The mechanisms by which cells adapt to proteotoxic stress are largely unknown, but are key to understanding how tumor cells, particularly in vivo, are largely resistant to proteasome inhibitors. Analysis of cancer cell lines, mouse xenografts and patient-derived tumor samples all showed an association between mitochondrial metabolism and proteasome inhibitor sensitivity. When cells were forced to use oxidative phosphorylation rather than glycolysis, they became proteasome-inhibitor resistant. This mitochondrial state, however, creates a unique vulnerability: sensitivity to the small molecule compound elesclomol. Genome-wide CRISPR–Cas9 screening showed that a single gene, encoding the mitochondrial reductase FDX1, could rescue elesclomol-induced cell death. Enzymatic function and nuclear-magnetic-resonance-based analyses further showed that FDX1 is the direct target of elesclomol, which promotes a unique form of copper-dependent cell death. These studies explain a fundamental mechanism by which cells adapt to proteotoxic stress and suggest strategies to mitigate proteasome inhibitor resistance.
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The data that support the findings of this study are available in the paper (and its Supplementary Information files) or on a public server (GEO: GSE123639). Additional information and reasonable requests for data, resources, sequences and reagents should be directed to and will be fulfilled by the corresponding author.
Luo, J. et al. A genome-wide RNAi screen identifies multiple synthetic lethal interactions with the ras oncogene. Cell 137, 835–848 (2009).
Petrocca, F. et al. A genome-wide siRNA screen identifies proteasome addiction as a vulnerability of basal-like triple-negative breast cancer cells. Cancer Cell 24, 182–196 (2013).
Adams, J. et al. Proteasome inhibitors: a novel class of potent and effective antitumor agents. Cancer Res. 59, 2615–2622 (1999).
Deshaies, R. J. Proteotoxic crisis, the ubiquitin-proteasome system, and cancer therapy. BMC Biol. 12, 94 (2014).
Holbeck, S. L., Collins, J. M. & Doroshow, J. H. Analysis of food and drug administration-approved anticancer agents in the NCI60 panel of human tumor cell lines. Mol. Cancer Ther. 9, 1451–1460 (2010).
Orlowski, R. Z. & Kuhn, D. J. Proteasome inhibitors in cancer therapy: lessons from the first decade. Clin. Cancer Res. 14, 1649–1657 (2008).
Markovina, S. et al. Bortezomib-resistant nuclear factor-kappaB activity in multiple myeloma cells. Mol. Cancer Res. 6, 1356–1364 (2008).
Li, B. et al. The nuclear factor (erythroid-derived 2)-like 2 and proteasome maturation protein axis mediate bortezomib resistance in multiple myeloma. J. Biol. Chem. 290, 29854–29868 (2015).
Zhang, X. D. et al. Tight junction protein 1 modulates proteasome capacity and proteasome inhibitor sensitivity in multiple myeloma via EGFR/JAK1/STAT3 signaling. Cancer Cell 29, 639–652 (2016).
Kisselev, A. F., van der Linden, W. A. & Overkleeft, H. S. Proteasome inhibitors: an expanding army attacking a unique target. Chem. Biol. 19, 99–115 (2012).
Tsvetkov, P. et al. Suppression of 19S proteasome subunits marks emergence of an altered cell state in diverse cancers. Proc. Natl Acad. Sci. USA 114, 382–387 (2017).
Tsvetkov, P. et al. Compromising the 19S proteasome complex protects cells from reduced flux through the proteasome. eLife 4, https://doi.org/10.7554/eLife.08467 (2015).
Shi, C. X. et al. CRISPR genome-wide screening identifies dependence on the proteasome subunit PSMC6 for bortezomib sensitivity in multiple myeloma. Mol. Cancer. Ther. 16, 2862–2870 (2017).
Acosta-Alvear, D. et al. Paradoxical resistance of multiple myeloma to proteasome inhibitors by decreased levels of 19S proteasomal subunits. eLife 4, e08153 (2015).
Gohil, V. M. et al. Nutrient-sensitized screening for drugs that shift energy metabolism from mitochondrial respiration to glycolysis. Nat. Biotechnol. 28, 249–255 (2010).
Yu, C. et al. High-throughput identification of genotype-specific cancer vulnerabilities in mixtures of barcoded tumor cell lines. Nat. Biotechnol. 34, 419–423 (2016).
Ackler, S. et al. The Bcl-2 inhibitor ABT-263 enhances the response of multiple chemotherapeutic regimens in hematologic tumors in vivo. Cancer Chemo. Pharmacol. 66, 869–880 (2010).
O’Day, S. et al. Phase II, randomized, controlled, double-blinded trial of weekly elesclomol plus paclitaxel versus paclitaxel alone for stage IV metastatic melanoma. J. Clin. Oncol. 27, 5452–5458 (2009).
Hasinoff, B. B., Yadav, A. A., Patel, D. & Wu, X. The cytotoxicity of the anticancer drug elesclomol is due to oxidative stress indirectly mediated through its complex with Cu(II). J. Inorg. Biochem. 137, 22–30 (2014).
Nagai, M. et al. The oncology drug elesclomol selectively transports copper to the mitochondria to induce oxidative stress in cancer cells. Free Radic. Biol. Med. 52, 2142–2150 (2012).
Soma, S. et al. Elesclomol restores mitochondrial function in genetic models of copper deficiency. Proc. Natl Acad. Sci. USA 115, 8161–8166 (2018).
Yadav, A. A., Patel, D., Wu, X. & Hasinoff, B. B. Molecular mechanisms of the biological activity of the anticancer drug elesclomol and its complexes with Cu(II), Ni(II) and Pt(II). J. Inorg. Biochem. 126, 1–6 (2013).
Barbi de Moura, M. et al. Mitochondrial respiration–an important therapeutic target in melanoma. PLoS ONE 7, e40690 (2012).
Blackman, R. K. et al. Mitochondrial electron transport is the cellular target of the oncology drug elesclomol. PLoS ONE 7, e29798 (2012).
Kirshner, J. R. et al. Elesclomol induces cancer cell apoptosis through oxidative stress. Mol Cancer Ther. 7, 2319–2327 (2008).
Cai, K., Tonelli, M., Frederick, R. O. & Markley, J. L. Human mitochondrial ferredoxin 1 (FDX1) and ferredoxin 2 (FDX2) both bind cysteine desulfurase and donate electrons for iron–sulfur cluster biosynthesis. Biochemistry 56, 487–499 (2017).
Sheftel, A. D. et al. Humans possess two mitochondrial ferredoxins, Fdx1 and Fdx2, with distinct roles in steroidogenesis, heme, and Fe/S cluster biosynthesis. Proc. Natl Acad. Sci. USA 107, 11775–11780 (2010).
Shi, Y., Ghosh, M., Kovtunovych, G., Crooks, D. R. & Rouault, T. A. Both human ferredoxins 1 and 2 and ferredoxin reductase are important for iron-sulfur cluster biogenesis. Biochim Biophys. Acta 1823, 484–492 (2012).
Arroyo, J. D. et al. A genome-wide CRISPR death screen identifies genes essential for oxidative phosphorylation. Cell Metab. 24, 875–885 (2016).
Yang, W. S. et al. Regulation of ferroptotic cancer cell death by GPX4. Cell 156, 317–331 (2014).
Shimada, K. et al. Copper-binding small molecule induces oxidative stress and cell-cycle arrest in glioblastoma-patient-derived cells. Cell Chem. Biol. 25, 585–594 e587 (2018).
Tardito, S. et al. Copper binding agents acting as copper ionophores lead to caspase inhibition and paraptotic cell death in human cancer cells. J. Am. Chem. Soc. 133, 6235–6242 (2011).
Cen, D., Brayton, D., Shahandeh, B., Meyskens, F. L. Jr. & Farmer, P. J. Disulfiram facilitates intracellular Cu uptake and induces apoptosis in human melanoma cells. J. Med. Chem. 47, 6914–6920 (2004).
Kuntz, E. M. et al. Targeting mitochondrial oxidative phosphorylation eradicates therapy-resistant chronic myeloid leukemia stem cells. Nat. Med. 23, 1234–1240 (2017).
Lee, K. M. et al. MYC and MCL1 cooperatively promote chemotherapy-resistant breast cancer stem cells via regulation of mitochondrial oxidative phosphorylation. Cell Metab. 26, 633–647 e637 (2017).
Matassa, D. S. et al. Oxidative metabolism drives inflammation-induced platinum resistance in human ovarian cancer. Cell Death Differ. 23, 1542–1554 (2016).
Vazquez, F. et al. PGC1alpha expression defines a subset of human melanoma tumors with increased mitochondrial capacity and resistance to oxidative stress. Cancer Cell 23, 287–301 (2013).
Vellinga, T. T. et al. SIRT1/PGC1alpha-dependent increase in oxidative phosphorylation supports chemotherapy resistance of colon cancer. Clin. Cancer Res. 21, 2870–2879 (2015).
Soriano, G. P. et al. Proteasome inhibitor-adapted myeloma cells are largely independent from proteasome activity and show complex proteomic changes, in particular in redox and energy metabolism. Leukemia 30, 2198–2207 (2016).
Zaal, E. A. et al. Bortezomib resistance in multiple myeloma is associated with increased serine synthesis. Cancer Metab. 5, 7 (2017).
Frumkin, I. et al. Gene architectures that minimize cost of gene expression. Mol. Cell 65, 142–153 (2017).
Peth, A., Nathan, J. A. & Goldberg, A. L. The ATP costs and time required to degrade ubiquitinated proteins by the 26 S proteasome. J. Biol. Chem. 288, 29215–29222 (2013).
Raynes, R., Pomatto, L. C. & Davies, K. J. Degradation of oxidized proteins by the proteasome: distinguishing between the 20S, 26S, and immunoproteasome proteolytic pathways. Mol. Aspects. Med. 50, 41–55 (2016).
Vabulas, R. M. & Hartl, F. U. Protein synthesis upon acute nutrient restriction relies on proteasome function. Science 310, 1960–1963 (2005).
Suraweera, A., Munch, C., Hanssum, A. & Bertolotti, A. Failure of amino acid homeostasis causes cell death following proteasome inhibition. Mol. Cell 48, 242–253 (2012).
Wang, X., Yen, J., Kaiser, P. & Huang, L. Regulation of the 26S proteasome complex during oxidative stress. Sci. Signal 3, ra88 (2010).
Cho-Park, P. F. & Steller, H. Proteasome regulation by ADP-ribosylation. Cell 153, 614–627 (2013).
Tsvetkov, P. et al. NADH binds and stabilizes the 26S proteasomes independent of ATP. J. Biol. Chem. 289, 11272–11281 (2014).
Rousseau, A. & Bertolotti, A. An evolutionarily conserved pathway controls proteasome homeostasis. Nature 536, 184–189 (2016).
Zhao, J., Zhai, B., Gygi, S. P. & Goldberg, A. L. mTOR inhibition activates overall protein degradation by the ubiquitin proteasome system as well as by autophagy. Proc. Natl Acad. Sci. USA 112, 15790–15797 (2015).
Dobin, A. et al. STAR: ultrafast universal RNA-Seq aligner. Bioinformatics 29, 15–21 (2013).
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).
Zhu, Y., Qiu, P. & Ji, Y. TCGA-assembler: open-source software for retrieving and processing TCGA data. Nat. Methods 11, 599–600 (2014).
Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003).
Ritz, C., Baty, F., Streibig, J. C. & Gerhard, D. Dose-Response analysis using R. PLoS ONE 10, e0146021 (2015).
Safikhani, Z. et al. Revisiting inconsistency in large pharmacogenomic studies. F1000Res. 5, 2333 (2016).
Wijeratne, E. M. et al. Structure-activity relationships for withanolides as inducers of the cellular heat-shock response. J. Med. Chem. 57, 2851–2863 (2014).
Wang, T., Lander, E. S. & Sabatini, D. M. Viral Packaging and cell culture for CRISPR-based screens. Cold Spring Harb. Protoc. 2016, pdb.prot090811 (2016).
Cai, K., Frederick, R. O., Tonelli, M. & Markley, J. L. ISCU(M108I) and ISCU(D39V) differ from wild-type ISCU in Their failure to form cysteine desulfurase complexes containing both frataxin and ferredoxin. Biochemistry 57, 1491–1500 (2018).
Cai, K., Frederick, R. O., Tonelli, M. & Markley, J. L. Interactions of iron-bound frataxin with ISCU and ferredoxin on the cysteine desulfurase complex leading to Fe–S cluster assembly. J. Inorg. Biochem. 183, 107–116 (2018).
This work is dedicated to the memory of Susan Lindquist who served as a great inspiration as a scientist, mentor and human being. We thank L. Clayton, C. Kayatekin, B. Bevis, N. Kanarek, N. Dharia, V. Viswanathan, J. Eaton, T. Ast, I. Fung, B. Wang and J. McFarland for constructive discussion and comments. Special thanks to D. Sabatini, D. Pincus, J. Rettenmaier and V. Mootha for providing critical comments and reviewing of the manuscript and G. Fink for his supervision. We thank G. Botta, J. Fonseka, J. Roth and S. Bender for help with the PRISM experiments setup and analysis. We thank C. Lewis and the Whitehead Institue Metabolite Profiling Core Facility for the help with the metabolite profiling. We thank the Koch Institute Swanson Biotechnology Center for technical support, specifically J. Cheah for her support conducting the chemical drug screen. NMR spectroscopy was carried out at the National Magnetic Resonance Facility at Madison, which is supported by National Institutes of Health (NIH) grant no. P41GM103399; other work at the University of Wisconsin-Madison was supported by funds from the Biochemistry Department. S.S was supported by K08NS064168 and R01CA194005. P.T was supported by EMBO Fellowship ALTF 739-2011 and by the Charles A. King Trust Postdoctoral Fellowship Program. A.D was supported by the Multiple Myeloma Research Foundation. T.R.G is an HHMI investigator.
T.R.G. is a consultant in GlaxoSmithKline, Sherlock Biosciences and Foundation medicine; co-founder of Sherlock Biosciences and Foundation medicine. S.S. has consulted for RareCyte Inc. A.T. is a consultant for Tango Therapeutics. W.Y. is employed by Ranok Therapeutics Co. Ltd. and is also the sole proprietor of OnTarget Pharmaceutical Consulting LLC.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Figures 1–7
The drug sensitivity of cancer cell lines to bortezomib (n = 294) as downloaded from GDSC (www.cancerrxgene.org).
Gene expression of the inducible Lo19S state in the presence or absence of bortezomib (n = 3 biologically independent samples).
Metabolite profiling of controls and Lo19S state cells in the presence or absence of 20 nM bortezomib treatment for 16 h.
Gene expression of MM.1S orthotopic tumors grown out from control and bortezomib-treated mice.
GSEA of genes upregulated in Lo19S but not control tumors was conducted for breast, prostate, thyroid, skin and kidney cancers from the TCGA. Tumor samples as previously described 11.
Viability results from the PRISM experiment where cells were grown in either glucose or galactose containing media with and without bortezomib.
Drug libraries used in the chemical screens.
The cell viability measurements from the drug screens conducted comparing the control versus Lo19S states and the glucose versus galactose media states.
The viability measurements from the PRISM experiment with elesclomol and the overall gene expression and gene deletion associations used in the study.
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Tsvetkov, P., Detappe, A., Cai, K. et al. Mitochondrial metabolism promotes adaptation to proteotoxic stress. Nat Chem Biol 15, 681–689 (2019). https://doi.org/10.1038/s41589-019-0291-9
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