DNA methyltransferase expression in triple-negative breast cancer predicts sensitivity to decitabine
Jia Yu, … , Matthew P. Goetz, Liewei Wang
Jia Yu, … , Matthew P. Goetz, Liewei Wang
Published April 30, 2018
Citation Information: J Clin Invest. 2018;128(6):2376-2388. https://doi.org/10.1172/JCI97924.
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Research Article Oncology

DNA methyltransferase expression in triple-negative breast cancer predicts sensitivity to decitabine

Abstract

Triple-negative breast cancer (TNBC) is a heterogeneous disease with poor prognosis that lacks targeted therapies, especially in patients with chemotherapy-resistant disease. Since DNA methylation-induced silencing of tumor suppressors is common in cancer, reversal of promoter DNA hypermethylation by 5-aza-2′-deoxycytidine (decitabine), an FDA-approved DNA methyltransferase (DNMT) inhibitor, has proven effective in treating hematological neoplasms. However, its antitumor effect varies in solid tumors, stressing the importance of identifying biomarkers predictive of therapeutic response. Here, we focused on the identification of biomarkers to select decitabine-sensitive TNBC through increasing our understanding of the mechanism of decitabine action. We showed that protein levels of DNMTs correlated with response to decitabine in patient-derived xenograft (PDX) organoids originating from chemotherapy-sensitive and -resistant TNBCs, suggesting DNMT levels as potential biomarkers of response. Furthermore, all 3 methytransferases, DNMT1, DNMT3A, and DNMT3B, were degraded following low-concentration, long-term decitabine treatment both in vitro and in vivo. The DNMT proteins could be ubiquitinated by the E3 ligase, TNF receptor–associated factor 6 (TRAF6), leading to lysosome-dependent protein degradation. Depletion of TRAF6 blocked decitabine-induced DNMT degradation, conferring resistance to decitabine. Our study suggests a potential mechanism of regulating DNMT protein degradation and DNMT levels as response biomarkers for DNMT inhibitors in TNBCs.

Authors

Jia Yu, Bo Qin, Ann M. Moyer, Somaira Nowsheen, Tongzheng Liu, Sisi Qin, Yongxian Zhuang, Duan Liu, Shijia W. Lu, Krishna R. Kalari, Daniel W. Visscher, John A. Copland, Sarah A. McLaughlin, Alvaro Moreno-Aspitia, Donald W. Northfelt, Richard J. Gray, Zhenkun Lou, Vera J. Suman, Richard Weinshilboum, Judy C. Boughey, Matthew P. Goetz, Liewei Wang

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Figure 5

TRAF6 E3-ligase activity is essential for the ubiquitination.

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TRAF6 E3-ligase activity is essential for the ubiquitination. (A) Breast...
(A) Breast cancer cell lines were transfected with negative or TRAF6-specific siRNAs for 72 hours. Cell lysates were subjected to Western blot to determine DNMT protein levels with the indicated antibodies. (B) Cell lysates from the WT and Crispr/Cas9 TRAF6-KO (KO1) MDA-MB-231 cell lines were subjected to Western blot analysis as described above. (C) Dot blot for detecting global DNA methylation. Genomic DNA from WT and Crispr/Cas9 TRAF6-KO cells were isolated and dot blotted with specific anti-5mC antibody. Two-fold dilution of 1 μg of genomic DNA isolated from each sample was spotted on the membrane, followed by incubation with the antibody. (D) MDA-MB-231 Crispr/Cas9 TRAF6-KO cells were transfected with FLAG-tagged WT TRAF6 (WT) and catalytic-dead CA mutant (C70A). Cell lysates were subjected to Western blot analysis with the indicated antibodies. (E) MDA-MB-231 TRAF6-WT and Crispr/Cas9 TRAF6-KO cells were treated with decitabine for 6 days with or without concanamycin A for an additional 24 hours. Cell lysates were subjected to Western blot analysis with the indicated antibodies. (F) MDA-MB-231 TRAF6-WT and Crispr/Cas9 TRAF6-KO cells were treated with the indicated doses of decitabine for 7 days, and colony-formation assay was performed. Crispr/Cas9 TRAF6-KO clone 1 (KO1) or clone 2 (KO2) were used. Data represent mean ± SD (n = 3 independent experiments). (G) Crispr/Cas9 TRAF6-KO cells were transfected with TRAF6-WT and CA mutants. Cells were treated with the indicated doses of decitabine for 7 days, and colony-formation assay was performed as above. Data represent mean ± SD (n = 3 independent experiments).