TY - JOUR
T1 - The genomic landscape of metastatic castration-resistant prostate cancers reveals multiple distinct genotypes with potential clinical impact
AU - van Dessel, Lisanne F.
AU - van Riet, Job
AU - Smits, Minke
AU - Zhu, Yanyun
AU - Hamberg, Paul
AU - van der Heijden, Michiel S.
AU - Bergman, Andries M.
AU - van Oort, Inge M.
AU - de Wit, Ronald
AU - Voest, Emile E.
AU - Steeghs, Neeltje
AU - Yamaguchi, Takafumi N.
AU - Livingstone, Julie
AU - Boutros, Paul C.
AU - Martens, John W. M.
AU - Sleijfer, Stefan
AU - Cuppen, Edwin
AU - Zwart, Wilbert
AU - van de Werken, Harmen J. G.
AU - Mehra, Niven
AU - Lolkema, Martijn P.
N1 - Funding Information:
This publication and the underlying study have been made possible in parts by the data that the Hartwig Medical Foundation and the Center of Personalized Cancer Treatment (CPCT) have made available to the study. We would like to thank the local principal investigators of all contributing centers for their help with patient enrollment (listed in Supplementary Table 1). We would also like to thank Tesa M. Severson for her help with the computational analyses of the ChIP-seq data, Suzan Stelloo for providing ChIP-seq results on cell lines and Arne van Hoeck for providing the CHORD (HR-deficiency) prediction scores. We thank Dr. Joost van Rosmalen for his advises on the statistical analyses. In addition, we would like to thank the Barcode for Life foundation for making this research possible. Figure 1 was created with BioRender.com. This work was supported in parts by a KWF-Alpe d’HuZes project [NKI 2014-7080], a grant from Astellas Pharma [Lolkema/NL-72-RG-11] and a Johnson & Johnson grant [212082PCR3014]. This work was supported by the NIH/NCI under award number P30CA016042. H.J.G.v.D.W., J.v.R. and the Erasmus MC Cancer Computational Biology Center (CCBC) were financed through a grant from the Daniel den Hoed foundation.
Publisher Copyright:
© 2019, The Author(s).
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/12/1
Y1 - 2019/12/1
N2 - Metastatic castration-resistant prostate cancer (mCRPC) has a highly complex genomic landscape. With the recent development of novel treatments, accurate stratification strategies are needed. Here we present the whole-genome sequencing (WGS) analysis of fresh-frozen metastatic biopsies from 197 mCRPC patients. Using unsupervised clustering based on genomic features, we define eight distinct genomic clusters. We observe potentially clinically relevant genotypes, including microsatellite instability (MSI), homologous recombination deficiency (HRD) enriched with genomic deletions and BRCA2 aberrations, a tandem duplication genotype associated with CDK12
−/− and a chromothripsis-enriched subgroup. Our data suggests that stratification on WGS characteristics may improve identification of MSI, CDK12
−/− and HRD patients. From WGS and ChIP-seq data, we show the potential relevance of recurrent alterations in non-coding regions identified with WGS and highlight the central role of AR signaling in tumor progression. These data underline the potential value of using WGS to accurately stratify mCRPC patients into clinically actionable subgroups.
AB - Metastatic castration-resistant prostate cancer (mCRPC) has a highly complex genomic landscape. With the recent development of novel treatments, accurate stratification strategies are needed. Here we present the whole-genome sequencing (WGS) analysis of fresh-frozen metastatic biopsies from 197 mCRPC patients. Using unsupervised clustering based on genomic features, we define eight distinct genomic clusters. We observe potentially clinically relevant genotypes, including microsatellite instability (MSI), homologous recombination deficiency (HRD) enriched with genomic deletions and BRCA2 aberrations, a tandem duplication genotype associated with CDK12
−/− and a chromothripsis-enriched subgroup. Our data suggests that stratification on WGS characteristics may improve identification of MSI, CDK12
−/− and HRD patients. From WGS and ChIP-seq data, we show the potential relevance of recurrent alterations in non-coding regions identified with WGS and highlight the central role of AR signaling in tumor progression. These data underline the potential value of using WGS to accurately stratify mCRPC patients into clinically actionable subgroups.
UR - https://www.scopus.com/pages/publications/85075391947
U2 - 10.1038/s41467-019-13084-7
DO - 10.1038/s41467-019-13084-7
M3 - Article
C2 - 31748536
SN - 2041-1723
VL - 10
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 5251
ER -