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Oncogenic TFE3 fusions drive OXPHOS and confer metabolic vulnerabilities in translocation renal cell carcinoma

Nature Metabolism volume 7, pages 478–492 (2025)Cite this article

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Abstract

Translocation renal cell carcinoma (tRCC) is an aggressive subtype of kidney cancer driven by TFE3 gene fusions, which act via poorly characterized downstream mechanisms. Here we report that TFE3 fusions transcriptionally rewire tRCCs toward oxidative phosphorylation (OXPHOS), contrasting with the highly glycolytic nature of most other renal cancers. Reliance on this TFE3 fusion-driven OXPHOS programme renders tRCCs vulnerable to NADH reductive stress, a metabolic stress induced by an imbalance of reducing equivalents. Genome-scale CRISPR screening identifies tRCC-selective vulnerabilities linked to this metabolic state, including EGLN1, which hydroxylates HIF-1α and targets it for proteolysis. Inhibition of EGLN1 compromises tRCC cell growth by stabilizing HIF-1α and promoting metabolic reprogramming away from OXPHOS, thus representing a vulnerability for OXPHOS-dependent tRCC cells. Our study defines tRCC as being dependent on a mitochondria-centred metabolic programme driven by TFE3 fusions and nominates EGLN1 inhibition as a therapeutic strategy in this cancer.

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Fig. 1: tRCCs bioenergetically favour OXPHOS.
Fig. 2: OXPHOS metabolism in tRCC is driven by the TFE3 fusion.
Fig. 3: Selective EGLN1 dependency in tRCC.

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Data availability

The data and unique reagents generated in this study are available upon request from the corresponding author. RCC patient-derived xenograft data were downloaded from the European Genome–Phenome Archive under accession code EGAS00001005516; IMmotion 151 data were downloaded from the European Genome–Phenome Archive under accession code EGAS00001004353; TCGA data were downloaded and processed as previously described2. Public H3K27ac ChIP-seq data were downloaded from GEO under accession code GSE143653. Raw sequencing data are available in GEO under accession code GSE266517 (RNA-seq) and GSE266530 (ChIP-seq). Analysed data from ChIP-seq and RNA-seq are available in Supplementary Tables 2–4. Source data are provided with this paper.

Code availability

Algorithms used for data analysis are all publicly available from the indicated references in the paper. No custom code was used in the study.

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Acknowledgements

S.R.V. acknowledges the Doris Duke Charitable Foundation (Clinician-Scientist Development Award grant no. 2020101), Department of Defense Kidney Cancer Research Program (DoD KCRP) (W81XWH-22-1-016), Damon Runyon-Rachleff Innovation Award (grant no. 71-22), the National Cancer Institute (NCI) R01CA279044, NCI R01CA286652, V Scholar Foundation (V2022-018) and Rally Foundation (23IN37). L.B.-P. acknowledges NCI 1R21CA226082-01 and NCI R37CA260062. J.L. acknowledges the DoD KCRP Postdoctoral and Clinical Fellowship Award (W81XWH-22-1-0399). P.K. acknowledges the Kidney Cancer Association Trailblazer Award. C.N.W. acknowledges the AACR-Exelixis Renal Cell Carcinoma Research Fellowship. M. Ge acknowledges the Executive Committee on Research Fund for Medical Discovery. T.K.C. acknowledges the Dana-Farber/Harvard Cancer Center Kidney SPORE (2P50CA101942-16) and programme 5P30CA006516-56, the Kohlberg Chair at Harvard Medical School and the Trust Family, Michael Brigham, Pan Mass Challenge, the Hinda and Arthur Marcus Fund, and Loker Pinard Funds for Kidney Cancer Research at the Dana-Farber Cancer Institute. S.S. acknowledges the NCI (R01CA279044).

Author information

Author notes

  1. These authors jointly supervised this work: Liron Bar-Peled, Srinivas R. Viswanathan.

Authors and Affiliations

  1. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA

    Jiao Li, Meha Thakur, Fiona McBride, Ananthan Sadagopan, Daniel S. Gallant, Prateek Khanna, Bingchen Li, Cary N. Weiss, Mingkee Achom, Qingru Xu, Gwo-Shu Mary Lee, Toni K. Choueiri & Srinivas R. Viswanathan

  2. Department of Medicine, Harvard Medical School, Boston, MA, USA

    Jiao Li, Kaimeng Huang, Bingchen Li, Mingkee Achom, Toni K. Choueiri, Liron Bar-Peled & Srinivas R. Viswanathan

  3. Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, MA, USA

    Kaimeng Huang

  4. Department of Pathology, Brigham and Women’s Hospital, Boston, MA, USA

    Yasmin Nabil Laimon, Razan Mohanna, Sayed Matar & Sabina Signoretti

  5. Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA

    Maolin Ge & Liron Bar-Peled

  6. Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA, USA

    Cary N. Weiss

  7. Molecular Imaging Core and Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA, USA

    Kun Huang

  8. Department of Obstetrics and Gynecology, Sir Run Run Shaw Hospital, School of Medicine and Liangzhu Laboratory, Zhejiang University, Hangzhou, China

    Miao Gui

  9. Department of Pathology, Massachusetts General Hospital, Boston, MA, USA

    Chin-Lee Wu & Kristine M. Cornejo

  10. Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA

    Toni K. Choueiri

  11. Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA

    Birgitta A. Ryback

  12. Cancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Srinivas R. Viswanathan

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Contributions

Conceptualization: J.L., L.B.-P. and S.R.V. Performed experiments: J.L., M.T., D.S.G., P.K., Y.N.L., B.L., R.M. and C.N.W. Performed or designed analyses on genomic and/or metabolomic data: K. Huang with assistance from F.M., A.S., M.A., Q.X., K. Huang, B.A.R., S.M. and M. Gui. Procurement or analysis of clinical samples: G.-S.M.L., C.-L.W., S.M., K.M.C., T.K.C. and S.S. Provided reagents, conceptual input and experimental design: M. Ge, L.B.-P. and S.R.V. Supervision and funding acquisition: S.R.V. Manuscript, original draft: J.L., L.B.-P. and S.R.V. Manuscript, editing and final draft: all authors. K.H., M.T., F.M., A.S., D.S.G., P.K., Y.N.L. and B.L. contributed equally.

Corresponding authors

Correspondence to Liron Bar-Peled or Srinivas R. Viswanathan.

Ethics declarations

Competing interests

S.R.V. has consulted for Jnana Therapeutics within the past 3 years and receives research support from Bayer. L.B.-P. is a co-founder, holds equity in and is a consultant for Scorpion Therapeutics. T.K.C. reports institutional and/or personal paid and/or unpaid support for research, advisory board, consultancy, and/or honoraria past 5 years from Alkermes, Arcus Bio, AstraZeneca, Aravive, Aveo, Bayer, Bristol Myers Squibb, Bicycle Therapeutics, Calithera, Circle Pharma, Deciphera Pharmaceuticals, Eisai, EMD Serono, Exelixis, GSK, Gilead, HiberCell, IQVA, Infinity, Institut Servier, Ipsen, Jansen, Kanaph, Lilly, Merck, Nikang, Neomorph, Nuscan/PrecedeBio, Novartis, Oncohost, Pfizer, Roche, Sanofi/Aventis, Scholar Rock, Surface Oncology, Takeda, Tempest, Up-To-Date, CME and non-CME events (Mashup Media Peerview, OncLive, MJH, CCO and others), outside the submitted work; institutional patents filed on molecular alterations and immunotherapy response/toxicity, and ctDNA; equity from Tempest, Pionyr, Osel, PrecedeBio, CureResponse, InnDura Therapeutics, and Primium, Abalytics; is a committee member for NCCN, the GU Steering Committee, ASCO, ESMO, ACCRU, and KidneyCan; medical writing and editorial assistance support that might have been founded by communications companies in part, no speaker’s bureau; mentored several non-US citizens on research projects with potential funding (in part) from non-US sources/foreign components; the institution (Dana-Farber Cancer Institute) may have received additional independent funding of drug companies or/and royalties potentially involved in research around the subject matter. S.S. reports receiving commercial research grants from Bristol Myers Squibb, AstraZeneca, Exelixis and Novartis; is a consultant/advisory board member for Merck & Co., Rahway, NJ, AstraZeneca, Bristol Myers Squibb, CRISPR Therapeutics AG, AACR and NCI; and receives royalties from Biogenex. The other authors declare no competing interests.

Peer review

Peer review information

Nature Metabolism thanks Valentin Cracan, Ed Reznik and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Alfredo Giménez-Cassina in collaboration with the Nature Metabolism team.

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Extended data

Extended Data Fig. 1 tRCCs display activation of OXPHOS programmes.

a, Source of H3K27ac ChIP-Seq data for ccRCC or tRCC cell lines analysed in this study. b, H3K27ac signal (quantified by ROSE2, Methods) at enhancers in proximity to OXPHOS genes in ccRCC and tRCC cell lines. c, Heatmap showing H3K27ac signal (quantified by ROSE2) at ETC and TCA cycle genes in tRCC vs. ccRCC cell lines. d, Normalized cell proliferation of ccRCC and tRCC cells in glucose or galactose media. Data are shown as mean -+ s.d. for n = 4 biological replicates per cell line except FU-UR-1 (n = 3) in glucose condition. e, Quantification of clonogenic capacity of ccRCC and tRCC cells under normoxic or hypoxic conditions. Data are shown as mean -+ s.d. for n = 3 (normoxia: 786-O, FU-UR-1. hypoxia: A498, FU-UR-1) and n = 4 (normoxia: Caki-1, A498, RCC4, Caki-2, KRMC-1, UOK109, s-TFE. hypoxia: 786-O, Caki-1,RCC4, Caki-2, KRMC-1, UOK109, s-TFE) biological replicates per cell line. f, Representative well for colony formation assay of ccRCC and tRCC cultured under normoxic or hypoxic conditions. g, OXPHOS gene signature scores in ccRCC, chRCC and tRCC tumours in the TCGA cohort. Centre line, median; box limits, upper and lower quartiles; whiskers, 1.5 times the interquartile range. h, OCR after the addition of oligomycin, FCCP, or antimycin A/rotenone in a chRCC cell line (UOK276) and a tRCC cell line (FU-UR-1). Data are shown as mean -+ s.d. for n = 16 (UOK276) and n = 13 (FU-UR-1) biological replicates. i, OCR after the addition of oligomycin, FCCP, or antimycin A/rotenone in an FH-RCC cell line (UOK262). Data are shown as mean -+ s.d. for n = 16 biological replicates. For (d-e), statistical significance was determined by two-tailed Student’s t-test. For (g), statistical significance was determined by two-sided Mann–Whitney test.

Source data

Extended Data Fig. 2 Dynamic 13C carbon labelling for TCA-related metabolites and glycolytic metabolites in ccRCC and tRCC cells.

a, Experimental design for dynamic stable isotope labelling of TCA cycle and glycolysis metabolites using U-13C glucose, U-13C glutamine, and U-13C alanine as carbon sources. b, Labelling distribution of different isotopologues for TCA-related metabolites (α-KG, malate, (iso)citrate, fumarate) and glycolytic metabolites (pyruvate, lactate) over time in two ccRCC (786-O and RCC4) and two tRCC cell lines (UOK109 and s-TFE). Data are shown as mean -+ s.d. for n = 5 biological replicates per cell line.

Source data

Extended Data Fig. 3 Transcriptional activation of OXPHOS genes by TFE3 fusions.

a, IGV snapshot showing TFE3 fusion (orange track) and H3K27ac (light or dark blue tracks) signal at representative OXPHOS-related loci in ccRCC and tRCC cell lines. b, Bar plot showing the top gene sets depleted upon ASPSCR1-TFE3 knockout in FU-UR-1 cells. c, GSEA plot showing depletion of OXPHOS gene signature in FU-UR-1 cells upon ASPSCR1-TFE3 knockout. d, Heatmap showing the change in expression of OPXHOS genes targeted by TFE3 fusion following ASPSCR1-TFE3 knockout in s-TFE cells or FU-UR-1 cells. e, Western blot for TFE3 and SDHA after knockout of WT TFE3 or TFE3 fusion in ccRCC cell line (786-O) or tRCC cell lines (UOK109, FU-UR-1, s-TFE). Change in SDHA protein level was quantified by ImageJ. f, Western blot for TFE3, OXPHOS after knockout of TFE3 or TFE3 fusion in ccRCC cell line (786-O) or tRCC cell lines (UOK109, FU-UR-1, s-TFE). Change of NDUFB8 protein level was quantified by ImageJ. g, IGV snapshot showing TFE3 fusion (orange track) and H3K27ac (light or dark blue tracks) signal at ASS1 locus in ccRCC and tRCC cell lines. h, OCR after knockdown of ASPSCR1-TFE3 in FU-UR-1cell line. Data shown as mean -+ s.d. for n = 8 biological replicates. i, GSEA plot showing no significant change of OXPHOS gene signature in 786-O ccRCC cells upon TFE3 knockdown. j, Change in levels of TCA cycle-related metabolites following TFE3 knockout in 786-O cells. For each metabolite, fold change was normalized to control sgRNA condition. Data are shown as mean (vertical line) and n = 5 biological replicates per cell line. k, Change in levels of arginine biosynthesis-related metabolites following TFE3 knockout in 786-O cells. For each metabolite, fold change was normalized to control sgRNA condition. Data are shown as mean (vertical line) and n = 5 biological replicates per cell line. l, OCR after knockout of TFE3 in 786-O ccRCC cell line. Data are shown as mean -+ s.d. for n = 13 (786-O control sgRNA) and n = 10 (786-O TFE3 sgRNA-1) biological replicates. For (c) and (i), p value was determined by one-sided permutation test. For (j and k), statistical significance was determined by two-sided Mann–Whitney test.

Source data

Extended Data Fig. 4 TFE3 knockout perturbs NADH/NAD+ ratio selectively in tRCC.

a, NAD+ or NADH levels in ccRCC and tRCC cell lines. Data are shown as mean -+ s.d. for n = 4 biological replicates. b, NADPH or NADP+ levels in ccRCC and tRCC cell lines. Data are shown mean -+ s.d. for n = 4 biological replicates. c, Baseline ratio of NADH/NAD+ and NADPH/NADP+ in 5 ccRCC and 3 tRCC cell lines, Data are shown as mean, biological replicates information as for Extended Data Fig. 4a and 4b. d, Levels of NADH and NAD+, as well as the ratio of NADH/NAD+ upon ASPSCR1-TFE3 knockout in FU-UR-1 tRCC cells. Data are shown mean -+ s.d. for n = 4 biological replicates. e, Quantification of NADH to NAD+ ratio following TFE3 knockout in tRCC cell lines (UOK109 and s-TFE). f, Levels of NADH and NAD+, as well as the ratio of NADH/NAD+ upon TFE3 knockout in 786-O ccRCC cells. Data are shown mean -+ s.d. for n = 4 biological replicates. g, Levels of NADPH and NADP+, as well as the ratio of NADPH/NADP+ upon ASPSCR1-TFE3 knockout in FU-UR-1 tRCC cells. Data are shown mean -+ s.d. for n = 4 biological replicates. h, Levels of NADPH and NADP+, as well as the ratio of NADPH/NADP+ upon TFE3 knockout in 786-O ccRCC cells. Data are shown mean -+ s.d. for n = 4 biological replicates. For (c-h), statistical significance was determined by two-sided Mann–Whitney test.

Source data

Extended Data Fig. 5 Induction of reductive stress by NRF2 activation in tRCC cells.

a, Western blot showing TFE3 and NRF2 protein levels across a panel of ccRCC and tRCC cell lines. Note, A498 (ccRCC) cells have been previously reported to have high NRF2 activation, possibly due to SQSTM1 overexpression and/or CUL3 mutation79. b, Immunofluorescence showing subcellular localization of NRF2 in tRCC cell lines vs. a ccRCC cell line (786-O). Scale bar: 50 μm. c, IGV snapshot showing TFE3 fusion signal at NFE2L2 and SQSTM1 loci in tRCC cell lines. d, Western blot of p62 expression in ccRCC and tRCC cell lines. e, SQSTM1 mRNA level in ccRCC or tRCC tumours from three independent studies (TCGA, Motzer et al., Elias et al. (PDX)). Centre line, median; box limits, upper and lower quartiles; whiskers, 1.5 times the interquartile range. f, Western blot showing NRF2 and KEAP1 levels following KEAP1 knockout in ccRCC cell line (786-O) and tRCC cell lines (UOK109, s-TFE and FU-UR-1). g, Western blot showing doxycycline-inducible V5-tagged NRF2 overexpression in ccRCC and tRCC cells. h, Quantification of clonogenic capacity (Crystal Violet assay) after NRF2 overexpression in ccRCC or tRCC cell lines. Data are shown as mean -+ s.d. for n = 3 biological replicates. i, Representative wells for colony formation in ccRCC and tRCC cells upon KEAP1 knockout. j, Quantification of clonogenic capacity after knockout of KEAP1 in ccRCC or tRCC cell lines. Data are shown as mean -+ s.d. for n = 3 biological replicates. k, Quantification of NADH to NAD+ ratio following NRF2 overexpression in ccRCC cell line and tRCC cell lines. l, Representative images displaying NADH/NAD+ ratio in tRCC vs. ccRCC cells (images pseudocolored by NADH/NAD+ ratio). Scale bar: 20 μm. m, Western blot confirming LbNOX overexpression in UOK109 and s-TFE cells transduced with lentiviral vector encoding doxycycline-inducible LbNOX-V5. n, Quantification of clonogenic capacity after doxycycline-inducible expression of NRF2, with or without co-expression of the NADH-oxidizing enzyme LbNOX in UOK109 and s-TFE cells. Data are shown as mean -+ s.d. for n = 3 biological replicates. For (e) and (k), statistical significance was determined by two-sided Mann–Whitney test. For (h), (j) and (n), statistical significance was determined by two-tailed Student’s t-test.

Source data

Extended Data Fig. 6 Regulation of redox balance by TFE3 fusions in tRCC.

a, Ratio of GSH to GSSG levels as measured by untargeted metabolomics in three ccRCC cell lines (786-O, A498, RCC4) vs. three tRCC cell lines (UOK109, FU-UR-1, s-TFE). Data are shown as mean -+ s.d for each group of cell lines. for n = 5 biological replicates per cell line. b, Profile plot showing TFE3 fusion ChIP-Seq signal at glutathione metabolism and pentose phosphate pathway (PPP) genes. c, Schematic of glutathione metabolism and PPP, annotated with genes that are ASPL-TFE3 targets as determined by ChIP-Seq in s-TFE cells (orange boxes). In the schematic, enzymes are in black text, metabolites are in grey text. d, Heatmap showing the change in expression of glutathione metabolism and PPP-related genes following ASPSCR1-TFE3 knockout in s-TFE cells or knockdown in FU-UR-1 cells. e, Change in levels of glutathione metabolism and PPP-related metabolites following ASPSCR1-TFE3 knockout in s-TFE cells. For each metabolite, fold change was normalized to control sgRNA condition. Data are shown as mean and individual replicates for n = 5 biological replicates per cell line. f, Intracellular ROS level in ccRCC and tRCC cell lines. Quantification of intracellular ROS levels via CM-H2DCFDA indicator in tRCC (n = 3, UOK109, FU-UR-1, s-TFE) and ccRCC cell lines (n = 5, 786-O, Caki-1, KRMC-1, RCC4, A498). Points shown are mean across replicates each cell line and horizontal line represents mean for each group of cell lines. g, Intracellular ROS levels (measured by CM-H2DCFDA indicator) after TFE3 knockout in ccRCC cell line (786-O) and tRCC cell lines (UOK109, FU-UR-1). For (a), and (e-f), statistical significance was determined by two-sided Mann–Whitney test.

Source data

Extended Data Fig. 7 EGLN1 and VHL are selectively essential in tRCC cells.

a, HIF1A mRNA level in ccRCC or tRCC tumours from three independent studies (TCGA, Motzer et al., Elias et al. (PDX))20,21,22. b, HIF1A mRNA level in tRCC cell lines (n = 3, UOK109, FU-UR-1, s-TFE) versus ccRCC cell lines (n = 7, A498, A704, 786-O, 769-P, Caki-1, Caki-2, OS-RC-2). c, OCR after knockout of VHL in UOK109 and s-TFE cell lines. Data are shown as mean -+ s.d. for n = 8 (UOK109 control sgRNA), n = 12 (UOK109 VHL sgRNA-1), n = 11 (UOK109 VHL sgRNA-2), n = 13 (s-TFE control sgRNA, s-TFE VHL sgRNA-1) and n = 10 (s-TFE VHL sgRNA-2) biological replicates. d, Genes whose knockout has been previously reported27 to confer sensitivity (422 genes) or resistance (79 genes) to NRF2 activation were compared for dependency in s-TFE cells vs. ccRCC cells (average of dependency score for 5 ccRCC cell lines, for each gene). e, Western blot showing the expression of EGLN1, VHL, HIF-1-α after knockout of VHL in ccRCC (786-O) and tRCC (UOK109, s-TFE and FU-UR-1) cell lines. f, Cell proliferation of tRCC cell lines (UOK109 and s-TFE) and ccRCC (786-O) cell lines after knockout of VHL. Data are shown as mean -+ s.d. for n = 3 (UOK109, 786-O) and n = 5 (s-TFE) biological replicates. g, Western blot showing the expression of EGLN1, VHL after knockout of EGLN1 or VHL in tRCC (FU-UR-1) cell line. h, Cell proliferation of FU-UR-1 cells after knockout of EGLN1 or VHL. Data are shown as mean -+ s.d. for n = 3 biological replicates. i, Western blot showing the expression of EGLN1, VHL after knockout of EGLN1 or VHL in ccRCC (Caki-1) cell line. j, Cell proliferation of Caki-1 cells (VHL preserved) after knockout of EGLN1 or VHL. Data are shown as mean -+ s.d. for n = 6 biological replicates. k, Western blot showing the HIF-1-α expression in UOK109 and s-TFE expressing sgRNA target HIF1A after treatment with EGLN inhibitor (FG4592). Western blot performed once. For (a) and (d), statistical significance was determined by two-sided Mann–Whitney test. Centre line, median; box limits, upper and lower quartiles; whiskers, 1.5 times the interquartile range. For (f), (h) and (j), statistical significance was determined by two-tailed Student’s t-test.

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Supplementary information

Supplementary Information

Supplementary Fig. 1

Reporting Summary

Supplementary Tables 1–4

Table 1. sgRNA sequences used in this study. Table 2. ROSE2 analysis of H3K27ac ChIP-seq data from ccRCC and tRCC cells. Table 3. TFE3 fusion ChIP-seq binding peaks in tRCC cells. Table 4. Gene expression quantification with or without TFE3 knockdown in ccRCC and tRCC cell lines.

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Li, J., Huang, K., Thakur, M. et al. Oncogenic TFE3 fusions drive OXPHOS and confer metabolic vulnerabilities in translocation renal cell carcinoma. Nat Metab 7, 478–492 (2025). https://doi.org/10.1038/s42255-025-01218-9

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