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Cancer cells exploit an orphan RNA to drive metastatic progression

Abstract

Here we performed a systematic search to identify breast-cancer-specific small noncoding RNAs, which we have collectively termed orphan noncoding RNAs (oncRNAs). We subsequently discovered that one of these oncRNAs, which originates from the 3′ end of TERC, acts as a regulator of gene expression and is a robust promoter of breast cancer metastasis. This oncRNA, which we have named T3p, exerts its prometastatic effects by acting as an inhibitor of RISC complex activity and increasing the expression of the prometastatic genes NUPR1 and PANX2. Furthermore, we have shown that oncRNAs are present in cancer-cell-derived extracellular vesicles, raising the possibility that these circulating oncRNAs may also have a role in non–cell autonomous disease pathogenesis. Additionally, these circulating oncRNAs present a novel avenue for cancer fingerprinting using liquid biopsies.

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Fig. 1: Discovery, annotation and validation of cancer-specific oncRNAs in breast cancer.
Fig. 2: The oncRNA T3p is associated with breast cancer progression.
Fig. 3: T3p regulates gene expression and drives metastatic progression.
Fig. 4: T3p biogenesis and function.
Fig. 5: T3p-mediated inhibition of miR-10b and miR-378c results in overexpression of metastasis promoters NUPR1 and PANX2.
Fig. 6: Systematic profiling of oncRNAs in the extracellular compartment.

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Data Availability

All sequencing data generated for this study has been deposited in the Gene Expression Omnibus under the accession number GSE114366.

References

  1. Tavazoie, S. F. et al. Endogenous human microRNAs that suppress breast cancer metastasis. Nature 451, 147–152 (2008).

    Article  CAS  Google Scholar 

  2. Fish, L. et al. Muscleblind-like 1 suppresses breast cancer metastatic colonization and stabilizes metastasis suppressor transcripts. Genes Dev. 30, 386–398 (2016).

    Article  CAS  Google Scholar 

  3. Vanharanta, S. et al. Loss of the multifunctional RNA-binding protein RBM47 as a source of selectable metastatic traits in breast cancer. eLife 3, e02734 (2014).

    Article  Google Scholar 

  4. David, C. J., Chen, M., Assanah, M., Canoll, P. & Manley, J. L. HnRNP proteins controlled by c-Myc deregulate pyruvate kinase mRNA splicing in cancer. Nature 463, 364–368 (2010).

    Article  CAS  Google Scholar 

  5. Chen, L.-Y. & Lingner, J. AUF1/HnRNP D RNA binding protein functions in telomere maintenance. Mol. Cell 47, 1–2 (2012).

    Article  Google Scholar 

  6. Goodarzi, H. et al. Modulated expression of specific tRNAs drives gene expression and cancer progression. Cell 165, 1416–1427 (2016).

    Article  CAS  Google Scholar 

  7. Goodarzi, H. et al. Endogenous tRNA-derived fragments suppress breast cancer progression via YBX1 displacement. Cell 161, 790–802 (2015).

    Article  CAS  Google Scholar 

  8. Simanshu, D. K., Nissley, D. V. & McCormick, F. RAS proteins and their regulators in human disease. Cell 170, 17–33 (2017).

    Article  CAS  Google Scholar 

  9. Bhargava, R. et al. EGFR gene amplification in breast cancer: correlation with epidermal growth factor receptor mRNA and protein expression and HER-2 status and absence of EGFR-activating mutations. Mod. Pathol. 18, 1027–1033 (2005).

    Article  CAS  Google Scholar 

  10. Ren, R. Mechanisms of BCR–ABL in the pathogenesis of chronic myelogenous leukaemia. Nat. Rev. Cancer 5, 172–183 (2005).

    Article  CAS  Google Scholar 

  11. Lin, R.-K. & Wang, Y.-C. Dysregulated transcriptional and post-translational control of DNA methyltransferases in cancer. Cell Biosci. 4, 46 (2014).

    Article  Google Scholar 

  12. Wu, C.-I., Wang, H.-Y., Ling, S. & Lu, X. The ecology and evolution of cancer: the ultra-microevolutionary process. Annu. Rev. Genet. 50, 347–369 (2016).

    Article  CAS  Google Scholar 

  13. Minn, A. J. et al. Distinct organ-specific metastatic potential of individual breast cancer cells and primary tumors. J. Clin. Invest. 115, 44–55 (2005).

    Article  CAS  Google Scholar 

  14. Loo, J. M. et al. Extracellular metabolic energetics can promote cancer progression. Cell 160, 393–406 (2015).

    Article  CAS  Google Scholar 

  15. Bak, R. O., Hollensen, A. K., Primo, M. N., Sørensen, C. D. & Mikkelsen, J. G. Potent microRNA suppression by RNA Pol II-transcribed ‘Tough Decoy’ inhibitors. RNA 19, 280–293 (2013).

    Article  Google Scholar 

  16. Cooper, D. N., Berg, L. P., Kakkar, V. V. & Reiss, J. Ectopic (illegitimate) transcription: new possibilities for the analysis and diagnosis of human genetic disease. Ann. Med. 26, 9–14 (1994).

    Article  CAS  Google Scholar 

  17. Margolin, A. A. et al. ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics 7, S7 (2006).

    Article  Google Scholar 

  18. Goodarzi, H. et al. Metastasis-suppressor transcript destabilization through TARBP2 binding of mRNA hairpins. Nature 513, 256–260 (2014).

    Article  CAS  Google Scholar 

  19. Kim, B., Jeong, K. & Kim, V. N. Genome-wide mapping of DROSHA cleavage sites on primary microRNAs and noncanonical substrates. Mol. Cell 66, 258–269 (2017).

    Article  CAS  Google Scholar 

  20. Ray, D. et al. A compendium of RNA-binding motifs for decoding gene regulation. Nature 499, 172–177 (2013).

    Article  CAS  Google Scholar 

  21. Yang, Y.-C. T. et al. CLIPdb: a CLIP-seq database for protein–RNA interactions. BMC Genomics 16, 51 (2015).

    Article  CAS  Google Scholar 

  22. Van Nostrand, E. L. et al. Robust transcriptome-wide discovery of RNA-binding protein binding sites with enhanced CLIP (eCLIP). Nat. Methods 13, 508–514 (2016).

    Article  Google Scholar 

  23. Goodarzi, H. et al. Systematic discovery of structural elements governing stability of mammalian messenger RNAs. Nature 485, 264–268 (2012).

    Article  CAS  Google Scholar 

  24. Kishore, S. et al. A quantitative analysis of CLIP methods for identifying binding sites of RNA-binding proteins. Nat. Methods 8, 559–564 (2011).

    Article  CAS  Google Scholar 

  25. Helwak, A., Kudla, G., Dudnakova, T. & Tollervey, D. Mapping the human miRNA interactome by CLASH reveals frequent noncanonical binding. Cell 153, 654–665 (2013).

    Article  CAS  Google Scholar 

  26. Elemento, O., Slonim, N. & Tavazoie, S. A universal framework for regulatory element discovery across all genomes and data types. Mol. Cell 28, 337–350 (2007).

    Article  CAS  Google Scholar 

  27. Bos, P. D. et al. Genes that mediate breast cancer metastasis to the brain. Nature 459, 1005–1009 (2009).

    Article  CAS  Google Scholar 

  28. Fiskaa, T. et al. Distinct small RNA signatures in extracellular vesicles derived from breast cancer cell lines. PLoS ONE 11, e0161824 (2016).

    Article  Google Scholar 

  29. Zhou, W. et al. Cancer-secreted miR-105 destroys vascular endothelial barriers to promote metastasis. Cancer Cell 25, 501–515 (2014).

    Article  CAS  Google Scholar 

  30. Ainsztein, A. M. et al. The NIH Extracellular RNA Communication Consortium. J. Extracell. Vesicles 4, 27493 (2015).

    Article  Google Scholar 

  31. Hooten, N. N. et al. Age-related changes in microRNA levels in serum. Aging 5, 725–740 (2013).

    Article  Google Scholar 

  32. Wu, X. et al. De novo sequencing of circulating miRNAs identifies novel markers predicting clinical outcome of locally advanced breast cancer. J. Transl. Med. 10, 42 (2012).

    Article  CAS  Google Scholar 

  33. Roth, C. et al. Circulating microRNAs as blood-based markers for patients with primary and metastatic breast cancer. Breast Cancer Res. 12, R90 (2010).

    Article  CAS  Google Scholar 

  34. Huo, D., Clayton, W. M., Yoshimatsu, T. F., Chen, J. & Olopade, O. I. Identification of a circulating microRNA signature to distinguish recurrence in breast cancer patients. Oncotarget 7, 55231–55248 (2016).

    PubMed  PubMed Central  Google Scholar 

  35. Cuk, K. et al. Plasma microRNA panel for minimally invasive detection of breast cancer. PLoS ONE 8, e76729 (2013).

    Article  CAS  Google Scholar 

  36. Kodahl, A. R. et al. Novel circulating microRNA signature as a potential non-invasive multi-marker test in ER-positive early-stage breast cancer: a case control study. Mol. Oncol. 8, 874–883 (2014).

    Article  CAS  Google Scholar 

  37. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Meth. 9, 357–359 (2012).

    Article  CAS  Google Scholar 

  38. Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    Article  CAS  Google Scholar 

  39. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Article  Google Scholar 

  40. DeRose, Y. S. et al. Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes. Nat. Med. 17, 1514–1520 (2011).

    Article  CAS  Google Scholar 

  41. Fabregat, A. et al. The reactome pathway knowledgebase. Nucleic Acids Res. 46, D649–D655 (2018).

    Article  CAS  Google Scholar 

  42. Rehmsmeier, M., Steffen, P., Hochsmann, M. & Giegerich, R. Fast and effective prediction of microRNA/target duplexes. RNA 10, 1507–1517 (2004).

    Article  CAS  Google Scholar 

  43. Moore, M. J. et al. Mapping Argonaute and conventional RNA-binding protein interactions with RNA at single-nucleotide resolution using HITS-CLIP and CIMS analysis. Nat. Protoc. 9, 263–293 (2014).

    Article  CAS  Google Scholar 

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Acknowledgements

We thank D. Ruggero, D. Erle, F. Feng, S. Tavazoie and S. Tavazoie for reading earlier versions of this manuscript; D. Erle and P. Godoy for providing early access to their serum smRNA profiles; B. Hann and the Preclinical Therapeutics core as well as the Laboratory Animal Resource Center (LARC); S. Kilinc for her assistance with extracellular vesicle size analysis; F. Fattahi for helpful discussions; and J. Massagué for providing cell lines. We are also grateful for the genomic data contributed by the TCGA Research Network, including donors and researchers. We acknowledge the UCSF Center for Advanced Technology (CAT) for high-throughput sequencing and other genomic analyses; and support from our colleagues at the Breast Oncology Program (Helen Diller Family Comprehensive Cancer Center). This work was supported by the NIH (R01GM123977 and R00CA194077), Friends for an Earlier Breast Cancer Test, the American Cancer Society (130920-RSG-17-114-01-RMC) and the Goldberg-Benioff Fund in Translational Research. S.Z. was supported through the HHMI Medical Research Fellowship. J.X.Y. is an NSF GRFP fellow. A.G. was supported by the CDMRP Breast Cancer Research Program W81XWH-12-1-0272 and W81XWH-16-1-0603.

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Contributions

H.G. conceived and designed the study. L.F. and S.Z. performed RNA isolations and prepared smRNA-seq libraries. J.X.Y. performed FACS analysis. S.Z., B.C. and H.G. performed mouse experiments. H.G. performed computational analyses. A.G. and A.Y.Z. contributed data from PDX models. L.F., S.Z. and H.G. wrote the manuscript. H.G. supervised the project.

Corresponding author

Correspondence to Hani Goodarzi.

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Fish, L., Zhang, S., Yu, J.X. et al. Cancer cells exploit an orphan RNA to drive metastatic progression. Nat Med 24, 1743–1751 (2018). https://doi.org/10.1038/s41591-018-0230-4

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