Analysis of the translatome in solid tumors using polyribosome profiling/RNA-Seq

Main Article Content

Pauline Adjibade
Valerie Grenier St-Sauveur
Arnaud Droit
Edouard W. Khandjian
Paul Toren
Rachid Mazroui

Keywords

polyribosome profiling, RNA-seq, xenografts, translatome, prostate tumors

Abstract

Gene expression involves multiple steps from the transcription of a mRNA in the nucleus to the production of the encoded protein in the cytoplasm. This final step occurs through a highly regulated process of mRNA translation on ribosomes that is required to maintain cell homeostasis. Alterations in the control of mRNA translation may lead to cell transformation, a hallmark of cancer development. Indeed, recent advances indicated that increased translation of mRNAs encoding tumor-promoting proteins may be a key mechanism of tumor resistance in several cancers. Moreover, it was found that proteins whose encoding mRNAs are translated at higher efficiencies may be effective biomarkers. Evaluation of global changes in translation efficiency in human tumors has thus the potential of better understanding what can be used as biomarkers and therapeutic targets. Investigating changes in translation efficiency in human cancer cells has been made possible through the development and the use of the polyribosome profiling combined with DNA microarray or deep RNA sequencing. While helpful, the use of cancer cell lines has many limitations and it is essential to define translational changes in human tumor samples in order to properly prioritize genes implicated in cancer phenotype. We present an optimized polyribosome RNA-Seq protocol suitable for quantitative analysis of mRNA translation that occurs in human tumor samples and murine xenografts. Applying this innovative approach to human tumors, which requires a complementary bioinformatics analysis, unlocks the potential to identify key mRNAs which are preferentially translated in tumor tissue compared to benign tissue as well as translational changes which occur following treatment. These technical advances will be of interest to those researching all solid tumors, opening possibilities for understanding what may be therapeutic Achilles heels’ or relevant biomarkers.

 

 

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...
Abstract 30 | HTML Downloads 309 PDF Downloads 165

References

1. Adjibade P, Mazroui R. Control of mRNA turnover: implication of cytoplasmic RNA granules. Semin Cell Dev Biol. 2014 Jun 16;34:15–23.
2. Keene JD. Minireview: global regulation and dynamics of ribonucleic Acid. Endocrinology. 2010 Apr;151(4):1391–7.
3. Keene JD, Lager PJ. Post-transcriptional operons and regulons co-ordinating gene expression. Chromosome Res. 2005;13(3):327–37.
4. Kuersten S, Radek A, Vogel C, Penalva LOF. Translation regulation gets its “omics” moment. Wiley Interdiscip Rev RNA. 2013;4(6):617–30.
5. Piccirillo C a, Bjur E, Topisirovic I, Sonenberg N, Larsson O. Translational control of immune responses: from transcripts to translatomes. Nat Immunol. 2014;15(6):503–11.
6. Gao B, Roux PP. Translational control by oncogenic signaling pathways. Biochim Biophys Acta - Gene Regul Mech. 2015;1849(7):753–65.
7. Koromilas AE. Roles of the translation initiation factor eIF2alpha serine 51 phosphorylation in cancer formation and treatment. Biochim Biophys Acta - Gene Regul Mech. 2014;1849(7):871–80.
8. Koromilas AE, Mounir Z. Control of oncogenesis by eIF2alpha phosphorylation: implications in PTEN and PI3K-Akt signaling and tumor treatment. Futur Oncol. 2013;9(7):1005–15.
9. Wengrod JC, Gardner LB. Cellular adaptation to nutrient deprivation: crosstalk between the mTORC1 and eIF2alpha signaling pathways and implications for autophagy. 2015;14(16):2571–7.
10. Hinnebusch AG, Ivanov IP, Sonenberg N. Translational control by 5 ′ -untranslated regions of eukaryotic mRNAs. Science (80- ). 2016;352(6292):1413–6.
11. Walters B, Thompson SR. Cap-Independent Translational Control of Carcinogenesis. Front Oncol. 2016;6(May):128.
12. Yao P, Eswarappa SM, Fox PL. Translational Control Mechanisms in Angiogenesis and Vascular Biology. Curr Atheroscler Rep. 2015;17(5):30.
13. Luo D, Wang Z, Wu J, Jiang C, Wu J. The role of hypoxia inducible factor-1 in hepatocellular carcinoma. Biomed Res Int. 2014;2014:409272.
14. Blagosklonny M. Antiangiogenic therapy and tumor progression. Cancer Cell. 2004;5(1):13–7.
15. Cosse J-P, Michiels C. Tumour Hypoxia Affects the Responsiveness of Cancer Cells to Chemotherapy and Promotes Cancer Progression. Anticancer Agents Med Chem. 2008;8(7):790–7.
16. Baird T, Wek R. Eukaryotic initiation factor 2 phosphorylation and translational control in metabolism. Adv Nutr. 2012;3(3):307–21.
17. Donnelly N, Gorman AM, Gupta S, Samali A. The eIF2alpha kinases: Their structures and functions. Cell Mol Life Sci. 2013;70(19):3493–511.
18. Zheng Q, Ye J, Cao J. Translational regulator eIF2α in tumor. Tumor Biol. 2014;35(7):6255–64.
19. Masuda S, Izpisua Belmonte JC. A recipe for targeted therapy in prostate cancer. Nat Rev Urol. 2014;11(7):419.
20. Adjibade P, St-Sauveur VG, Huberdeau MQ, Fournier M, Savard A, Coudert L, et al. Sorafenib, a multikinase inhibitor, induces formation of stress granules in hepatocarcinoma cells. Oncotarget. 2015;6(41):43927–43.
21. Coudert L, Adjibade P, Mazroui R. Analysis of Translation Initiation During Stress Conditions by Polysome Profiling. J Vis Exp. 2014;(87).
22. Fournier M-J, Coudert L, Mellaoui S, Adjibade P, Gareau C, Côté M-F, et al. Inactivation of the mTORC1-eIF4E Pathway alters Stress Granules Formation. Mol Cell Biol. 2013 Apr 1;33(11):2285–301.
23. Mazroui R, Huot M-E, Tremblay S, Boilard N, Labelle Y, Khandjian EW. Fragile X Mental Retardation protein determinants required for its association with polyribosomal mRNPs. Hum Mol Genet. 2003 Dec 1;12(23):3087–96.
24. Mazroui R, Huot M-E, Tremblay S, Filion C, Labelle Y, Khandjian EW. Trapping of messenger RNA by Fragile X Mental Retardation protein into cytoplasmic granules induces translation repression. Hum Mol Genet. 2002;11(24):3007–17.
25. Arava Y. Isolation of Polysomal RNA for Microarray Analysis. Methods Mol Biol. 2003;224:79–87.
26. Sampath P, Pritchard DK, Pabon L, Reinecke H, Schwartz SM, Morris DR, et al. A Hierarchical Network Controls Protein Translation during Murine Embryonic Stem Cell Self-Renewal and Differentiation. Cell Stem Cell. 2008;2(5):448–60.
27. Johannes G, Carter MS, Eisen MB, Brown PO, Sarnow P. Identification of eukaryotic mRNAs that are translated at reduced cap binding complex eIF4F concentrations using a cDNA microarray. Proc Natl Acad Sci U S A. 1999 Nov 9;96(23):13118–23.
28. Larsson O, Morita M, Topisirovic I, Alain T, Blouin M-J, Pollak M, et al. Distinct perturbation of the translatome by the antidiabetic drug metformin. Proc Natl Acad Sci U S A. 2012;109(23):8977–82.
29. Melamed D, Arava Y. Genome-wide analysis of mRNA polysomal profiles with spotted DNA microarrays. Methods Enzymol. 2007;431:177–201.
30. Karginov F V., Hannon GJ. Remodeling of Ago2-mRNA interactions upon cellular stress reflects miRNA complementarity and correlates with altered translation rates. Genes Dev. 2013;27(14):1624–32.
31. Floor SN, Doudna JA. Tunable protein synthesis by transcript isoforms in human cells. Elife. 2016;5:e10921.
32. Spangenberg L, Shigunov P, Abud APR, Cofré AR, Stimamiglio MA, Kuligovski C, et al. Polysome profiling shows extensive posttranscriptional regulation during human adipocyte stem cell differentiation into adipocytes. Stem Cell Res. 2013;11(2):902–12.
33. Zych J, Spangenberg L, Stimamiglio M a, Abud APR, Shigunov P, Marchini FK, et al. Polysome profiling shows the identity of human adipose-derived stromal/stem cells in detail and clearly distinguishes them from dermal fibroblasts. Stem Cells Dev. 2014;23(22):2791–802.
34. Zhang X, Rosen BD, Tang H, Krishnakumar V, Town CD. Polyribosomal RNA-seq reveals the decreased complexity and diversity of the arabidopsis translatome. PLoS One. 2015;10(2):e0117699.
35. Kumaraswamy S, Chinnaiyan P, Shankavaram UT, Lü X, Camphausen K, Tofilon PJ. Radiation-induced gene translation profiles reveal tumor type and cancer-specific components. Cancer Res. 2008 May 15;68(10):3819–26.
36. Wahba A, Rath BH, Bisht K, Camphausen K, Tofilon PJ. Polysome profiling links translational control to the radioresponse of glioblastoma stem-like cells. Cancer Res. 2016;76(10):3078–87.
37. Lai M-C, Chang C-M, Sun HS. Hypoxia Induces Autophagy through Translational Up-Regulation of Lysosomal Proteins in Human Colon Cancer Cells. PLoS One. 2016;11(4):e0153627.
38. Van Den Beucken T, Magagnin MG, Jutten B, Seigneuric R, Lambin P, Koritzinsky M, et al. Translational control is a major contributor to hypoxia induced gene expression. Radiother Oncol. 2011;99(3):379–84.
39. Hsieh AC, Liu Y, Edlind MP, Ingolia NT, Janes MR, Sher A, et al. The translational landscape of mTOR signalling steers cancer initiation and metastasis. Nature. 2012;485(7396):55–61.
40. Sheridan CM, Grogan TR, Nguyen HG, Galet C, Rettig MB, Hsieh AC, et al. YB-1 and MTA1 protein levels and not DNA or mRNA alterations predict for prostate cancer recurrence. Oncotarget. 2015;6(10):7470–80.
41. Xu Y, Chen SY, Ross KN, Balk SP. Androgens induce prostate cancer cell proliferation through mammalian target of rapamycin activation and post-transcriptional increases in cyclin D proteins. Cancer Res. 2006;66(15):7783–92.
42. Khandjian EW, Huot M-E, Tremblay S, Davidovic L, Mazroui R, Bardoni B. Biochemical evidence for the association of fragile X mental retardation protein with brain polyribosomal ribonucleoparticles. Proc Natl Acad Sci U S A. 2004 Sep 7;101(36):13357–62.
43. Foley E, O’Farrell PH. Functional dissection of an innate immune response by a genome-wide RNAi screen. PLoS Biol. 2004;2(8):e203.
44. Bray NL, Pimentel H, Melsted P, Pachter L. Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol. 2016;34(5):525–7.
45. Ingolia NT, Brar GA, Rouskin S, Mcgeachy AM, Weissman JS. Genome-wide annotation and quantitation of translation by ribosome profiling. Curr Protoc Mol Biol. 2013;Chapter 4:Unit–4.18.
46. Koch A, Gawron D, Steyaert S, Ndah E, Crappé J, De Keulenaer S, et al. A proteogenomics approach integrating proteomics and ribosome profiling increases the efficiency of protein identification and enables the discovery of alternative translation start sites. Proteomics. 2014;14(23–24):2688–98.
47. Wilson DN, Arenz S, Beckmann R. Translation regulation via nascent polypeptide-mediated ribosome stalling. Curr Opin Struct Biol. 2016;37:123–33.
48. Aviner R, Geiger T, Elroy-Stein O. Novel proteomic approach (PUNCH-P) reveals cell cycle-specific fluctuations in mRNA translation. Genes Dev. 2013;27(16):1834–44.
49. Aviner R, Geiger T, Elroy-Stein O. PUNCH-P for global translatome profiling. Translation. 2013;1(2):e27516.
50. Aviner R, Geiger T, Elroy-stein O. Genome-wide identification and quantification of protein synthesis in cultured cells and whole tissues by puromycin-associated nascent chain proteomics ( PUNCH-P ). Nat Protoc. 2014;9(4):751–60.
51. Gene T, Consortium O. The Gene ontology project in 2008. Nucleic Acids Res. 2008;36(Database issue):D440-444.
52. Schwanhäusser B, Busse D, Li N, Dittmar G, Schuchhardt J, Wolf J, et al. Global quantification of mammalian gene expression control. Nature. 2011;473(7347):337–42.