| Literature DB >> 32784785 |
Yoko Yagishita1, Tonibelle N Gatbonton-Schwager1, Melissa L McCallum1, Thomas W Kensler1.
Abstract
The transcription factor NF-E2 p45-related factor 2 (NRF2; encoded by NFE2L2) plays a critical role in the maintenance of cellular redox and metabolic homeostasis, as well as the regulation of inflammation and cellular detoxication pathways. The contribution of the NRF2 pathway to organismal homeostasis is seen in many studies using cell lines and animal models, raising intense attention towards targeting its clinical promise. Over the last three decades, an expanding number of clinical studies have examined NRF2 inducers targeting an ever-widening range of diseases. Full understanding of the pharmacokinetic and pharmacodynamic properties of drug candidates rely partly on the identification, validation, and use of biomarkers to optimize clinical applications. This review focuses on results from clinical trials with four agents known to target NRF2 signaling in preclinical studies (dimethyl fumarate, bardoxolone methyl, oltipraz, and sulforaphane), and evaluates the successes and limitations of biomarkers focused on expression of NRF2 target genes and others, inflammation and oxidative stress biomarkers, carcinogen metabolism and adduct biomarkers in unavoidably exposed populations, and targeted and untargeted metabolomics. While no biomarkers excel at defining pharmacodynamic actions in this setting, it is clear that these four lead clinical compounds do touch the NRF2 pathway in humans.Entities:
Keywords: NRF2 (nuclear factor erythroid 2 related factor 2); bardoxolone methyl; biomarkers; carcinogenesis; dimethyl fumarate; gene expression; inflammation; oltipraz; oxidative stress; sulforaphane
Year: 2020 PMID: 32784785 PMCID: PMC7464243 DOI: 10.3390/antiox9080716
Source DB: PubMed Journal: Antioxidants (Basel) ISSN: 2076-3921
Figure 1Study populations examined in peer-reviewed clinical studies of nuclear factor erythroid 2 related factor 2 (NRF2) inducers. Studies for bardoxolone methyl (BARD-Me), oltipraz, dimethyl fumarate (DMF), and sulforaphane (SFN) totaled 5, 18, 26, and 75, respectively, from 1982 to June 2020. Literature searches were conducted on PubMed, Google Scholar, and ClinicalTrials.gov. Publications based on the same clinical trial were aggregated as one study in this graph. The chemical structure for each NRF2 inducer is indicated below each name. CKD, chronic kidney disease; CVD, cardiovascular disease.
Figure 2(A) Classification of biomarkers used in published clinical studies of “NRF2 Inducers”. (B) Distribution of biomarker categories used in the clinical studies. The size of each pie reflects the total number of times a biomarker of each class was used in the clinical studies. Multiple classes of biomarkers were used in some studies. PK, pharmacokinetics.
Figure 3NRF2 signaling pathway and biomarkers targeting oxidative stress and inflammation. ROS, reactive oxygen species.
Figure 4Induction of KEAP1-NRF2 signaling leads to enhanced detoxication of carcinogens in clinical trials. Air-borne (e.g., acrolein, benzene, polycyclic aromatic hydrocarbons) and food-borne (e.g., aflatoxins) carcinogens are metabolized to reactive electrophiles (E*) by cytochrome P450 and other enzymes. NRF2 target genes such as GSTs can conjugate glutathione (GSH) to E*, leading to formation of nonreactive, water-soluble mercapturic acids. E* can also initiate carcinogenesis by forming promutagenic DNA adducts. Some DNA adducts undergo spontaneous or enzymatic depurination allowing for excretion in urine. E* can also form protein adducts with lysine or cysteine residues in albumin. Mercapturic acids and the adducts can be quantified in clinical samples following ambient exposures using mass spectrometric techniques. Cys, cysteine; SH, sulfhydryl; Ub, ubiquitin; Cul3, cullin 3, Rbx1, ring-box 1.
Figure 5Sankey diagram of mechanism-based biomarkers measured in clinical trials for SFN (green), DMF (orange), BARD-Me (blue), and oltipraz (red). Darker lines (green, orange, blue, red) marked with “+” are studies in which at least 1 biomarker was reported to exhibit a statistically significant (p < 0.05) change. Lighter lines marked with “-“ indicate nonsignificant (i.e., null) responses for all biomarkers examined within a study. This accounting overemphasizes positive outcomes. Lines emanating from each inducer are connected to different measured biomarker categories. The box height for each NRF2 inducer and the thickness of the flow lines or nodes emanating from each inducer to the biomarker categories are proportional to the number of biomarker category counts.
Significant vs. null (nonsignificant) outcomes of individual biomarker measures.
| DMF | BARD-Me | Oltipraz | SFN | TOTAL | Percent Significant Outcomes | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Sig. Δ | NS | Sig. Δ | NS | Sig. Δ | NS | Sig. Δ | NS | Sig. Δ | NS | |||
|
| Activity | |||||||||||
| NQO1 | 1 | 1 | 1 | 1 | 50% | |||||||
| GST | 1 | 2 | 1 | 2 | 2 | 50% | ||||||
| SOD | 1 | 0 | 1 | ALL NULL | ||||||||
| GPX | 1 | 0 | 1 | ALL NULL | ||||||||
| Transcripts | ||||||||||||
|
| 1 | 1 | 1 | 1 | 4 | 5 | 7 | 6 | 54% | |||
|
| 1 | 3 | 6 | 3 | 7 | 30% | ||||||
|
| 1 | 2 | 0 | 3 | ALL NULL | |||||||
|
| 2 | 2 | 2 | 2 | 50% | |||||||
|
| 1 | 1 | 2 | 1 | 3 | 25% | ||||||
|
| 1 | 1 | 1 | 1 | 50% | |||||||
|
| 1 | 0 | 1 | ALL NULL | ||||||||
|
| 1 | 1 | 0 | 2 | ALL NULL | |||||||
|
| 2 | 2 | 0 | 100% | ||||||||
|
| 1 | 1 | 0 | 100% | ||||||||
|
| 1 | 1 | 0 | 100% | ||||||||
|
| 1 | 2 | 1 | 2 | 33% | |||||||
|
| 1 | 1 | 0 | 100% | ||||||||
|
| 1 | 0 | 1 | ALL NULL | ||||||||
|
| 1 | 0 | 1 | ALL NULL | ||||||||
|
| 1 | 1 | 1 | 1 | 50% | |||||||
|
| 1 | 0 | 1 | ALL NULL | ||||||||
| PCA cytoprotection/detox/antioxidant | 1 | 1 | 0 | 100% | ||||||||
| Nrf2 related genes (aggregated transcripts) | ||||||||||||
|
| 1 | 1 | 0 | 100% | ||||||||
|
| HDAC | 3 | 2 | 3 | 2 | 60% | ||||||
| Histone acetylation | 1 | 1 | 1 | 1 | 50% | |||||||
| CYP3A4 | 1 | 0 | 1 | ALL NULL | ||||||||
| TGFβ pathway | 1 | 1 | 0 | 100% | ||||||||
| Epidermal growth factor receptor | 1 | 1 | 0 | 100% | ||||||||
| Insulin signaling | 1 | 1 | 0 | 100% | ||||||||
| Cancer-related | ||||||||||||
| RNA-seq of prostate cancer genes | 1 | 1 | 0 | 100% | ||||||||
| p21WAF/CIP1 | 1 | 0 | 1 | ALL NULL | ||||||||
| Cyclin D1 | 1 | 1 | 0 | 100% | ||||||||
| STAT3 | 1 | 0 | 1 | ALL NULL | ||||||||
| p-STAT3 | 1 | 0 | 1 | ALL NULL | ||||||||
| p21 | 1 | 0 | 1 | ALL NULL | ||||||||
| Active caspase 3 | 1 | 0 | 1 | ALL NULL | ||||||||
| VEGF | 1 | 0 | 1 | ALL NULL | ||||||||
| HIF1α | 1 | 0 | 1 | ALL NULL | ||||||||
| Decorin | 1 | 1 | 0 | 100% | ||||||||
| Insulin-like growth factor | 1 | 0 | 1 | ALL NULL | ||||||||
| p16 | 1 | 1 | 0 | 100% | ||||||||
|
| GSH (Glutathione) levels | 2 | 3 | 2 | 1 | 4 | 4 | 50% | ||||
| 8-OHdG and oxidized nucleosides | 1 | 3 | 3 | 1 | 75% | |||||||
| DNA strand breaks | 1 | 1 | 0 | 100% | ||||||||
| PCOOH (phosphatidylcholine hydroperoxide) | 1 | 1 | 0 | 100% | ||||||||
| 8-isoprostane | 1 | 3 | 1 | 3 | 25% | |||||||
| TBARS | 2 | 0 | 2 | ALL NULL | ||||||||
| Protein carbonyls | 1 | 0 | 1 | ALL NULL | ||||||||
| TAC (Total antioxidant capacity) | 1 | 2 | 1 | 2 | 33% | |||||||
| TOS (Total oxidant status) | 1 | 0 | 1 | ALL NULL | ||||||||
| OSI (Oxidative stress index) | 1 | 1 | 0 | 100% | ||||||||
| MDA | 2 | 2 | 0 | 100% | ||||||||
| Oxidized-LDL | 1 | 1 | 0 | 100% | ||||||||
|
| Cytokine | |||||||||||
| IL-1 | 1 | 2 | 0 | 3 | ALL NULL | |||||||
| IL-4 | 1 | 0 | 1 | ALL NULL | ||||||||
| IL-6 | 1 | 3 | 3 | 3 | 4 | 43% | ||||||
| IL-8 | 1 | 3 | 0 | 4 | ALL NULL | |||||||
| IL-10 | 1 | 0 | 1 | ALL NULL | ||||||||
| IL-12 | 1 | 0 | 1 | ALL NULL | ||||||||
| IL-13 | 1 | 1 | 0 | 2 | ALL NULL | |||||||
| IL-17 | 1 | 0 | 1 | ALL NULL | ||||||||
| TNFα | 1 | 1 | 1 | 1 | 2 | 33% | ||||||
| IFNγ | 1 | 2 | 0 | 3 | ALL NULL | |||||||
| Chemokines | ||||||||||||
| CCL5 | 1 | 0 | 1 | ALL NULL | ||||||||
| MIP-1B (CCL4) | 1 | 0 | 1 | ALL NULL | ||||||||
| MCP-1 (CCL2) | 1 | 2 | 2 | 1 | 67% | |||||||
| CXCL1 | 1 | 0 | 1 | ALL NULL | ||||||||
| IP-10 (CXCL10) | 1 | 1 | 1 | 1 | 50% | |||||||
| MIG | 1 | 1 | 0 | 100% | ||||||||
| Lipid mediators | ||||||||||||
| PGD2 | 1 | 1 | 0 | 100% | ||||||||
| Tetranor-PGEM | 1 | 1 | 0 | 100% | ||||||||
| 11β-PGF2α | 1 | 1 | 0 | 100% | ||||||||
| 11-dehydro-TXB2 | 1 | 1 | 0 | 100% | ||||||||
| NF-kB pathway | 1 | 1 | 0 | 100% | ||||||||
| CRP | 2 | 3 | 2 | 3 | 40% | |||||||
| Immune response | ||||||||||||
| WBC counts | 1 | 1 | 0 | 100% | ||||||||
| Neutrophil counts | 1 | 0 | 1 | ALL NULL | ||||||||
| Monocyte counts | 1 | 0 | 1 | ALL NULL | ||||||||
| Macrophage counts | 1 | 0 | 1 | ALL NULL | ||||||||
| T cell counts | 1 | 0 | 1 | ALL NULL | ||||||||
| NKT cells | 1 | 0 | 1 | ALL NULL | ||||||||
| CD4+ and CD8+ T-lymphocytes | 1 | 1 | 1 | 1 | 50% | |||||||
| Proinflammatory genes (aggregated transcripts) | 1 | 1 | 0 | 100% | ||||||||
| PCA immune-response genes | 1 | 0 | 1 | ALL NULL | ||||||||
| Others | ||||||||||||
| MIF | 1 | 1 | 0 | 100% | ||||||||
| SLPI | 1 | 1 | 0 | 100% | ||||||||
| CD105+ and iNOS+ cells | 1 | 1 | 0 | 100% | ||||||||
| Virus-induced granzyme B production in NK cells | 1 | 1 | 0 | 100% | ||||||||
| Serum pepsinogen I and II | 1 | 1 | 1 | 1 | 50% | |||||||
|
| Aflatoxin-albumin adducts | 1 | 1 | 0 | 100% | |||||||
| Aflatoxin-DNA adducts | 1 | 1 | 0 | 100% | ||||||||
| Aflatoxin mercapturic acid | 1 | 1 | 0 | 100% | ||||||||
| Polycyclic aromatic hydrocarbon-DNA adducts | 1 | 0 | 1 | ALL NULL | ||||||||
| Benzo(a)pyrene-7,8-diol-9,10-epoxide adducts | 1 | 0 | 1 | ALL NULL | ||||||||
| Mutagenicity (urine) | 1 | 0 | 1 | ALL NULL | ||||||||
| Acrolein mercapturic acid | 2 | 2 | 0 | 100% | ||||||||
| Benzene mercapturic acid | 3 | 3 | 0 | 100% | ||||||||
| Crotonaldehyde mercapturic acid | 2 | 2 | 0 | 100% | ||||||||
|
| Cystine | 1 | 1 | 0 | 100% | |||||||
| Plasma metabolites | 1 | 1 | 1 | 1 | 50% | |||||||
| Urinary metabolites | 1 | 1 | 0 | 100% | ||||||||
| Metabolites in prostate biopsies | 1 | 0 | 1 | ALL NULL | ||||||||
The abbreviations used are as follows: AKR1C, aldo-keto reductase family 1 member C; CBR, carbonyl reductase; CCL, chemokine ligands; CD, cluster of differentiation; CRP, C-reactive protein; CXCL, C-X-C motif chemokine ligand; CYP3A4, cytochrome P450 3A4; GCLC, glutamate-cysteine ligase catalytic subunit; GCLM, glutamate-cysteine ligase modifier subunit; γGCS, γ-glutamylcysteine synthase, GPX, glutathione peroxidase; GST, glutathione-S-transferase; GSTM, glutathione S-transferase M; GSTP, glutathione S-transferase P; HBG, hemoglobin subunit gamma, HDAC, histone deacetylase; HIF1 α, hypoxia-inducible factor 1α; HSP, heat shock protein; IFNγ, interferon γ; IL – interleukin; iNOS, inducible nitric oxide synthase; IP-10, interferonγ -induced protein 10; LDL, low-density lipoprotein; MCP-1, monocyte chemoattractant protein1; MDA, malondialdehyde; MIF macrophage migration inhibitory factor; MIG, monokine induced by interferon γ; MIP-1β, macrophage inflammatory protein 1β; NFκB, nuclear factor κ β; NKT, natural killer T; NQO1, NAD(P)H: quinone oxidoreductase 1; NS, not significant; p21, cyclin-dependent kinase inhibitor 1; PCA, principal component analysis; PGD2, prostaglandin D2; PGEM, prostaglandin E metabolite; PGF2α, prostaglandin F 2 α; Sig, significant; SLC7A11, solute carrier family 7 member 11; SLPI, secretory leukocyte peptidase inhibitor; SOD, superoxide dismutase; STAT3, signal transducer and activator of transcription 3; TBARS, thiobarbituric acid reactive substances; TGFβ, transforming growth factor β; TNFα, tumor necrosis factor α; TR, thioredoxin reductase; TXB2, thromboxane B2; UGT, UDP-glucuronosyltransferases; VEGF, vascular endothelial growth factor; WBC, white blood cell; 8-OHdG, 8-hydroxy-2′-deoxyguanosine.