Integrated analyses highlight interactions between the three-dimensional genome and DNA, RNA and epigenomic alterations in metastatic prostate cancer.

Journal

Nature genetics

ISSN: 1546-1718

Titre abrégé: Nat Genet

Pays: United States

ID NLM: 9216904

Informations de publication

Date de publication:
17 Jul 2024

Historique:

received: 16 05 2023

accepted: 10 06 2024

medline: 18 7 2024

pubmed: 18 7 2024

entrez: 17 7 2024

Statut: aheadofprint

Résumé

The impact of variations in the three-dimensional structure of the genome has been recognized, but solid cancer tissue studies are limited. Here, we performed integrated deep Hi-C sequencing with matched whole-genome sequencing, whole-genome bisulfite sequencing, 5-hydroxymethylcytosine (5hmC) sequencing and RNA sequencing across a cohort of 80 biopsy samples from patients with metastatic castration-resistant prostate cancer. Dramatic differences were present in gene expression, 5-methylcytosine/5hmC methylation and in structural variation versus mutation rate between A and B (open and closed) chromatin compartments. A subset of tumors exhibited depleted regional chromatin contacts at the AR locus, linked to extrachromosomal circular DNA (ecDNA) and worse response to AR signaling inhibitors. We also identified topological subtypes associated with stark differences in methylation structure, gene expression and prognosis. Our data suggested that DNA interactions may predispose to structural variant formation, exemplified by the recurrent TMPRSS2-ERG fusion. This comprehensive integrated sequencing effort represents a unique clinical tumor resource.

Identifiants

DOI: 10.1038/s41588-024-01826-3 PMID: 39020220

pubmed: 39020220

doi: 10.1038/s41588-024-01826-3

pii: 10.1038/s41588-024-01826-3

doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

Subventions

Organisme : U.S. Department of Defense (United States Department of Defense)

ID : W81XWH2010799

Organisme : U.S. Department of Defense (United States Department of Defense)

ID : W81XWH-21-1-0046

Organisme : U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)

ID : 1DP2CA271832-01, P30 CA014520

Organisme : NCI NIH HHS

ID : P30 CA014520

Pays : United States

Organisme : U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)

ID : R01 CA251245, P50 CA097186, P50 CA186786, P50 CA186786-07S1, P30 CA046592, and W81XWH-20-1-0405

Organisme : EIF | Stand Up To Cancer (SU2C)

ID : SU2C-AACR-DT0812

Investigateurs

Adina M Bailey (AM)

Li Zhang (L)

Tomasz M Beer (TM)

George Thomas (G)

Kim N Chi (KN)

Martin Gleave (M)

Amina Zoubeidi (A)

Robert E Reiter (RE)

Matthew B Rettig (MB)

Owen Witte (O)

Rohit Bose (R)

Franklin W Huang (FW)

Larry Fong (L)

Primo N Lara (PN)

Christopher P Evans (CP)

Jiaoti Huang (J)

Informations de copyright

Références

Abeshouse, A. et al. The molecular taxonomy of primary prostate cancer. Cell 163, 1011–1025 (2015).

doi: 10.1016/j.cell.2015.10.025

Pomerantz, M. M. et al. The androgen receptor cistrome is extensively reprogrammed in human prostate tumorigenesis. Nat. Genet. 47, 1346–1351 (2015).

pubmed: 26457646 pmcid: 4707683 doi: 10.1038/ng.3419

Armenia, J. et al. The long tail of oncogenic drivers in prostate cancer. Nat. Genet. 50, 645–651 (2018).

pubmed: 29610475 pmcid: 6107367 doi: 10.1038/s41588-018-0078-z

Quigley, D. A. et al. Genomic hallmarks and structural variation in metastatic prostate cancer. Cell 174, 758–769 (2018).

pubmed: 30033370 pmcid: 6425931 doi: 10.1016/j.cell.2018.06.039

Zhao, S. G. et al. The DNA methylation landscape of advanced prostate cancer. Nat. Genet. 52, 778–789 (2020).

pubmed: 32661416 pmcid: 7454228 doi: 10.1038/s41588-020-0648-8

Sjöström, M. et al. The 5-hydroxymethylcytosine landscape of prostate cancer. Cancer Res. 82, 3888–3902 (2022).

pubmed: 36251389 pmcid: 9627125 doi: 10.1158/0008-5472.CAN-22-1123

Robinson, D. et al. Integrative clinical genomics of advanced prostate cancer. Cell 161, 1215–1228 (2015).

pubmed: 26000489 pmcid: 4484602 doi: 10.1016/j.cell.2015.05.001

Grasso, C. S. et al. The mutational landscape of lethal castration-resistant prostate cancer. Nature 487, 239–243 (2012).

pubmed: 22722839 pmcid: 3396711 doi: 10.1038/nature11125

Kumar, A. et al. Substantial interindividual and limited intraindividual genomic diversity among tumors from men with metastatic prostate cancer. Nat. Med. 22, 369–378 (2016).

pubmed: 26928463 pmcid: 5045679 doi: 10.1038/nm.4053

Pomerantz, M. M. et al. Prostate cancer reactivates developmental epigenomic programs during metastatic progression. Nat. Genet. 52, 790–799 (2020).

pubmed: 32690948 pmcid: 10007911 doi: 10.1038/s41588-020-0664-8

Takeda, D. Y. et al. A somatically acquired enhancer of the androgen receptor is a noncoding driver in advanced prostate cancer. Cell 174, 422–432 (2018).

pubmed: 29909987 pmcid: 6046260 doi: 10.1016/j.cell.2018.05.037

Viswanathan, S. R. et al. Structural alterations driving castration-resistant prostate cancer revealed by linked-read genome sequencing. Cell 174, 433–447 (2018).

pubmed: 29909985 pmcid: 6046279 doi: 10.1016/j.cell.2018.05.036

Krijger, P. H. & de Laat, W. Regulation of disease-associated gene expression in the 3D genome. Nat. Rev. Mol. Cell Biol. 17, 771–782 (2016).

pubmed: 27826147 doi: 10.1038/nrm.2016.138

Ntziachristos, P., Abdel-Wahab, O. & Aifantis, I. Emerging concepts of epigenetic dysregulation in hematological malignancies. Nat. Immunol. 17, 1016–1024 (2016).

pubmed: 27478938 pmcid: 5134743 doi: 10.1038/ni.3517

Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293 (2009).

pubmed: 19815776 pmcid: 2858594 doi: 10.1126/science.1181369

Beagan, J. A. & Phillips-Cremins, J. E. On the existence and functionality of topologically associating domains. Nat. Genet. 52, 8–16 (2020).

pubmed: 31925403 pmcid: 7567612 doi: 10.1038/s41588-019-0561-1

Javierre, B. M. et al. Lineage-specific genome architecture links enhancers and non-coding disease variants to target gene promoters. Cell 167, 1369–1384 (2016).

pubmed: 27863249 pmcid: 5123897 doi: 10.1016/j.cell.2016.09.037

Hawley, J. R. et al. Reorganization of the 3D genome pinpoints noncoding drivers of primary prostate tumors. Cancer Res. 81, 5833–5848 (2021).

pubmed: 34642184 doi: 10.1158/0008-5472.CAN-21-2056

Dunham, I. et al. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).

doi: 10.1038/nature11247

Díaz, N. et al. Chromatin conformation analysis of primary patient tissue using a low input Hi-C method. Nat. Commun. 9, 4938 (2018).

pubmed: 30498195 pmcid: 6265268 doi: 10.1038/s41467-018-06961-0

Li, T. et al. Integrative analysis of genome, 3D genome, and transcriptome alterations of clinical lung cancer samples. Genomics Proteomics Bioinformatics 19, 741–753 (2021).

pubmed: 34116262 pmcid: 9170781 doi: 10.1016/j.gpb.2020.05.007

Animesh, S. et al. Profiling of 3D genome organization in nasopharyngeal cancer needle biopsy patient samples by a modified Hi-C approach. Front. Genet. 12, 673530 (2021).

pubmed: 34539729 pmcid: 8446523 doi: 10.3389/fgene.2021.673530

Yang, Y. et al. High-throughput chromosome conformation capture-based analysis of higher-order chromatin structure in nasopharyngeal carcinoma. Ann. Transl. Med. 9, 1314 (2021).

pubmed: 34532451 pmcid: 8422082 doi: 10.21037/atm-21-3273

Wang, J. et al. Epigenomic landscape and 3D genome structure in pediatric high-grade glioma. Sci. Adv. 7, eabg4126 (2021).

pubmed: 34078608 pmcid: 10166578 doi: 10.1126/sciadv.abg4126

Kloetgen, A. et al. Three-dimensional chromatin landscapes in T cell acute lymphoblastic leukemia. Nat. Genet. 52, 388–400 (2020).

pubmed: 32203470 pmcid: 7138649 doi: 10.1038/s41588-020-0602-9

Yang, L. et al. 3D genome alterations associated with dysregulated HOXA13 expression in high-risk T-lineage acute lymphoblastic leukemia. Nat. Commun. 12, 3708 (2021).

pubmed: 34140506 pmcid: 8211852 doi: 10.1038/s41467-021-24044-5

Johnstone, S. E. et al. Large-scale topological changes restrain malignant progression in colorectal cancer. Cell 182, 1474–1489 (2020).

pubmed: 32841603 pmcid: 7575124 doi: 10.1016/j.cell.2020.07.030

Xu, J. et al. Subtype-specific 3D genome alteration in acute myeloid leukaemia. Nature 611, 387–398 (2022).

pubmed: 36289338 pmcid: 10060167 doi: 10.1038/s41586-022-05365-x

Buitrago, D. et al. Impact of DNA methylation on 3D genome structure. Nat. Commun. 12, 3243 (2021).

pubmed: 34050148 pmcid: 8163762 doi: 10.1038/s41467-021-23142-8

Du, Q. et al. DNA methylation is required to maintain both DNA replication timing precision and 3D genome organization integrity. Cell Rep. 36, 109722 (2021).

pubmed: 34551299 doi: 10.1016/j.celrep.2021.109722

Fortin, J.-P. & Hansen, K. D. Reconstructing A/B compartments as revealed by Hi-C using long-range correlations in epigenetic data. Genome Biol. 16, 180 (2015).

pubmed: 26316348 pmcid: 4574526 doi: 10.1186/s13059-015-0741-y

Berman, B. P. et al. Regions of focal DNA hypermethylation and long-range hypomethylation in colorectal cancer coincide with nuclear lamina-associated domains. Nat. Genet. 44, 40–46 (2011).

pubmed: 22120008 pmcid: 4309644 doi: 10.1038/ng.969

Briand, N. & Collas, P. Lamina-associated domains: peripheral matters and internal affairs. Genome Biol. 21, 85 (2020).

pubmed: 32241294 pmcid: 7114793 doi: 10.1186/s13059-020-02003-5

Makova, K. D. & Hardison, R. C. The effects of chromatin organization on variation in mutation rates in the genome. Nat. Rev. Genet. 16, 213–223 (2015).

pubmed: 25732611 pmcid: 4500049 doi: 10.1038/nrg3890

Schuster-Böckler, B. & Lehner, B. Chromatin organization is a major influence on regional mutation rates in human cancer cells. Nature 488, 504–507 (2012).

pubmed: 22820252 doi: 10.1038/nature11273

Akdemir, K. C. et al. Somatic mutation distributions in cancer genomes vary with three-dimensional chromatin structure. Nat. Genet. 52, 1178–1188 (2020).

pubmed: 33020667 pmcid: 8350746 doi: 10.1038/s41588-020-0708-0

Kim, H. et al. Extrachromosomal DNA is associated with oncogene amplification and poor outcome across multiple cancers. Nat. Genet. 52, 891–897 (2020).

pubmed: 32807987 pmcid: 7484012 doi: 10.1038/s41588-020-0678-2

Keshavarzian, T. & Lupien, M. ecDNAs personify cancer gangsters. Mol. Cell 82, 500–502 (2022).

pubmed: 35120647 doi: 10.1016/j.molcel.2022.01.003

Prensner, J. R. et al. The long noncoding RNA SChLAP1 promotes aggressive prostate cancer and antagonizes the SWI/SNF complex. Nat. Genet. 45, 1392–1398 (2013).

pubmed: 24076601 pmcid: 3812362 doi: 10.1038/ng.2771

Prensner, J. R. et al. RNA biomarkers associated with metastatic progression in prostate cancer: a multi-institutional high-throughput analysis of SChLAP1. Lancet Oncol. 15, 1469–1480 (2014).

pubmed: 25456366 pmcid: 4559342 doi: 10.1016/S1470-2045(14)71113-1

Servant, N., Varoquaux, N., Heard, E., Barillot, E. & Vert, J.-P. Effective normalization for copy number variation in Hi-C data. BMC Bioinformatics 19, 313 (2018).

pubmed: 30189838 pmcid: 6127909 doi: 10.1186/s12859-018-2256-5

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

pubmed: 31748743 pmcid: 7094777 doi: 10.1038/s41586-019-1763-5

Zivanovic, A. et al. Co-evolution of AR gene copy number and structural complexity in endocrine therapy resistant prostate cancer. NAR Cancer 5, zcad045 (2023).

pubmed: 37636316 pmcid: 10448862 doi: 10.1093/narcan/zcad045

Aggarwal, R. et al. Prognosis associated with luminal and basal subtypes of metastatic prostate cancer. JAMA Oncol. 7, 1644–1652 (2021).

pubmed: 34554200 pmcid: 8461554 doi: 10.1001/jamaoncol.2021.3987

Lancho, O. & Herranz, D. The MYC enhancer-ome: long-range transcriptional regulation of MYC in cancer. Trends Cancer 4, 810–822 (2018).

pubmed: 30470303 pmcid: 6260942 doi: 10.1016/j.trecan.2018.10.003

Parolia, A. et al. Distinct structural classes of activating FOXA1 alterations in advanced prostate cancer. Nature 571, 413–418 (2019).

pubmed: 31243372 pmcid: 6661908 doi: 10.1038/s41586-019-1347-4

Schuijers, J. et al. Transcriptional dysregulation of MYC reveals common enhancer-docking mechanism. Cell Rep. 23, 349–360 (2018).

pubmed: 29641996 pmcid: 5929158 doi: 10.1016/j.celrep.2018.03.056

Cho, S. W. et al. Promoter of lncRNA gene PVT1 is a tumor-suppressor DNA boundary element. Cell 173, 1398–1412 (2018).

pubmed: 29731168 pmcid: 5984165 doi: 10.1016/j.cell.2018.03.068

Ramanand, S. G. et al. The landscape of RNA polymerase II-associated chromatin interactions in prostate cancer. J. Clin. Invest. 130, 3987–4005 (2020).

pubmed: 32343676 pmcid: 7410051

Matejcic, M. et al. Germline variation at 8q24 and prostate cancer risk in men of European ancestry. Nat. Commun. 9, 4616 (2018).

pubmed: 30397198 pmcid: 6218483 doi: 10.1038/s41467-018-06863-1

Dixon, J. R. et al. Integrative detection and analysis of structural variation in cancer genomes. Nat. Genet. 50, 1388–1398 (2018).

pubmed: 30202056 pmcid: 6301019 doi: 10.1038/s41588-018-0195-8

Nikiforova, M. N. et al. Proximity of chromosomal loci that participate in radiation-induced rearrangements in human cells. Science 290, 138–141 (2000).

pubmed: 11021799 doi: 10.1126/science.290.5489.138

Zhang, Y. et al. Spatial organization of the mouse genome and its role in recurrent chromosomal translocations. Cell 148, 908–921 (2012).

pubmed: 22341456 pmcid: 3320767 doi: 10.1016/j.cell.2012.02.002

Mani, R.-S. et al. Induced chromosomal proximity and gene fusions in prostate cancer. Science 326, 1230 (2009).

pubmed: 19933109 pmcid: 2935583 doi: 10.1126/science.1178124

San Martin, R. et al. Chromosome compartmentalization alterations in prostate cancer cell lines model disease progression. J. Cell Biol. 221, e202104108 (2022).

pubmed: 34889941 doi: 10.1083/jcb.202104108

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

pubmed: 31761532 pmcid: 7241652 doi: 10.1016/j.cell.2019.10.039

van Leen, E., Brückner, L. & Henssen, A. G. The genomic and spatial mobility of extrachromosomal DNA and its implications for cancer therapy. Nat. Genet. 54, 107–114 (2022).

pubmed: 35145302 doi: 10.1038/s41588-021-01000-z

Oobatake, Y. & Shimizu, N. Double-strand breakage in the extrachromosomal double minutes triggers their aggregation in the nucleus, micronucleation, and morphological transformation. Genes Chromosomes Cancer 59, 133–143 (2020).

pubmed: 31569279 doi: 10.1002/gcc.22810

Shoshani, O. et al. Chromothripsis drives the evolution of gene amplification in cancer. Nature 591, 137–141 (2021).

pubmed: 33361815 doi: 10.1038/s41586-020-03064-z

Rhie, S. K. et al. A high-resolution 3D epigenomic map reveals insights into the creation of the prostate cancer transcriptome. Nat. Commun. 10, 4154 (2019).

pubmed: 31515496 pmcid: 6742760 doi: 10.1038/s41467-019-12079-8

Lourenco, C. et al. MYC protein interactors in gene transcription and cancer. Nat. Rev. Cancer 21, 579–591 (2021).

pubmed: 34188192 doi: 10.1038/s41568-021-00367-9

Patange, S. et al. MYC amplifies gene expression through global changes in transcription factor dynamics. Cell Rep. 38, 110292 (2022).

pubmed: 35081348 pmcid: 8849550 doi: 10.1016/j.celrep.2021.110292

Amjadi-Moheb, F., Paniri, A. & Akhavan-Niaki, H. Insights into the links between MYC and 3D chromatin structure and epigenetics regulation: implications for cancer therapy. Cancer Res. 81, 1925–1936 (2021).

pubmed: 33472888 doi: 10.1158/0008-5472.CAN-20-3613

Hyle, J. et al. Acute depletion of CTCF directly affects MYC regulation through loss of enhancer-promoter looping. Nucleic Acids Res. 47, 6699–6713 (2019).

pubmed: 31127282 pmcid: 6648894 doi: 10.1093/nar/gkz462

Chen, W. S. et al. Germline polymorphisms associated with impaired survival outcomes and somatic tumor alterations in advanced prostate cancer. Prostate Cancer Prostatic Dis. 23, 316–323 (2020).

pubmed: 31745256 doi: 10.1038/s41391-019-0188-4

Servant, N. et al. HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome Biol. 16, 259 (2015).

pubmed: 26619908 pmcid: 4665391 doi: 10.1186/s13059-015-0831-x

Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

pubmed: 22388286 pmcid: 3322381 doi: 10.1038/nmeth.1923

Imakaev, M. et al. Iterative correction of Hi-C data reveals hallmarks of chromosome organization. Nat. Methods 9, 999–1003 (2012).

pubmed: 22941365 pmcid: 3816492 doi: 10.1038/nmeth.2148

Shin, H. et al. TopDom: an efficient and deterministic method for identifying topological domains in genomes. Nucleic Acids Res. 44, e70 (2016).

pubmed: 26704975 doi: 10.1093/nar/gkv1505

Servant, N. et al. HiTC: exploration of high-throughput ‘C’ experiments. Bioinformatics 28, 2843–2844 (2012).

pubmed: 22923296 pmcid: 3476334 doi: 10.1093/bioinformatics/bts521

Boltsis, I., Grosveld, F., Giraud, G. & Kolovos, P. Chromatin conformation in development and disease. Front. Cell Dev. Biol. 9, 723859 (2021).

pubmed: 34422840 pmcid: 8371409 doi: 10.3389/fcell.2021.723859

Priestley, P. et al. Pan-cancer whole-genome analyses of metastatic solid tumours. Nature 575, 210–216 (2019).

pubmed: 31645765 pmcid: 6872491 doi: 10.1038/s41586-019-1689-y

Kim, S. et al. Strelka2: fast and accurate calling of germline and somatic variants. Nat. Methods 15, 591–594 (2018).

pubmed: 30013048 doi: 10.1038/s41592-018-0051-x

Cibulskis, K. et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat. Biotechnol. 31, 213–219 (2013).

pubmed: 23396013 pmcid: 3833702 doi: 10.1038/nbt.2514

Chen, X. et al. Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications. Bioinformatics 32, 1220–1222 (2016).

pubmed: 26647377 doi: 10.1093/bioinformatics/btv710

Shale, C. et al. Unscrambling cancer genomes via integrated analysis of structural variation and copy number. Cell Genom. 2, 100112 (2022).

pubmed: 36776527 pmcid: 9903802 doi: 10.1016/j.xgen.2022.100112

Robinson, J. T. et al. Integrative genomics viewer. Nat. Biotechnol. 29, 24–26 (2011).

pubmed: 21221095 pmcid: 3346182 doi: 10.1038/nbt.1754

Hadi, K. et al. Distinct classes of complex structural variation uncovered across thousands of cancer genome graphs. Cell 183, 197–210 (2020).

pubmed: 33007263 pmcid: 7912537 doi: 10.1016/j.cell.2020.08.006

Krueger, F. & Andrews, S. R. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics 27, 1571–1572 (2011).

pubmed: 21493656 pmcid: 3102221 doi: 10.1093/bioinformatics/btr167

Burger, L., Gaidatzis, D., Schübeler, D. & Stadler, M. B. Identification of active regulatory regions from DNA methylation data. Nucleic Acids Res. 41, e155 (2013).

pubmed: 23828043 pmcid: 3763559 doi: 10.1093/nar/gkt599

Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

pubmed: 23104886 doi: 10.1093/bioinformatics/bts635

Amemiya, H. M., Kundaje, A. & Boyle, A. P. The ENCODE blacklist: identification of problematic regions of the genome. Sci. Rep. 9, 9354 (2019).

pubmed: 31249361 pmcid: 6597582 doi: 10.1038/s41598-019-45839-z

Zhang, Y. et al. Model-based analysis of ChIP–Seq (MACS). Genome Biol. 9, R137 (2008).

pubmed: 18798982 pmcid: 2592715 doi: 10.1186/gb-2008-9-9-r137

Samb, R. et al. Using informative Multinomial-Dirichlet prior in a t-mixture with reversible jump estimation of nucleosome positions for genome-wide profiling. Stat. Appl. Genet. Mol. Biol. 14, 517–532 (2015).

pubmed: 26656614 doi: 10.1515/sagmb-2014-0098

Zhang, Z. et al. An AR-ERG transcriptional signature defined by long-range chromatin interactomes in prostate cancer cells. Genome Res. 29, 223–235 (2019).

pubmed: 30606742 pmcid: 6360806 doi: 10.1101/gr.230243.117