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Epigenetic therapy potentiates transposable element transcription to create tumor-enriched antigens in glioblastoma cells

Nature Genetics volume 56, pages 1903–1913 (2024)Cite this article

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Abstract

Inhibiting epigenetic modulators can transcriptionally reactivate transposable elements (TEs). These TE transcripts often generate unique peptides that can serve as immunogenic antigens for immunotherapy. Here, we ask whether TEs activated by epigenetic therapy could appreciably increase the antigen repertoire in glioblastoma, an aggressive brain cancer with low mutation and neoantigen burden. We treated patient-derived primary glioblastoma stem cell lines, an astrocyte cell line and primary fibroblast cell lines with epigenetic drugs, and identified treatment-induced, TE-derived transcripts that are preferentially expressed in cancer cells. We verified that these transcripts could produce human leukocyte antigen class I-presented antigens using liquid chromatography with tandem mass spectrometry pulldown experiments. Importantly, many TEs were also transcribed, even in proliferating nontumor cell lines, after epigenetic therapy, which suggests that targeted strategies like CRISPR-mediated activation could minimize potential side effects of activating unwanted genomic regions. The results highlight both the need for caution and the promise of future translational efforts in harnessing treatment-induced TE-derived antigens for targeted immunotherapy.

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Fig. 1: Epigenetic therapy reshapes the epigenetic landscape in proliferating GSCs to activate antiviral response pathways.
Fig. 2: Epigenetic therapy generates antigenic chimeric transcripts from TE cryptic promoters.
Fig. 3: Treatment-induced TE-chimeric antigens are presented on HLA-I molecules on GSCs.
Fig. 4: Long-read technology detects TE-chimeric transcripts that generate TI-TEAs in B49 GSCs.
Fig. 5: Targeted epigenetic reactivation of TE-chimeric transcripts with CRISPRa technology.

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Data availability

All omics data generated during this study are available through the Gene Expression Omnibus (GSE227059) and Proteomics Identification Database (PXD039893). Genotype-Tissue Expression transcriptomic data were obtained with database of Genotypes and Phenotypes approval through the accession number phs000424.v9.p2. Source data are provided with this paper.

Code availability

All custom scripts are available on GitHub (https://github.com/twlab/epitherapy_induced_antigen_GBM) and Zenodo (https://zenodo.org/records/11869293)93.

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Acknowledgements

We would like to thank J. Hoisington-López and M. L. Jaeger from The Edison Family Center for Genome Sciences & Systems Biology (CGSSB) for assistance with sequencing; B. Koebbe and E. Martin from CGSSB for assistance with data processing; M. Savio, M. Patana and D. Schweppe from the Siteman Flow Cytometry Core for FACS-related expertise; D. Mao from A. Kim’s laboratory for expertise pertaining to GSCs; D. Chandler from Van Andel Institute for valuable editorial help with the manuscript. T.W. was funded by National Institutes of Health (NIH) grants (5R01HG007175, U24ES026699 and U01HG009391) and an American Cancer Society Research Scholar Grant (RSG-14-049-01-DMC). N.M.S. was a Howard Hughes Medical Institute Medical Research Fellow. H.J.J. was supported by a grant from the National Institute of General Medical Sciences (T32GM007067). The LC–MS/MS synthetic peptide analysis was performed by the Proteomics & Mass Spectrometry Facility at the Donald Danforth Plant Science Center and the acquisition of the Orbitrap Fusion Lumos LC–MS/MS was supported by a National Science Foundation grant (DBI-1827534). Mass spectrometry analyses for LTR12C_TP63 were performed by the Mass Spectrometry Technology Access Center at the McDonnell Genome Institute at Washington University School of Medicine, which was supported by a grant from the Diabetes Research Center and the NIH (P30DK020579), a Clinical and Translational Science Award from the Institute of Clinical and Translational Sciences and the National Center for Advancing Translational Sciences (UL1TR002345), and a Cancer Center Support Grant from the Siteman Cancer Center and the National Cancer Institute (P30CA091842).

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Author notes

  1. These authors contributed equally: H. Josh Jang, Nakul M. Shah, Ju Heon Maeng, Yonghao Liang.

Authors and Affiliations

  1. Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA

    H. Josh Jang, Nakul M. Shah, Ju Heon Maeng, Yonghao Liang, Noah L. Basri, Jiaxin Ge, Xuan Qu, Michael J. Moore, Justin Y. Chen, Hyung Joo Lee, Daofeng Li, Xiaoyun Xing & Ting Wang

  2. The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA

    H. Josh Jang, Nakul M. Shah, Ju Heon Maeng, Yonghao Liang, Noah L. Basri, Jiaxin Ge, Xuan Qu, Michael J. Moore, Justin Y. Chen, Hyung Joo Lee, Daofeng Li, Xiaoyun Xing & Ting Wang

  3. Department of Epigenetics, Van Andel Institute, Grand Rapids, MI, USA

    H. Josh Jang

  4. Department of Neurological Surgery, Washington University School of Medicine, St Louis, MO, USA

    Tatenda Mahlokozera, Devi Annamalai, Patrick A. DeSouza & Albert H. Kim

  5. Donald Danforth Plant Science Center, St. Louis, MO, USA

    Shin-Cheng Tzeng & Russell B. Williams

  6. The Brain Tumor Center, Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA

    Albert H. Kim

  7. McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA

    Ting Wang

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H.J.J., N.M.S. and T.W. conceived and implemented the study; H.J.J., N.M.S., J.H.M., Y.L., J.Y.C., D.L. and H.J.L. contributed to the computational analysis; H.J.J., J.H.M. and X.X. generated the epigenetic and transcriptomic profiles of the cell lines; H.J.J., X.Q., T.M., D.A., P.A.D. and A.H.K. cultured the GSCs and contributed reagents; H.J.J., Y.L., N.L.B. and J.G. designed and implemented the CRISPRa experiments; H.J.J. performed the HLA pulldown for LC–MS/MS; Y.L. performed the TP63 immunoprecipitation for LC–MS/MS; N.M.S., J.H.M., Y.L., S.-C.T., R.B.W. and M.J.M. performed the proteomics analysis; and H.J.J., N.M.S., J.H.M., Y.L. and T.W. prepared and revised the manuscript with input from all authors.

Corresponding authors

Correspondence to Albert H. Kim or Ting Wang.

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Competing interests

A.H.K. is a consultant for Monteris Medical. The other authors have no competing interests.

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Nature Genetics thanks Artem Babaian and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 GSCs are treated with non-cytotoxic doses of Decitabine and Panobinostat.

a, Schematic of the different treatment conditions used to quantify GSC proliferation and cell death rates after epigenetic drug treatment. b, Control and treated GSCs at end of treatment (Day 6) show minimal differences in cell confluency; bright-field microscope images obtained at 10x magnification. c, Cell viability after epigenetic drug treatment. Live cells were identified by flow cytometry after propidium iodide (PI) and annexin staining. d, Example gating strategy for detection of live cells (that is B36 GSCs) after treatment. Population of PI-negative and annexin-negative were identified as live cells. The experiment was repeated twice with similar results.

Source data

Extended Data Fig. 2 LTR family of transposable elements are enriched to be activated by epigenetic therapy treatment.

a, Number of treatment-induced TSSs annotated with TE class. b, Number of treatment-induced TSSs annotated with LTR subfamilies. Nine LTR subfamilies that have at least 15 treatment-induced TSSs in at least one cell line are shown. Treatment-induced TSSs are defined as CAGE peaks with the minimum expression level of 0.3 TPM. Others = peaks not in TEs.

Extended Data Fig. 3 SQuIRE rescues transcriptional activation of young endogenous transposable elements.

Heatmap showing enrichment score of TE subfamilies that were activated by epigenetic therapy, after rescuing multi-mapped reads in CAGE-seq (left) and RNA-seq (right) with SQuIRE.

Extended Data Fig. 4 Expression of the unique genomic loci of endogenous TE antigens detected by HLA-pulldown mass spectrometry.

a, Number of HLA-I antigens detected across TE classes for the Decitabine+Panobinostat (DP) and DMSO treated B49 cell line (left), and Venn diagram comparing the antigens found between the two treatments (right). b, Same as (a) but for B66 cells. c, Number of endogenous TE antigens detected across replicate experiments in DP-treated B49 cells (top) and B66 cells (bottom). d, Venn diagram of the endogenous TE antigens found in DP-treated B49 and B66 cell lines. e, Stacked bar plot with the x-axis being the number of genomic loci found for a particular antigen using BLAT, and the y-axis is the number of HLA-I antigens detected after epigenetic therapy in B49 (left) and B66 (right) cell lines. The fill color is the class of transposable elements that the peptides originate from. f, Heatmap of the endogenous TE antigens with genomic support that are derived from unique loci. The highlighted boxes are the samples in which they are detected as being expressed.

Extended Data Fig. 5 Synthetic peptide validation of TI-TEAs.

Mass spectra for antigen candidates discovered in the HLA-pulldown mass spectrometry experiments (top), and the mass spectra of a corresponding synthetic peptide with same sequence (bottom). The TI-TEA candidate and synthetic peptide mass spectra for LISNSWGQAI did not match, so the LISNSWGQAI peptide was excluded from the TI-TEA candidate list. GLFCGDVHTV synthetic peptide was generated with a carbamidomethyl cysteine after consideration of cysteine alkylation caused by iodoacetamide in lysis buffer.

Extended Data Fig. 6 Long-read technology detects additional TE-derived antigens presented on HLA molecules in GSCs.

a, RNA-seq expression levels of TI-TEA encoding transcripts detected by long-read sequencing in GTEx samples. Peptide sequences for TI-TEAs are on the left of the heatmap. Transcript IDs are on the right of the heatmap. * denotes immune-privileged tissue. b, Detection of TE-derived antigens from HLA-pulldown experiments from B49 GSCs. Purple circles signify TE-derived antigens that were specifically induced by epigenetic therapy with genomic support. c, The number of genomic loci that encode each of the TI-TEAs, as estimated by BLAT. The value of 0 genomic loci represents antigens derived from TE-exon junctions of TE-derived transcripts. d, The number of coding transcripts that encode each of the TI-TEAs based on long-read data. For each TI-TEA, there is a primary transcript that originates from a treatment-induced TE. The coding transcripts are categorized into four groups based on their 5′ overlap with TE and their exon overlap with annotated genes; Same TE - transcripts derived from the same TE as the primary transcript; Alternative TE - transcripts that originate from a different TE compared to the primary transcript; Canonical Gene Isoform - transcripts that overlap with exons of annotated genes; Alternative Non-TE - transcripts that do not derive from a TE and do not overlap with exons of annotated genes. e, Transcript expression levels for TE-derived or other types of transcripts that are predicted to create 18 TI-TEAs in B49 GSCs.

Supplementary information

Supplementary Information

Supplementary Methods, Supplementary Table titles and Supplementary Figs. 1–17.

Reporting Summary

Supplementary Tables

Supplementary Tables 1–9.

Source data

Source Data Fig. 5

Unprocessed Western blot for Fig. 5i.

Source Data Extended Data Fig. 1

Unprocessed bright-field microscopy image from Extended Data Fig. 1b.

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Jang, H.J., Shah, N.M., Maeng, J.H. et al. Epigenetic therapy potentiates transposable element transcription to create tumor-enriched antigens in glioblastoma cells. Nat Genet 56, 1903–1913 (2024). https://doi.org/10.1038/s41588-024-01880-x

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