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The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Epigenetic therapy induces transcription of inverted SINEs and ADAR1 dependency

Mehdipour, Parinaz, Marhon, Sajid A., Ettayebi, Ilias, Chakravarthy, Ankur, Hosseini, Amir, Wang, Yadong, de Castro, Fabíola Attié, Loo Yau, Helen, Ishak, Charles, Abelson, Sagi, O’Brien, Catherine A., De Carvalho, Daniel D.·2020·Nature
DOI 10.1038/s41586-020-2844-1
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Crossref · 10.1038/s41586-020-2844-1

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9 of 9 references verified0 citation errors · 0 not checkable

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  • The long-term impact of interventions on whole organisms is still poorly understood.

    “Such interventions have been successful in reducing cell damage and preserving tissue health, but the long-term impact on whole organisms is still poorly understood [11][12][13][14] .”

    From Mechanisms, pathways and strategies for rejuvenation through epigenetic reprogramming (2023) · cites this paper as [14]

    The Main section reports short-term tumour outcomes in mice, including measurements around days 14–15, and cellular responses up to 24 days. Neither those passages nor searches for long-term organism-level effects state that the long-term impact of interventions on whole organisms is poorly understood. (LLM, conf=0.74)

    Experimental — accuracy not yet measured

  • Multiple interventions, acting at different levels, can delay or even reverse the aging process.

    “In contrast to the view of aging as an irreversible and unidirectional process akin to an increase in cell entropy, recent studies have demonstrated that multiple interventions, acting at different levels, can delay or even reverse this process [10][11][12][13][14][15][16][17] .”

    From Mechanisms, pathways and strategies for rejuvenation through epigenetic reprogramming (2023) · cites this paper as [14]

    The Abstract and Main section report effects of epigenetic therapy and ADAR1 depletion on cancer cells and tumour growth, not on aging. Searches for interventions that delay or reverse aging, including rejuvenation and lifespan, found no passage addressing the claim. No page numbers are available in our copy. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

  • Interventions have been successful in reducing cell damage and preserving tissue health.

    “Such interventions have been successful in reducing cell damage and preserving tissue health, but the long-term impact on whole organisms is still poorly understood [11][12][13][14] .”

    From Mechanisms, pathways and strategies for rejuvenation through epigenetic reprogramming (2023) · cites this paper as [14]

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Citations

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Flagged first, then by citations

Research works printed but not linked: 35

  1. Roulois, D. et al. DNA-demethylating agents target colorectal cancer cells by inducing viral mimicry by endogenous transcripts. Cell 162, 961–973 (2015). · DOI · Paper page
  2. Sheng, W. et al. LSD1 ablation stimulates anti-tumor immunity and enables checkpoint blockade. Cell 174, 549–563 (2018). · DOI · Paper page
  3. Cuellar, T. L. et al. Silencing of retrotransposons by SETDB1 inhibits the interferon response in acute myeloid leukemia. J. Cell Biol. 216, 3535–3549 (2017). · DOI
  4. Guler, G. D. et al. Repression of stress-induced LINE-1 expression protects cancer cell subpopulations from lethal drug exposure. Cancer Cell 32, 221–237 (2017). · DOI · Paper page
  5. Loo Yau, H., Ettayebi, I. & De Carvalho, D. D. The cancer epigenome: exploiting its vulnerabilities for immunotherapy. Trends Cell Biol. 29, 31–43 (2019). · DOI
  6. Jones, P. A., Ohtani, H., Chakravarthy, A. & De Carvalho, D. D. Epigenetic therapy in immune-oncology. Nat. Rev. Cancer 19, 151–161 (2019). · DOI
  7. Deaton, A. M. & Bird, A. CpG islands and the regulation of transcription. Genes Dev. 25, 1010–1022 (2011). · DOI · Paper page
  8. Levanon, E. Y. et al. Systematic identification of abundant A-to-I editing sites in the human transcriptome. Nat. Biotechnol. 22, 1001–1005 (2004). · DOI
  9. Liddicoat, B. J. et al. RNA editing by ADAR1 prevents MDA5 sensing of endogenous dsRNA as nonself. Science 349, 1115–1120 (2015). · DOI
  10. Leruste, A. et al. Clonally expanded T cells reveal immunogenicity of rhabdoid tumors. Cancer Cell 36, 597–612 (2019). · DOI
  11. Krug, B. et al. Pervasive H3K27 acetylation leads to ERV expression and a therapeutic vulnerability in H3K27M gliomas. Cancer Cell 35, 782–797 (2019). · DOI
  12. Deininger, P. Alu elements: know the SINEs. Genome Biol. 12, 236 (2011). · DOI
  13. Iorio, F. et al. A landscape of pharmacogenomic interactions in cancer. Cell 166, 740–754 (2016). · DOI · Paper page
  14. Skene, P. J. & Henikoff, S. An efficient targeted nuclease strategy for high-resolution mapping of DNA binding sites. eLife 6, e21856 (2017).
  15. Gruber, A. J. et al. A comprehensive analysis of 3′ end sequencing data sets reveals novel polyadenylation signals and the repressive role of heterogeneous ribonucleoprotein C on cleavage and polyadenylation. Genome Res. 26, 1145–1159 (2016). · DOI
  16. Samuel, C. E. Adenosine deaminases acting on RNA (ADARs) are both antiviral and proviral. Virology 411, 180–193 (2011). · DOI
  17. Hou, F. et al. MAVS forms functional prion-like aggregates to activate and propagate antiviral innate immune response. Cell 146, 448–461 (2011). · DOI
  18. Issa, J. P. & Kantarjian, H. M. Targeting DNA methylation. Clin. Cancer Res. 15, 3938–3946 (2009). · DOI
  19. Ishizuka, J. J. et al. Loss of ADAR1 in tumours overcomes resistance to immune checkpoint blockade. Nature 565, 43–48 (2019). · DOI · Paper page
  20. Gannon, H. S. et al. Identification of ADAR1 adenosine deaminase dependency in a subset of cancer cells. Nat. Commun. 9, 5450 (2018). · DOI
  21. Saito, Y. et al. Inhibition of DNA methylation suppresses intestinal tumor organoids by inducing an anti-viral response. Sci. Rep. 6, 25311 (2016).
  22. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009). · DOI · Paper page
  23. Pertea, M. et al. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat. Biotechnol. 33, 290–295 (2015). · DOI
  24. Jun, G., Wing, M. K., Abecasis, G. R. & Kang, H. M. An efficient and scalable analysis framework for variant extraction and refinement from population-scale DNA sequence data. Genome Res. 25, 918–925 (2015). · DOI
  25. Narasimhan, V. et al. BCFtools/RoH: a hidden Markov model approach for detecting autozygosity from next-generation sequencing data. Bioinformatics 32, 1749–1751 (2016). · DOI
  26. Chen, S., Zhou, Y., Chen, Y. & Gu, J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884–i890 (2018). · DOI · Paper page
  27. Skene, P. J., Henikoff, J. G. & Henikoff, S. Targeted in situ genome-wide profiling with high efficiency for low cell numbers. Nat. Protoc. 13, 1006–1019 (2018). · DOI · Paper page
  28. Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).
  29. Ramirez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44, W160–W165, (2016). · DOI · Paper page
  30. Kwon, M. & Firestein, B. L. DNA transfection: calcium phosphate method. Methods Mol. Biol. 1018, 107–110 (2013). · DOI
  31. Halfmann, R. & Lindquist, S. Screening for amyloid aggregation by semi-denaturing detergent-agarose gel electrophoresis. J. Vis. Exp. 17, e838 (2008). · DOI
  32. Ettayebi, I., Yau, H. L. & De Carvalho, D. D. Methods to detect endogenous dsRNA induction and recognition. Methods Enzymol. 629, 35–51 (2019). · DOI
  33. Teissandier, A., Servant, N., Barillot, E. & Bourc’his, D. Tools and best practices for retrotransposon analysis using high-throughput sequencing data. Mob. DNA 10, 52 (2019). · DOI
  34. Sergushichev, A. A. An algorithm for fast preranked gene set enrichment analysis using cumulative statistic calculation. Preprint at https://doi.org/10.1101/060012 (2016). · DOI
  35. Hu, Y. & Smyth, G. K. ELDA: extreme limiting dilution analysis for comparing depleted and enriched populations in stem cell and other assays. J. Immunol. Methods 347, 70–78 (2009). · DOI

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Metadata

Authors
Mehdipour, P., Marhon, S. A., Ettayebi, I., Chakravarthy, A., Hosseini, A., Wang, Y., de Castro, F. A., Loo Yau, H., Ishak, C., Abelson, S., O’Brien, C. A., & De Carvalho, D. D.
Venue
Nature
Publisher
Springer Science and Business Media LLC
Published
2020-10-21
Volume
588
Issue
7836
Pages
169-173
ISSN
  • 0028-0836
  • 1476-4687
DOI
10.1038/s41586-020-2844-1
Cited by
304
References
9
Language
en
Update notices
correction (2021-03-02)
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