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SETDB1-mediated methylation of Akt promotes its K63-linked ubiquitination and activation leading to tumorigenesis

Nature Cell Biology volume 21, pages 214–225 (2019)Cite this article

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Abstract

The serine/threonine kinase Akt plays a central role in cell proliferation, survival and metabolism, and its hyperactivation is linked to cancer progression. Here we report that Akt undergoes K64 methylation by SETDB1, which is crucial for cell membrane recruitment, phosphorylation and activation of Akt following growth factor stimulation. Furthermore, we reveal an adaptor function of histone demethylase JMJD2A, which is important for recognizing Akt K64 methylation and recruits E3 ligase TRAF6 and Skp2-SCF to the Akt complex, independently of its demethylase activity, thereby initiating K63-linked ubiquitination, cell membrane recruitment and activation of Akt. Notably, the cancer-associated Akt mutant E17K displays enhanced K64 methylation, leading to its hyper-phosphorylation and activation. SETDB1-mediated Akt K64 methylation is upregulated and correlated with Akt hyperactivation in non-small-cell lung carcinoma (NSCLC), promotes tumour development and predicts poor outcome. Collectively, these findings reveal complicated layers of Akt activation regulation coordinated by SETDB1-mediated Akt K64 methylation to drive tumorigenesis.

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Fig. 1: SETDB1 interacts with Akt and is required for Akt activation.
Fig. 2: SETDB1 triggers Akt K64 methylation leading to Akt phosphorylation.
Fig. 3: Akt K64 methylation is critical for Akt activation and membrane localization.
Fig. 4: SETDB1-mediated Akt K64 methylation promotes tumorigenesis, correlates with Akt activation and predicts poor survival of cancer patients.
Fig. 5: Akt K64 methylation is essential for Akt K63-linked ubiquitination and Akt-E3 ligase interaction.
Fig. 6: JMJD2A is important for recognizing K64-methylated Akt and facilities the Akt-E3 ligase interaction.
Fig. 7: JMJD2A non-demethylase function contributes to Akt ubiquitination and activation.

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Data availability

Mass spectrometry data have been deposited in ProteomeXchange with the primary accession code code PXD011966. The human lung adenocarcinoma data were derived from the TCGA Research Network: http://cancergenome.nih.gov/. The dataset derived from this resource that supports the findings of this study is available in http://www.cbioportal.org. The human cancer SETDB1 protein expression data were derived from the Human Protein Atlas Network and the supports the findings of this study is available in https://www.proteinatlas.org/ENSG00000143379-SETDB1/pathology. Source data for Figs. 4 and 7 and Supplementary Figs. 3 and 6 have been provided in Supplementary Table 4. All other data supporting the findings of this study are available from the corresponding author on reasonable request.

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Acknowledgements

We are grateful to the members of Lin’s lab for critical inputs and suggestions. We thank Z.-P. Liu, Y. Shinkai, F. J. Rauscher III, B. Vogelstein, D. Bohmann, M.C. Hung and R. Janknecht for providing mice, cell lines or plasmids. We thank E. Spooner for performing mass spectrometry assays. We acknowledge the support of Cellular Imaging & flow cytometry Shared of Resource, the Wake Forest Baptist Comprehensive Cancer Center, supported by the National Cancer Institute’s Cancer Center Support Grant (P30CA012197). This work is supported by start-ups from Wake Forest School of Medicine, NIH grants (R01CA182424 and R01CA193813) to H.K.L., NIH grants (RO1CA194094 and RO1CA197178) to H.L. and NIH grants (R01CA207098 and R01CA207109) to M.G.L.

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Author notes

  1. These authors contributed equally: Jie Long and Yuan Gao.

Authors and Affiliations

  1. Department of GI Cancer Research Institute, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China

    Guihua Wang, Li Sun, Jingqin Lan, Zhenlin Hou & Junbo Hu

  2. Department of Cancer Biology, Wake Forest Baptist Medical Center, Wake Forest University, Winston Salem, NC, USA

    Guihua Wang, Jie Long, Weina Zhang, Fei Han, Chuan Xu, Li Sun, Shun-Chin Yang, Zhen Cai, Guoxiang Jin, Che-Chia Hsu, Yu-Hui Wang & Hui-Kuan Lin

  3. Department of Pathology, School of Basic Medical Science, Guangzhou Medical University, Guangzhou, Guangdong, China

    Jie Long

  4. Department of Molecular and Cellular Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Yuan Gao, Tsai-Yu Chen & Min Gyu Lee

  5. University of Arkansas for Medical Sciences, College of Pharmacy, Department of Pharmaceutical Science, Little Rock, AR, USA

    Hongyu Li

  6. Graduate Institute of Basic Medical Science, China Medical University, Taichung, Taiwan

    Hui-Kuan Lin

  7. Department of Biotechnology, Asia University, Taichung, Taiwan

    Hui-Kuan Lin

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Contributions

G.W. and H.K.L. designed the research and analysed the data. G.W. carried out the major experiments. J.L. performed the immunohistological characterization. J.L., Y.G., W.Z., F.H., C.X., L.S., Z. H. and Z.C. assisted with the experiments. S.C.Y., J.L., G.J., C.C.H., Y.H.W., and J.H. assisted with experimental design, T.Y.C. and M.G.L. assisted with in vitro methylation assay, G.W. and W.Z. developed the work models. M.G.L. and H.L. provided scientific inputs. G.W. and H.K.L. wrote the manuscript.

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Correspondence to Hui-Kuan Lin.

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Integrated supplementary information

Supplementary Figure 1 SETDB1 interacts with Akt, induces Akt K64 methylation and is required for Akt activation.

(a) Mass spectrometry analysis shows Akt binding proteins, including SETDB1 and JMJD2A. The mass spectrometry was performed once. (b) Setdb1± and Setdb1-/- MEFs were serum-starved, treated with EGF for 5 mins, and WCE were collected for IB analysis. (c) HEK293 cells transfected with Vector (Vec), Flag-SETDB1 (WT) and Flag-SETDB1 H1224K (HK) along with HA-Akt were serum-starved for 1 day, treated with 50 ng/ml IGF-1 for various times, and WCE were collected for IP with HA, followed by IB analysis indicated proteins. (d) HEK293 cells transfected with HA-Akt were serum-starved for 1 day, treated with 50 ng/ml IGF-1 for various times, and Whole cell extracts (WCE) were collected for IP with HA, followed by IB analysis indicated proteins. Data in b-d represent results from 3 independent experiments. (e) We immunoprecipitated endogenous Akt and performed mass spectrometry analysis, which reveals Akt methylation sites in normal condition, including K64, K112, K183, K268 and K400. The mass spectrometry was performed once. (f) We immunoprecipitated endogenous Akt in shLuc or shSETDB1 HEK293 cells and performed the Time-of-flight mass spectrometry (TOFMS) analysis, which identified Akt methylation sites that are different between Shluc and ShSETDB1 cells. TOFMS was performed once. Unprocessed blots are shown in Supplementary Figure 8.

Supplementary Figure 2 Akt K64 methylation promotes Akt membrane translocation.

(a) Immunofluorescence (IF) assay showed the localization of indicated proteins in A549 cells treated with IGF-1 at 0 min or 10 mins. All IF representative data from 3–4 independent repeats. (b) HEK293 cells silenced with control (Shluc) or SETDB1 ShRNA (#1, #2) were serum-starved, treated with IGF-1 for 15 mins, and harvested for IF staining for indicated proteins. Scale bar represents 50 μm.All IF representative data from 3 independent repeats.

Supplementary Figure 3 SETDB1-mediated Akt k64 methylation regulates cancer development.

(a) Tumour weight of xenograft tumours derived from A549 cells silenced with control (Shluc) or SETDB1 ShRNA (#1 and #2), data shown represent mean ± s.d, n = 5 mice for each group, **** p < 0.0001, statistical significance was assessed using Student’s two-tailed t-test. (b) Tumour weight of xenograft tumours derived from A549 cells silenced with control (Shluc), SETDB1 ShRNA (#1) and SETDB1 ShRNA plus Myr-Akt overexpression, data shown represent mean ± s.d, n = 5 mice for each group, **** p < 0.0001, statistical significance was assessed using Student’s two-tailed t-test. (c) Soft agar transformation assay of 3T3 cells stable transfected with Vector (Vec), Akt1 (WT), Akt1 E17K (E17K) and Akt1 E17K/K64R (E17K/K64R). Crystal Violet staining before photograph. The average colony ( > 0,03 mm colony) number was quantitation (n = 3 independent experiments, Student’s two-tailed t-test, **** p < 0.0001). All Statistics source data are shown in Supplementary Table. 4.

Supplementary Figure 4 SETDB1 is overexpressed in cancers and correlates with overall survival (OS).

(a) cBioPortal databases examine SETDB1 gene amplification, mutation, deletion in multiple types of cancers. (b) Oncomine databases examine SETDB1 gene expression in multiple subtypes of lung cancers. (c) KM-Plot database reveals lung cancer patient overall OS with SETDB1 low or high expression. Affymetrix ID:214197-s-at. Total patients number is 1926 cases. (d) The overall survival of patients with higher and lower expressions of SETDB1 was marked in purple and blue, respectively. Overall survival in 429 Colorectal Adenocarcinoma Cancer patients (P = 2.13e-2), 541 Endometrial cancer patients (P = 2.24e-3), 501 Thyroid Cancer patients (P = 3.14e-2), 365 Liver Cancer patients (P = 8.88e-4), 877 Renal Cancer patients (P = 4.25e-4) and 102 Melanoma patients (P = 9.94e-3) was analysed, n means the sample number for each group. Log-rank P value for Kaplan-Meier plot showing results from analysis of correlation between mRNA expression level and patient survival. The P value obtained from log-rank test. The data-set that supports the findings of this study is available in http://www.cbioportal.org. The human cancer SETDB1 protein expression data were derived from the Human Protein Atlas Network and the supports the findings of this study is available in https://www.proteinatlas.org/ENSG00000143379-SETDB1/pathology.

Supplementary Figure 5 Akt K64 tri-methylation is critical for Akt binding to TRAF6 and Skp2.

(a) HEK293 cells were transfected with Vector (Vec), HA-Akt1 (WT) and HA-Akt1 K8R (K8R), and WCE were collected for IB analysis. (b-c) HEK293 cells were transfected with Vector (Vec), HA-Akt1 (WT) and HA-Akt1 K64R (K64R), and WCE were collected for IP with HA, followed by IB analysis. All IB data represent results from 3 independent experiments. Unprocessed blots are shown in Supplementary Figure 8.

Supplementary Figure 6 JMJD2A promotes the phosphorylation of Akt and tumorigenesis.

(a) JMJD2Alox/lox MEFs cells were infected with retrovirus control (MSCV1) or retrovirus Cre (Cre), serum-starved for 1 day, treated with 50 ng/ml IGF-1 for various times, and WCE were collected for IB analysis. (b) HEK293 cells were silenced with JMJD2A ShRNA (#1), transfected with pBabe Vector or pBabe-JMJD2A (pBabe-2A), and WCE were collected for IB analysis. (c) A549 cells silenced with control (Shluc) or JMJD2A ShRNA (#1 and #2) were were serum-starved for 1 day, treated with 50 ng/ml IGF-1 for 15 mins, and WCE were collected for IB analysis. Data in a-c represent results from 3 independent experiments. (d) Tumour volume of xenograft tumours derived from A549 cells silenced with control (Shluc), JMJD2A ShRNA (#1) and JMJD2A ShRNA (#1) plus Myr-Akt overexpression (data shown represent mean ± s.d, n = 6 or 7 mice for each group as indicated, **** p < 0.0001, statistical significance was assessed using Student’s two-tailed t-test.). (e) Tumour weight of xenograft tumours derived from A549 cells silenced with control (Shluc), JMJD2A ShRNA (#1) and JMJD2A ShRNA (#1) plus Myr-Akt overexpression, data shown represent mean ± s.d, n = 6 or 7 mice for each group as indicated, **** p < 0.0001, statistical significance was assessed using Student’s two-tailed t-test. Statistics source data for d and e are shown in Supplementary Table. 4. Unprocessed blots are shown in Supplementary Figure 8.

Supplementary Figure 7 PI 3-Kinase did not regulate Akt K64 methylation and Akt K140 and K142 methylation regulates Akt activation.

(a) HEK293 cells were transfected with Vector (Vec), HA-Akt1 (WT) and HA-Akt1 R25C (R25C), and WCE were collected for IB analysis. (b) HEK293 cells were treated with LY294002 in different concentration for 4 h and WCE were collected for IB analysis. (c) HEK293 cells were transfected with Vector (Vec), HA-Akt1 (WT), HA-Akt1 K140R (K140R), HA-Akt1 K142R (K142R) and HA-Akt1 K64R (K64R), and WCE were collected for IP with HA, followed by IB analysis. (d) HEK293 cells were transfected with Vector (Vec), HA-Akt1 (WT), HA-Akt1 K140/K142R (K140/142R) and HA-Akt1 K64R (K64R), and WCE were collected for IB analysis. Three independent experiments were performed with similar results for the IB. Unprocessed blots are shown in Supplementary Figure 8.

Supplementary Figure 8

Unprocessed blots.

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Wang, G., Long, J., Gao, Y. et al. SETDB1-mediated methylation of Akt promotes its K63-linked ubiquitination and activation leading to tumorigenesis. Nat Cell Biol 21, 214–225 (2019). https://doi.org/10.1038/s41556-018-0266-1

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