Recurrent mechanisms of biallelic epigenetic inactivation reveal new putative tumour suppressor genes in prostate cancer

Kiriy, Daria, Favero, Francesco, Gerhäuser, Clarissa, Heilmann, Jessica, Lutsik, Pavlo, Rodriguez Gonzalez, Francisco German, Locallo, Alessio, Schmidt Jespersen, Jakob, Gruber, Andreas J., Olsen, André V., Hernando, Barbara, Cheng, Kevin C. L., Pellegrina, Diogo, Macintyre, Andreas J., Bova, G. Steven, Brewer, Daniel S. ORCID: https://orcid.org/0000-0003-4753-9794, Bristow, Robert G., Brook, Mark, Brors, Benedikt, Butler, Adam, Cancel-Tassin, Géraldine, Corcoran, Niall M., Cussenot, Olivier, Eeles, Ros A., Gihawi, Abraham ORCID: https://orcid.org/0000-0002-3676-5561, Girma, Etsehiwot G., Gnanapragasam, Vincent J., Hamid, Anis, Hayes, Vanessa M., He, Housheng Hansen, Hovens, Christopher M., Imada, Eddie Luidy L., Jakobsdottir, G. Maria, Jung, Chol-Hee, Khani, Francesca, Kote-Jarai, Zsofia, Lamy, Philippe P., Leeman, Gregory, Loda, Massimo, Marchionni, Luigi, Molania, Ramyar, Papenfuss, Anthony T., Pope, Bernard, Queiroz, Lucio R., Rausch, Tobias, Robinson, Brian, Sahli, Atef, Sørensen, Karina D., Uhrig, Sebastian, Wedge, David C., Xu, Yaobo, Yamaguchi, Takafumi N., Zanettini, Claudio, Cooper, Colin S. ORCID: https://orcid.org/0000-0003-2013-8042, Schlomm, Thorsten, Reimand, Jüri and Weischenfeldt, Joachim (2026) Recurrent mechanisms of biallelic epigenetic inactivation reveal new putative tumour suppressor genes in prostate cancer. Nature Communications, 17 (1). p. 9646. ISSN 2041-1723

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Abstract

The inactivation of tumour suppressor genes is a key step in cancer development, and is usually achieved by homozygous loss. In prostate cancer, however, large genomic regions are often hemizygously lost, which complicates the identification of putative tumour suppressors in these regions. Here, we develop Epi2Hit, an integrative computational method that leverages whole genome sequencing, epigenomic profiling and gene expression to identify biallelic inactivation of tumour suppressor genes involving DNA methylation of promoter and enhancer regions of one allele and genomic loss of the other allele. We apply Epi2Hit to a cohort of 2,021 prostate cancers to discover tumour suppressor genes. In particular, we identify epigenetic biallelic inactivation of ZFHX3 at a recurrence level similar to TP53. Biallelic inactivation of ZFHX3, a transcriptional repressor, leads to upregulation of oncogenes, including MYC and a shorter time to metastasis. Finally, we provide evidence that epigenetic silencing as 2nd hit is particularly enriched in regions with nearby essential genes, precluding homozygous loss.

Item Type:	Article
Additional Information:	Data availability PPCG dataset comprises whole-genome sequencing (WGS), RNA-seq, DNA methylation, clinical, and histopathological data from 2,021 prostate cancer donors. Due to the sensitive nature of human genomic/clinical data and participant-consent restrictions, PPCG data are provided under controlled access and are available only for approved research purposes. Raw genome sequencing data have been deposited in the European Genome-Phenome 1360 Archive (EGA) under the study ID EGAS00001002876 and is described in the Reporting Summary and our companion manuscript29. In addition, PPCG working project data (e.g., variant calls, pipeline outputs and intermediate analyses) and harmonised RNA-seq/methylation data are made available to approved projects through secure transfer (Globus), and clinical/histopathological data are hosted in a GDPR-compliant secure environment (REDCap); access is limited to approved PPCG researchers. Access to PPCG controlled data requires submission of a Project Concept Form, available at https://panprostate.org, and approval by the PPCG Steering Committee. Requests are submitted by emailing the completed form to PPCG@icr.ac.uk. We will respond to the data access request within 14 days. We will provide guidance on the application process; access, once granted, is provided for the duration of the approved project under the applicable data access agreement/terms. To support reproducibility without redistribution of controlled PPCG data, we provide a compact, self-contained example dataset in the project repository that is sufficient to run the Epi2Hit workflow end-to-end and reproduce representative outputs. Specifically, the repository includes a TCGA-PRAD chromosome 8 example dataset (450 K methylation β-values for chr8, a matched gene expression matrix, prostate ATAC-seq peaks, ChromHMM segmentation, and Hi-C loops), together with example mutation calls and copy-number segment inputs used for downstream biallelic analyses. These files are provided under the repository’s data/ directory and are used by analysis/TCGA_run.ipynb (and the containerised demo) to reproduce the main workflow outputs on the example dataset. The publicly available data used in this study are available in the NCBI Gene Expression Omnibus (GEO) database under accession code GSE164347 (prostate Hi-C loops): https://www-ncbi-nlm-nih-gov.uea.idm.oclc.org/geo/query/acc.cgi?acc=GSE16434737. The publicly available data used in this study are available in the GEO database under accession code GSE188797 (tumour ATAC-seq peaks): https://www-ncbi-nlm-nih-gov.uea.idm.oclc.org/geo/query/acc.cgi?acc=GSE18879736. The publicly available data used in this study are available in the GEO database under accession code GSE49402 (GSM1208743, ZFHX3 ChIP-seq): https://www-ncbi-nlm-nih-gov.uea.idm.oclc.org/geo/query/acc.cgi?acc=GSE4940272. The publicly available data used in this study are available from the ENCODE Project database (epigenetic marks (H3K4me3, H3K27ac) and CTCF tracks derived for prostate cancer cells (PC-3, C4-2B)): https://www.encodeproject.org/110. The remaining data are available within the Article, Supplementary Information or Source Data file. Source data are provided with this paper. Code availability: Code used to generate results and plots are available at https://github.com/panprostate/Epi2Hit. A static version of the code is available at https://doi-org.uea.idm.oclc.org/10.5281/ZENODO.18788787122.
Uncontrolled Keywords:	sdg 3 - good health and well-being ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being
Faculty \ School:	Faculty of Medicine and Health Sciences > Norwich Medical School
UEA Research Groups:	Faculty of Medicine and Health Sciences > Research Groups > Cancer Studies Faculty of Medicine and Health Sciences > Research Centres > Metabolic Health
Related URLs:	https://www.scopus.com/pages/publication...
Depositing User:	LivePure Connector
Date Deposited:	18 Sep 2026 14:19
Last Modified:	21 Sep 2026 12:43
URI:	https://ueaeprints.uea.ac.uk/id/eprint/104586
DOI:	10.1038/s41467-026-72182-5

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