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An EGFR co-amplified lncRNA HELDR promotes glioblastoma malignancy through KAT7-driven gene programs

Nature Cell Biology (2026)Cite this article

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Abstract

EGFR amplification frequently occurs within extrachromosomal DNAs (ecDNAs) and is the most prevalent mutation in glioblastoma (GBM). However, targeting EGFR for GBM treatments has been unsuccessful. Here we show a long non-coding RNA (lncRNA) that is co-amplified with EGFR, which we name hidden EGFR long non-coding downstream RNA (HELDR). HELDR is a GBM-selective lncRNA that promotes tumorigenicity independent of EGFR signalling. HELDR exhibits widespread chromatin association and recruits the transcription co-activator p300 to the KAT7 promoter. p300-induced H3K27ac at the KAT7 promoter enlists other co-transcription factors, activating KAT7 transcription. KAT7 induces H3K14ac and H4K12ac that activate KAT7-driven gene programmes that are critical for GBM malignancy. Targeting KAT7 or HELDR markedly enhances therapeutic effects of anti-EGFR treatments for GBM. These results not only reveal the role of HELDR in EGFR-amplified GBM but also provide a strong rationale to characterize the role of lncRNAs co-amplified with driver oncogenes in human cancers.

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Fig. 1: The lncRNA ELDR is co-amplified with EGFR in GBM.
Fig. 2: De novo lncRNA HELDR is the major transcript in the ELDR locus and localized in the nucleus.
Fig. 3: HELDR is critical for cell proliferation and tumorigenicity and globally regulates gene expression independent of EGFR in GSCs with EGFR amplification.
Fig. 4: HELDR exhibits widespread genomic DNA binding.
Fig. 5: HELDR epigenetically regulates KAT7 expression.
Fig. 6: KAT7 mediates HELDR-promoted GBM tumourigenesis.
Fig. 7: KAT7 inhibitor WM-3835 synergistically enhanced anti-GBM activity of EGFR inhibitor erlotinib.
Fig. 8: ASO-targeting HELDR synergistically enhanced anti-GBM activity of EGFR inhibitor erlotinib.

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Data availability

The short-read RNA-seq, long-read RNA-seq and ChIRP-seq data that support the findings of this study have been deposited in the Gene Expression Omnibus under accession codes GSE286179, GSE286318, GSE286319, GSE286320 and GSE286432. Previously published RNA-seq datasets for Mayo Clinic PDX models and NU cohort that were re-analysed here are available under accession codes PRJNA548556 (ref. 24), SRR8236743 (ref. 3) and GSE147352 (ref. 21). The Ivy GAP dataset was acquired from its portal (https://glioblastoma.alleninstitute.org/)28. Publicly available datasets from the TCGA and CPTAC cohorts were obtained from the GDC Data Portal (https://portal.gdc.cancer.gov/). All other data supporting the findings of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.

References

  1. Horbinski, C., Berger, T., Packer, R. J. & Wen, P. Y. Clinical implications of the 2021 edition of the WHO classification of central nervous system tumours. Nat. Rev. Neurol. 18, 515–529 (2022).

    Article  PubMed  Google Scholar 

  2. Brennan, C. W. et al. The somatic genomic landscape of glioblastoma. Cell 155, 462–477 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  3. Wu, S. et al. Circular ecDNA promotes accessible chromatin and high oncogene expression. Nature 575, 699–703 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Morton, A. R. et al. Functional enhancers shape extrachromosomal oncogene amplifications. Cell 179, 1330–1341.e13 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Yan, X., Mischel, P. & Chang, H. Extrachromosomal DNA in cancer. Nat. Rev. Cancer 24, 261–273 (2024).

    Article  PubMed  CAS  Google Scholar 

  6. Westphal, M., Maire, C. L. & Lamszus, K. EGFR as a target for glioblastoma treatment: an unfulfilled promise. CNS Drugs 31, 723–735 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. McClellan, B. L. et al. Impact of epigenetic reprogramming on antitumor immune responses in glioma. J. Clin. Invest. 133, e163450 (2023).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  8. Esteller, M. et al. The epigenetic hallmarks of cancer. Cancer Discov. 14, 1783–1809 (2024).

    Article  PubMed  CAS  Google Scholar 

  9. Shvedunova, M. & Akhtar, A. Modulation of cellular processes by histone and non-histone protein acetylation. Nat. Rev. Mol. Cell Biol. 23, 329–349 (2022).

    Article  PubMed  CAS  Google Scholar 

  10. Roadmap Epigenomics Consortium et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).

  11. Ogryzko, V. V., Schiltz, R. L., Russanova, V., Howard, B. H. & Nakatani, Y. The transcriptional coactivators p300 and CBP are histone acetyltransferases. Cell 87, 953–959 (1996).

    Article  PubMed  CAS  Google Scholar 

  12. Maldotti, M. et al. The acetyltransferase p300 is recruited in trans to multiple enhancer sites by lncSmad7. Nucleic Acids Res. 50, 2587–2602 (2022).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Yokoyama, A., Niida, H., Kutateladze, T. G. & Cote, J. HBO1, a MYSTerious KAT and its links to cancer. Biochim. Biophys. Acta 1867, 195045 (2024).

  14. White, J. et al. Histone lysine acetyltransferase inhibitors: an emerging class of drugs for cancer therapy. Trends Pharmacol. Sci. 45, 243–254 (2024).

    Article  PubMed  CAS  Google Scholar 

  15. Mattick, J. S. et al. Long non-coding RNAs: definitions, functions, challenges and recommendations. Nat. Rev. Mol. Cell Biol. 24, 430–447 (2023).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Statello, L., Guo, C. J., Chen, L. L. & Huarte, M. Gene regulation by long non-coding RNAs and its biological functions. Nat. Rev. Mol. Cell Biol. 22, 96–118 (2021).

    Article  PubMed  CAS  Google Scholar 

  17. Ferrer, J. & Dimitrova, N. Transcription regulation by long non-coding RNAs: mechanisms and disease relevance. Nat. Rev. Mol. Cell Biol. 25, 396–415 (2024).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Bailey, C. et al. Origins and impact of extrachromosomal DNA. Nature 635, 193–200 (2024).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Tang, J. et al. Enhancing transcription-replication conflict targets ecDNA-positive cancers. Nature 635, 210–218 (2024).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Noorani, I. et al. Extrachromosomal DNA-driven oncogene spatial heterogeneity and evolution in glioblastoma. Cancer Discov. 15, 2078–2095 (2025).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Huang, T. et al. PRMT6 methylation of RCC1 regulates mitosis, tumorigenicity, and radiation response of glioblastoma stem cells. Mol. Cell 81, 1276–1291.e9 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Sur, S. & Ray, R. B. Emerging role of lncRNA ELDR in development and cancer. FEBS J. 289, 3011–3023 (2022).

    Article  PubMed  CAS  Google Scholar 

  23. Rossi, M. R. et al. Novel amplicons on the short arm of chromosome 7 identified using high resolution array CGH contain over expressed genes in addition to EGFR in glioblastoma multiforme. Genes Chromosomes Cancer 44, 392–404 (2005).

    Article  PubMed  CAS  Google Scholar 

  24. Vaubel, R. A. et al. Genomic and phenotypic characterization of a broad panel of patient-derived xenografts reflects the diversity of glioblastoma. Clin. Cancer Res. 26, 1094–1104 (2020).

    Article  PubMed  CAS  Google Scholar 

  25. Niazi, F. & Valadkhan, S. Computational analysis of functional long noncoding RNAs reveals lack of peptide-coding capacity and parallels with 3′ UTRs. RNA 18, 825–843 (2012).

  26. Wang, L. et al. CPAT: coding-potential assessment tool using an alignment-free logistic regression model. Nucleic Acids Res. 41, e74 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. Kong, L. et al. CPC: assess the protein-coding potential of transcripts using sequence features and support vector machine. Nucleic Acids Res. 35, W345–W349 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Puchalski, R. B. et al. An anatomic transcriptional atlas of human glioblastoma. Science 360, 660–663 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. Wu, S. et al. EGFR amplification induces increased DNA damage response and renders selective sensitivity to talazoparib (PARP inhibitor) in glioblastoma. Clin. Cancer Res. 26, 1395–1407 (2020).

    Article  PubMed  CAS  Google Scholar 

  30. Guo, G. et al. EGFR ligand shifts the role of EGFR from oncogene to tumour suppressor in EGFR-amplified glioblastoma by suppressing invasion through BIN3 upregulation. Nat. Cell Biol. 24, 1291–1305 (2022).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. Song, X. et al. RNA splicing analysis deciphers developmental hierarchies and reveals therapeutic targets in adult glioma. J. Clin. Invest. 134, e173789 (2024).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Lathia, J. D. et al. Integrin α6 regulates glioblastoma stem cells. Cell Stem Cell 6, 421–432 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Anido, J. et al. TGF-β receptor inhibitors target the CD44(high)/Id1(high) glioma-initiating cell population in human glioblastoma. Cancer Cell 18, 655–668 (2010).

    Article  PubMed  CAS  Google Scholar 

  34. Zhu, Y. et al. The long noncoding RNA glycoLINC assembles a lower glycolytic metabolon to promote glycolysis. Mol. Cell 82, 542–554.e6 (2022).

    Article  PubMed  CAS  Google Scholar 

  35. Haderk, F. et al. Focal adhesion kinase-YAP signaling axis drives drug-tolerant persister cells and residual disease in lung cancer. Nat. Commun. 15, 3741 (2024).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Chokshi, C. R. et al. Targeting axonal guidance dependencies in glioblastoma with ROBO1 CAR T cells. Nat. Med. 30, 2936–2946 (2024).

    Article  PubMed  CAS  Google Scholar 

  37. Lin, B. et al. EGFR, the Lazarus target for precision oncology in glioblastoma. Neuro Oncol. 24, 2035–2062 (2022).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. Huang, L. & Fu, L. Mechanisms of resistance to EGFR tyrosine kinase inhibitors. Acta Pharm. Sin. B 5, 390–401 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Dhaka, B. et al. Functional identification of cis-regulatory long noncoding RNAs at controlled false discovery rates. Nucleic Acids Res. 52, 2821–2835 (2024).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Luo, H. et al. HOTTIP-dependent R-loop formation regulates CTCF boundary activity and TAD integrity in leukemia. Mol. Cell 82, 833–851.e11 (2022).

  41. Fierro, C. et al. The long non-coding RNA NEAT1 is a deltaNp63 target gene modulating epidermal differentiation. Nat. Commun. 14, 3795 (2023).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. West, J. A. et al. The long noncoding RNAs NEAT1 and MALAT1 bind active chromatin sites. Mol. Cell 55, 791–802 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Li, L. et al. Transcriptional regulation of the Warburg effect in cancer by SIX1. Cancer Cell 33, 368–385.e7 (2018).

    Article  PubMed  CAS  Google Scholar 

  44. Niu, Z. et al. HBO1 catalyzes lysine lactylation and mediates histone H3K9la to regulate gene transcription. Nat. Commun. 15, 3561 (2024).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. Au, Y. Z. et al. KAT7 is a genetic vulnerability of acute myeloid leukemias driven by MLL rearrangements. Leukemia 35, 1012–1022 (2021).

    Article  PubMed  CAS  Google Scholar 

  46. Lv, W. et al. Long noncoding RNA lncMREF promotes myogenic differentiation and muscle regeneration by interacting with the Smarca5/p300 complex. Nucleic Acids Res. 50, 10733–10755 (2022).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  47. Lunde, B. M., Moore, C. & Varani, G. RNA-binding proteins: modular design for efficient function. Nat. Rev. Mol. Cell Biol. 8, 479–490 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Chen, Q. et al. Histone acetyltransferases CBP/p300 in tumorigenesis and CBP/p300 inhibitors as promising novel anticancer agents. Theranostics 12, 4935–4948 (2022).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Bell, R. J. et al. Cancer. The transcription factor GABP selectively binds and activates the mutant TERT promoter in cancer. Science 348, 1036–1039 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Mancini, A. et al. Disruption of the β1L isoform of GABP reverses glioblastoma replicative immortality in a TERT promoter mutation-dependent manner. Cancer Cell 34, 513–528.e8 (2018).

  51. Lasko, L. M. et al. Discovery of a selective catalytic p300/CBP inhibitor that targets lineage-specific tumours. Nature 550, 128–132 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Su, Z., Zhang, Y., Tang, J., Zhou, Y. & Long, C. Multifunctional acyltransferase HBO1: a key regulatory factor for cellular functions. Cell. Mol. Biol. Lett. 29, 141 (2024).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Fang, Z. et al. NOGOB receptor deficiency increases cerebrovascular permeability and hemorrhage via impairing histone acetylation-mediated CCM1/2 expression. J. Clin. Invest. 132, e151382 (2022).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  54. Kueh, A. J. et al. Stem cell plasticity, acetylation of H3K14, and de novo gene activation rely on KAT7. Cell Rep. 42, 111980 (2023).

    Article  PubMed  CAS  Google Scholar 

  55. Xiao, Y. et al. HBO1 is a versatile histone acyltransferase critical for promoter histone acylations. Nucleic Acids Res. 49, 8037–8059 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Reifenberger, G., Wirsching, H. G., Knobbe-Thomsen, C. B. & Weller, M. Advances in the molecular genetics of gliomas - implications for classification and therapy. Nat. Rev. Clin. Oncol. 14, 434–452 (2017).

    Article  PubMed  CAS  Google Scholar 

  57. Guo, G. et al. A TNF-JNK-Axl-ERK signaling axis mediates primary resistance to EGFR inhibition in glioblastoma. Nat. Neurosci. 20, 1074–1084 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Korovina, I., Vehlow, A., Temme, A. & Cordes, N. Targeting integrin α2 as potential strategy for radiochemosensitization of glioblastoma. Neuro Oncol. 25, 648–661 (2023).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  59. Ahn, B. Y. et al. Glioma invasion mediated by the p75 neurotrophin receptor (p75(NTR)/CD271) requires regulated interaction with PDLIM1. Oncogene 35, 1411–1422 (2016).

    Article  PubMed  CAS  Google Scholar 

  60. Li, Y. et al. TRAF4 maintains deubiquitination of caveolin-1 to drive glioblastoma stemness and temozolomide resistance. Cancer Res. 82, 3573–3587 (2022).

    Article  PubMed  CAS  Google Scholar 

  61. Ding, J. et al. EGFR suppresses p53 function by promoting p53 binding to DNA-PKcs: a noncanonical regulatory axis between EGFR and wild-type p53 in glioblastoma. Neuro Oncol. 24, 1712–1725 (2022).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  62. Mao, P. et al. Mesenchymal glioma stem cells are maintained by activated glycolytic metabolism involving aldehyde dehydrogenase 1A3. Proc. Natl Acad. Sci. USA 110, 8644–8649 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  63. Park, H. S. et al. Targeting YAP-p62 signaling axis suppresses the EGFR-TKI-resistant lung adenocarcinoma. Cancer Med. 10, 1405–1417 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  64. Rinaldi, C. & Wood, M. J. A. Antisense oligonucleotides: the next frontier for treatment of neurological disorders. Nat. Rev. Neurol. 14, 9–21 (2018).

    Article  PubMed  CAS  Google Scholar 

  65. Goenka, A. et al. Oncogenic long noncoding RNA LINC02283 enhances PDGF receptor A-mediated signaling and drives glioblastoma tumorigenesis. Neuro Oncol. 25, 1592–1604 (2023).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  66. Bhat, K. P. L. et al. Mesenchymal differentiation mediated by NF-κB promotes radiation resistance in glioblastoma. Cancer Cell 24, 331–346 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  67. Huang, T. et al. A regulatory circuit of miR-125b/miR-20b and Wnt signalling controls glioblastoma phenotypes through FZD6-modulated pathways. Nat. Commun. 7, 12885 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  68. Gel, B. et al. regioneR: an R/Bioconductor package for the association analysis of genomic regions based on permutation tests. Bioinformatics 32, 289–291 (2016).

    Article  PubMed  CAS  Google Scholar 

  69. Stark, R. & Brown, G. DiffBind: differential binding analysis of ChIP-seq peak data. R package version 100, 2–21 (2011).

    Google Scholar 

  70. Rosenbloom, K. R. et al. ENCODE data in the UCSC Genome Browser: year 5 update. Nucleic Acids Res. 41, D56–D63 (2013).

    Article  PubMed  CAS  Google Scholar 

  71. Eley, G. D. et al. A chromosomal region 7p11.2 transcript map: its development and application to the study of EGFR amplicons in glioblastoma. Neuro Oncol. 4, 86–94 (2002).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Acknowledgements

All shared resources at RHLCC and NU Feinberg School of Medicine were supported by National Cancer Institute Cancer Center grant P30CA060553. We thank E. Sulman and J. Sarkaria for providing the GSC cell lines and GBM6 cells. We thank the NU Feinberg School of Medicine Center for Advanced Microscopy/Nikon Imaging Center and NUSeq core for help with experiments. This work was supported by US NIH grants NS113160, NS126810, NS115403, NS122375 and NS125318 (S.-Y.C.); NIH CA234799, United States Army Medical Research Acquisition Activity W81XWH-22-10373 (D.T.); W81XWH-22-1-0374 and HT9425-24-1-0573 (X.S.); NIH CA259388 and GM142441 (R.Y.); and CA285684, CA278832, CA256741 and P50CA180995 Development Research Program, the Polsky Urologic Cancer Institute of the Robert H. Lurie Comprehensive Cancer Center of NU at Northwestern Memorial Hospital (Q.C.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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  1. Deanna Tiek

    Present address: Center for Immunotherapy & Precision Immuno-Oncology, Cleveland Clinic, Cleveland, OH, USA

Authors and Affiliations

  1. The Ken & Ruth Davee Department of Neurology, The Lou and Jean Malnati Brain Tumor Institute, The Robert H. Lurie Comprehensive Cancer Center, Simpson Querrey Institute for Epigenetics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

    Xiaozhou Yu, Xiao Song, Deanna Tiek, Runxin Wu, Qiu He, Maya Walker, Bo Hu & Shi-Yuan Cheng

  2. Department of Urology, Northwestern University Feinberg School of Medicine, Department of Urology & Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

    Richard A. Schäfer, Qingshu Meng, Qi Cao & Rendong Yang

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Contributions

Conceptualization, S.-Y.C., B.H. and X.Y.; data production, analysis and investigation, X.Y., X.S., R.A.S., Q.M., R.W., S.-Y.C. and B.H.; writing-original draft: X.Y., B.H. and S.-Y.C., review and editing: X.Y., S.-Y.C., X.S., R.A.S., D.T., R.W., Q.H., M.W., B.H., Q.C. and R.Y. Supervision, S.-Y.C. and B.H.; funding acquisition, S.-Y.C. and B.H. All authors have read and agreed to the published version of the paper.

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Correspondence to Bo Hu or Shi-Yuan Cheng.

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Extended data

Extended Data Fig. 1 The lncRNA ELDR is co-amplified with EGFR in GBM.

a, Heatmap depicts expressions of 118 lncRNAs that exhibited significant correlation with EGFR expression in NU GBM samples (|r | > 0.4 and p < 0.05). Expression levels of lncRNAs and EGFR are indicated. b, The correlation in RNA transcripts between EGFR and ELDR in CPTAC (n = 94) GBM samples. c, Percentage of ELDR amplification in GBM patients with or without EGFR amplification in TCGA (n = 284/319 vs. 2/223) and CPTAC (n = 61/64 vs. 0/35). d, Expression of ELDR RNA in normal brain (n = 5), LGG (n = 530), and GBM (n = 169) in TCGA dataset. e, Kaplan–Meier analysis of ELDR expression in TCGA glioma samples. f, TCGA Pan-Cancer analysis of expression of RNA transcript at the ELDR locus via the UALCAN portal (https://ualcan.path.uab.edu/). In box-and-whisker plots, the centre line indicates the median; the box boundaries represent the interquartile range (25th–75th percentiles); and the whiskers show the minimum and maximum values. BLCA, bladder urothelial carcinoma (n = 414); BRCA, breast invasive carcinoma (n = 1102); CESC, cervical squamous cell carcinoma and endocervical adenocarcinoma (n = 304); COAD, colon adenocarcinoma (n = 478); CHOL, cholangiocarcinoma (n = 36); ESCA, oesophageal carcinoma (n = 161); GBM, glioblastoma (n = 156); HNSC, head and neck squamous cell carcinoma (n = 500); KICH, kidney chromophobe (n = 65); KIRC, kidney renal clear cell carcinoma (n = 538); KIRP, kidney renal papillary cell carcinoma (n = 288); LIHC, liver hepatocellular carcinoma (n = 371); LUAD, lung adenocarcinoma (n = 533); LUSC, lung squamous cell carcinoma (n = 502); PAAD, pancreatic adenocarcinoma (n = 177); PCPG, pheochromocytoma and paraganglioma (n = 178); PRAD, prostate adenocarcinoma (n = 498); READ, rectum adenocarcinoma (n = 166); SARC, sarcoma (n = 259); STAD, stomach adenocarcinoma (n = 375); THCA, thyroid carcinoma (n = 502); THYM, thymoma (n = 119); UCEC, uterine corpus endometrial carcinoma (n = 551); ACC, adrenocortical carcinoma (n = 79); DLBC, diffuse large B-cell lymphoma (n = 48); LGG, low-grade glioma (n = 511); UCS, uterine serous carcinoma (n = 56); UVM, uveal melanoma (n = 80); OV, ovarian serous cystadenocarcinoma (n = 374); LAML, acute myeloid leukaemia (n = 151); MESO, mesothelioma (n = 86); TGCT, testicular germ cell tumour (n = 150); SKCM, skin cutaneous melanoma (n = 103); Mets, metastasis (n = 367). g, Correlation of EGFR and ELDR RNA expression in head and neck squamous cell carcinoma (HNSC; n = 381) and lung adenocarcinoma (LUAD; n = 389) samples. h, The correlation of CNV between EGFR and ELDR gene loci in HNSC (n = 399) and LUAD (n = 562) samples. i, Proportion of ELDR amplification in HNSC (with EGFR amplification: 11/17; without: 6/382) and LUAD (with: 15/22; without: 9/540). Two-sided Spearman’s rank correlation test in a, b, g, h, one-way ANOVA with Tukey’s post hoc test in d, log-rank test in e. Data are presented as mean ± s.d. (d).

Source data

Extended Data Fig. 2 De novo lncRNA HELDR is the major transcript in the ELDR locus and localized in the nucleus.

a, b, Integrative genomics viewer (IGV) showed short-read RNA-seq of GSC34 and GBM39 at the ELDR locus. c, Agarose gel electrophoresis. 5’ rapid amplification of cDNA ends (RACE) and 3’ RACE for HELDR transcripts in GBM6. Data are representative of three independent experiments with similar results. d, Representative Sanger sequencing for 5’ RACE and 3’ RACE products. e, Open reading frame (ORF) assessment using the ORF Finder (https://www.ncbi.nlm.nih.gov/orffinder). No ORFs > 300 nt were detected. f, Coding potential of indicated genes predicted by an online software CPC (https://cpc.gao-lab.org/). g, UCSC Genome Browser tracks showing HELDR conservation (PhyloP 100, vertebrates) and ENCODE70 ChIP–seq marks for enhancers (H3K4me1), promoters (H3K4me3), and active regulatory elements (H3K27ac). h, RNA-seq data from the Ivy Glioblastoma Atlas Project showing HELDR expression across GBM anatomical regions (LE, leading edge, n = 7; IT, infiltrating tumour, n = 9; CT, cellular tumour, n = 36; PZ, perinecrotic zone, n = 12; PS, pseudopalisading cells around necrosis, n = 14; HPV, hyperplastic blood vessels in the cellular tumour, n = 10; MP, microvascular proliferation, n = 11). i, Correlation of EGFR and HELDR RNA expression in Ivy GAP dataset (n = 269). Kruskal–Wallis test followed by Dunn’s multiple comparisons test in h, two-sided Spearman’s rank correlation test in i, the centre line marks the median, the box spans the 25th–75th percentiles, and the whiskers extend to the minimum and maximum in h.

Source data

Extended Data Fig. 3 HELDR is critical for cell proliferation and tumorigenicity.

a, smFISH for HELDR in GSC34 and GSC11 cells (representative of 50 cells). Cells treated with RNase served as a negative control. Arrow: HELDR. b, smFISH quantification of HELDR loci per cell (n = 50 cells). c, HELDR expression (TPM) from RNA-seq. d, qRT–PCR for HELDR expression in U87, patient-derived GSCs, and patient-derived xenograft (PDX) GBM6 cell lines with indicated levels of EGFR expression (n = 3). HELDR was presented as the log2 of its relative expression level. e, qRT–PCR of HELDR in GSCs and matched differentiated glioblastoma cells (DGCs) (n = 3). f, qRT–PCR for shRNA KD of HELDR in GSC34 (n = 3) cells that EGFR is amplified. g, Cell proliferation for GSC34 (n = 3) cells with or without HELDR KD. h, Glioma sphere formation (self-renewal capacity) of GSC34 cells with or without HELDR KD. i, IB for representative GBM stem-cell markers in GSCs with or without HELDR KD. β-actin is a sample processing control. j, CRISPR-Cas9-mediated HELDR deletion (Del) in GSCs. k, l, PCR (k) and Sanger sequencing (l) for two single clones of CRISPR/Cas9-mediated HELDR deletion GSC17 cells. m, qRT–PCR results confirmed deletion (Del) of HELDR in GSC17 cells (n = 3). n, Cell proliferation for GSC17 cells with or without HELDR deletion (n = 6). o, Self-renewal capacity of GSC17 cells with or without HELDR deletion. p, Representative BLI images of indicated GSC17 tumour xenograft-bearing mice. q, Kaplan–Meier analysis of GSC17 tumour xenograft-bearing mice (n = 5). r, s, qRT–PCR for shRNA KD of HELDR and overexpression of shRNA-resistant HELDR in GSC17 (n = 3) and GSC34 cells (n = 3). t, u, Cell proliferation for GSC17 (n = 3) and GSC34 (n = 3) cells with HELDR KD and overexpression of shRNA-resistant HELDR. v, w, Glioma sphere formation of GSC17 and GSC34 cells with HELDR KD and overexpression of shRNA-resistant HELDR. Scale bar, 10 μm. All blots, qRT–PCR, and in vitro assays are representative of three independent experiments. Two-sided unpaired t-test in e, one-way ANOVA with Dunnett’s post hoc test in f, g, m, n, two-sided likelihood ratio test in h, o, v, w, log-rank test in q, one-way ANOVA with Tukey’s post hoc test in r-u. Data are shown as mean ± s.d. (b, d-g, m, n, and r-u).

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Extended Data Fig. 4 EGFR pathway activity is unaffected by HELDR, and EGFR does not affect HELDR expression.

a, Diagram of EGFR, ELDR/HELDR gene locus and nearby genes in Chromosome (Chr) 7 genomic DNA71 or ecDNAs3,4 in GBM. b, Dot plot showing expression changes of the indicated genes at the EGFR and ELDR/HELDR loci in GSC17 cells after HELDR knockdown with two independent shRNAs. The box highlights SEC61G, the only gene significantly regulated by HELDR KD in both shRNAs. c, IB for EGFR and EGFR downstream signalling proteins in GSC34 or GSC11 cells with or without HELDR KD. d, e, IB of EGFR-pathway proteins (d) and qRT–PCR (n = 3) of HELDR (e) in GSCs with or without EGFR knockdown or treatment with the EGFR inhibitor erlotinib. β-actin is a sample processing control in c and d. All blots and qRT–PCR are representative of three independent experiments. Two-sided Wald test with Benjamini–Hochberg adjustment for multiple comparisons in b, one-way ANOVA with Dunnett’s post hoc test in e, Data are shown as mean ± s.d. (e).

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Extended Data Fig. 5 HELDR exhibits widespread genomic DNA binding.

a, b, ChIRP-seq targeting NEAT1 (a) and MALAT1 (b) visualized in IGV at the NEAT1 and MALAT1 loci (GSC17). c, d, Venn diagrams illustrating the shared and distinct peaks identified by ChIRP-seq targeting NEAT1 (c) or MALAT1 (d) in comparison with HELDR (GSC17). e, Bar plot showing common peak number of ChIRP-seq in probe targeting HELDR and negative controls including RNase-treated sample before hybridization, probes targeting antisense strand of HELDR, and HELDR negative cell (GSC1478). f, Volcano plot showing log2 fold changes and adjusted p-values (padj) for HELDR occupancy (ChIRP-seq) differences between control and HELDR-KD GSC17 cells across 7,095 HELDR binding sites (Supplementary Table 5). Peaks with |log2FC | > 1 and padj < 0.05 were considered significant. g, IGV of two representative genes, UBASH3B and ATP2B4 that were identified in HELDR ChIRP-seq and RNA-seq analysis. The peaks of HELDR ChIRP-seq in the promoter region are shaded. h, ChIRP–qPCR: Enrichment of HELDR at the promoters of KAT7 (n = 3), UBASH3B (n = 3), and ATP2B4 (n = 3) in GSC17 cells. qPCR assays are representative of three independent experiments. Two-sided Wald test with Benjamini–Hochberg adjustment for multiple comparisons in f, two-sided unpaired t-test in h, Data are presented as mean ± s.d. (h).

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Extended Data Fig. 6 HELDR facilitates KAT7 gene expression through recruiting p300 to the KAT7 gene promoter.

a, IB for KAT7 protein expression in GSC34 and GSC11 cells with or without HELDR KD. b, IB of KAT7 in GSCs with or without EGFR KD or treatment with the EGFR inhibitor erlotinib. c-e, Representative images of HELDR smFISH with IF for KAT7 or EGFR in GSCs (representative of 50 cells). Arrow: HELDR. f-h, Representative HELDR smFISH with IF for KAT7 or EGFR in human GBM tissue (representative of 7 patients). Arrow: HELDR. i, Gene correlation analysis of HELDR and KAT7 genes in TCGA (n = 169) and CPTAC (n = 91) GBM samples. j, Correlation analysis of RNA-seq data for EGFR RNA in relation to KAT7 in GBM of indicated datasets (TCGA, n = 169; CPTAC, n = 91; NU, n = 47). k, Images of smFISH (HELDR) and IF (p300) in GSC34 and GSC11 cells (representative of 30 cells). Arrow: HELDR. l, HELDR localization compared between top-50% and bottom-50% p300 intensity regions within each nucleus (n = 30 cells). m, n, ChIP-qPCR. Enrichment of p300 (left) and H3K27ac (right) at the KAT7 gene promoter in GSC34 (n = 3) and GSC11 (n = 3) cells with or without HELDR KD. IgG is a control. o, Sequence logo plot and enrichment of ETS family member-binding motif in HELDR ChIRP-seq. Scale bar, 10 μm. β-actin is a sample processing control in a and b. All blots and qPCR are representative of three independent experiments. Two-sided Spearman’s rank correlation test in i, j, two-sided paired t-test in l, two-sided unpaired t-test in m, n, one-sided cumulative binomial test in o, Data are presented as mean ± s.d. (l-n).

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Extended Data Fig. 7 HELDR recruits p300 and ETS transcription factors to the KAT7 promoter to promote KAT7 transcription.

a, b, ChIP-qPCR. Enrichment of GABPA at KAT7 gene promoters were compared in GSC34 (n = 3) and GSC11 (n = 3) cells with or without HELDR KD. IgG is a control. c, IB for GABPA protein expression in GSCs with or without HELDR KD. d-g, ChIP-re-ChIP-qPCR. Enrichment of P300/GABPA (n = 3) or H3K27ac/GABPA (n = 3) complexes at KAT7 gene promoters were compared in GSC34 or GSC11 cells with or without HELDR KD. The first ChIP was performed with p300, H3K27ac, or IgG, followed by a second ChIP using GABPA. IgG is a control in (a, b, and d-g). h-l, Effects of ± treatment of 5 μM p300 inhibitor A-485 on KAT7 protein expression (h, IB, treatment for three days), cell proliferation (n = 3) (i, j) or self-renewal (glioma sphere formation, k, l) in GSC34 or GSC11 cells with or without HELDR KD. β-actin is a sample processing control in c and h. All blots, qPCR, and in vitro assays are representative of three independent experiments. Two-sided unpaired t-test in a, b, and d-g, one-way ANOVA with Tukey’s post hoc test in i and j, two-sided likelihood ratio test in k and l. Data are presented as mean ± s.d. (a, b, d-g, i, and j).

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Extended Data Fig. 8 KAT7 mediates HELDR-promoted GBM tumorigenesis by inducing transcriptions of genes that are critical for GBM malignancy.

a, IB for KAT7 proteins and its substrate H3K14ac and H4K12ac in GSCs with or without KAT7 KD. b, c, KAT7 KD inhibits cell proliferation (n = 3) (b) and glioma sphere formation (c) in GSCs. d-f, Re-expression of KAT7 rescued HELDR KD-suppressed KAT7 proteins and its substrate H3K14ac and H4K12ac (d, IB), cell proliferation (n = 3) (e), and glioma sphere formation (f) of GSCs. g, Co-regulated genes shared between KAT7 knockdown and HELDR knockdown in GSC17 cells (two biological replicates). The dot plot shows gene-expression changes after HELDR knockdown (shRNA-2). h, ChIP-qPCR. Enrichment of KAT7 (see Fig. 6k) and IgG (negative control) at the promoters of indicated genes in GSC17 cells, with or without HELDR KD or rescue by KAT7 OE (n = 3). i-k, ChIP-qPCR. Enrichment of KAT7 (n = 3) (i), H3K14ac (n = 3) (j), and H4K12ac (n = 3) (k) at the promoters of indicated genes in GSC17 cells with or without KAT7 KD. β-actin is a sample processing control in a and d. All blots, qPCR, and in vitro assays are representative of three independent experiments. One-way ANOVA with Dunnett’s post hoc test in b, two-sided likelihood ratio test in c and f, one-way ANOVA with Tukey’s post hoc test in e and h, two-sided Wald test with Benjamini–Hochberg adjustment for multiple comparisons in g, two-sided unpaired t-test in i-k. Data are presented as mean ± s.d. (b, e, and h-k).

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Extended Data Fig. 9 KAT7 inhibitor WM-3835 synergistically enhanced anti-GBM activity of EGFR inhibitor erlotinib.

a, Cell viability of EGFR-amplified (GSC11, GBM6) and non-amplified (GSC1478, GSC157) GSC/GBM cells after 6 days of erlotinib treatment at indicated concentrations (n = 3). b, Cell inhibition rates for combinations of indicated concentrations of KAT7 inhibitor (WM-3835) and EGFR inhibitor (Erlotinib) are presented in the matrix. Data were obtained by cell viability assays. c, Cell viability of EGFR-amplified (GSC11, GBM6) and non-amplified (GSC1478, GSC157) GSC/GBM cells after 6 days of WM-3835 treatment at indicated concentrations (n = 3). d, IB for indicated protein expressions in GSC11 or GBM6 cells treated with vehicle or WM-3835 for 72 h. β-actin is a sample processing control. e, Representative images of IF staining for brain sections with GBM6 xenograft tumours with indicated treatments. f, Quantification of IF staining for brain sections with GBM6 (n = 5) and GSC11 (n = 5) xenograft tumours. Scale bar, 100 μm. All blots and in vitro assays are representative of three independent experiments. By one-way ANOVA with Tukey’s post hoc test. Data are presented as mean ± s.d. (a, c, and f).

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Extended Data Fig. 10 ASO-mediated inhibition of HELDR synergistically enhanced anti-GBM activity of EGFR inhibitor erlotinib.

a, qRT–PCR analysis of GSC11 cells 24 h after transfection with 100 nM HELDR-targeting ASOs or a control ASO in vitro (n = 3). b, c, IB for indicated proteins in GBM6 and GSC11 cells 72 h after transfection with 100 nM HELDR-targeting ASOs or a control ASO in vitro. d, Cell viability of EGFR-amplified (GSC11, GBM6) and non-amplified (GSC1478, GSC157) GSC/GBM cells after 6 days of indicated ASO treatment (n = 3). e-j, Cell proliferation (n = 3) (e-g), and glioma sphere formation (h-j) with indicated treatment. In d-j, ASO, 100 nM; Erlotinib, 0.8 μM. k, Analysis of coding DEGs from RNA-seq of GSC17 cells 24 h after transfection with 100 nM control or HELDR-targeting ASO in vitro (two biological replicates; threshold: |fold change|> 1.5 and adjusted p < 0.05). Venn diagrams showing common coding DEGs between HELDR knockdown by shRNA (shared by both shRNAs; see Fig. 3n) and ASO treatment. l, BLI images for mice bearing GSC11 brain tumour xenografts with indicated treatments (n = 5 in each group). Treatments: ASO, 4 µg/mouse, twice/week, erlotinib, 50 mg/kg, 5 days on/2 days off; until morbibund. m, qRT–PCR analysis of HELDR expression in tumour area from brain sections (n = 4). n, Representative images of IF staining for brain sections with GBM6 xenograft tumours with indicated treatments. o-q, Quantification of IF staining shown in n (n = 5). r-t, Quantification of IF staining for brain sections with GSC11 xenograft tumours with indicated treatments (n = 5). Scale bar, 100 μm. β-actin is a sample processing control in b and c. All blots, qRT-PCR, and in vitro assays are representative of three independent experiments. One-way ANOVA with Dunnett’s post hoc test in a, two-sided unpaired t-test in d, one-way ANOVA with Tukey’s post hoc test in e-g, m, and o-t, two-sided likelihood ratio test in h-j, two-sided Wald test with Benjamini–Hochberg adjustment for multiple comparisons in k, Data are presented as mean ± s.d. (a, d, e-g, m, and o-t).

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Yu, X., Song, X., Schäfer, R.A. et al. An EGFR co-amplified lncRNA HELDR promotes glioblastoma malignancy through KAT7-driven gene programs. Nat Cell Biol (2026). https://doi.org/10.1038/s41556-026-01924-w

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