Temporal evolution of cellular heterogeneity during the progression to advanced AR-negative prostate cancer.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
07 06 2021
Historique:
received: 20 09 2020
accepted: 11 05 2021
entrez: 8 6 2021
pubmed: 9 6 2021
medline: 29 6 2021
Statut: epublish

Résumé

Despite advances in the development of highly effective androgen receptor (AR)-directed therapies for the treatment of men with advanced prostate cancer, acquired resistance to such therapies frequently ensues. A significant subset of patients with resistant disease develop AR-negative tumors that lose their luminal identity and display neuroendocrine features (neuroendocrine prostate cancer (NEPC)). The cellular heterogeneity and the molecular evolution during the progression from AR-positive adenocarcinoma to AR-negative NEPC has yet to be characterized. Utilizing a new genetically engineered mouse model, we have characterized the synergy between Rb1 loss and MYCN (encodes N-Myc) overexpression which results in the formation of AR-negative, poorly differentiated tumors with high metastatic potential. Single-cell-based approaches revealed striking temporal changes to the transcriptome and chromatin accessibility which have identified the emergence of distinct cell populations, marked by differential expression of Ascl1 and Pou2f3, during the transition to NEPC. Moreover, global DNA methylation and the N-Myc cistrome are redirected following Rb1 loss. Altogether, our data provide insight into the progression of prostate adenocarcinoma to NEPC.

Identifiants

pubmed: 34099734
doi: 10.1038/s41467-021-23780-y
pii: 10.1038/s41467-021-23780-y
pmc: PMC8185096
doi:

Substances chimiques

N-Myc Proto-Oncogene Protein 0
Receptors, Androgen 0
Retinoblastoma Protein 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

3372

Subventions

Organisme : NCI NIH HHS
ID : P50 CA211024
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA230913
Pays : United States
Organisme : NCI NIH HHS
ID : T32 CA203702
Pays : United States

Références

Aparicio, A. et al. Neuroendocrine prostate cancer xenografts with large-cell and small-cell features derived from a single patient’s tumor: morphological, immunohistochemical, and gene expression profiles. Prostate 71, 846–856 (2011).
pubmed: 21456067 doi: 10.1002/pros.21301
Beltran, H. et al. Divergent clonal evolution of castration-resistant neuroendocrine prostate cancer. Nat. Med. 22, 298–305 (2016).
pubmed: 26855148 pmcid: 4777652 doi: 10.1038/nm.4045
Tzelepi, V. et al. Modeling a lethal prostate cancer variant with small-cell carcinoma features. Clin. Cancer Res. 18, 666–677 (2012).
pubmed: 22156612 doi: 10.1158/1078-0432.CCR-11-1867
Rickman, D. S., Beltran, H., Demichelis, F. & Rubin, M. A. Biology and evolution of poorly differentiated neuroendocrine tumors. Nat. Med. 23, 1–10 (2017).
pubmed: 28586335 doi: 10.1038/nm.4341
Beltran, H. et al. Molecular characterization of neuroendocrine prostate cancer and identification of new drug targets. Cancer Discov. 1, 487–495 (2011).
pubmed: 22389870 pmcid: 3290518 doi: 10.1158/2159-8290.CD-11-0130
Berger, A. et al. N-Myc-mediated epigenetic reprogramming drives lineage plasticity in advanced prostate cancer. J. Clin. Invest. 130, 3924–3940 (2019).
doi: 10.1172/JCI127961
Dardenne, E. et al. N-Myc induces an EZH2-mediated transcriptional program driving neuroendocrine prostate cancer. Cancer Cell 30, 563–577 (2016).
pubmed: 27728805 pmcid: 5540451 doi: 10.1016/j.ccell.2016.09.005
Lee, J. K. et al. N-Myc drives neuroendocrine prostate cancer initiated from human prostate epithelial cells. Cancer Cell 29, 536–547 (2016).
pubmed: 27050099 pmcid: 4829466 doi: 10.1016/j.ccell.2016.03.001
Aparicio, A. M. et al. Combined tumor suppressor defects characterize clinically defined aggressive variant prostate cancers. Clin. Cancer Res. 22, 1520–1530 (2016).
pubmed: 26546618 doi: 10.1158/1078-0432.CCR-15-1259
Ku, S. Y. et al. Rb1 and Trp53 cooperate to suppress prostate cancer lineage plasticity, metastasis, and antiandrogen resistance. Science 355, 78–83 (2017).
pubmed: 28059767 pmcid: 5367887 doi: 10.1126/science.aah4199
Martin, P. et al. Prostate epithelial Pten/TP53 loss leads to transformation of multipotential progenitors and epithelial to mesenchymal transition. Am. J. Pathol. 179, 422–435 (2011).
pubmed: 21703421 pmcid: 3123810 doi: 10.1016/j.ajpath.2011.03.035
Mu, P. et al. SOX2 promotes lineage plasticity and antiandrogen resistance in TP53- and RB1-deficient prostate cancer. Science 355, 84–88 (2017).
pubmed: 28059768 pmcid: 5247742 doi: 10.1126/science.aah4307
Tan, H. L. et al. Rb loss is characteristic of prostatic small cell neuroendocrine carcinoma. Clin. Cancer Res. 20, 890–903 (2014).
pubmed: 24323898 doi: 10.1158/1078-0432.CCR-13-1982
Zhou, Z. et al. Synergy of p53 and Rb deficiency in a conditional mouse model for metastatic prostate cancer. Cancer Res. 66, 7889–7898 (2006).
pubmed: 16912162 doi: 10.1158/0008-5472.CAN-06-0486
Zou, M. et al. Transdifferentiation as a mechanism of treatment resistance in a mouse model of castration-resistant prostate cancer. Cancer Discov. 7, 736–749 (2017).
pubmed: 28411207 pmcid: 5501744 doi: 10.1158/2159-8290.CD-16-1174
Wu, N. et al. A mouse model of MYCN-driven retinoblastoma reveals MYCN-independent tumor reemergence. J. Clin. Invest. 127, 888–898 (2017).
pubmed: 28165337 pmcid: 5330763 doi: 10.1172/JCI88508
Weiss, W. A., Aldape, K., Mohapatra, G., Feuerstein, B. G. & Bishop, J. M. Targeted expression of MYCN causes neuroblastoma in transgenic mice. EMBO J. 16, 2985–2995 (1997).
pubmed: 9214616 pmcid: 1169917 doi: 10.1093/emboj/16.11.2985
Balanis, N. G. et al. Pan-cancer convergence to a small-cell neuroendocrine phenotype that shares susceptibilities with hematological malignancies. Cancer Cell 36, 17–34 e17 (2019).
pubmed: 31287989 pmcid: 6703903 doi: 10.1016/j.ccell.2019.06.005
Rosenbaum, J. N. et al. INSM1: a novel immunohistochemical and molecular marker for neuroendocrine and neuroepithelial neoplasms. Am. J. Clin. Pathol. 144, 579–591 (2015).
pubmed: 26386079 doi: 10.1309/AJCPGZWXXBSNL4VD
Agoff, S. N. et al. Thyroid transcription factor-1 is expressed in extrapulmonary small cell carcinomas but not in other extrapulmonary neuroendocrine tumors. Mod. Pathol. 13, 238–242 (2000).
pubmed: 10757334 doi: 10.1038/modpathol.3880044
Dubchak, I. et al. Active conservation of noncoding sequences revealed by three-way species comparisons. Genome Res. 10, 1304–1306 (2000).
pubmed: 10984448 pmcid: 310906 doi: 10.1101/gr.142200
Frazer, K. A., Pachter, L., Poliakov, A., Rubin, E. M. & Dubchak, I. VISTA: computational tools for comparative genomics. Nucleic Acids Res. 32, W273–W279 (2004).
pubmed: 15215394 pmcid: 441596 doi: 10.1093/nar/gkh458
Cerami, E. et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2, 401–404 (2012).
pubmed: 22588877 doi: 10.1158/2159-8290.CD-12-0095
Gao, J. et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci. Signal. 6, pl1 (2013).
pubmed: 23550210 pmcid: 4160307 doi: 10.1126/scisignal.2004088
Smith, B. A. et al. A human adult stem cell signature marks aggressive variants across epithelial cancers. Cell Rep. 24, 3353–3366 e3355 (2018).
pubmed: 30232014 pmcid: 6382070 doi: 10.1016/j.celrep.2018.08.062
Trapnell, C. et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol. 32, 381–386 (2014).
pubmed: 24658644 pmcid: 4122333 doi: 10.1038/nbt.2859
Korenjak, M., Anderssen, E., Ramaswamy, S., Whetstine, J. R. & Dyson, N. J. RBF binding to both canonical E2F targets and noncanonical targets depends on functional dE2F/dDP complexes. Mol. Cell Biol. 32, 4375–4387 (2012).
pubmed: 22927638 pmcid: 3486151 doi: 10.1128/MCB.00536-12
Lin, P. C. et al. Epigenomic alterations in localized and advanced prostate cancer. Neoplasia 15, 373–383 (2013).
pubmed: 23555183 pmcid: 3612910 doi: 10.1593/neo.122146
Onder, T. T. et al. Loss of E-cadherin promotes metastasis via multiple downstream transcriptional pathways. Cancer Res. 68, 3645–3654 (2008).
pubmed: 18483246 doi: 10.1158/0008-5472.CAN-07-2938
Ireland, A. S. et al. MYC Drives temporal evolution of small cell lung cancer subtypes by reprogramming neuroendocrine fate. Cancer Cell https://doi.org/10.1016/j.ccell.2020.05.001 (2020).
Althoff, K. et al. A Cre-conditional MYCN-driven neuroblastoma mouse model as an improved tool for preclinical studies. Oncogene 34, 3357–3368 (2015).
pubmed: 25174395 doi: 10.1038/onc.2014.269
Drost, J. et al. Organoid culture systems for prostate epithelial and cancer tissue. Nat. Protoc. 11, 347–358 (2016).
pubmed: 26797458 pmcid: 4793718 doi: 10.1038/nprot.2016.006
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
pubmed: 24695404 pmcid: 4103590 doi: 10.1093/bioinformatics/btu170
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
pubmed: 23104886 doi: 10.1093/bioinformatics/bts635
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
pubmed: 19505943 pmcid: 2723002 doi: 10.1093/bioinformatics/btp352
Trapnell, C. et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protoc. 7, 562–578 (2012).
pubmed: 22383036 pmcid: 3334321 doi: 10.1038/nprot.2012.016
Anders, S., Pyl, P. T. & Huber, W. HTSeq–a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015).
pubmed: 25260700 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).
pubmed: 25516281 pmcid: 4302049 doi: 10.1186/s13059-014-0550-8
DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet 43, 491–498 (2011).
pubmed: 21478889 pmcid: 3083463 doi: 10.1038/ng.806
Van der Auwera, G. A. et al. From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline. Curr. Protoc. Bioinforma. 43, 11 10 11–11 10 33 (2013).
Engstrom, P. G. et al. Systematic evaluation of spliced alignment programs for RNA-seq data. Nat. Methods 10, 1185–1191 (2013).
pubmed: 24185836 pmcid: 4018468 doi: 10.1038/nmeth.2722
Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164 (2010).
pubmed: 20601685 pmcid: 2938201 doi: 10.1093/nar/gkq603
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
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
Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).
pubmed: 20513432 pmcid: 2898526 doi: 10.1016/j.molcel.2010.05.004
Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).
pubmed: 20110278 pmcid: 2832824 doi: 10.1093/bioinformatics/btq033
Ramirez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44, W160–W165 (2016).
pubmed: 27079975 pmcid: 4987876 doi: 10.1093/nar/gkw257
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).
pubmed: 16199517 doi: 10.1073/pnas.0506580102 pmcid: 1239896
Cao, J. et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496–502 (2019).
pubmed: 30787437 pmcid: 6434952 doi: 10.1038/s41586-019-0969-x
Levine, J. H. et al. Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis. Cell 162, 184–197 (2015).
pubmed: 26095251 pmcid: 4508757 doi: 10.1016/j.cell.2015.05.047
Qiu, X. et al. Reversed graph embedding resolves complex single-cell trajectories. Nat. Methods 14, 979–982 (2017).
pubmed: 28825705 pmcid: 5764547 doi: 10.1038/nmeth.4402
Traag, V. A., Waltman, L. & van Eck, N. J. From Louvain to Leiden: guaranteeing well-connected communities. Sci. Rep. 9, 5233 (2019).
pubmed: 30914743 pmcid: 6435756 doi: 10.1038/s41598-019-41695-z
La Manno, G. et al. RNA velocity of single cells. Nature 560, 494–498 (2018).
pubmed: 30089906 pmcid: 6130801 doi: 10.1038/s41586-018-0414-6
Gu, H. et al. Preparation of reduced representation bisulfite sequencing libraries for genome-scale DNA methylation profiling. Nat. Protoc. 6, 468–481 (2011).
pubmed: 21412275 doi: 10.1038/nprot.2010.190
Akalin, A. et al. Base-pair resolution DNA methylation sequencing reveals profoundly divergent epigenetic landscapes in acute myeloid leukemia. PLoS Genet. 8, e1002781 (2012).
pubmed: 22737091 pmcid: 3380828 doi: 10.1371/journal.pgen.1002781
Garrett-Bakelman, F. E. et al. Enhanced reduced representation bisulfite sequencing for assessment of DNA methylation at base pair resolution. J. Vis. Exp. e52246, https://doi.org/10.3791/52246 (2015).
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
Akalin, A. et al. methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles. Genome Biol. 13, R87 (2012).
pubmed: 23034086 pmcid: 3491415 doi: 10.1186/gb-2012-13-10-r87
Ittmann, M. et al. Animal models of human prostate cancer: the consensus report of the New York meeting of the Mouse Models of Human Cancers Consortium Prostate Pathology Committee. Cancer Res. 73, 2718–2736 (2013).
pubmed: 23610450 pmcid: 3644021 doi: 10.1158/0008-5472.CAN-12-4213

Auteurs

Nicholas J Brady (NJ)

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.

Alyssa M Bagadion (AM)

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.

Richa Singh (R)

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.

Vincenza Conteduca (V)

Department of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, USA.

Lucie Van Emmenis (L)

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.

Elisa Arceci (E)

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.

Hubert Pakula (H)

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.

Ryan Carelli (R)

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.

Francesca Khani (F)

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.
Department of Urology, Weill Cornell Medicine, New York, NY, USA.
Caryl and Israel Englander Institute for Precision Medicine, New York-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA.
Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.

Martin Bakht (M)

Department of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, USA.

Michael Sigouros (M)

Caryl and Israel Englander Institute for Precision Medicine, New York-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA.

Rohan Bareja (R)

Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.
Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.

Andrea Sboner (A)

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.
Caryl and Israel Englander Institute for Precision Medicine, New York-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA.
Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.

Olivier Elemento (O)

Caryl and Israel Englander Institute for Precision Medicine, New York-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA.
Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.
Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.

Scott Tagawa (S)

Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
Department of Medicine, Weill Cornell Medicine, New York, NY, USA.

David M Nanus (DM)

Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
Department of Medicine, Weill Cornell Medicine, New York, NY, USA.

Massimo Loda (M)

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.
Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.

Himisha Beltran (H)

Department of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, USA.

Brian Robinson (B)

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.
Department of Urology, Weill Cornell Medicine, New York, NY, USA.
Caryl and Israel Englander Institute for Precision Medicine, New York-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA.
Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.

David S Rickman (DS)

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA. dsr2005@med.cornell.edu.
Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. dsr2005@med.cornell.edu.

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