Senescence-associated ribosome biogenesis defects contributes to cell cycle arrest through the Rb pathway

Abstract

Cellular senescence is a tumour suppressor programme characterized by a stable cell cycle arrest. Here we report that cellular senescence triggered by a variety of stimuli leads to diminished ribosome biogenesis and the accumulation of both rRNA precursors and ribosomal proteins. These defects were associated with reduced expression of several ribosome biogenesis factors, the knockdown of which was also sufficient to induce senescence. Genetic analysis revealed that Rb but not p53 was required for the senescence response to altered ribosome biogenesis. Mechanistically, the ribosomal protein S14 (RPS14 or uS11) accumulates in the soluble non-ribosomal fraction of senescent cells, where it binds and inhibits CDK4 (cyclin-dependent kinase 4). Overexpression of RPS14 is sufficient to inhibit Rb phosphorylation, inducing cell cycle arrest and senescence. Here we describe a mechanism for maintaining the senescent cell cycle arrest that may be relevant for cancer therapy, as well as biomarkers to identify senescent cells.

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Fig. 1: Senescence involves diminished ribosome biogenesis.
Fig. 2: Accumulation of RPL29 as a senescence biomarker.
Fig. 3: Nuclear RPL29, a biomarker of decreased ribosome biogenesis and senescent cells in vivo.
Fig. 4: Reduction of ribosome biogenesis factors RSL1D1, nucleostemin, EBP2 or DDX21 triggers senescence.
Fig. 5: E7 and CDK4, but not E6, bypass RSL1D1 knockdown-induced senescence.
Fig. 6: RPS14 regulates the retinoblastoma pathway and senescence.
Fig. 7: RPS14 regulates senescence by inhibiting CDK4.
Fig. 8: Tumour suppression by the RPS14-mediated checkpoint.

References

  1. 1.

    Deschenes-Simard, X., Lessard, F., Gaumont-Leclerc, M. F., Bardeesy, N. & Ferbeyre, G. Cellular senescence and protein degradation: breaking down cancer. Cell Cycle 13, 1840–1858 (2014).

  2. 2.

    Michaloglou, C. et al. BRAFE600-associated senescence-like cell cycle arrest of human naevi. Nature 436, 720–724 (2005).

  3. 3.

    Vernier, M. et al. Regulation of E2Fs and senescence by PML nuclear bodies. Genes Dev. 25, 41–50 (2011).

  4. 4.

    Kang, T. W. et al. Senescence surveillance of pre-malignant hepatocytes limits liver cancer development. Nature 479, 547–551 (2011).

  5. 5.

    Xue, W. et al. Senescence and tumour clearance is triggered by p53 restoration in murine liver carcinomas. Nature 445, 656–660 (2007).

  6. 6.

    Chen, Z. et al. Crucial role of p53-dependent cellular senescence in suppression of Pten-deficient tumorigenesis. Nature 436, 725–730 (2005).

  7. 7.

    Guerra, C. et al. Pancreatitis-induced inflammation contributes to pancreatic cancer by inhibiting oncogene-induced senescence. Cancer Cell 19, 728–739 (2011).

  8. 8.

    Stumpf, C. R. & Ruggero, D. The cancerous translation apparatus. Curr. Opin. Genet. Dev. 21, 474–483 (2011).

  9. 9.

    Bhat, M. et al. Targeting the translation machinery in cancer. Nat. Rev. Drug Discov. 14, 261–278 (2015).

  10. 10.

    Nishimura, K. et al. Perturbation of ribosome biogenesis drives cells into senescence through 5S RNP-mediated p53 activation. Cell Rep. 10, 1310–1323 (2015).

  11. 11.

    Drygin, D. et al. Targeting RNA polymerase I with an oral small molecule CX-5461 inhibits ribosomal RNA synthesis and solid tumor growth. Cancer Res. 71, 1418–1430 (2011).

  12. 12.

    Bywater, M. J. et al. Inhibition of RNA polymerase I as a therapeutic strategy to promote cancer-specific activation of p53. Cancer Cell 22, 51–65 (2012).

  13. 13.

    Devlin, J. R. et al. Combination therapy targeting ribosome biogenesis and mRNA translation synergistically extends survival in MYC-driven lymphoma. Cancer Discov. 6, 59–70 (2016).

  14. 14.

    Serrano, M., Lin, A. W., McCurrach, M. E., Beach, D. & Lowe, S. W. Oncogenic ras provokes premature cell senescence associated with accumulation of p53 and p16INK4a. Cell 88, 593–602 (1997).

  15. 15.

    Ohtani, N. et al. Opposing effects of Ets and Id proteins on p16INK4a expression during cellular senescence. Nature 409, 1067–1070 (2001).

  16. 16.

    Takahashi, A. et al. Mitogenic signalling and the p16INK4a-Rb pathway cooperate to enforce irreversible cellular senescence. Nat. Cell Biol. 8, 1291–1297 (2006).

  17. 17.

    Chicas, A. et al. Dissecting the unique role of the retinoblastoma tumor suppressor during cellular senescence. Cancer Cell 17, 376–387 (2010).

  18. 18.

    Zou, X. et al. Cdk4 disruption renders primary mouse cells resistant to oncogenic transformation, leading to Arf/p53-independent senescence. Genes Dev. 16, 2923–2934 (2002).

  19. 19.

    Acevedo, M. et al. A CDK4/6-dependent epigenetic mechanism protects cancer cells from PML-induced senescence. Cancer Res. 76, 3252–3264 (2016).

  20. 20.

    Goel, S. et al. Overcoming therapeutic resistance in HER2-positive breast cancers with CDK4/6 inhibitors. Cancer Cell 29, 255–269 (2016).

  21. 21.

    Langhendries, J. L., Nicolas, E., Doumont, G., Goldman, S. & Lafontaine, D. L. The human box C/D snoRNAs U3 and U8 are required for pre-rRNA processing and tumorigenesis. Oncotarget 7, 59519–59534 (2016).

  22. 22.

    Wild, T. et al. A protein inventory of human ribosome biogenesis reveals an essential function of exportin 5 in 60S subunit export. PLoS Biol. 8, e1000522 (2010).

  23. 23.

    Deschenes-Simard, X. et al. Tumor suppressor activity of the ERK/MAPK pathway by promoting selective protein degradation. Genes Dev. 27, 900–915 (2013).

  24. 24.

    Meng, L., Yasumoto, H. & Tsai, R. Y. Multiple controls regulate nucleostemin partitioning between nucleolus and nucleoplasm. J. Cell Sci. 119, 5124–5136 (2006).

  25. 25.

    Romanova, L. et al. Critical role of nucleostemin in pre-rRNA processing. J. Biol. Chem. 284, 4968–4977 (2009).

  26. 26.

    Ma, L. et al. CSIG inhibits PTEN translation in replicative senescence. Mol. Cell Biol. 28, 6290–6301 (2008).

  27. 27.

    Mallette, F. A., Goumard, S., Gaumont-Leclerc, M. F., Moiseeva, O. & Ferbeyre, G. Human fibroblasts require the Rb family of tumor suppressors, but notp53, for PML-induced senescence. Oncogene 23, 91–99 (2004).

  28. 28.

    Helt, A. M. & Galloway, D. A. Destabilization of the retinoblastoma tumor suppressor by human papillomavirus type 16 E7 is not sufficient to overcome cell cycle arrest in human keratinocytes. J. Virol. 75, 6737–6747 (2001).

  29. 29.

    Malumbres, M. & Barbacid, M. Cell cycle, CDKs and cancer: a changing paradigm. Nat. Rev. Cancer 9, 153–166 (2009).

  30. 30.

    Donati, G., Peddigari, S., Mercer, C. A. & Thomas, G. 5S ribosomal RNA is an essential component of a nascent ribosomal precursor complex that regulates the Hdm2-p53 checkpoint. Cell Rep. 4, 87–98 (2013).

  31. 31.

    Sloan, K. E., Bohnsack, M. T. & Watkins, N. J. The 5S RNP couples p53 homeostasis to ribosome biogenesis and nucleolar stress. Cell Rep. 5, 237–247 (2013).

  32. 32.

    Rabl, J., Leibundgut, M., Ataide, S. F., Haag, A. & Ban, N. Crystal structure of the eukaryotic 40S ribosomal subunit in complex with initiation factor 1. Science 331, 730–736 (2011).

  33. 33.

    Rodier, F. et al. Persistent DNA damage signalling triggers senescence-associated inflammatory cytokine secretion. Nat. Cell Biol. 11, 973–979 (2009).

  34. 34.

    Coppe, J. P. et al. Tumor suppressor and aging biomarkerp16(INK4a) induces cellular senescence without the associated inflammatory secretory phenotype. J. Biol. Chem. 286, 36396–36403 (2011).

  35. 35.

    Ebert, B. L. et al. Identification of RPS14 as a 5q− syndrome gene by RNA interference screen. Nature 451, 335–339 (2008).

  36. 36.

    Dorr, J. R. et al. Synthetic lethal metabolic targeting of cellular senescence in cancer therapy. Nature 501, 421–425 (2013).

  37. 37.

    Coppe, J. P. et al. Senescence-associated secretory phenotypes reveal cell-nonautonomous functions of oncogenic RAS and the p53 tumor suppressor. PLoS Biol. 6, 2853–2868 (2008).

  38. 38.

    Horn, H. F. & Vousden, K. H. Cooperation between the ribosomal proteins L5 and L11 in the p53 pathway. Oncogene 27, 5774–5784 (2008).

  39. 39.

    Marechal, V., Elenbaas, B., Piette, J., Nicolas, J. C. & Levine, A. J. The ribosomal L5 protein is associated with mdm-2 and mdm-2-p53 complexes. Mol. Cell Biol. 14, 7414–7420 (1994).

  40. 40.

    Zhou, X., Hao, Q., Liao, J., Zhang, Q. & Lu, H. Ribosomal protein S14 unties the MDM2-p53 loop upon ribosomal stress. Oncogene 32, 388–396 (2013).

  41. 41.

    Lessard, F. et al. The ARF tumor suppressor controls ribosome biogenesis by regulating the RNA polymerase I transcription factor TTF-I. Mol. Cell 38, 539–550 (2010).

  42. 42.

    Ingolia, N. T., Brar, G. A., Rouskin, S., McGeachy, A. M. & Weissman, J. S. The ribosome profiling strategy for monitoring translation in vivo by deep sequencing of ribosome-protected mRNA fragments. Nat. Protoc. 7, 1534–1550 (2012).

  43. 43.

    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).

  44. 44.

    Al-Shahrour, F., Diaz-Uriarte, R. & Dopazo, J. FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes. Bioinformatics 20, 578–580 (2004).

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Acknowledgements

We thank D. P. Baker (Biogen Idec), D. A. Galloway (Fred Hutchinson Cancer Center), N. Bardeesy (MGH), S. Lowe (MSK), A. Koff (MSK), T. Moss (U. Laval), I. Topisirovic, P. Chartrand (U. Montréal), V. Blank (McGill University) and B. Weinberg (MIT) for comments and/or reagents. We thank É. Bonneil, F. McManus and the IRIC Proteomics Core Facility for proteomic analysis. We thank J. Hinsinger, M. Birlea and the IRIC Histology Core Facility for immunohistochemistry. F.L. is supported by FRQS (Fonds de Recherche du Québec-Santé) and the CRS (Cancer Research Society). G.F. is supported by FRQS. Work was funded by grants from the CIHR (Canadian Institute of Health and Research: CIHR MOP11151) to G.F., (Canadian Institutes of Health Research: CIHR MOP106628) to M.O. and the CCSRI (Canadian Cancer Society Research Institute: 704223) to G.F.

Author information

F.L. performed most of the cell culture experiments, IHC experiments, immunoprecipitation, cellular fractionation, kinase assays, pulldown, western blots, pulse labelling, SA-β-gal, growth curves, data analysis and northern blotting in collaboration. S.I. performed all the immunofluorescences, bioinformatics analysis of data from LC-MS/MS, helped in quantification of SA-β-gal, IHC and FISH. He also confirmed RPS14 senescence and the bypass by shRB. C.T. performed the northern blotting. G.H. made pBABE-3×FLAG-CDK4(WT) and pBABE-3×FLAG-CDK4(K35M), performed many qPCR and performed cell culture experiments leading to Fig. 5a, Fig. 6a,i–m, Supplementary Figs. 4, 6g–i and 8a–h. E.S.-G. performed the experiment leading to Figs. 2d and 7c,d. L.M. constructed pBabe-RPS14-Myc, confirmed the qPCR in Supplementary Figs. 5c–,h,j–m and 6c–e. L.M. also performed cell culture experiments confirming Fig. 6a–h and Supplementary Fig. 8a–h. N.D.T performed ribosomes purification experiments. S.L.-P. participated in CX-5461 experiments. M.M. performed the FISH experiments leading to Fig. 1g–h and Supplementary Fig. 2. M.M. was the first to show nucleolar accumulation of RPL29. X.D.-S. did the bioinformatics analysis presented in Supplementary Fig. 3a. O.M. was the first to do the experiment on Supplementary Fig. 4f. M.-C.R. participated in qPCR optimization. C.E.Z. and D.Z. contributed by conceptual and technical input with FISH experiments. M.O. contributed by conceptual and technical input with northern blotting experiments. M.B. and B.L.C. performed the first experiment with CDK1/cyclin B1. B.L.C. also contributed by conceptual and technical input with IHC and helped with statistical analysis and IHC analysis. V.B. designed and performed many qPCR in Supplementary Fig. 1b–d and Supplementary Fig. 3b–d. F.L., V.B., D.Z., L.B.-G., M.O. and G.F. participated in experimental design. F.L. and G.F. wrote the manuscript.

Correspondence to Gerardo Ferbeyre.

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Supplementary Figure 1 Ribosome biogenesis defects in senescent cells induced by oncogenic ras, short telomeres or the tumour suppressor PML.

(a) Autoradiography for de novo rRNA synthesis after a three hours pulse labelling with [3H]-uridine. Total RNA was extracted after the pulse from IMR90 cells expressing H-RASV12 (RAS) or an empty control vector (Vect) at day 2, 4, 6 and 8 post-infection and compared to total 28S rRNA detected with ethidium bromide (EtBr) under UV light, (1 out of 3 independent experiments with similar results). (b-d) QPCR for senescence biomarkers. Total RNA was extracted from (b-c) IMR90 cells at day 20 post-infection expressing (b) H-RASV12 (RAS), (c) PML-IV (PML) or an empty control vector (Vect) and from (d) uninfected young (passage 24) and old (passage 38) IMR90 cells. RNA was reverse transcribed and analysed by qPCR for the indicated genes. Data were normalized over TBP and HMBS and presented as mean relative to vector-infected cells or young cells, (1 out of 3 independent experiments with similar results).

Supplementary Figure 2 Nucleolar accumulation of ribosomal RNA precursors in senescent cells.

(a-c) Fluorescence in situ hybridization (FISH) with an antisense or sense probe overlapping the 5.8S(5′) rRNA processing site 2 as shown in Fig. 1c and counterstained with DAPI of (a-b) IMR90 cells at day 20 post-infection expressing (a) H-RASV12 (RAS), (b) PML-IV (PML) or an empty control vector and of (c) uninfected young (passage 25), old (passage 43) cells or confluent arrested for 4 days or arrested by serum starvation for 6 days (Starved), (1 out of 2 independent experiments with similar results). (d-e) Quantification of (d) nucleolar mean area (μm2) relative to vector infected cells and (e) nucleolar fluorescence mean intensity relative to vector-infected cells after FISH for cells marked as in (a-c). Number of nucleoli analysed per condition: Vector (Vect) (n = 174), RAS (n = 100), PML (n = 117), Old (n = 93) and Confluent (n = 166). Error bars indicate SEM. * = p<0.05, using Mann-Whitney U test.

Supplementary Figure 3 Depletion of nucleolar proteins leads to senescence in IMR90 cells.

(a) Proteomic analysis of RAS-senescent IMR90 cells treated with MG132 (10 μM, 18 hours) or vehicle. 1018 proteins were enriched in MG132-treated cells compared to control. Proteins associated to protein synthesis machinery and the indicated subcategories were retrieved using the Babelomics 4.3 platform. (b-d) QPCR for the indicated genes performed with total RNA extracted from (b-c) cells at day 20 post-infection expressing (b) H-RASV12 (RAS), (c) PML-IV (PML) or an empty control vector (Vect) and from (d) uninfected young (passage 24) and old (passage 38) IMR90 cells. Data were normalized over TBP and HMBS and presented as means relative to vector-infected cells or young cells, (n = 1). (e-g) QPCR for the indicated genes performed with total RNA extracted from cells expressing shNTC (non-targeting shRNA); shR-A or -B (shRNAs against RSL1D1); shN-A or -B, (shRNAs against nucleostemin); shD-A or -B, (shRNAs against DDX21); shE-A or -B, (shRNAs against EBP2) at day 14 post-infection. Data were normalized over TBP and HMBS and presented as mean relative to shNTC infected cells, (1 out of 2 independent experiments with similar results). (h) SA-β-gal of cells expressing the indicated shRNA expression vectors and fixed at day 14 post-infection. Data were quantified from >5-independent cell counts up to a total of at least 150 cells and are presented as the mean percentage of positive cells, (1 out of 3 independent experiments with similar results). (i-j) QPCR for p21 and p16INK4a performed with total RNA extracted from cells as in (e-g). Data were normalized over TBP and HMBS and presented as means relative to shNTC infected cells, (1 out of 2 independent experiments with similar results). (k) Indirect immunofluorescence with specific anti-fibrillarin (FBL) and anti-RPL29 antibodies followed by confocal microscopy of cells as in (h) and fixed at day 7 post-infection. Data were quantified from 100 cell counts in triplicate and are presented as the mean percentage of positives cells for nucleolar localization of RPL29, (1 out of 3 independent experiments with similar results).

Supplementary Figure 4 RSL1D1 knockdown-induced senescence requires the RB pathway.

(a) SA-β-gal of IMR90 cells expressing the indicated shRNA expression vectors in combination with the expression of E6 alone, E7 alone, E6/E7 together or an empty control vector (Vect) at day 20 post-infection. Data were quantified from >5-independent cell counts up to a total of at least 150 cells and are presented as the mean percentage of positive cells, (1 out of 2 independent experiments with similar results). shNTC: non-targeting shRNA; shR-A or -B: shRNAs against RSL1D1. (b-e) QPCR for the indicated genes performed with total RNA extracted from cells as in (a) at day 20 post-infection. Data were normalized over TBP and HMBS and presented as mean relative to vector/shNTC infected cells, (n = 1). (f) Growth curves of IMR90 cells expressing the indicated shRNA expression vectors in combination with the expression of E7(Δ6-10), E7(Δ21-24), E7(Δ79-83) or an empty control vector (Vect). Data are presented as mean normalized to day 0 of each condition. (1 out of 2 independent experiments with similar results). The percent of SA-β-gal positive cells for each condition at day 20 post-infection is indicated under each growth curve. Data were quantified from >5-independent cell counts up to a total of at least 150 cells and are presented as the mean percentage of positive cells, (1 out of 2 independent experiments with similar results). shNTC: non-targeting shRNA; shR-A or -B: shRNAs against RSL1D1. (g-j) QPCR for the indicated genes performed on reverse transcribed total RNA extracted from cells as in (f) at day 20 post-infection. Data were normalized over TBP and HMBS and presented as mean relative to vector/shNTC infected cells, (n = 1).

Supplementary Figure 5 CDK4 and CDK6 bypass RSL1D1 knockdown-induced senescence.

(a) SA-β-gal of IMR90 cells expressing the indicated shRNA expression vectors in combination with the expression of CDK4 (1 out of 3 independent experiments with similar results), CDK6 (n = 1) or a control vector (Vect) at day 20 post-infection. Data were quantified from >5-independent cell counts up to a total of at least 150 cells and are presented as the mean percentage of positive cells. shNTC: non-targeting shRNA; shR-A or -B: shRNAs against RSL1D1. (b) Growth curves of IMR90 cells as in (a). Data are presented as means normalized to day 0 of each condition. (1 out of 3 independent experiments with similar results for CDK4) and (1 out of 2 independent experiments with similar results for CDK6). (c-h) QPCR for the indicated genes performed on reverse transcribed total RNA extracted from cells as in (a) at day 20 post-infection. Data were normalized over TBP and HMBS and presented as means relative to vector/shNTC infected cells, (1 out of 2 independent experiments with similar results). (i) SA-β-gal of IMR90 cells expressing the indicated shRNA expression vectors in combination with the expression of 3xFLAG-CDK4(WT), 3xFLAG-CDK4(K35M) or an empty control vector (Vect) at day 20 post-infection. Data were quantified from >5-independent cell counts up to a total of at least 150 cells and are presented as the mean percentage of positive cells, (1 out of 2 independent experiments with similar results). shNTC: non-targeting shRNA; shR-A or -B: shRNAs against RSL1D1. (j-m) QPCR for the indicated genes performed on reverse transcribed total RNA extracted from cells as in (i). Data were normalized over TBP and HMBS and presented as mean relative to vector/shNTC infected cells, (1 out of 2 independent experiments with similar results).

Supplementary Figure 6 RSL1D1 knockdown-induced senescence is not affected by CDK4 inhibitors p16INK4a and p21.

(a-b) Growth curves of IMR90 cells expressing combinations of the indicated shRNAs. Data are presented as means normalized to day 0 of each condition. (1 out of 2 independent experiments with similar results). shNTC: non-targeting shRNA; shp16: shRNA against p16INK4a (CDKN2A); shp21: shRNA against p21 (CDKN1A); shR-A or -B: shRNAs against RSL1D1. (c-e) QPCR for the indicated genes performed on total RNA extracted from cells, as in (a-b), at day 20 post-infection. Data were normalized over TBP and HMBS and presented as means relative to shNTC/shNTC infected cells, (1 out of 2 independent experiments with similar results). (f) Immunoprecipitation with pre-immune serum or with RPS14 antibody in H1299 cells. Lysates and immunoprecipitates were immunoblotted for the indicated proteins (1 out of 3 independent experiments with similar results). (g) SA-β-gal of IMR90 cells expressing RPS14-Myc or an empty control vector (Vect) at day 12 post-infection. Data were quantified from >5-independent cell counts up to a total of at least 150 cells and are presented as the mean percentage of positive cells, (1 out of 3 independent experiments with similar results). (h) Immunoblots for the indicated proteins for cells as in (g) at day 7 post-infection, (1 out of 3 independent experiments with similar results). Western blot panels for Myc and tubulin are the same as in Fig. 6b. (i) QPCR for the indicated genes performed on total RNA extracted from cells as in (g) and at day 9 post-infection. Data are normalized over TBP and HMBS and presented as mean relative to vector infected cells, (1 out of 2 independent experiments with similar results). (j-k) Indirect immunofluorescence (IF) with specific anti-53BP1, anti-γH2A.X, anti-RPL29 and anti-PML antibodies as indicated and nuclear counterstaining with DAPI. Images represent IMR90 cells expressing RPS14-Myc, p16INK4a or an empty control vector at day 14 post-infection, (1 out of 3 independent experiments with similar results). (k) IF data were quantified from 100 cell counts in triplicate and are presented as the mean percentage of cells with positive nucleolar localization of RPL29. (l-n) IF foci data in cells as in (j-k) were quantified from 100 cell counts in triplicate and are presented as the mean. Quantification of the percentage of cells with 0-1, 2-5 or more than 5 foci of (l) 53BP1 and (m) γH2A.X per cell. (n) Quantification of the percentage of cells with 0-5, 6-10 or more than 10 foci of PML per cell. Unprocessed blots can be found in Supplementary Figure 9.

Supplementary Figure 7 Nuclear accumulation of RPS14 in senescence.

(a-c) Indirect immunofluorescence (IF) with specific anti-RPS14 antibody and nuclear counterstaining with DAPI. Images from (a) IMR90 cells expressing H-RASV12 (RAS) (1 out of 3 independent experiments with similar results), PML-IV (PML) (1 out of 2 independent experiments with similar results) or an empty control vector at day 12 post-infection, (b) young (passage 25) and old (passage 43) IMR90 cells (1 out of 2 independent experiments with similar results) and (c) IMR90 cells treated with DMSO (CTRL) or camptothecin in DMSO (final concentration in medium of 35 nM) for 3 days (1 out of 2 independent experiments with similar results). Data in RPS14 panel were quantified from 100 cell counts in triplicate and are presented as the mean percentage of cells with RPS14 nuclear staining. (d) Scale for intensity of staining by indirect IF with specific anti-RPS14 as in (a-c). (e-g) Hyperresolution structure illumination microscopy of immunofluorescence staining using a specific anti-RPS14 antibody and counterstaining with DAPI. (e) Comparison of IMR90 cells expressing H-RASV12 (RAS) or an empty control vector and fixed at day 12 post-infection. CTRL: 2 cells out of 15 showed nuclear staining; RAS: 5 cells out of 6 showed nuclear staining. (f) Comparison of IMR90 cells treated with DMSO (CTRL) or camptothecin in DMSO (final concentration in medium of 35 nM) for 3 days. DMSO: 2 cells out of 24 showed nuclear staining; Camptothecin: 4 cells out of 5 showed nuclear staining. (g) Comparison of young (passage 25) or old (passage 43) IMR90 cells. Young: 1 cell out of 10 showed nuclear staining; Old: 4 cells out of 4 showed nuclear staining.

Supplementary Figure 8 Cells do not tolerate a significant depletion of RPS14 but RPS14 mRNA levels are downregulated in different types of cancer and increased in nevi.

(a, c, e and g) Growth curves of (a) IMR90 cells, (c) U2OS cells, (e) PC3 cells or (g) H1299 cells expressing a control shRNA (shNTC) and two shRNA against RPS14 (shRPS14-A and -B). Data are presented as means normalized to day 0 of each condition. (1 out of 2 independent experiments with similar results). (b, d, f and h) Immunoblots for the indicated proteins at day 5 post-infection with a control shRNA (shNTC) and two shRNA against RPS14 (shRPS14-A and -B) in (b) IMR90 cells, (d) U2OS cells, (f) PC3 cells or (h) H1299 cells, (1 out of 2 independent experiments with similar results). (i-m) Studies showing the decrease of RPS14 transcript levels using the Oncomine database selected with the following settings: threshold P-value: 1E-4; fold change: 2; gene rank top 10%. Each box plot shows median RPS14 expression, boxes are upper and lower 25% percentiles, whiskers are upper and lower 10% percentiles, minima and maxima are shown by dots. (For precision see Oncomine database). (i) RPS14 expression in Finak Breast. Comparison of Breast (n = 6) and Invasive Breast Carcinoma (n = 53). (j) RPS14 expression in Haslinger Leukaemia. Comparison of B-Lymphocyte (n = 11) and Chronic Lymphocytic Leukaemia (n = 100). (k) RPS14 expression in Bhattacharjee Lung. Comparison of Lung (n = 17) and Small Cell Lung Carcinoma (n = 6). (l) RPS14 expression in Grasso Prostate. Comparison of Primary Site (n = 59) and Metastasis (n = 35). (m) RPS14 expression in Haqq Melanoma. Comparison of Normal tissue (n = 3), Non-Neoplastic Nevus (n = 9) and Melanoma (n = 25). (n) Summary of studies comparing levels of RPS14, CDK4 and RB1 (RB) transcripts in Skotheim Testis cancers, using the Oncomine database with the following settings: threshold P-value: 1E-4; fold change: 2; gene rank top 10%. Red colour indicated an increase in the tumour whereas blue colour indicated a decrease and n for each tumour type is indicated between parentheses. (For precision see Oncomine database). Unprocessed blots can be found in Supplementary Figure 9.

Supplementary Figure 9 Unprocessed blots.

Of note, some membranes were cut into pieces to incubate with different antibodies.

Supplementary information

Supplementary Information

Supplementary Figures 1–9 and Supplementary Table legends.

Reporting Summary

Supplementary Table 1

RSL1D1 interactome.

Supplementary Table 2

CDK4(K35M) interactome in RSL1D1 knockdown-induced senescence.

Supplementary Table 3

Sequence of shRNAs target sequences.

Supplementary Table 4

Sequence of qPCR and PCR cloning primers.

Supplementary Table 5

Statistics source data for qPCR, northern blots, growth curves and FISH.

Supplementary Table 6

Antibodies for immunoblots, IP, IF and IHC.

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Lessard, F., Igelmann, S., Trahan, C. et al. Senescence-associated ribosome biogenesis defects contributes to cell cycle arrest through the Rb pathway. Nat Cell Biol 20, 789–799 (2018). https://doi.org/10.1038/s41556-018-0127-y

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