Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

The long non-coding RNA ROSALIND protects the mitochondrial translational machinery from oxidative damage

Cell Death & Differentiation (2024)Cite this article

Subjects

Abstract

Upregulation of mitochondrial respiration coupled with high ROS-scavenging capacity is a characteristic shared by drug-tolerant cells in several cancers. As translational fidelity is essential for cell fitness, protection of the mitochondrial and cytosolic ribosomes from oxidative damage is pivotal. While mechanisms for recognising and repairing such damage exist in the cytoplasm, the corresponding process in the mitochondria remains unclear.By performing Ascorbate PEroXidase (APEX)-proximity ligation assay directed to the mitochondrial matrix followed by isolation and sequencing of RNA associated to mitochondrial proteins, we identified the nuclear-encoded lncRNA ROSALIND as an interacting partner of ribosomes. ROSALIND is upregulated in recurrent tumours and its expression can discriminate between responders and non-responders to immune checkpoint blockade in a melanoma cohort of patients. Featuring an unusually high G content, ROSALIND serves as a substrate for oxidation. Consequently, inhibiting ROSALIND leads to an increase in ROS and protein oxidation, resulting in severe mitochondrial respiration defects. This, in turn, impairs melanoma cell viability and increases immunogenicity both in vitro and ex vivo in preclinical humanised cancer models. These findings underscore the role of ROSALIND as a novel ROS buffering system, safeguarding mitochondrial translation from oxidative stress, and shed light on potential therapeutic strategies for overcoming cancer therapy resistance.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: ROSALIND is a nuclear-encoded lncRNA localising to the mitochondrial matrix.
Fig. 2: ROSALIND expression correlates with cancer recurrence and therapy resistance.
Fig. 3: ROSALIND interacts with MRPL38 at the mitochondrial ribosome.
Fig. 4: ROSALIND affects mitochondrial mass and respiration.
Fig. 5: ROSALIND affects melanoma viability.
Fig. 6: ROSALIND is a novel ROS buffering system.
Fig. 7: ROSALIND knock-down affects melanoma viability and immunogenicity.

Similar content being viewed by others

Data availability

Sequencing data have been deposited to GEO database with accession number GSE249588. Proteomics data have been deposited to ProteomeXchange consortium with the following accession number PXD047963.

References

  1. Fabbri L, Chakraborty A, Robert C, Vagner S. The plasticity of mRNA translation during cancer progression and therapy resistance. Nat Rev Cancer. 2021;21:558–77. https://doi.org/10.1038/s41568-021-00380-y.

    Article  CAS  PubMed  Google Scholar 

  2. Xu Y, Ruggero D. The Role of Translation Control in Tumorigenesis and Its Therapeutic Implications. Annu Rev Cancer Biol. 2020;4:437–57. https://doi.org/10.1146/annurev-cancerbio-030419-033420.

    Article  Google Scholar 

  3. Falletta P, Sanchez-del-Campo L, Chauhan J, Effern M, Kenyon A, Kershaw CJ, et al. Translation reprogramming is an evolutionarily conserved driver of phenotypic plasticity and therapeutic resistance in melanoma. Genes Dev. 2017;31:18–33. https://doi.org/10.1101/gad.290940.116.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Vendramin, R, Katopodi, V, Cinque, S, Konnova, A, Knezevic, Z, Adnane, S, et al. (2021). Activation of the integrated stress response confers vulnerability to mitoribosome-targeting antibiotics in melanoma. J Experimental Med. 218. https://doi.org/10.1084/jem.20210571.

  5. Pu Y, Li L, Peng H, Liu L, Heymann D, Robert C, et al. Drug-tolerant persister cells in cancer: the cutting edges and future directions. Nat Rev Clin Oncol. 2023;20:799–813. https://doi.org/10.1038/s41571-023-00815-5.

    Article  PubMed  Google Scholar 

  6. Rapino F, Delaunay S, Rambow F, Zhou Z, Tharun L, De Tullio P, et al. Codon-specific translation reprogramming promotes resistance to targeted therapy. Nature. 2018;558:605–9. https://doi.org/10.1038/s41586-018-0243-7.

    Article  CAS  PubMed  Google Scholar 

  7. Cinque S, Verheyden Y, Adnane S, Marino M, Katopodi V, Demesmaeker E, et al. The assembly of cancer-specific ribosomes by the lncRNA LISRR suppresses melanoma anti-tumour immunity. bioRxiv 2023.01.06.523012 https://doi.org/10.1101/2023.01.06.523012.

  8. Gambi G, Mengus G, Davidson G, Demesmaeker E, Cuomo A, Bonaldi T, et al. The LncRNA LENOX Interacts with RAP2C to Regulate Metabolism and Promote Resistance to MAPK Inhibition in Melanoma. Cancer Res. 2022;82:4555–70. https://doi.org/10.1158/0008-5472.CAN-22-0959.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Oren Y, Tsabar M, Cuoco MS, Amir-Zilberstein L, Cabanos HF, Hütter J-C, et al. Cycling cancer persister cells arise from lineages with distinct programs. Nature. 2021;596:576–82. https://doi.org/10.1038/s41586-021-03796-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Cheung EC, Vousden KH. The role of ROS in tumour development and progression. Nat Rev Cancer. 2022;22:280–97. https://doi.org/10.1038/s41568-021-00435-0.

    Article  CAS  PubMed  Google Scholar 

  11. Willi J, Küpfer P, Evéquoz D, Fernandez G, Katz A, Leumann C, et al. Oxidative stress damages rRNA inside the ribosome and differentially affects the catalytic center. Nucleic Acids Res. 2018;46:1945–57. https://doi.org/10.1093/nar/gkx1308.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Zhang J, Simpson CM, Berner J, Chong HB, Fang J, Ordulu Z, et al. Systematic identification of anticancer drug targets reveals a nucleus-to-mitochondria ROS-sensing pathway. Cell. 2023;186:2361–2379.e25. https://doi.org/10.1016/j.cell.2023.04.026.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Rysman E, Brusselmans K, Scheys K, Timmermans L, Derua R, Munck S, et al. De novo Lipogenesis Protects Cancer Cells from Free Radicals and Chemotherapeutics by Promoting Membrane Lipid Saturation. Cancer Res. 2010;70:8117–26. https://doi.org/10.1158/0008-5472.CAN-09-3871.

    Article  CAS  PubMed  Google Scholar 

  14. Eichhoff OM, Stoffel CI, Käsler J, Briker L, Turko P, Karsai G, et al. ROS Induction Targets Persister Cancer Cells with Low Metabolic Activity in NRAS-Mutated Melanoma. Cancer Res. 2023;83:1128–46. https://doi.org/10.1158/0008-5472.CAN-22-1826.

    Article  CAS  PubMed  Google Scholar 

  15. Talebi A, de Laat V, Spotbeen X, Dehairs J, Rambow F, Rogiers A, et al. Pharmacological induction of membrane lipid poly-unsaturation sensitizes melanoma to ROS inducers and overcomes acquired resistance to targeted therapy. J Exp Clin Cancer Res. 2023;42:92 https://doi.org/10.1186/s13046-023-02664-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Snieckute, G, Ryder, L, Vind, AC, Wu, Z, Arendrup, FS, Stoneley, M, et al. (2023). ROS-induced ribosome impairment underlies ZAKα-mediated metabolic decline in obesity and aging. Science (1979) 382. https://doi.org/10.1126/science.adf3208.

  17. Yang Y-M, Jung Y, Abegg D, Adibekian A, Carroll KS, Karbstein K. Chaperone-directed ribosome repair after oxidative damage. Mol Cell. 2023;83:1527–1537.e5. https://doi.org/10.1016/j.molcel.2023.03.030.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Vendramin, R, Verheyden, Y, Ishikawa, H, Goedert, L, Nicolas, E, Saraf, K, et al. (2018). SAMMSON fosters cancer cell fitness by concertedly enhancing mitochondrial and cytosolic translation. Nat Struct Mol Biol. https://doi.org/10.1038/s41594-018-0143-4.

  19. Leucci E, Vendramin R, Spinazzi M, Laurette P, Fiers M, Wouters J, et al. Melanoma addiction to the long non-coding RNA SAMMSON. Nature. 2016;531:518–22. https://doi.org/10.1038/nature17161.

    Article  CAS  PubMed  Google Scholar 

  20. Pozniak J, Pedri D, Landeloos E, Van Herck Y, Antoranz A, Vanwynsberghe L, et al. A TCF4/BRD4-dependent regulatory network confers cross-resistance to targeted and immune checkpoint therapy in melanoma. Cell 2024;187:166–183.e25. https://doi.org/10.1016/j.cell.2023.11.037.

    Article  CAS  PubMed  Google Scholar 

  21. Greber BJ, Boehringer D, Leitner A, Bieri P, Voigts-Hoffmann F, Erzberger JP, et al. Architecture of the large subunit of the mammalian mitochondrial ribosome. Nature. 2014;505:515–9. https://doi.org/10.1038/nature12890.

    Article  CAS  PubMed  Google Scholar 

  22. Lang B, Armaos A, Tartaglia GG. RNAct: Protein-RNA interaction predictions for model organisms with supporting experimental data. Nucleic Acids Res 2019;47:D601–D606. https://doi.org/10.1093/nar/gky967.

    Article  CAS  PubMed  Google Scholar 

  23. Verfaillie A, Imrichova H, Atak ZK, Dewaele M, Rambow F, Hulselmans G, et al. Decoding the regulatory landscape of melanoma reveals TEADS as regulators of the invasive cell state. Nat Commun. 2015;6:6683. https://doi.org/10.1038/ncomms7683.

    Article  CAS  PubMed  Google Scholar 

  24. Chen, X, Sunkel, B, Wang, M, Kang, S, Wang, T, Gnanaprakasam, JNR, et al. (2022). Succinate dehydrogenase/complex II is critical for metabolic and epigenetic regulation of T cell proliferation and inflammation. Sci Immunol 7. https://doi.org/10.1126/sciimmunol.abm8161.

  25. Tavassolifar Mjavad, Vodjgani M, Salehi Z, Izad M. The Influence of Reactive Oxygen Species in the Immune System and Pathogenesis of Multiple Sclerosis. Autoimmune Dis. 2020;2020:1–14. https://doi.org/10.1155/2020/5793817.

    Article  CAS  Google Scholar 

  26. Hecht F, Zocchi M, Alimohammadi F, Harris IS. Regulation of antioxidants in cancer. Mol Cell 2023. https://doi.org/10.1016/j.molcel.2023.11.001.

    Article  PubMed  Google Scholar 

  27. Piskounova E, Agathocleous M, Murphy MM, Hu Z, Huddlestun SE, Zhao Z, et al. Oxidative stress inhibits distant metastasis by human melanoma cells. Nature. 2015;527:186–91. https://doi.org/10.1038/nature15726.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Mangalhara KC, Varanasi SK, Johnson MA, Burns MJ, Rojas GR, Esparza Moltó PB, et al. Manipulating mitochondrial electron flow enhances tumor immunogenicity. Science. 2023;381:1316–23. https://doi.org/10.1126/science.abq1053.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Fortmann SP, Burda BU, Senger CA, Lin JS, Whitlock EP. Vitamin and Mineral Supplements in the Primary Prevention of Cardiovascular Disease and Cancer: An Updated Systematic Evidence Review for the U.S. Preventive Services Task Force. Ann Intern Med. 2013;159:824–34. https://doi.org/10.7326/0003-4819-159-12-201312170-00729.

    Article  PubMed  Google Scholar 

  30. El-Botty R, Morriset L, Montaudon E, Tariq Z, Schnitzler A, Bacci M, et al. Oxidative phosphorylation is a metabolic vulnerability of endocrine therapy and palbociclib resistant metastatic breast cancers. Nat Commun. 2023;14:4221 https://doi.org/10.1038/s41467-023-40022-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Sun N, Youle RJ, Finkel T. The Mitochondrial Basis of Aging. Mol Cell. 2016;61:654–66. https://doi.org/10.1016/j.molcel.2016.01.028.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Amunts A, Brown A, Toots J, Scheres SHW, Ramakrishnan V. The structure of the human mitochondrial ribosome. Science. 2015;348:95–98. https://doi.org/10.1126/science.aaa1193.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Flaherty KT, Robert C, Hersey P, Nathan P, Garbe C, Milhem M, et al. Improved Survival with MEK Inhibition in BRAF-Mutated Melanoma. N. Engl J Med. 2012;367:107–14. https://doi.org/10.1056/NEJMoa1203421.

    Article  CAS  PubMed  Google Scholar 

  34. Nikolaisen J, Nilsson LIH, Pettersen IKN, Willems PHGM, Lorens JB, Koopman WJH, et al. Automated Quantification and Integrative Analysis of 2D and 3D Mitochondrial Shape and Network Properties. PLoS One. 2014;9:e101365 https://doi.org/10.1371/journal.pone.0101365.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Chaudhry A, Shi R, Luciani DS. A pipeline for multidimensional confocal analysis of mitochondrial morphology, function, and dynamics in pancreatic β-cells. Am J Physiol-Endocrinol Metab. 2020;318:E87–E101. https://doi.org/10.1152/ajpendo.00457.2019.

    Article  CAS  PubMed  Google Scholar 

  36. Merrill, RA, Flippo, KH, and Strack, S (2017). Measuring Mitochondrial Shape with ImageJ. In, pp. 31–48. https://doi.org/10.1007/978-1-4939-6890-9_2.

  37. Wickham, H (2016). ggplot2 (Springer International Publishing) https://doi.org/10.1007/978-3-319-24277-4.

  38. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550 https://doi.org/10.1186/s13059-014-0550-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005;102:15545–50. https://doi.org/10.1073/pnas.0506580102.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Kang Y-J, Yang D-C, Kong L, Hou M, Meng Y-Q, Wei L, et al. CPC2: a fast and accurate coding potential calculator based on sequence intrinsic features. Nucleic Acids Res. 2017;45:W12–W16. https://doi.org/10.1093/nar/gkx428.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We would like to thank the Light Microscopy and Imaging Network - LiMoNe (VIB-KULeuven) and Guy Schepers and Frédérick Coosemans (Rega Institute) for the excellent technical support with microscopy and with ASO synthesis respectively. We would like to thank Dr. G. Gambi and Dr. R. Vendramin for the useful discussion and assistance with the mitochondrial measurements.

Funding

The present study was funded by a KU Leuven C1 grant, a Belgian federation for Cancer grant (FAF-F/2018/1184). E. Leucci was funded by the Melanoma Research Alliance Amanda and Jonathan Eilian young investigator award. V. Katopodi is a recipient of a FWO – Flanders research organization PhD fellowship (1S47519N). Y. Verheyden is FWO – Flanders research organization PhD fellowship (1SC5122N). S. Cinque is a recipient of FWO – Flanders research organization PhD fellowship (1SD1620N). A. Scomparin and N. Pateraki were supported by an ERASMUS+ fellowship.

Author information

Author notes

  1. These authors contributed equally: Nikoleta Pateraki, Yvessa Verheyden.

Authors and Affiliations

  1. Laboratory for RNA Cancer Biology, Department of Oncology, KU Leuven, Leuven, Belgium

    Vicky Katopodi, Alessandro Marino, Nikoleta Pateraki, Yvessa Verheyden, Sonia Cinque, Elena Lara Jimenez, Sara Adnane, Ewout Demesmaeker, Alice Scomparin & Eleonora Leucci

  2. Laboratory for Protein Phosphorylation and Proteomics, Leuven, Belgium

    Rita Derua

  3. Rega Institute for Medical Research, Medicinal Chemistry, KU Leuven, Leuven, Belgium

    Elisabetta Groaz

  4. Trace, Leuven Cancer Institute, KU Leuven, Leuven, Belgium

    Eleonora Leucci

Authors
  1. Vicky Katopodi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alessandro Marino
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nikoleta Pateraki
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yvessa Verheyden
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sonia Cinque
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Elena Lara Jimenez
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Sara Adnane
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ewout Demesmaeker
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Alice Scomparin
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Rita Derua
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Elisabetta Groaz
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Eleonora Leucci
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

VK performed most of the wet lab experiments and assembled figures. YV performed all the bioinformatic analysis. ELJ performed Incucyte analysis in Fig. 5 and supplemental Fig. 3. ED prepared PDTF, PDX-derived cell lines and stable clones for downstream applications. EG provided ASO. AM and RD designed and interpreted mass spectrometry experiments. AM performed pulldown on mutant ROSALIND. SA quantified mutant colonies. NP engineered ROSALIND mutants. AS maintained stable cell lines for downstream applications and performed western blots. EL designed the study. EL interpreted the data and wrote the manuscript. All authors read and edited the manuscript.

Corresponding author

Correspondence to Eleonora Leucci.

Ethics declarations

Competing interests

The authors declare no competing interests

Ethics approval

The cutaneous melanoma PDX models use for the PDTFs are part of the Trace collection: https://gbiomed.kuleuven.be/english/research/50488876/54502087/Trace. All the procedures for the establishment and biobanking of these models have been performed in accordance with the principles of the Declaration of Helsinki, with GDPR regulations and with the internal, national and European guidelines of animal care and use. All procedures have been approved by the animal ethical committee of KU Leuven (P164/2019) and by the Ethical committee research of UZ/KUL (S63799).

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

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.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Katopodi, V., Marino, A., Pateraki, N. et al. The long non-coding RNA ROSALIND protects the mitochondrial translational machinery from oxidative damage. Cell Death Differ (2024). https://doi.org/10.1038/s41418-024-01377-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41418-024-01377-4

Search

Advanced search

Quick links