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Discovery of a first-in-class reversible DNMT1-selective inhibitor with improved tolerability and efficacy in acute myeloid leukemia

Nature Cancer volume 2, pages 1002–1017 (2021)Cite this article

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Abstract

DNA methylation, a key epigenetic driver of transcriptional silencing, is universally dysregulated in cancer. Reversal of DNA methylation by hypomethylating agents, such as the cytidine analogs decitabine or azacytidine, has demonstrated clinical benefit in hematologic malignancies. These nucleoside analogs are incorporated into replicating DNA where they inhibit DNA cytosine methyltransferases DNMT1, DNMT3A and DNMT3B through irreversible covalent interactions. These agents induce notable toxicity to normal blood cells thus limiting their clinical doses. Herein we report the discovery of GSK3685032, a potent first-in-class DNMT1-selective inhibitor that was shown via crystallographic studies to compete with the active-site loop of DNMT1 for penetration into hemi-methylated DNA between two CpG base pairs. GSK3685032 induces robust loss of DNA methylation, transcriptional activation and cancer cell growth inhibition in vitro. Due to improved in vivo tolerability compared with decitabine, GSK3685032 yields superior tumor regression and survival mouse models of acute myeloid leukemia.

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Fig. 1: Biochemical and cellular engagement of DNMT1 by GSK3484862.
Fig. 2: Biochemical and biophysical characterization of DNMT1-selective inhibitors.
Fig. 3: Phenotypic response following treatment with DNMT inhibitors in hematologic cancer cell lines.
Fig. 4: GSK3685032 induces changes in DNA methylation and gene expression in treated cells.
Fig. 5: GSK3685032 activates immune response pathways.
Fig. 6: Mechanistic evaluation of GSK3685032 and DAC in AML.
Fig. 7: Comparison of nucleoside versus non-nucleoside DNMT inhibitors.
Fig. 8: GSK3685032 reveals improved in vivo efficacy and tolerability in AML models compared with DAC.

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Data availability

All data generated to support the findings of this study are available. The functional genomics data have been deposited in the NCBI Gene Expression Omnibus (GEO) and are accessible through the GEO SuperSeries accession number: GSE135207 (https://www.ncbi.nlm.nih.gov/geo). The atomic coordinates and structure factors of DNMT1–DNA (zebularine)–SAH (PDB 6X9I), DNMT1–DNA–GSK3830052 (PDB 6X9J) and DNMT1–DNA–GSK3685032 (PDB 6X9K) have been deposited in the Protein Data Bank (http://www.rcsb.org). Source data are provided with this paper. All other data are available from the corresponding authors upon reasonable request.

Code availability

The code generated to analyze Infinium Methylation EPIC array, RNA-seq gene expression and hERV expression data (Figs. 4–6 and Extended Data Fig. 5) can be found at https://github.com/ShawnWFoley-GSK/Pappalardi_et_al_2021. A detailed list of software and package versions can be found in the Methods section.

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Acknowledgements

We thank T. Tomaszek and P. Keller for their contributions toward the high-throughput screen, K. Morasco and D. Depagnier for execution of the CBC panel, D. Cooper and H. Tran for input regarding statistical analysis, and S. Rajapurkar for assistance with genomics data analysis and visualization. We also thank A.C. Wong for original development of the DNA-binding and fluorescence-coupled breaklight assays, B. Waszkowycz for early computational design input and H. Hashimoto for his effort preparing initial human DNMT1 constructs and protein for the crystallization studies. Lastly, we thank S. Pessagno, D. Wilson and M. Bottomley for alliance oversight. Work conducted at the Cancer Research UK Manchester Institute was wholly funded by Cancer Research UK (grant nos. C480/A11411 and C5759/A17098). Work at the MD Anderson Cancer Center was supported by the Cancer Prevention Research Institute of Texas (CPRIT) grant no. RR160029 and National Institutes of Health (NIH) grant no. R35GM134744 to X.C., who is a CPRIT Scholar in Cancer Research. Work at the Van Andel Research Institute (P.A.J.) was supported by National Cancer Institute grant no. R35CA209859 and by the Van Andel Research Institute–Stand Up to Cancer Epigenetics Dream Team. Stand Up to Cancer is a division of the Entertainment Industry Foundation, administered by AACR.

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Author notes

  1. These authors contributed equally: Mark Cockerill, Wendy A. Kellner.

Authors and Affiliations

  1. Cancer Epigenetics Research Unit, Oncology, GlaxoSmithKline, Collegeville, PA, USA

    Melissa B. Pappalardi, Kathryn Keenan, Wendy A. Kellner, Christian Sherk, Kristen Wong, Charles F. McHugh, Lourdes Rueda, David T. Fosbenner, Cunyu Zhang, Jessica L. Handler, Susan Merrihew, Shawn W. Foley, Mei Li, Stuart P. Romeril, Elisabeth Minthorn, Helai P. Mohammad, Rab K. Prinjha, Christopher Carpenter, Dirk Heerding, Bryan W. King, Juan I. Luengo, Ryan G. Kruger & Michael T. McCabe

  2. Drug Discovery Unit, Cancer Research UK Manchester Institute, University of Manchester, Alderley Park, Macclesfield, UK

    Mark Cockerill, Alexandra Stowell, Philip Chapman, Emma Fairweather, Ali Raoof, Roger J. Butlin, Charlotte Burt, Kristin Goldberg, Christopher S. Kershaw, Donald Ogilvie, Allan M. Jordan & Ian Waddell

  3. Department of Epigenetics and Molecular Carcinogenesis, University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Sarath Pathuri, John R. Horton, Xing Zhang & Xiaodong Cheng

  4. Medicinal Science & Technology, GlaxoSmithKline, Collegeville, PA, USA

    Jacques Briand, Nino Campobasso, Alan P. Graves, Makda Mebrahtu, Jon-Paul Jaworski, Dean E. McNulty, Amy N. Taylor, Thau Ho, Anthony J. Jurewicz & Mehul Patel

  5. Cellzome GmbH, Functional Genomics, GlaxoSmithKline, Heidelberg, Germany

    Michael Steidel, Thilo Werner, H. Christian Eberl, Anna Rutkowska, Marcus Bantscheff & Paola Grandi

  6. Future Pipeline Discovery, GlaxoSmithKline, Collegeville, PA, USA

    Arthur Groy, Andrew B. Benowitz & Aidan G. Gilmartin

  7. Center for Epigenetics, Van Andel Research Institute, Grand Rapids, MI, USA

    Ashley K. Wiseman & Peter A. Jones

  8. Drug Metabolism and Pharmacokinetics Modelling, GlaxoSmithKline, Stevenage, UK

    Morris Muliaditan

  9. Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA

    Stephen B. Baylin

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Contributions

M.P. and A.J.J. contributed to the high-throughput screen. A.N.T. and T.H. generated DNMT proteins. M.B.P., A.S., K.W. and C.B. designed, executed and/or analyzed enzymatic studies. M.C. conducted the DNMT3B −/− HCT-116 vimentin assays. M. Mebrahtu and J.-P.J. executed the wild-type HCT-116 vimentin assay. A.S. and E.F. executed the DNA binding assay. M.S., T.W., H.C.E., A.Rutkowska, M.B. and P.G. contributed to thermal shift assays. J.B. and N.C. conducted the covalent modification and photoaffinity labeling studies. A.K.W. executed the mouse embryonic fibroblast studies under guidance from P.A.J. A.P.G. performed sequence alignment. A.G. executed the mutagenesis studies under guidance from A.G.G. and A.B.B. S.P. performed protein purification, complex formation and crystallization under guidance from X.Z. J.R.H. collected X-ray diffraction data and determined structures. K.K. and S.M. executed the AML proliferation studies. M.T.M., K.K., J.L.H., C.F.M. and M.B.P. designed, executed and/or analyzed the AML in vitro studies. K.K. executed the western blot studies with advice from S.B.B.; D.E.M. developed the LC–MS/MS methodology for the 5-methylcytosine assay. W.A.K. and S.W.F. analyzed the genomics data. C.S., C.F.M., E.M. and M.B.P. designed, executed and/or analyzed the in vivo studies. M. Muliaditan modeled the pharmacokinetic data. A.Raoof, R.J.B., L.R., D.T.F., C.Z., M.L., S.P.R., K.G., C.S.K., A.B.B., D.H., B.W.K., J.I.L. and A.M.J. designed and/or synthesized compounds. X.C. organized and designed the scope of the crystallography study. M.C., P.C., H.P.M., R.K.P., D.O., C.C., R.G.K., I.W., M.T.M. and M.B.P. provided conceptual advice. M.B.P. and M.T.M. wrote the manuscript.

Corresponding authors

Correspondence to Melissa B. Pappalardi or Michael T. McCabe.

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Competing interests

M.B.P., K.K., W.A.K., C.S., K.W., J.B., M.S., A.G., C.F.M., N.C., A.P.G., T.W., L.R., D.T.F., C.Z., J.L.H., M.Muliaditan, M.Mebrahtu, J.P.J., D.E.M., H.C.E., A.N.T., T.H., S.M., S.W.F., A. Rutkowska, M.L., S.P.R., M.B., A.J.J., E.M., P.G., M.P., A.B.B., H.P.M., A.G.G., R.K.P., C.C., D.H., B.W.K., J.I.L., R.G.K. and M.T.M. are/were employees and/or shareholders of GlaxoSmithKline (GSK). The remaining authors declare no competing interests.

Additional information

Peer review information Nature Cancer thanks the anonymous reviewers for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Characterization of GSK3484862 and GSK3685032.

a, Stability of GSK3484862 (1,000 nM) as determined by LC-MS/MS in media without or with cells (MV4-11) at 37 °C versus decitabine (1,000 nM). b, Thermal profile (Tm, 77.5 °C, n = 2 biologically independent experiments with two technical replicates each) of the hemi-methylated hairpin oligonucleotide with DMSO or GSK3484862 (100 µM). c, DNMT1 activity (average of technical replicates, data is representative of two biologically independent experiments) for uninhibited reaction (DMSO, n = 2) and recovery of inhibited enzyme activity following rapid dilution (100-fold) of pre-complexed DNMT1:GSK3484862 (n = 3) or DNMT1:SAH (n = 3). d, Dose-dependent increase in vimentin expression (n = 2 biologically independent experiments with two technical replicates each) following treatment of DNMT3B -/- HCT-116 cells with GSK3484862 or decitabine. e, Table summarizing up-regulation of vimentin expression in wild-type or DNMT3B -/- HCT-116 cells after treatment with GSK3484862 or decitabine (average ± s.d.; n = independently fitted EC50 values). f, IC50 values (bar represents average, n = biologically independent determinations) following a 0-minute (n = 15), 60-minute DNMT1:Inhibitor (EI, n = 2), or 60-minute DNMT1:Inhibitor:hemi-methylated DNA (ESI, n = 2) preincubation. g, Intact protein mass spectrometry for mDNMT1 (731-1602) following incubation with hemi-methylated DNA in the absence or presence of GSK3685032 showed no covalent adduct. h, Inhibition of a kinase panel (n = 369) by 10 µM GSK3685032. i, Inhibition of a methyltransferase panel by 10 µM GSK3685032. j, Isothermal dose-response curves for DNMT1 following treatment with GSK3685032 in a recombinant system (DNMT1 601-1600 in the presence of 40-mer hemi-methylated DNA) or in a cellular system (HepG2). k, Dose response curves (average ± s.d., n = biologically independent samples) for full-length DNMT1 using a 40-mer hemi-methylated or poly(dIdC) DNA substrate in a radioactive SPA assay with GSK3685032 (n = 4 or 5, respectively) or SAH (n = 4 or 6), respectively).

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Extended Data Fig. 2 DNMT1 residues important for compound binding and inhibition.

a, Analogues containing a photoreactive benzophenone or diazerine moiety. b, c, Murine DNMT1 (731-1602) spectra in the absence or presence of a 45-minute photolysis step with 14-mer hemi-methylated DNA and GSK3844831 (b) or GSK3901839 (c). d, Dose response curves for HEK293 cells expressing either wild-type or site-directed alanine mutant DNMT1 (n = 2; technical replicates) treated for 6 days with decitabine or GSK3685032. Dashed line represents starting cell number (T0). e, Dose response curves (n = 4 biologically independent samples; average ± s.d.) for full-length wild-type or H1507Y DNMT1 activity in a radioactive SPA assay.

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Extended Data Fig. 3 Sequence alignment of the methyltransferase domains of human DNMT1, DNMT3A, and DNMT3B.

Identical residues are shaded blue while similar residues are shaded yellow. The boxes indicate the target recognition domain of DNMT1 (dashed, black) and the active-site loop (solid, red). Residues that were photoaffinity labeled*, residues that conferred resistance to GSK3685032 upon mutation to alanine (gIC50 > 10 µM)† and are reported to be involved in recognition of the methylated cytosine‡, or the catalytic cysteine (C1226)♯ are marked within the DNMT1 sequence.

Extended Data Fig. 4 Crystal structure of DNMT1-DNA in complex with DNMT1 inhibitor.

a, View of the active-site loop bound in the space left by the flipped-out zebularine in the DNMT1-DNA complex. b, The omit electron density map in mesh for GSK3685032 contoured at 4σ above the mean. c, d, Orthogonal views of DNMT1-DNA in the presence of GSK3685032. The active-site loop is colored brown and adopts an open conformation. e, The omit electron density map in mesh for GSK3830052 contoured at 4σ above the mean. f, Superimposition of inhibitor (pink) and the active-site loop in the native complex (cyan). g, The inhibitor intercalates into DNA between two G:C base pairs. h, Two hydrogen bonds formed between G1 and zebularine. i, Inhibitor interacts with 5-methylcytosine (5mC) of the parent DNA strand and Trp1510 of DNMT1. j, The end of the inhibitor N-methyl-N-phenylmethanesulfonamide moiety is close to the DNMT1 active-site Cys1226.

Extended Data Fig. 5 Biochemical, phenotypic, and mechanistic activity of DNMT inhibitors.

a, Table reporting GSK3685032 activity in a panel of AML cell lines (day 6, average ± s.d., n = biologically independent experiments). b, Heatmap showing induction of caspase-glo 3/7 activity (Promega, average log2 fold change, n = 2 biologically independent experiments) in MV4-11 cells following treatment with GSK3510477, GSK3484862 (with 2 technical replicates), or GSK3685032 at days 1, 2, 4 & 6 (0.06-7,340 nM). c, Compound structures for reported DNMT inhibitors. d, Table containing output parameters (average ± SEM, n = biologically independent experiments) following biochemical, phenotypic (MV4-11, day 6) or mechanistic (MV4-11, day 4) assessment using a panel of DNMT inhibitors. NA, not applicable to assay format. 5mC, 5-methylcytosine. e, Top, Venn diagram for significantly increased genes in MV4-11 (RNA-seq, FDR < 0.05, |log2 fold-change| > 1, day 4, 400 nM) following treatment with GSK3685032 or decitabine. Bottom, Heatmap of log2 fold change differential expression (RNA-seq, day 4) following treatment with GSK3685032 or decitabine (3.2-10,000 nM) for overlapping genes (n = 1,542) from the Venn diagram.

Source data

Extended Data Fig. 6 Pharmacokinetic evaluation of GSK3685032.

a, Summary of mouse pharmacokinetic parameters for GSK3685032. NA, not applicable to dosing route. ND, value not determined. IV, intravenous. SC, subcutaneous. b, Blood concentration of GSK3685032 at multiple timepoints following a single dose of 2 mg/kg IV (male CD-1 mice), 2 mg/kg SC (male C57/BL6 mice), or 30 mg/kg SC (female Nu/Nu mice). Individual data shown (n = 3 animals/group). c, Dose proportional blood concentration of GSK3685032 following twice daily subcutaneous dosing for 8.5 days in a SKM-1 subcutaneous xenograft model (NOD-scid) collected 6 hours post last dose. Individual concentrations (n = 3 animals/group) with linear regression (R square = 0.9780) fit to the mean concentration for each group. d, Simulated profile of GSK3685032 over a 24 hour time frame adjusted for unbound fraction (2.5%) in the blood following twice daily subcutaneous dosing. 5-mC, 5-methylcytosine.

Source data

Extended Data Fig. 7 Compound effect in subcutaneous MV4-11 and SKM-1 xenograft models.

a, b, Animal body weight measurements for MV4-11 (a) or SKM-1 (b) xenograft models spanning the dosing duration of the study (average ± s.d.; n = 10 animals/group, # represents day first animal came off study due to tumor volume). c-f, Individual tumor volume measurements for MV4-11 (c, day 35) or SKM-1 (d, day 20). Solid line represents the median for each group (n = 10 animals unless noted). Dotted line represents the median tumor volume for vehicle. Statistical significance* of treatment versus vehicle was calculated using one-way ANOVA, Dunnett’s multiple comparisons test. Table summarizes adjusted P values to account for multiple comparisons and corresponding tumor growth inhibition (TGI) values for each group within the MV4-11 (e) or SKM-1 (f) xenograft models. g, h, Individual tumor volume measurements for the 45 mg/kg GSK3685032 group in MV4-11 (g) or SKM-1 (h) xenograft models during the dosing segment (orange bar) and continuing for ≥ 27 days off drug (blue bar) to monitor durability (n = 10 animals unless noted). The minimum measurable tumor volume was set to 10 mm3.

Source data

Extended Data Fig. 8 Effects of GSK3685032 and decitabine on complete blood cell counts.

a, b, Complete blood cell count (a) at day 28 across all dose groups (n = 5 animals/group; mean ± s.d.). Statistical significance* of treatment versus vehicle was calculated using one-way ANOVA, Dunnett’s multiple comparisons test. Each P value was adjusted to account for multiple comparisons. Table (b) showing output parameters following statistical analysis. ^Used log10 transformed values due to unequal variance between groups. Ratio represents treatment group normalized to vehicle. c, Complete blood cell count (mean ± s.d.) at day 28 on treatment (n = 5 animals/group) followed by 27 days off treatment (n = 5 animals/group for 15 and 45 mg/kg or n = 8 animals for 30 mg/kg group) with GSK3685032.

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Supplementary information

Supplementary Information

Supplementary Data Tables 1–5.

Reporting Summary

Supplementary Table 6

Directed mutagenesis constructs.

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Pappalardi, M.B., Keenan, K., Cockerill, M. et al. Discovery of a first-in-class reversible DNMT1-selective inhibitor with improved tolerability and efficacy in acute myeloid leukemia. Nat Cancer 2, 1002–1017 (2021). https://doi.org/10.1038/s43018-021-00249-x

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