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NRF2 mediates melanoma addiction to GCDH by modulating apoptotic signalling

Nature Cell Biology volume 24, pages 1422–1432 (2022)Cite this article

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Abstract

Tumour dependency on specific metabolic signals has been demonstrated and often guided numerous therapeutic approaches. We identify melanoma addiction to the mitochondrial protein glutaryl-CoA dehydrogenase (GCDH), which functions in lysine metabolism and controls protein glutarylation. GCDH knockdown induced cell death programmes in melanoma cells, an activity blocked by inhibition of the upstream lysine catabolism enzyme DHTKD1. The transcription factor NRF2 mediates GCDH-dependent melanoma cell death programmes. Mechanistically, GCDH knockdown induces NRF2 glutarylation, increasing its stability and DNA binding activity, with a concomitant transcriptional upregulation of ATF4, ATF3, DDIT3 and CHAC1, resulting in cell death. In vivo, inducible inactivation of GCDH effectively inhibited melanoma tumour growth. Correspondingly, reduced GCDH expression correlated with improved survival of patients with melanoma. These findings identify melanoma cell addiction to GCDH, limiting apoptotic signalling by controlling NRF2 glutarylation. Inhibiting the GCDH pathway could thus represent a therapeutic approach to treat melanoma.

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Fig. 1: GCDH is required for melanoma cell survival.
Fig. 2: GCDH inhibition promotes DHTKD1-dependent cell death.
Fig. 3: GCDH loss increases NRF2 levels and enhances cell death.
Fig. 4: Cell death following GCDH inhibition is NRF2 dependent.
Fig. 5: Lysine glutarylation attenuates KEAP1 binding increasing NRF2 stability.
Fig. 6: Inducible GCDH KD decreases melanoma proliferation and tumourigenesis.

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Data availability

RNA-seq data that support the findings of this study have been deposited in Gene Expression Omnibus under accession code GSE200424. The pan-cancer data were derived from the TCGA Research Network: http://cancergenome.nih.gov/. The dataset derived from this resource that supports the findings of this study is available in cBioPortal (https://www.cbioportal.org/). Databases/datasets used in the study for human genome and gene annotations: human genome hg38, http://ftp.ensembl.org/pub/release-84/fasta/homo_sapiens/dna/; Ensembl human gene annotations version 84, http://ftp.ensembl.org/pub/release-84/gtf/homo_sapiens/. Source data are provided with this paper. All other data supporting the findings of this study are available from the corresponding author on reasonable request.

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Acknowledgements

We thank D. D. Zhang (University of Arizona) and V. R. Sanghvi (University of Miami) for providing us with the NRF2 mutants (HA-NRF2 K6R, K12R and K18R) and H.-G. Wendel for providing us with NRF2-glycation mutant (NRF2E79V-A6), Y. Altman for help with flow cytometry analysis, members of the Prebys Center for Chemical Genomics for help with the screen for GCDH inhibitors and members of the Ronai lab for discussions. National Cancer Insitute (NCI) support (R35CA197465) to Z.R. and SBP support for translational initiatives (to E.S. and Z.A.R.) is gratefully acknowledged. Sanford Burnham Prebys Shared Resources are supported by an NCI Cancer Center Support Grant (P30 CA030199). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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  1. Gaurav Pathria

    Present address: Genentech, San Francisco, CA, USA

Authors and Affiliations

  1. Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA

    Sachin Verma, Ali Khateb, Yongmei Feng, Gaurav Pathria, David Scott, Rabi Murad & Ze’ev A. Ronai

  2. Cancer Data Science Lab (CDSL), National Cancer Institute, National Institute of Health, Bethesda, MD, USA

    David Crawford & Eytan Ruppin

  3. Conrad Prebys Center for Chemical Genomics, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA

    Eduard Sergienko, Chen-Ting Ma, Steven H. Olson & Michael Jackson

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Contributions

S.V., G.P., A.K., D.S. and Y.F. performed experiments; D.C., E.R. and R.M. performed bioinformatic analyses; Z.A.R. and S.V. designed the studies; E.S., C.-T.M., S.H.O. and M.J. designed GCDH targeting studies, and Z.A.R. and S.V. wrote the manuscript.

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Correspondence to Ze’ev A. Ronai.

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Z.A.R. and E.R. (fully divested) are founders and scientific advisors for Pangea Therapeutics. All other authors declare no conflicts of interest.

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Nature Cell Biology thanks Afshin Samali, Thales Papagiannakopoulos and the other, anonymous, reviewer for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 GCDH inhibition promotes apoptosis of melanoma cells.

(A) UACC903 and 1205LU melanoma cells were transduced with siRNAs targeting AASS, AADAT, DHTKD1, GCDH, or ECHS1 or with a control sequence using Jetprime for 96 hr, followed by an analysis of cell viability. (B) Various melanoma cells were transfected with siRNAs targeting AASS, AADAT, DHTKD1, GCDH, or ECHS1 or with a control sequence for 72 hr, and then lysates were subjected to western analysis with indicated antibodies. (C) Cell growth after GCDH KD with two independent siRNAs for 0–96 hr in UACC903 or 1205LU cells. Proliferation was analyzed by counting cells at indicated time points. (D) UACC903 or 1205LU cells were transfected with GCDH siRNA for 72 hr, and then lysates were subjected to western analysis with indicated antibodies. (E) Viability assay of control or GCDH KD A375 cells treated with the caspase inhibitor Z-VAD(OH)-FMK (10µM for 48 hr). (F) A375 cells transfected with GCDH siRNA were grown in the indicated growth medium, and then viability was determined 96 hr-post transfections. (G) Measurement of basal, maximum oxygen consumption rate (OCR), and spare respiratory capacity using Agilent Seahorse XF Analyzers. A375 cells were transfected with GCDH siRNA for 48 hours before analysis. (H) Viability assay of immortalized H3A cells, 96 hr after transfection with indicated constructs. Viability was measured by quantifying crystal violet staining. (I) Immortalized H3A cells were transfected with siRNAs targeting AASS, AADAT, DHTKD1, GCDH, or ECHS1 or with a control sequence for 72 hours, then lysates were subjected to western analysis with indicated antibodies. Data are representative of three experiments for (B, D, and I) and presented as the mean values ± SD of n = 3 (A, C, and H), n= 4 (E and F) independent experiments and mean values ± SD of n = 6 technical replicates for (G). Each p value is adjusted to account for multiple comparisons. Statistical significance (indicated p-value or ns- not significant w.r.t control) was calculated using One-way ANOVA for (B, E, F and H) and two-way ANOVA for (C). Statistics source data for Extended Data Fig. 1 can be found in Source data files - Extended Data Fig. 1 and uncropped scans of all blots and gels for Extended Data Fig. 1 can be found in Source data files for blots - Extended Fig. 1.

Source data

Extended Data Fig. 2 GCDH expression correlates with melanoma patients outcome.

(A) Survival correlation analysis of GCDH expression in various cancer subtypes (prostate adenocarcinoma (PRAD), breast cancer (BRCA), diffuse large B-cell lymphoma (DLBC), glioblastoma (GBM), acute myeloid leukemia (LAML), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), and lung squamous cell carcinoma (LUSC), using TCGA. (B) Comparison of patient survival based on analysis of NRF2 expression in melanoma patients using TCGA. Total number (n) of patients = 428; n (NRF2 high) =362 and n (NRF2 low) =66. (C) Scatterplot depicting a comparison of GCDH and NRF2 expression levels in TCGA-SKCM (melanoma) patient cohort. GCDH and NRF2 expressions are anti-correlated (Spearman correlation coefficient = -0.41). (D) Boxplots depicting GCDH expression in NRF2 high (n=362) and NRF2 low (n=66) patient samples stratified according to survival analysis of TCGA-SKCM patient cohort based on NRF2 expression (refer to NRF2 survival analysis in (B). The difference in expression of GCDH between NRF2 high and low groups is statistically significant (p-value = 8.653e-14, calculated using two-sided Wilcoxon Rank Sum test). NRF2 low group minimum = 242.2, maximum = 1907, median = 815.6, 1st quartile (25th percentile) = 633 and 3rd quartile (75th percentile) = 1142.5. NRF2 high group minimum = 132.8, maximum =1242.4, median =556.4, 1st quartile (25th percentile) = 446 and 3rd quartile (75th percentile) = 686.6. (E) Various cancer cells were transfected with siRNAs targeting GCDH or with a control sequence for 72 hr, and then lysates were subjected to confirm GCDH-KD. (F) GCDH expression was compared among various cancer cells and immortalized H3A cells. HSP90 was used as a loading control. Data are representative of three experiments. Uncropped scans of all blots and gels for Extended Data Fig. 2 can be found in Source data files for blots - Extended figure 2.

Source data

Extended Data Fig. 3 DHTKD1 KD rescues GCDH KD- induced phenotypes.

(A) Selected enriched canonical pathways from Ingenuity Pathway Analysis (IPA) of siGCDH vs. siControl differentially expressed genes. Shown pathways were selected from the top 20 canonical pathways based on enrichment p-value (p-value < 5.14e-3). (B) RT-qPCR analysis of UACC903 cells for relative expression of indicated transcripts following GCDH-KD or DHTKD1-KD alone or GCDH/DHTKD1 double KD. (C) Western blot analysis with indicated antibodies of lysates from A375 cells transfected with indicated siRNA for 96 hr. (D) RT-qPCR analysis of A375 cells for relative expression of indicated transcripts following GCDH-KD. (E) Western blot analysis on A375 cells after GCDH KD for 24–96 hr in A375 cells. Cells were transfected with siRNA targeting GCDH, and cell lysates were prepared at indicated time points. (F) SubG0 DNA content analysis by flow cytometry to evaluate A375 cell apoptosis. A375 cells were transfected for 72 hr with indicated siRNAs, harvested and fixed in ethanol, and stained with propidium iodide (PI). (G) Western blot analysis of indicated proteins in A375 cells following GCDH-KD or DHTKD1-KD alone or GCDH/DHTKD1 double KD. (H) Rescue of cell death seen in GCDH-KD 1205LU by DHTKD1-KD. Viability was measured by quantifying crystal violet staining. (I) Western blot analysis of indicated proteins in A375 lines. Data are representative of three experiments (C, E, G, and I), n= 1 experiment for F and presented as the mean values ± SD of n = 3 independent experiments for B, D and H. Statistical significance (indicated p-value or ns- not significant w.r.t control) was calculated using one-way ANOVA. Each p value is adjusted to account for multiple comparisons. Statistics source data for Extended Data Fig. 3 can be found in Source data files - Extended Data Fig. 3 and uncropped scans of all blots and gels for Extended Data Fig. 3 can be found in Source data files for blots - Extended figure 3.

Source data

Extended Data Fig. 4 GCDH antagonizes NRF2-mediated activation of ATF3/4-dependent apoptotic signaling.

(A) GC-MS analysis of glutarate concentrations in A375 cells. (B) Western blot analysis of indicated proteins in UACC903 cells, 72 hr after transfection with siRNAs targeting GCDH, NRF2, or DHTKD1 or combinations thereof. (C) RT-qPCR analysis of NRF2 transcript levels in A375 and UACC903 cells, 72 hr following transfection with GCDH siRNAs. (D) RT-qPCR analysis of ATF3, ATF4, DDIT3, and CHAC1 transcript levels in UACC903 cells, 72 hr following transfection with indicated siRNAs. (E) Western blot analysis of indicated proteins in UACC903 cells 72 hr following transfection with siRNAs targeting GCDH, ATF3, or DHTKD1 or combinations thereof. After quantification, signals obtained in panels B and E for 3 independent experiments were used to calculate the ratio of the indicated protein relative to HSP90 levels, described as fold change (FD) +/-SD for indicated proteins. (F) RT-qPCR analysis of ATF3, ATF4, DDIT3, and CHAC1 expression levels in UACC903 following transfection with indicated siRNAs. Data are representative of three experiments for (B and E), presented as the mean values ± SD of n = 3 independent experiments for C, D and F and mean values ± SD of n = 3 technical replicates for A. Statistical significance (indicated p-value or ns- not significant w.r.t control) was calculated using one-way ANOVA. Each p value is adjusted to account for multiple comparisons. Statistics source data for Extended Data Fig. 4 can be found in Source data files - Extended Data Fig. 4 and uncropped scans of all blots and gels for Extended Data Fig. 4 can be found in Source data files for blots - Extended figure 4.

Source data

Extended Data Fig. 5 Cell death upon GCDH KD in melanoma is ATF3/4-dependent.

(A) Selected upstream regulators and their activation z-scores obtained from Ingenuity Pathway Analysis (IPA) of differentially expressed (DE) genes in siGCDH vs. siControl comparisons in A375 (melanoma), SK-Hep1 (liver cancer), and SKBR3 (breast cancer). (B) Heatmap of log2 fold-changes of selected targets of ATF4-ATF3 computed from siGCDH vs. siControl comparisons in melanoma (A375), liver cancer (SK-Hep1), and breast cancer (SKBR3). Rows (genes) were hierarchically clustered. Missing values correspond to genes that were not expressed in the given samples. (C) RTqPCR analysis of ATF3, ATF4, DDIT3 and CHAC1 expression in various cancer cells transfected with indicated siRNAs. (D) Western blot analysis of indicated proteins in indicated cells 72 hr following transfection with control or GCDH siRNAs. Data are representative of three experiments for (D) and presented as the mean values +/- SD of n = 3 independent experiments for (C). Statistical significance (indicated p-value or ns- not significant w.r.t control) was calculated using one-way ANOVA. Each p value is adjusted to account for multiple comparisons. Statistics source data for Extended Data Fig. 5 can be found in Source data files - Extended Data Fig. 5 and uncropped scans of all blots and gels for Extended Data Fig. 5 can be found in Source data files for blots - Extended figure 5.

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Extended Data Fig. 6 Lysine glutarylation antagonizes KEAP1 binding, increasing NRF2 stability.

(A) Cycloheximide (CHX) chase analysis of HA-NRF2 stability in control and GCDH KD HEK-293T cells ectopically expressing HA-NRF2. HEK293T cells were transfected for 72 hr with indicated constructs and treated with 50 µM Cycloheximide (CHX) for different time periods, followed by western blotting with indicated antibodies. After quantification, signals obtained were used to calculate HA-NRF2/HSP90 ratios and described as fold change relative to CHX treatment time = 0. (B) Immunoprecipitation and Western blot analysis of A375 transfected with indicated constructs. Cells were treated with the proteasomal inhibitor MG132 for 4 hr, followed by IP/Western blotting analysis with antibodies to detect K-Glu PTM, KEAP1, and NRF2. (C) Immunoprecipitation and Western blot analysis of UACC903 cells transfected with indicated constructs as described in (B). (D) HEK293T cells were transfected with HA-NRF2 for 72 hr, and NRF2 glutarylation was measured in HA-NRF2 pull-downs fractions using HA-binding beads. (E) Enrichment of NRF2 glutarylation in nuclear fractions was measured in HA-NRF2 pull-downs from HEK293T cells transfected with HA-NRF2 after an initial cell fractionation step to isolate membrane (MF), cytoplasmic (CF), and nuclear (NF) fractions. Successful fractionation was confirmed by immunoblotting with indicated markers: MF (E-cadherin), CF (GAPDH), and NF (Histone H3). (F) HEK293T cells transfected with indicated constructs and IP of indicated HA-NRF2 mutants using HA-affinity beads were performed, followed by Western blot analysis using K-Glu and HA-tag antibodies. (G) HEK293T cells were transfected with indicated constructs and IP of various HA-NRF2 mutants using HA-affinity beads, followed by Western blot analysis using K-Glu and HA-tag antibodies. After quantification, signals obtained were used to calculate K-Glu/HA-NRF2 ratios and described as fold change relative to HA-NRF2 control. After quantification, signals obtained in panels C for 3 independent experiments were used to calculate the ratio of the indicated protein relative to NRF2 levels in IP samples, described as fold change (FD) +/-SD for indicated proteins. Data are representative of three experiments. Statistics source data for Extended Data Fig. 6 can be found in Source data files - Extended Data Fig. 6 and uncropped scans of all blots and gels for Extended Data Fig. 6 can be found in Source data files for blots - Extended figure 6.

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Extended Data Fig. 7 Melanoma Addiction to GCDH is mediated by NRF2.

The model shows GCDH control of NRF2 glutarylation and the implications for ATF4-ATF3-DDIT3-CHAC1 signaling culminating in apoptosis of melanoma cells subjected to GCDH inhibition.

Supplementary information

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Gating strategy for Extended Data Fig. 3f.

Reporting Summary

Peer Review File

Supplementary Table

Supplementary Table 1. Patient survival based on GCDH expression in TCGA of melanoma specimens (relate to Fig. 1i). Supplementary Table 2. Differential gene expression in melanoma A375 cells subjected to siGCDH compared with siControl (batch 1). Supplementary Tables 3–5. Differential gene expression in breast cancer SKBR3 (Table 3), liver cancer SK-HEP1 (Table 4) and melanoma A375 cells (Table 5, batch 2), based on RNA-seq analyses of siGCDH compared with siControl-treated cells. Supplementary Table 6. Sequence of the primers used in this study. Supplementary Table 7. Complete list of antibodies used in this study.

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Verma, S., Crawford, D., Khateb, A. et al. NRF2 mediates melanoma addiction to GCDH by modulating apoptotic signalling. Nat Cell Biol 24, 1422–1432 (2022). https://doi.org/10.1038/s41556-022-00985-x

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