Abstract
Dysregulated transcription due to disruption in histone lysine methylation dynamics is an established contributor to tumorigenesis1,2. However, whether analogous pathologic epigenetic mechanisms act directly on the ribosome to advance oncogenesis is unclear. Here we find that trimethylation of the core ribosomal protein L40 (rpL40) at lysine 22 (rpL40K22me3) by the lysine methyltransferase SMYD5 regulates mRNA translation output to promote malignant progression of gastric adenocarcinoma (GAC) with lethal peritoneal ascites. A biochemical–proteomics strategy identifies the monoubiquitin fusion protein partner rpL40 (ref. 3) as the principal physiological substrate of SMYD5 across diverse samples. Inhibiting the SMYD5–rpL40K22me3 axis in GAC cell lines reprogrammes protein synthesis to attenuate oncogenic gene expression signatures. SMYD5 and rpL40K22me3 are upregulated in samples from patients with GAC and negatively correlate with clinical outcomes. SMYD5 ablation in vivo in familial and sporadic mouse models of malignant GAC blocks metastatic disease, including peritoneal carcinomatosis. Suppressing SMYD5 methylation of rpL40 inhibits human cancer cell and patient-derived GAC xenograft growth and renders them hypersensitive to inhibitors of PI3K and mTOR. Finally, combining SMYD5 depletion with PI3K–mTOR inhibition and chimeric antigen receptor T cell administration cures an otherwise lethal in vivo mouse model of aggressive GAC-derived peritoneal carcinomatosis. Together, our work uncovers a ribosome-based epigenetic mechanism that facilitates the evolution of malignant GAC and proposes SMYD5 targeting as part of a potential combination therapy to treat this cancer.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 51 print issues and online access
$199.00 per year
only $3.90 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
Plasmids, antibodies and cell lines generated in this study will be available from the lead contact upon request with a completed material transfer agreement. The RNA sequencing data for total mRNA and polysome-associated mRNA have been deposited into the Gene Expression Omnibus database under accession number GSE238257. MS data have been deposited into the ProteomeXchange Consortium through the PRIDE partner repository with the dataset identifiers PXD052358 and PXD052359. Source data are provided with this paper.
References
Robichaud, N., Sonenberg, N., Ruggero, D. & Schneider, R. J. Translational control in cancer. Cold Spring Harb. Perspect. Biol. 11, a032896 (2019).
Kovalski, J. R., Kuzuoglu-Ozturk, D. & Ruggero, D. Protein synthesis control in cancer: selectivity and therapeutic targeting. EMBO J. 41, e109823 (2022).
Baker, R. T. & Board, P. G. The human ubiquitin-52 amino acid fusion protein gene shares several structural features with mammalian ribosomal protein genes. Nucleic Acids Res. 19, 1035–1040 (1991).
Morgan, E. et al. The current and future incidence and mortality of gastric cancer in 185 countries, 2020-40: a population-based modelling study. eClinicalMedicine 47, 101404 (2022).
Hirata, Y., Noorani, A., Song, S., Wang, L. & Ajani, J. A. Early stage gastric adenocarcinoma: clinical and molecular landscapes. Nat. Rev. Clin. Oncol. 20, 453–469 (2023).
Manzanedo, I., Pereira, F., Perez-Viejo, E. & Serrano, A. Gastric cancer with peritoneal metastases: current status and prospects for treatment. Cancers 15, 1777 (2023).
Bhat, K. P., Umit Kaniskan, H., Jin, J. & Gozani, O. Epigenetics and beyond: targeting writers of protein lysine methylation to treat disease. Nat. Rev. Drug. Discov. 20, 265–286 (2021).
Meng, X. et al. Comprehensive analysis of histone modification-associated genes on differential gene expression and prognosis in gastric cancer. Exp. Ther. Med. 18, 2219–2230 (2019).
Zhang, Y. et al. Unique SMYD5 structure revealed by AlphaFold correlates with its functional divergence. Biomolecules 12, 783 (2022).
Zhang, Y. et al. SMYD5 catalyzes histone H3 lysine 36 trimethylation at promoters. Nat. Commun. 13, 3190 (2022).
Stender, J. D. et al. Control of proinflammatory gene programs by regulated trimethylation and demethylation of histone H4K20. Mol. Cell 48, 28–38 (2012).
Husmann, D. & Gozani, O. Histone lysine methyltransferases in biology and disease. Nat. Struct. Mol. Biol. 26, 880–889 (2019).
Afjehi-Sadat, L. & Garcia, B. A. Comprehending dynamic protein methylation with mass spectrometry. Curr. Opin. Chem. Biol. 17, 12–19 (2013).
Stark, C. et al. BioGRID: a general repository for interaction datasets. Nucleic Acids Res. 34, D535–D539 (2006).
Williamson, N. A., Raliegh, J., Morrice, N. A. & Wettenhall, R. E. Post-translational processing of rat ribosomal proteins. Ubiquitous methylation of Lys22 within the zinc-finger motif of RL40 (carboxy-terminal extension protein 52) and tissue-specific methylation of Lys4 in RL29. Eur. J. Biochem. 246, 786–793 (1997).
Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).
Eastham, M. J., Pelava, A., Wells, G. R., Watkins, N. J. & Schneider, C. RPS27a and RPL40, which are produced as ubiquitin fusion proteins, are not essential for p53 signalling. Biomolecules 13, 898 (2023).
Shi, Z. et al. Heterogeneous ribosomes preferentially translate distinct subpools of mRNAs genome-wide. Mol. Cell 67, 71–83.e7 (2017).
Guimaraes, J. C. & Zavolan, M. Patterns of ribosomal protein expression specify normal and malignant human cells. Genome Biol. 17, 236 (2016).
Ferretti, M. B. & Karbstein, K. Does functional specialization of ribosomes really exist? RNA 25, 521–538 (2019).
Miller, S. C., MacDonald, C. C., Kellogg, M. K., Karamysheva, Z. N. & Karamyshev, A. L. Specialized ribosomes in health and disease. Int. J. Mol. Sci. 24, 6334 (2023).
Panda, A. et al. Tissue- and development-stage-specific mRNA and heterogeneous CNV signatures of human ribosomal proteins in normal and cancer samples. Nucleic Acids Res. 48, 7079–7098 (2020).
Lee, A. S., Burdeinick-Kerr, R. & Whelan, S. P. A ribosome-specialized translation initiation pathway is required for cap-dependent translation of vesicular stomatitis virus mRNAs. Proc. Natl Acad. Sci. USA 110, 324–329 (2013).
Gandin, V. et al. Polysome fractionation and analysis of mammalian translatomes on a genome-wide scale. J. Vis. Exp. 87, 51455 (2014).
Liu, S. et al. METTL13 methylation of eEF1A increases translational output to promote tumorigenesis. Cell 176, 491–504.e421 (2019).
Schmidt, E. K., Clavarino, G., Ceppi, M. & Pierre, P. SUnSET, a nonradioactive method to monitor protein synthesis. Nat. Methods 6, 275–277 (2009).
Iwasaki, S. & Ingolia, N. T. The growing toolbox for protein synthesis studies. Trends Biochem. Sci. 42, 612–624 (2017).
Nielsen, P. J. & McConkey, E. H. Evidence for control of protein synthesis in HeLa cells via the elongation rate. J. Cell. Physiol. 104, 269–281 (1980).
Oertlin, C. et al. Generally applicable transcriptome-wide analysis of translation using anota2seq. Nucleic Acids Res. 47, e70 (2019).
Oertlin, C., Watt, K., Ristau, J. & Larsson, O. Anota2seq analysis for transcriptome-wide atudies of mRNA translation. Methods Mol. Biol. 2418, 243–268 (2022).
Truitt, M. L. & Ruggero, D. New frontiers in translational control of the cancer genome. Nat. Rev. Cancer 16, 288–304 (2016).
Lim, H. J., Zhuang, L. & Fitzgerald, R. C. Current advances in understanding the molecular profile of hereditary diffuse gastric cancer and its clinical implications. J. Exp. Clin. Cancer Res. 42, 57 (2023).
Gregory, S. N. & Davis, J. L. CDH1 and hereditary diffuse gastric cancer: a narrative review. Chin. Clin. Oncol. 12, 25 (2023).
Pihlak, R., Fong, C. & Starling, N. Targeted therapies and developing precision medicine in gastric cancer. Cancers 15, 3248 (2023).
Seidlitz, T. et al. Mouse models of human gastric cancer subtypes with stomach-specific CreERT2-mediated pathway alterations. Gastroenterology 157, 1599–1614.e2 (2019).
Wong, H. H. & Chu, P. Immunohistochemical features of the gastrointestinal tract tumors. J. Gastrointest. Oncol. 3, 262–284 (2012).
Zhao, L. et al. Paracrine activation of MET promotes peritoneal carcinomatosis in scirrhous gastric cancer. Cancer Sci. 104, 1640–1646 (2013).
Staudt, R. E., Carlson, R. D. & Snook, A. E. Targeting gastrointestinal cancers with chimeric antigen receptor (CAR)-T cell therapy. Cancer Biol. Ther. 23, 127–133 (2022).
Sadelain, M., Riviere, I. & Riddell, S. Therapeutic T cell engineering. Nature 545, 423–431 (2017).
Labanieh, L. & Mackall, C. L. CAR immune cells: design principles, resistance and the next generation. Nature 614, 635–648 (2023).
Qi, C. et al. Claudin18.2-specific CAR T cells in gastrointestinal cancers: phase 1 trial interim results. Nat. Med. 28, 1189–1198 (2022).
Carpenito, C. et al. Control of large, established tumor xenografts with genetically retargeted human T cells containing CD28 and CD137 domains. Proc. Natl Acad. Sci. USA 106, 3360–3365 (2009).
Lv, J. et al. Mesothelin is a target of chimeric antigen receptor T cells for treating gastric cancer. J. Hematol. Oncol. 12, 18 (2019).
Jana, S. et al. Transcriptional–translational conflict is a barrier to cellular transformation and cancer progression. Cancer Cell 41, 853–870.e13 (2023).
Sfakianos, A. P., Raven, R. M. & Willis, A. E. The pleiotropic roles of eIF5A in cellular life and its therapeutic potential in cancer. Biochem. Soc. Trans. 50, 1885–1895 (2022).
Clarke, S. G. Protein methylation at the surface and buried deep: thinking outside the histone box. Trends Biochem. Sci. 38, 243–252 (2013).
Mealey-Farr, R. et al. Antibody toolkit to investigate eEF1A methylation dynamics in mRNA translation elongation. J. Biol. Chem. 299, 104747 (2023).
Simsek, D. & Barna, M. An emerging role for the ribosome as a nexus for post-translational modifications. Curr. Opin. Cell Biol. 45, 92–101 (2017).
Tian, X., Ju, H. & Yang, W. An ego network analysis approach identified important biomarkers with an association to progression and metastasis of gastric cancer. J. Cell. Biochem. 120, 15963–15970 (2019).
Reynoird, N. et al. Coordination of stress signals by the lysine methyltransferase SMYD2 promotes pancreatic cancer. Genes Dev. 30, 772–785 (2016).
Van Aller, G. S. et al. Smyd3 regulates cancer cell phenotypes and catalyzes histone H4 lysine 5 methylation. Epigenetics 7, 340–343 (2012).
Edmunds, J. W., Mahadevan, L. C. & Clayton, A. L. Dynamic histone H3 methylation during gene induction: HYPB/Setd2 mediates all H3K36 trimethylation. EMBO J. 27, 406–420 (2008).
Schotta, G. et al. A chromatin-wide transition to H4K20 monomethylation impairs genome integrity and programmed DNA rearrangements in the mouse. Genes Dev. 22, 2048–2061 (2008).
Pagans, S. et al. The cellular lysine methyltransferase Set7/9-KMT7 binds HIV-1 TAR RNA, monomethylates the viral transactivator Tat, and enhances HIV transcription. Cell Host Microbe 7, 234–244 (2010).
Luger, K., Rechsteiner, T. J. & Richmond, T. J. in Chromatin Protocols. Methods in Molecular Biology, vol. 119 (ed. Becker P. B.) 1–16 (1999).
Zoabi, M. et al. Methyltransferase-like 21 C (METTL21C) methylates alanine tRNA synthetase at Lys-943 in muscle tissue. J. Biol. Chem. 295, 11822–11832 (2020).
Baymaz, H. I., Spruijt, C. G. & Vermeulen, M. in Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC). Methods Mol. Biol., vol. 1188 (ed. Warscheid, B.) 207–226 (2014).
Wingfield P. Protein precipitation using ammonium sulfate. Curr. Protoc. Protein. Sci. Appendix 3:Appendix-3F (2001).
Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008).
Bushnell, B. BBMap: A Fast, Accurate, Splice-Aware Aligner (Lawrence Berkeley National Lab, 2014).
Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).
Kim, D., Langmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360 (2015).
Liao, Y., Smyth, G. K. & Shi, W. The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads. Nucleic Acids Res. 47, e47 (2019).
Pruitt, K. D. et al. RefSeq: an update on mammalian reference sequences. Nucleic Acids Res. 42, D756–D763 (2013).
Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2009).
Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).
Stacklies, W., Redestig, H., Scholz, M., Walther, D. & Selbig, J. pcaMethods—a Bioconductor package providing PCA methods for incomplete data. Bioinformatics 23, 1164–1167 (2007).
Wang, L., Wang, S. & Li, W. RSeQC: quality control of RNA-seq experiments. Bioinformatics 28, 2184–2185 (2012).
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).
Mootha, V. K. et al. PGC-α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat. Genet. 34, 267–273 (2003).
Korotkevich, G. et al. Fast gene set enrichment analysis. Preprint at bioRxiv https://doi.org/10.1101/060012 (2021).
Guan, B.-J. et al. A unique ISR program determines cellular responses to chronic stress. Mol. Cell 68, 885–900.e6 (2017).
Mansour, F. H. & Pestov, D. G. Separation of long RNA by agarose–formaldehyde gel electrophoresis. Anal. Biochem. 441, 18–20 (2013).
Rahman, S. & Zenklusen, D. in Imaging Gene Expresson. Methods in Molecular Biology, vol. 1042 (ed. Shav-Tal, Y.) 33–46 (Humana Press, 2013).
Scott, D. D. et al. Nol12 is a multifunctional RNA binding protein at the nexus of RNA and DNA metabolism. Nucleic Acids Res. 45, 12509–12528 (2017).
Evans, R. et al. Protein complex prediction with AlphaFold-Multimer. Preprint at bioRxiv https://doi.org/10.1101/2021.10.04.463034 (2022).
The Cancer Genome Atlas Research Network. Comprehensive molecular characterization of gastric adenocarcinoma. Nature 513, 202–209 (2014).
Gao, J. et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci. Signal. 6, pl1 (2013).
Cerami, E. et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2, 401–404 (2012).
Mazur, P. K. et al. SMYD3 links lysine methylation of MAP3K2 to Ras-driven cancer. Nature 510, 283–287 (2014).
Boussadia, O., Kutsch, S., Hierholzer, A., Delmas, V. & Kemler, R. E-cadherin is a survival factor for the lactating mouse mammary gland. Mech. Dev. 115, 53–62 (2002).
Jonkers, J. et al. Synergistic tumor suppressor activity of BRCA2 and p53 in a conditional mouse model for breast cancer. Nat. Genet. 29, 418–425 (2001).
Lesche, R. et al. Cre/loxP-mediated inactivation of the murine Pten tumor suppressor gene. Genesis 32, 148–149 (2002).
Gao, X. et al. ES cell pluripotency and germ-layer formation require the SWI/SNF chromatin remodeling component BAF250a. Proc. Natl Acad. Sci. USA 105, 6656–6661 (2008).
Hingorani, S. R. et al. Preinvasive and invasive ductal pancreatic cancer and its early detection in the mouse. Cancer Cell 4, 437–450 (2003).
Skarnes, W. C. et al. A conditional knockout resource for the genome-wide study of mouse gene function. Nature 474, 337–342 (2011).
Raymond, C. S. & Soriano, P. High-efficiency FLP and PhiC31 site-specific recombination in mammalian cells. PLoS ONE 2, e162 (2007).
Acknowledgements
We thank members of the Gozani and Mazur laboratories for critical reading of the manuscript; M. Ott for providing Tat1 cDNA and M. Oeffinger and C. Trahan for ribosome biogenesis protocols. This work was supported in part by grants from the NIH to O.G. (R35 GM139569), O.G. and P.K.M. (R01 CA236118, R01 CA278940 and R01 CA272844), P.K.M. (R01 CA236949, R01 CA266280 and R01 CA272843), B.A.G. (R01 HD106051 and R01 AI118891), J.W.F. and J.J. (5T32GM007276), J.W.F. (F31CA261128), and P.J. by an FRQS Doctoral award. P.K.M. is also supported by a DoD PRCRP Career Development Award (CA181486), CPRIT IIRA (RP220391) and CPRIT Scholar in Cancer Research (RR160078). B.A.G is also supported by NSF CHE-2127882. N.M.F. is supported by the American Cancer Society postdoctoral fellowship. I.T. is a Senior Scholar of the Fonds de la recherche du Québec–Santé (FRQS) and is in part supported by a grant from the Canadian Institutes of Health Research (CIHR PJT-175050). O.L. is supported by the Swedish Research Council (2020-01665), the Swedish Cancer Society (22 2186), the Stockholm Cancer Society (211222) and the Wallenberg Academy Fellow programme. J.P. received support from the Korean Government Scholarship Program for Study Abroad (NIIED).
Author information
Authors and Affiliations
Contributions
J.P. and J.W. contributed equally to this work. They were responsible for the experimental design, execution, data analyses and manuscript preparation. K.J.S. performed polysomal RNA sequencing bioinformatics and GSEA analyses with advice from O.L. and I.T. J.J. with J.P. performed rpL40K22me3 antibody characterization and in vitro methylation assays. P.J., with help from J.P., performed northern blotting. J.W.F. generated ribosome PDB figures and D.H. performed AlphaFold modelling work. Y.-J.C.C. performed biochemical fractionation. J.P. and E.Z. performed MS experiments and analyses, with supervision from B.A.G. N.M.F. performed mouse model and IHC analyses. A.M.B. helped with animal studies. J.A.A. and S.S. provided PDX and clinical samples. L.W. helped with expression analyses and data interpretation. K.S., O.L. and I.T. advised on experimental design and data interpretation. O.G. and P.K.M. were equally responsible for supervision of research, data interpretation and manuscript preparation.
Corresponding authors
Ethics declarations
Competing interests
O.G. is a co-scientific founder and stockholder of EpiCypher, K36 Therapeutics and Alternative Bio. P.K.M. is a consultant and stockholder of Ikena Oncology and Alternative bio. The other authors declare no competing interests.
Peer review
Peer review information
Nature thanks Ernesto Guccione, Davide Ruggero, Toshikazu Ushijima and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
Extended Data Fig. 1 SMYD5 is largely dispensable in mice and there is no evidence for SMYD5 having histone methylation activity in vitro or in cells.
a, SMYD5 expression levels in gastric cancer negatively correlate with GAC patient progression free survival (n = 498 patients). P-values determined by log-rank test. b, Summary of full embryonic Smyd5 knockout mice phenotype data from the IMPC (International Mouse Phenotyping Consortium). Smyd5 deletion has no impact on viability and fertility and mice have only minor phenotypes as shown in the table. c, Top, main domain structure of SMYD5. SMYD5, like the four other SMYD family members (SMYDs 1–4), contains a catalytic methyltransferase SET domain that is disrupted due to insertion of a MYND domain. When the protein folds, the two parts of the SET domain form a continuous functional domain as shown. Bottom, alignment of the putative catalytic region of SMYD5 with the catalytic regions of SMYD2 and SMYD3. Grey box, homology, or similarity. Red box, catalytic tyrosine in SMYD2 and SMYD3 that was used to generate a catalytic mutant for SMYD5. d, SMYD5 depletion has no effect on the levels of H3K36me3 and H4K20me3 in three different human cell lines. Western blots with the indicated antibodies of WCEs from control or SMYD5-depleted A549, KKLS, and U2OS cells. Total H3 and tubulin are shown as loading controls. e, SMYD5 does not methylate free histones, octamers, or nucleosomes in vitro. In vitro methylation assays with the indicated enzymes and substrates. H3: free histone H3; H4: free histone H4; Oct: recombinant octamers (2 each of H2A, H2B, H3 and H4); rNuc: recombinant nucleosome. SETD2 and SUV420H1 are included as positive controls for methylation of H3K36 and H4K20, respectively. Note that SUV420H1’s preferred substrate is H4K20me1 nucleosome and as indicated, H4K20me1 nucleosomes were used in the SUV420H1 methylation assays. Top panel, 3H-SAM was used as methyl donor and the methylation was visualized by autoradiography. Bottom panel, Coomassie stain of proteins present in the in vitro reactions. f, SMYD5 localizes to the cytoplasm. Western blots with the indicated antibodies of biochemically separated 293 T WCEs into nuclear and cytoplasmic fractions. Tubulin and H3 are shown as controls for the integrity of the fractionation with Tubulin exclusively present in cytoplasmic fractions and H3 exclusively present in nuclear fractions.
Extended Data Fig. 2 Purification of SMYD5 catalytic activity in cell lysates to identify UBA52 as candidate substrate.
a, Western blots of WCEs from control or SMYD5-depleted KKLS and U2OS cells used in b as substrates. b, SMYD5 methylates a ~ 10 kDa protein in KKLS and U2OS cell lysates. In vitro methylation assays as in Fig. 1d with the indicated enzymes and WCEs in a as substrates. c, The candidate SMYD5 substrate migrates faster than histone H4. In vitro methylation reactions as in b with the indicated KMT enzymes or GST alone as a negative control using SMYD5-depleted A549 WCEs as substrates as in Fig. 1d. Red arrowhead, SMYD5-dependent methylated protein. Blue arrowhead, SETD8-dependent histone H4 methylated at K20. d, Substantial enrichment of SMYD5-dependent methylated protein in extracts at 4th fractionation step (see schematic Fig. 1e). In vitro methylation assays as in Fig. 1d with the indicated enzymes using as substrate SMYD5-depleted A549 WCE, Input (lysate after 3 fractionation steps: (1) cytoplasmic isolation, (2) ammonium sulfate salt precipitation, and (3) hydrophobic interaction chromatography), and the indicated fractions (1–13) of the input material separated by size-exclusion chromatography. The Coomassie staining demonstrates the enrichment of the activity relative to total proteins present in the starting material. The region around the ~10 kDa band signal in Fraction 13, which showed the highest degree of purification, was analyzed by mass spectrometry (See Supplementary Tables 1–4). e, 2D gel electrophoresis separation of Fraction 13 in d further purifies the SMYD5-dependent methylated ~10kD protein. Red asterisk, SMYD5-dependent methyl band. The region around the red asterisk was analyzed by mass spectrometry to obtain UBA52 as the top hit. Left: Silver stain of 2D separation of Fraction 13 proteins; Middle: 3H-SAM was used as methyl donor and the methylation was visualized by autoradiography. Right: merge of the two panels.
Extended Data Fig. 3 SMYD5 specifically methylates rpL40 and has no activity on many other putative substrates in vitro.
a, The sequence of human rpL40 protein surrounding lysine 22. The site of methylation at K22 is indicated. Due to the many charged residues and the specific residues surrounding K22, irrespective of proteases, it is challenging to obtain suitable peptides for MS-based identification. b, SMYD5 methylates recombinant un-cleaved UBA52 protein in vitro. c, SMYD5 methylates recombinant rpL40 but not ubiquitin alone. d, Besides UBA52, SMYD5 did not in vitro methylate several other candidate proteins identified as potential candidates by MS/MS analysis of fraction 13 described in Extended Data Fig. 2d. e, SMYD5 does not in vitro methylate HIV-1 Tat protein. rpL40 is shown as a positive control.
Extended Data Fig. 4 Generation of a specific rpL40K22me3 antibody and evidence that SMYD5 is the principal enzyme that physiologically generates rpL40K22me3.
a, rpL40K22me3 antibody recognizes cognate methylated peptide sequence but not unmethylated peptide. Dot blot analysis with the indicated rpL40 peptides spanning amino acids (16–26) at the indicated concentrations probed with the rpL40K22me3 antibody (top) or stained with Ponceau S (bottom) to control for loading. b, rpL40K22me3 antibody recognizes cognate methylated peptide sequence but does not recognize several other histone and non-histone peptides harboring trimethylation. Dot bot analysis as in a. c, Western blot with the rpL40K22me3 antibody of in vitro methylation reactions with the indicated enzyme and substrates. d-e, Western blots with the indicated antibodies of WCEs from d, LMSU and e, SH-10-TC cell lines expressing CRISPR-Cas9 and two independent sgRNAs targeting SMYD5 or a control sgRNA. Tubulin was used as loading control. f, Western blots of SMYD5-depleted LMSU cells complemented with CRISPR-resistant SMYD5WT, SMYD5Y351A catalytic mutant, or control plasmid. g, Western blots with indicated antibodies of sucrose-cushion purified ribosome-depleted cytoplasmic lysates and ribosomes-enriched fractions from KKLS cells.
Extended Data Fig. 5 Alphafold analysis of SMYD5-rpL40 interaction and structural analysis of rpL40 in human ribosomes.
a-b, UBA52 + SMYD5 predicted structures (AlphaFold v2.3; see Methods) a, UBA52/rpL40 depicted by blue cartoon and SMYD5 by red molecular surface, as indicated. K22 of rpL40 the SMYD5 catalytic tunnel-forming residue (Y351) are shown. K22 of rpL40 directly inserts into SMYD5’s catalytic tunnel. b, UBA52 + SMYD5 predicted structures coloured by electrostatic charge. Colouring key depicts predict Coulombic electrostatic potential, with red corresponding to negative charge and blue corresponding to positive charge. rpL40 substrate lysine K22 and SMYD5 catalytic Y351 are shown. c-e, Ribosome-bound rpL40 undergoes rearrangements through different stages of elongation factor association. c, Top, ribbon representation of the overall complex of human 80 S ribosomes bound to eEF1A (PDB: 6ZMO), bottom, human 80 S ribosomes bound to eEF2 (PDB: 6D9J). rpL40, eEF1A and eEF2 are shown in surface representations and differentially coloured as indicated. d-e, close-up view of potential intermolecular interaction between rpL40K22 and adjacent 28 S rRNA. Distances are provided of hydrogen-bonding interactions depicted as dashed lines. d, rpL40K22 (shown in blue) from apo human 80 S ribosome structure (PDB: 4UG0) that is not bound to initiation/elongation factors and has close interactions with the 28 S rRNA at bases C4412 and C4413. rpL40K22 (shown in red) from 80 S ribosome bound to eEF1a (PDB: 6ZMO) leads to a shift in K22 of 5.3 Å toward an ionic interaction with G1945 of the 28 S rRNA. e, as in d but replacing eEF1A with 80 S ribosome bound to eEF2 (PDB: 6D9J), rpL40K22 shifts by 6.6 Å in favor of more distant interactions with G4411.
Extended Data Fig. 6 SMYD5 regulates ribosome dynamics and mRNA translation programs.
a, Western blots with the indicated antibodies of WCEs from the KKLS cells used in Fig. 2b. b, Ratio of area under polysomes (P) and monosome (M) peaks as in Fig. 2c from polysome profiling experiments of control or SMYD5-depleted LMSU cells fractionated on 10%–50% sucrose gradients are calculated and presented as P/M ratio from three independent biological replicates. P-value was determined by two-tailed unpaired t-test. c, Western analysis with the indicated antibodies of the indicated fractions from the polysome profiling experiments in KKLS cells as in Fig. 2b. d-e, SMYD5 depletion in LMSU cells leads to reduced global protein synthesis. d, Puromycylation assays in control or SMYD5-depleted LMSU cells. WCEs were probed with the indicated antibodies. e, AHA labeling assays as in (d). WCEs were probed with the indicated antibodies or HRP-strepavidin was used to detect biotin-clicked AHA. f, Linear regression analysis of ribosome half-transit time in control or SMYD5-depleted KKLS cells. PMS, post-mitochondrial supernatants (complete + nascent proteins); PRS, post-ribosomal supernatant (complete proteins). A representative graph is shown from four independent biological replicates. g, Summary of sequencing reads distribution mapped to the indicated categories. h, Principal component analysis (PCA) of the indicates datasets. i, Quality assessment of reads distribution across gene bodies, the absence of 3’ and 5’ bias indicates absence of high levels of RNA degradation (see Methods for g-i). j, GSEA analysis identifies the top significantly enriched signatures (Hallmark, KEGG, and selected) in differential polysome-associated mRNAs from Control versus SMYD5-depleted KKLS cells data sets (n = 3 biologically independent samples per group). Normalized enrichment scores (NES) and nominal P-values are shown. k, Westerns of the indicated proteins in control or SMYD5-depleted cell lines or GAC PDX samples as indicated (for KKLS, Western is representative of data from Fig. 2j). l, Quantification of Western signal (top row) and mRNA by RT-PCR (bottom row) for the indicated genes in the indicated cell lines ±SMYD5 as indicated. Data are represented as mean ± s.e.m. of three independent biological replicates.
Extended Data Fig. 7 SMYD5 and rpL40 K22me3 promote cancer cell proliferation.
a-f, SMYD5 depletion inhibits proliferation of KKLS (a,b), NCI-N87 (c,d) and AGS (e,f) cells. a, c, e, Western blots with the indicated antibodies of the indicated WCEs expressing CRISPR-Cas9 and two independent sgRNAs targeting SMYD5 or a control sgRNA. b, d, f, proliferation of cells shown in a, c, e, respectively. Data are represented as mean ± s.e.m from three biologically independent experiments. P-values were determined by two-tailed unpaired t-test. g, Representative immunohistochemical staining with rpL40 antibody of patient samples from normal gastric tissue (n = 12), GAC at advancing stages (n = 48 (stage I/II), 72 (III) and 16 (IV)) and GAC metastasis at the indicated organs (n = 34), scale bars: 100 µm. h, Representative immunohistochemical staining with rpS6 and rpL3 antibody of patient samples from normal gastric tissue (n = 12) and GAC at advancing stages (n = 48 (stage I/II), 72 (III) and 16 (IV)), scale bars: 100 µm. i, Puromycylation assays in control or SMYD5-depleted WI-38 (left), IMR-90 (right) cells. WCEs were probed with the indicated antibodies. j, Western blot analysis with the indicated antibodies of lysates from SMYD5-depleted KKLS gastric cancer cells complemented with CRISPR-resistant SMYD5WT or SMYD5Y351A. k, Tumor volume quantification for KKLS xenografts modified to express sgRNA SMYD5 or sgRNA control and overexpressing CRISPR-resistant SMYD5WT or catalytically deficient SMYD5Y351A as indicated (see j for Western blot analyses) in NSG mice (n = 5 mice, for each treatment group). P-values were calculated by two-way ANOVA with Tukey testing for multiple comparisons. Data are represented as mean ± s.e.m.
Extended Data Fig. 8 SMYD5 deletion represses malignant GAC tumorigenesis in vivo.
a, Representative IHC staining of gastric tumors from KPPC and KPPA models exhibit key histological features of human GAC, including positive staining for cytokeratin 7 (CK7) and CDX2 (representative of n = 9 samples for each group). Scale bars, 100 µm. b, Representative HE-stained section of gastric cancer lymph node, liver, and lung metastasis observed in KPPC and KPPA models. Scale bars, 100 µm. c, Schematic of the Smyd5LoxP/LoxP conditional allele. In the presence of Cre recombinase, exon 2 is deleted to disrupt Smyd5 expression. d, Confirmation of Smyd5LoxP/LoxP conditional allele by PCR on DNA isolated from mouse tail biopsies from indicated mouse genotypes, expected product sizes are marked. e, Left: Selected ion chromatograms for non-, mono-, di- and tri-methyl rpL40K22 peptides from Chymotrypsin digestion of endogenous rpL40 immunoprecipitated from biopsies from normal stomach tissue and GAC KPPC tissue. Note the Y axis scales for relative abundance are different between normal and tumor samples (see right panel for comparison of abundance of rpL40K22me3 peptides between normal and tumor samples). HPLC elution profiles show a 10-ppm mass window around expected peptide masses (peptide sequence ICRKCY, K22 is underlined; m/z are 300.4791, 305.1509, 309.8228, and 314.4947). Right: ion chromatograms for trimethyl rpL40K22 peptides as in the left panel using the Y axis scale from the tumor sample. Arrow indicates the relevant peak as in the left panel. f, Representative immunohistochemical staining and quantification of MYC and CD45 positive cells in gastric tumors from KPPC and KPPC;Smyd5 mutant mice at 6 weeks after tamoxifen induction (representative of n = 9 mice for each experimental group). Scale bars 100 µm. g, Representative HE-stained sections of gastric cancers at endpoint (severe morbidity) from KPPC and KPPA models indicate malignant histopathology with notable cancer cell invasion through basement membrane (dash line area with magnification). Scale bars 100 µm. h, Representative HE-stained sections, immunohistochemical staining with indicated antibodies and quantification of MYC and CD45 positive cells in gastric tumors from KPPA and KPPA;Smyd5 mutant mice at 6 weeks after tamoxifen induction (representative of n = 9 mice for each experimental group). Scale bars 100 µm. i, Westerns of the indicated proteins in tissue biopsy lysates from KPPC and KPPC;Smyd5 mutant mice. j, Quantification of Western signal (top) and mRNA by RT-PCR (bottom) for the indicated genes in tissue biopsy lysates from KPPC and KPPC;Smyd5 mutant mice. Data are represented as mean ± s.e.m. of three (Western) or four (RT-PCR) independent replicates. k, Dose-response analysis and half maximal inhibitory concentration values (IC50) for Omipalisib in LMSU GAC cell line ±SMYD5 knockdown. Data are represented as mean ± s.e.m. from three independent biological replicates. l, Western blot analysis with the indicated antibodies of WCE of control and SMYD5-depleted NUGC4 gastric cancer cell line. Boxes: 25th to 75th percentile, whiskers: min. to max., center line: median.
Extended Data Fig. 9 Analysis of therapeutic efficacy of PD1 and Mesothelin (MSLN)-CAR T cells immunotherapies against gastric cancer cells.
a, Representative bioluminescence imaging of syngeneic peritoneal carcinomatosis allograft model established in syngeneic mice from KPPC peritoneal metastases cells ±SMYD5 to test the efficacy of PD1 therapy. Animals were treated with ±PD1 (10 mg/kg, twice per week) and ±Omipalisib (4 mg/kg, daily) and tumor growth was monitored by bioluminescence imaging (n = 5 mice per group). b, Waterfall plot of KPPC ± SMYD5 allograph bioluminescence signal changes in individual mice receiving the indicated therapies (n = 5 mice per group). c, Kaplan-Meier survival curves of KPPC ± SMYD5 allograph receiving the indicated treatments. P-values were determined by log-rank test for significance. n = 5 mice per group. d, MSLN-CAR expression vector design containing truncated human nerve growth factor receptor (tNGFR), self-cleaving P2A peptide sequence followed by MSLN-specific scFv (SS1), the CD8a hinge, transmembrane, and CD28-CD3ζ co-stimulatory domain. tNGFR serves as a cell surface reporter to enable specific detection of CAR-expressing cells by flow cytometry. The right panel shows a representative flow cytometry plot identifying MSLN-CAR expressing T cells using NGFR staining. e, MSLN is a cell-surface glycoprotein expressed in NUGC4, LMSU cell lines and GAC-PDX cells as detected by flow cytometry. f, MSLN-CAR T cells co-cultured with MSLN+ NUGC4 cells shows selective killing of MSLN+ target cancer cells. Data are represented as mean ± s.e.m. from three independent biological replicates. g, MSLN-CAR T cells co-cultured with MSLN+ NUGC4 target cancer cells and analyzed for intracellular IL−2, IFN-γ and TNF-α cytokine levels by flow cytometry indicative of CAR T cell activation by MSLN+ target cells stimulation. Representative of three independent experiments is shown.
Extended Data Fig. 10 SMYD5 ablation or treatment with Omipalisib does not negatively impact CAR T cells efficacy and SMYD5 genetic alterations and mRNA expression in diverse cancers.
a, T cells isolated from Smyd5LoxP/LoxP conditional knockout were transduced with retrovirus expressing Cre-recombinase (Smyd5−/−) or mock control (wildtype). SMYD5 depletion was validated with rpL40 K22me3 specific antibody by flow cytometry. Representative of three independent experiments. b, Wildtype and Smyd5 deleted T cells exhibit similar distribution of naive (Tnaive; CD62L+CD44−), central memory (Tcm; CD62L+CD44+), effector memory (Tem; CD62L−CD44+) and CD62L−CD44− cell subsets. Data are represented as mean ± s.e.m. from three independent biological replicates. c, SMYD5 ablation in T cells does not significantly change the rate of apoptosis as assessed by Annexin V flow cytometry analysis. Data are represented as mean ± s.e.m. from three independent biological replicates. P-values were determined by a two-tailed unpaired t-test. d, MSLN-CAR T cells were generated from Smyd5LoxP/LoxP conditional knockout by transduction with retrovirus expressing CAR and Cre-recombinase (CAR T Smyd5−/−) or CAR only control (CAR T wildtype). SMYD5 depletion was validated with rpL40K22me3 specific antibody by flow cytometry. Representative of three independent experiments. e, Depletion of SMYD5 deletion does not inhibit MSLN-CAR T cells cytotoxicity against MSLN+ NUGC4 gastric cancer target cells. Data are represented as mean ± s.e.m. from three independent biological replicates. P-values were determined by a two-tailed unpaired t-test. f, Wildtype and Smyd5 deleted MSLN-CAR T cells exhibit similar distribution of naive (Tnaive; CD62L+CD44−), central memory (Tcm; CD62L+CD44+), effector memory (Tem; CD62L−CD44+) and CD62L−CD44− cell subsets. Data are represented as mean ± s.e.m. from three independent biological replicates. g, Depletion of SMYD5 does not significantly impact MSLN-CAR T cells apoptosis (Annexin V staining) or intracellular IFN-γ and TNF-α cytokine levels analyzed by flow cytometry following co-culture with MSLN+ NUGC4 target cells for 6 h. Data are represented as mean ± s.e.m. from three independent biological replicates. P-values were determined by a two-tailed unpaired t-test. h, Dose-response analysis and half maximal inhibitory concentration values (IC50) for Omipalisib in NUGC4 cells and CAR T cells shows that Omipalisib treatment more strongly suppresses SMYD5-depleted vs. control NUGC4 viability and has a much weaker impact on MSLN-CAR T cell viability at concentrations that effectively impact NUGC4 viability. Data from three independent biological replicates. i, Omipalisib treatment does not negatively impact MSLN-CAR T cell functions. CAR T cells were treated with Omipalisib at a concentration of 0.1 µM for 8 h, followed by co-culture with MSLN+ NUGC4 gastric cancer target cells for 6 h. Cell proliferation (cytoblue), apoptosis (Annexin V) and intracellular IFN-γ and TNF-α cytokine levels were analyzed by flow cytometry. Data are represented as mean ± s.e.m. from three independent biological replicates. P-values were determined by a two-tailed unpaired t-test. j, NUGC4 PC xenografted animal weight measurements over the course of the indicated treatments up to 63 days (as in Figs. 5e–g and i–l). Data are represented as mean ± s.e.m. of n = 5 mice per group. k, Copy number gain is the most frequent genetic alternation of SMYD5 present in common tumor types (TCGA data). l, SMYD5 expression relative to normal samples is elevated across diverse cancer types (TCGA data).
Supplementary information
Supplementary Fig. 1
Source gel, western blot and northern blot data for Figs. 1c,d,g,h–j,l, 2a,d–f, 3a,e,g,i, 4c,d and 5d and Extended Data Figs. 1d–f, 2a–e, 3b–e, 4–g, 6a,c–e,k, 7a,c,e,i,j and 8d,i,l. Flow cytometry data sequential gating and sorting strategies for Figs. 9d,e,g and 10a–d,f,gi.
Supplementary Table 1
List of candidate SMYD5 substrates identified with trypsin by MS after 2D gel separation of fraction 13 of size-exclusion chromatography.
Supplementary Table 2
List of candidate SMYD5 substrates identified with trypsin by MS of fraction 13 of size-exclusion chromatography.
Supplementary Table 3
List of candidate SMYD5 substrates identified with chymotrypsin by MS of fraction 13 of size-exclusion chromatography.
Supplementary Table 4
List of candidate SMYD5 substrates identified with Glu-C by MS of fraction 13 of size-exclusion chromatography (Extended Data Fig. 2d).
Supplementary Table 5
List of differential polysome-associated (polysome-seq) and total mRNA populations from control and SMYD5-depleted KKLS cells. Polysome association: mRNAs differentially associated (up or down) with polysomes that are independent of total mRNA abundance. mRNA abundance: list of upregulated and downregulated genes in total RNA-seq analysis (transcriptionally regulated). Buffering: total mRNA abundance up or down without a corresponding change in polysome association. Background: mRNAs with no significant change.
Supplementary Table 6
A list of compounds and their results used in cell growth inhibition screen with SMYD5 knockdown.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Park, J., Wu, J., Szkop, K.J. et al. SMYD5 methylation of rpL40 links ribosomal output to gastric cancer. Nature 632, 656–663 (2024). https://doi.org/10.1038/s41586-024-07718-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41586-024-07718-0
Comments
By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.