A genomic and epigenomic atlas of prostate cancer in Asian populations.

Asian People / genetics Carrier Proteins / genetics Cell Transformation, Neoplastic / genetics China Cohort Studies DNA Helicases / genetics DNA Methylation DNA-Binding Proteins / genetics Epigenesis, Genetic Epigenomics Gene Expression Regulation, Neoplastic Genome, Human / genetics Genomics Hepatocyte Nuclear Factor 3-alpha / genetics Humans Male Mutation Nerve Tissue Proteins / genetics Prostatic Neoplasms / classification RNA-Seq Transcriptome / genetics

Journal

Nature

ISSN: 1476-4687

Titre abrégé: Nature

Pays: England

ID NLM: 0410462

Informations de publication

Date de publication:
04 2020

Historique:

received: 21 11 2018

accepted: 17 01 2020

pubmed: 3 4 2020

medline: 17 6 2020

entrez: 3 4 2020

Statut: ppublish

Résumé

Prostate cancer is the second most common cancer in men worldwide

Identifiants

DOI: 10.1038/s41586-020-2135-x PMID: 32238934

pubmed: 32238934

doi: 10.1038/s41586-020-2135-x

pii: 10.1038/s41586-020-2135-x

doi:

Substances chimiques

Carrier Proteins 0

DNA-Binding Proteins 0

FOXA1 protein, human 0

Hepatocyte Nuclear Factor 3-alpha 0

Nerve Tissue Proteins 0

ZNF292 protein, human 0

DNA Helicases EC 3.6.4.-

CHD1 protein, human EC 3.6.4.12

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

Pagination

93-99

Références

Bray, F. et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 68, 394–424 (2018).

doi: 10.3322/caac.21492

Cancer Genome Atlas Research Network. The molecular taxonomy of primary prostate cancer. Cell 163, 1011–1025 (2015).

doi: 10.1016/j.cell.2015.10.025

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

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

Shoag, J. & Barbieri, C. E. Clinical variability and molecular heterogeneity in prostate cancer. Asian J. Androl. 18, 543–548 (2016).

doi: 10.4103/1008-682X.178852 pubmed: 4955177 pmcid: 4955177

Kimura, T. East meets West: ethnic differences in prostate cancer epidemiology between East Asians and Caucasians. Chin. J. Cancer 31, 421–429 (2012).

doi: 10.5732/cjc.011.10324 pubmed: 3777503 pmcid: 3777503

Baca, S. C. et al. Punctuated evolution of prostate cancer genomes. Cell 153, 666–677 (2013).

doi: 10.1016/j.cell.2013.03.021 pubmed: 3690918 pmcid: 3690918

Barbieri, C. E. et al. Exome sequencing identifies recurrent SPOP, FOXA1 and MED12 mutations in prostate cancer. Nat. Genet. 44, 685–689 (2012).

doi: 10.1038/ng.2279 pubmed: 3673022 pmcid: 3673022

Beltran, H. et al. Divergent clonal evolution of castration-resistant neuroendocrine prostate cancer. Nat. Med. 22, 298–305 (2016).

doi: 10.1038/nm.4045 pubmed: 4777652 pmcid: 4777652

Fraser, M. et al. Genomic hallmarks of localized, non-indolent prostate cancer. Nature 541, 359–364 (2017).

doi: 10.1038/nature20788

Gao, D. et al. Organoid cultures derived from patients with advanced prostate cancer. Cell 159, 176–187 (2014).

doi: 10.1016/j.cell.2014.08.016 pubmed: 4237931 pmcid: 4237931

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

doi: 10.1038/nature11125 pubmed: 3396711 pmcid: 3396711

Hieronymus, H. et al. Copy number alteration burden predicts prostate cancer relapse. Proc. Natl Acad. Sci. USA 111, 11139–11144 (2014).

doi: 10.1073/pnas.1411446111

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).

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

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

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

Taylor, B. S. et al. Integrative genomic profiling of human prostate cancer. Cancer Cell 18, 11–22 (2010).

doi: 10.1016/j.ccr.2010.05.026 pubmed: 3198787 pmcid: 3198787

Yuan, J. et al. Integrated analysis of genetic ancestry and genomic alterations across cancers. Cancer Cell 34, 549–560.e9 (2018).

doi: 10.1016/j.ccell.2018.08.019 pubmed: 6348897 pmcid: 6348897

Abida, W. et al. Prospective genomic profiling of prostate cancer across disease states reveals germline and somatic alterations that may affect clinical decision making. JCO Precis. Oncol. https://doi.org/10.1200/PO.17.00029 (2017).

Dall’Era, M. A., deVere-White, R., Rodriguez, D. & Cress, R. Changing incidence of metastatic prostate cancer by race and age, 1988–2015. Eur. Urol. Focus 5, 1014–1021 (2019).

doi: 10.1016/j.euf.2018.04.016

Ren, S. et al. Whole-genome and transcriptome sequencing of prostate cancer identify new genetic alterations driving disease progression. Eur. Urol. 73, 322–339 (2017).

doi: 10.1016/j.eururo.2017.08.027

Vogelstein, B. et al. Cancer genome landscapes. Science 339, 1546–1558 (2013).

doi: 10.1126/science.1235122 pubmed: 23539594 pmcid: 23539594

Alexandrov, L. B. et al. Signatures of mutational processes in human cancer. Nature 500, 415–421 (2013).

doi: 10.1038/nature12477 pubmed: 3776390 pmcid: 3776390

Shen, M. M. & Abate-Shen, C. Molecular genetics of prostate cancer: new prospects for old challenges. Genes Dev. 24, 1967–2000 (2010).

doi: 10.1101/gad.1965810 pubmed: 20844012 pmcid: 2939361

Tomlins, S. A. et al. Recurrent fusion of TMPRSS2 and ETS transcription factor genes in prostate cancer. Science 310, 644–648 (2005).

doi: 10.1126/science.1117679 pubmed: 16254181

Quigley, D. A. et al. Genomic hallmarks and structural variation in metastatic prostate cancer. Cell 174, 758–769.e9 (2018).

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

Viswanathan, S. R. et al. Structural alterations driving castration-resistant prostate cancer revealed by linked-read genome sequencing. Cell 174, 433–447.e19 (2018).

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

Cortés-Ciriano, I. et al. Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing. Nat. Genet. 52, 331–341 (2020).

Yu, Y. P. et al. Novel fusion transcripts associate with progressive prostate cancer. Am. J. Pathol. 184, 2840–2849 (2014).

doi: 10.1016/j.ajpath.2014.06.025 pubmed: 25238935 pmcid: 25238935

Jang, J. S. et al. Common oncogene mutations and novel SND1-BRAF transcript fusion in lung adenocarcinoma from never smokers. Sci. Rep. 5, 9755 (2015).

doi: 10.1038/srep09755 pubmed: 25985019 pmcid: 25985019

Fishilevich, S. et al. GeneHancer: genome-wide integration of enhancers and target genes in GeneCards. Database (Oxford) 2017, bax028 (2017).

doi: 10.1093/database/bax028

Huang, F. W. et al. Highly recurrent TERT promoter mutations in human melanoma. Science 339, 957–959 (2013).

doi: 10.1126/science.1229259 pubmed: 4423787 pmcid: 4423787

Rheinbay, E. et al. Analyses of non-coding somatic drivers in 2,658 cancer whole genomes. Nature 578, 102–111 (2020).

doi: 10.1038/s41586-020-1965-x pubmed: 7054214 pmcid: 7054214

Zhu, H. et al. Candidate cancer driver mutations in distal regulatory elements and long-range chromatin interaction networks. Mol. Cell. https://doi.org/10.1016/j.molcel.2019.12.027 (2020).

Jozwik, K. M. & Carroll, J. S. Pioneer factors in hormone-dependent cancers. Nat. Rev. Cancer 12, 381–385 (2012).

doi: 10.1038/nrc3263

Sahu, B. et al. Dual role of FoxA1 in androgen receptor binding to chromatin, androgen signalling and prostate cancer. EMBO J. 30, 3962–3976 (2011).

doi: 10.1038/emboj.2011.328 pubmed: 3209787 pmcid: 3209787

Espiritu, S. M. G. et al. The evolutionary landscape of localized prostate cancers drives clinical aggression. Cell 173, 1003–1013.e15 (2018).

doi: 10.1016/j.cell.2018.03.029

Gao, N. et al. The role of hepatocyte nuclear factor-3 alpha (Forkhead Box A1) and androgen receptor in transcriptional regulation of prostatic genes. Mol. Endocrinol. 17, 1484–1507 (2003).

doi: 10.1210/me.2003-0020

Adams, E. J. et al. FOXA1 mutations alter pioneering activity, differentiation and prostate cancer phenotypes. Nature 571, 408–412 (2019).

doi: 10.1038/s41586-019-1318-9 pubmed: 6661172 pmcid: 6661172

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

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

McGranahan, N. et al. Clonal status of actionable driver events and the timing of mutational processes in cancer evolution. Sci. Transl. Med. 7, 283ra54 (2015).

doi: 10.1126/scitranslmed.aaa1408 pubmed: 4636056 pmcid: 4636056

Mina, M. et al. Conditional selection of genomic alterations dictates cancer evolution and oncogenic dependencies. Cancer Cell 32, 155–168.e6 (2017).

doi: 10.1016/j.ccell.2017.06.010

Ishizaki, F. et al. Androgen deprivation promotes intratumoral synthesis of dihydrotestosterone from androgen metabolites in prostate cancer. Sci. Rep. 3, 1528 (2013).

doi: 10.1038/srep01528 pubmed: 3607121 pmcid: 3607121

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).

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

Hansen, K. D. et al. Increased methylation variation in epigenetic domains across cancer types. Nat. Genet. 43, 768–775 (2011).

doi: 10.1038/ng.865 pubmed: 3145050 pmcid: 3145050

Hon, G. C. et al. Global DNA hypomethylation coupled to repressive chromatin domain formation and gene silencing in breast cancer. Genome Res. 22, 246–258 (2012).

doi: 10.1101/gr.125872.111 pubmed: 3266032 pmcid: 3266032

Mazor, T. et al. DNA methylation and somatic mutations converge on the cell cycle and define similar evolutionary histories in brain tumors. Cancer Cell 28, 307–317 (2015).

doi: 10.1016/j.ccell.2015.07.012 pubmed: 4573399 pmcid: 4573399

Xiao, Q. et al. Systematic analysis reveals molecular characteristics of ERG-negative prostate cancer. Sci. Rep. 8, 12868 (2018).

doi: 10.1038/s41598-018-30325-9 pubmed: 6110738 pmcid: 6110738

Chakravarty, D. et al. OncoKB: a precision oncology knowledge base. JCO Precis. Oncol. https://doi.org/10.1200/PO.17.00011 (2017).

Xu, B. et al. Altered chromatin recruitment by FOXA1 mutations promotes androgen independence and prostate cancer progression. Cell Res. 29, 773–775 (2019).

doi: 10.1038/s41422-019-0204-1

Gao, S. et al. Forkhead domain mutations in FOXA1 drive prostate cancer progression. Cell Res. 29, 770–772 (2019).

doi: 10.1038/s41422-019-0203-2

Gao, X., Wang, H., Wang, Y., Xu, C. & Sun, Y. Construction and clinical application of prostate cancer database (PC-Follow) based on browser/server schema. Chin. J. Urol. 36, 694–698 (2015).

Bergmann, E. A., Chen, B. J., Arora, K., Vacic, V. & Zody, M. C. Conpair: concordance and contamination estimator for matched tumor-normal pairs. Bioinformatics 32, 3196–3198 (2016).

doi: 10.1093/bioinformatics/btw389 pubmed: 5048070 pmcid: 5048070

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

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

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

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

Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 14, R36 (2013).

doi: 10.1186/gb-2013-14-4-r36 pubmed: 4053844 pmcid: 4053844

Anders, S., Pyl, P. T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015).

doi: 10.1093/bioinformatics/btu638

Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

doi: 10.1186/s13059-014-0550-8 pubmed: 25516281 pmcid: 25516281

Trapnell, C. et al. Differential analysis of gene regulation at transcript resolution with RNA-seq. Nat. Biotechnol. 31, 46–53 (2013).

doi: 10.1038/nbt.2450

Trapnell, C. et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protocols 7, 562–578 (2012).

doi: 10.1038/nprot.2012.016

Friedländer, M. R., Mackowiak, S. D., Li, N., Chen, W. & Rajewsky, N. miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res. 40, 37–52 (2012).

doi: 10.1093/nar/gkr688

McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

doi: 10.1101/gr.107524.110 pubmed: 20644199 pmcid: 20644199

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

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

Saunders, C. T. et al. Strelka: accurate somatic small-variant calling from sequenced tumor-normal sample pairs. Bioinformatics 28, 1811–1817 (2012).

doi: 10.1093/bioinformatics/bts271 pubmed: 22581179

Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164 (2010).

doi: 10.1093/nar/gkq603 pubmed: 2938201 pmcid: 2938201

Thorvaldsdóttir, H., Robinson, J. T. & Mesirov, J. P. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief. Bioinform. 14, 178–192 (2013).

doi: 10.1093/bib/bbs017 pubmed: 22517427

Boeva, V. et al. Control-FREEC: a tool for assessing copy number and allelic content using next-generation sequencing data. Bioinformatics 28, 423–425 (2012).

doi: 10.1093/bioinformatics/btr670 pubmed: 22155870

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

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

Mermel, C. H. et al. GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers. Genome Biol. 12, R41 (2011).

doi: 10.1186/gb-2011-12-4-r41 pubmed: 21527027 pmcid: 3218867

Yang, L. et al. Diverse mechanisms of somatic structural variations in human cancer genomes. Cell 153, 919–929 (2013).

doi: 10.1016/j.cell.2013.04.010 pubmed: 23663786 pmcid: 3704973

Jia, W. et al. SOAPfuse: an algorithm for identifying fusion transcripts from paired-end RNA-Seq data. Genome Biol. 14, R12 (2013).

doi: 10.1186/gb-2013-14-2-r12 pubmed: 23409703 pmcid: 23409703

Panigrahi, P., Jere, A. & Anamika, K. FusionHub: A unified web platform for annotation and visualization of gene fusion events in human cancer. PLoS One 13, e0196588 (2018).

doi: 10.1371/journal.pone.0196588 pubmed: 5929557 pmcid: 5929557

Shugay, M., Ortiz de Mendíbil, I., Vizmanos, J. L. & Novo, F. J. Oncofuse: a computational framework for the prediction of the oncogenic potential of gene fusions. Bioinformatics 29, 2539–2546 (2013).

doi: 10.1093/bioinformatics/btt445

Gonzalez-Perez, A. et al. Computational approaches to identify functional genetic variants in cancer genomes. Nat. Methods 10, 723–729 (2013).

doi: 10.1038/nmeth.2642 pubmed: 3919555 pmcid: 3919555

Porta-Pardo, E. et al. Comparison of algorithms for the detection of cancer drivers at subgene resolution. Nat. Methods 14, 782–788 (2017).

doi: 10.1038/nmeth.4364 pubmed: 5935266 pmcid: 5935266

Dees, N. D. et al. MuSiC: identifying mutational significance in cancer genomes. Genome Res. 22, 1589–1598 (2012).

doi: 10.1101/gr.134635.111 pubmed: 3409272 pmcid: 3409272

Lawrence, M. S. et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 499, 214–218 (2013).

doi: 10.1038/nature12213 pubmed: 23770567 pmcid: 23770567

Sondka, Z. et al. The COSMIC Cancer Gene Census: describing genetic dysfunction across all human cancers. Nat. Rev. Cancer 18, 696–705 (2018).

doi: 10.1038/s41568-018-0060-1 pubmed: 6450507 pmcid: 6450507

Fu, Y. et al. FunSeq2: a framework for prioritizing noncoding regulatory variants in cancer. Genome Biol. 15, 480 (2014).

doi: 10.1186/s13059-014-0480-5 pubmed: 4203974 pmcid: 4203974

Melton, C., Reuter, J. A., Spacek, D. V. & Snyder, M. Recurrent somatic mutations in regulatory regions of human cancer genomes. Nat. Genet. 47, 710–716 (2015).

doi: 10.1038/ng.3332 pubmed: 4485503 pmcid: 4485503

Weinhold, N., Jacobsen, A., Schultz, N., Sander, C. & Lee, W. Genome-wide analysis of noncoding regulatory mutations in cancer. Nat. Genet. 46, 1160–1165 (2014).

doi: 10.1038/ng.3101 pubmed: 4217527 pmcid: 4217527

Clark, K. L., Halay, E. D., Lai, E. & Burley, S. K. Co-crystal structure of the HNF-3/fork head DNA-recognition motif resembles histone H5. Nature 364, 412–420 (1993).

doi: 10.1038/364412a0

Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38 (1996).

doi: 10.1016/0263-7855(96)00018-5

The ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).

doi: 10.1038/nature11247

Wu, H. et al. Detection of differentially methylated regions from whole-genome bisulfite sequencing data without replicates. Nucleic Acids Res. 43, e141 (2015).

pubmed: 4666378 pmcid: 4666378

Kishore, K. et al. methylPipe and compEpiTools: a suite of R packages for the integrative analysis of epigenomics data. BMC Bioinformatics 16, 313 (2015).

doi: 10.1186/s12859-015-0742-6 pubmed: 4587815 pmcid: 4587815

Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

doi: 10.1093/bioinformatics/btq033 pubmed: 20110278 pmcid: 20110278

Harrow, J. et al. GENCODE: the reference human genome annotation for The ENCODE Project. Genome Res. 22, 1760–1774 (2012).

doi: 10.1101/gr.135350.111 pubmed: 22955987 pmcid: 22955987

McLean, C. Y. et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 28, 495–501 (2010).

doi: 10.1038/nbt.1630 pubmed: 20436461 pmcid: 20436461

Weisenberger, D. J. et al. CpG island methylator phenotype underlies sporadic microsatellite instability and is tightly associated with BRAF mutation in colorectal cancer. Nat. Genet. 38, 787–793 (2006).

doi: 10.1038/ng1834

Noushmehr, H. et al. Identification of a CpG island methylator phenotype that defines a distinct subgroup of glioma. Cancer Cell 17, 510–522 (2010).

doi: 10.1016/j.ccr.2010.03.017 pubmed: 2872684 pmcid: 2872684

Mo, Q. et al. Pattern discovery and cancer gene identification in integrated cancer genomic data. Proc. Natl Acad. Sci. USA 110, 4245–4250 (2013).

doi: 10.1073/pnas.1208949110 pubmed: 23431203 pmcid: 23431203

Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).

doi: 10.1073/pnas.0506580102

Cerami, E. et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2, 401–404 (2012).

doi: 10.1158/2159-8290.CD-12-0095 pubmed: 22588877 pmcid: 22588877