediate metabolites in polyamine metabolism were upregulated by the combinatorial treatment with rapamycin and chloroquine, including MTA, arginine, and S-adenosyl-l-homocysteine. B, Volcano plot shows that polyamine metabolites were upregulated by treatment with rapamycin and chloroquine (CQ) compared with DMSO control, including MTA and arginine (labeled). Dots on the right sides represent metabolites upregulated by the treatment, and dots on the left side represent metabolites downregulated by the treatment. Metabolites in the polyamine metabolism pathway are depicted as green dots. The x axis represents fold change; the y axis represents negative log10-transformed P values. The dashed red line indicates a false discovery rate (FDR) cutoff of 0.05. Same experiment as described in (A). C, Arginine, but not MTA, was significantly upregulated by rapamycin. Metabolites in the polyamine pathway are represented as green dots. The horizontal dashed red line indicates an FDR cutoff of 0.05. Same experiment as described in (A). D, Arginine was significantly upregulated by the treatment with rapamycin and by the combinatorial treatment with rapamycin and CQ (FDR <0.05). Combinatorial treatment of rapamycin and chloroquine significantly decreased arginine compared with rapamycin treatment alone. E, MTA was significantly upregulated by the combinatorial treatment with rapamycin and CQ, but not by either rapamycin or chloroquine alone. No significant difference is observed between rapamycin treatment alone and combinatorial treatment of rapamycin and chloroquine (denoted as ns). ns = not significant; Rapa = rapamycin.

Figure 5

Expression upregulation of key enzymes in 5′-methylthioadenosine (MTA) metabolism in primary lymphangioleiomyomatosis (LAM)-activated lung fibroblasts on rapamycin treatment. A, Primary culture (passage 2) derived from an LAM lung was treated for 24 hours with rapamycin (20 nM) or dimethylsulfoxide (DMSO) control. Single-cell RNA-Seq was performed. The t-distributed stochastic neighbor embedding (t-SNE) plot shows 5,482 fibroblasts with 2,524 cells from the rapamycin treatment group (cyan) and 2,958 cells from the DMSO control group (blue). B, t-SNE plot showing LAM-activated fibroblasts (LAFs) and myofibroblasts in control and rapamycin groups. LAFs were defined by higher average expression of a panel of activated fibroblasts marker genes (FAP, PDPN, MMP2, MMP11, PDGFRA, PDGFRL, CTSK) over the mean value of all cells. C, Schematic showing selected enzymes involved in MTA metabolism. Metabolites are represented by blue hexagons. Enzymes are represented by red rectangles. D, Single-cell gene expression of key enzymes measured in LAM lung primary cultures treated with 20 nM rapamycin and DMSO (control) for 24 hours. ***FDR < 0.001. All enzymes showed upregulation by rapamycin treatment in both myofibroblasts and LAFs. The y axis represents normalized expression values. AMD1 = adenosylmethionine decarboxylase 1; Ctrl = control; dcSAM = decarboxylated S-adenosylmethionine; MyoF = myofibroblast; ODC1 = ornithine decarboxylase 1; Rapa = rapamycin; SAM = S-adenosylmethionine; SMS = spermine synthase; SRM = spermidine synthase.