Abstract
Germ-cell tumours (GCTs) are derived from germ cells and occur most frequently in the testes1,2. GCTs are histologically heterogeneous and distinctly curable with chemotherapy3. Gains of chromosome arm 12p and aneuploidy are nearly universal in GCTs4,5,6, but specific somatic genomic features driving tumour initiation, chemosensitivity and progression are incompletely characterized. Here, using clinical whole-exome and transcriptome sequencing of precursor, primary (testicular and mediastinal) and chemoresistant metastatic human GCTs, we show that the primary somatic feature of GCTs is highly recurrent chromosome arm level amplifications and reciprocal deletions (reciprocal loss of heterozygosity), variations that are significantly enriched in GCTs compared to 19 other cancer types. These tumours also acquire KRAS mutations during the development from precursor to primary disease, and primary testicular GCTs (TGCTs) are uniformly wild type for TP53. In addition, by functional measurement of apoptotic signalling (BH3 profiling) of fresh tumour and adjacent tissue7, we find that primary TGCTs have high mitochondrial priming that facilitates chemotherapy-induced apoptosis. Finally, by phylogenetic analysis of serial TGCTs that emerge with chemotherapy resistance, we show how TGCTs gain additional reciprocal loss of heterozygosity and that this is associated with loss of pluripotency markers (NANOG and POU5F1)8,9 in chemoresistant teratomas or transformed carcinomas. Our results demonstrate the distinct genomic features underlying the origins of this disease and associated with the chemosensitivity phenotype, as well as the rare progression to chemoresistance. These results identify the convergence of cancer genomics, mitochondrial priming and GCT evolution, and may provide insights into chemosensitivity and resistance in other cancers.
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Acknowledgements
We thank the patients for contributing to this study, and H.Taylor-Weiner for feedback on ES cells. This work was supported by NIH U54 HG003067, NIH 1K08 CA188615 (E.M.V.), Damon Runyon Clinical Investigator Award (E.M.V.), Shawmut Design and Construction Pan Mass Challenge Team (C.S.), and Giovino Jimmy Fund Golf Tournament (C.S.).
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Authors and Affiliations
Contributions
A.T.-W., T.Z., B.B., G.C.H., S.A., A.A.-M. and E.M.V. performed genomic analysis of discovery cohort. A.T.-W., T.Z., B.B., E.O., M.H., C.S. and E.M.V performed clinical integration and analysis. J.L.G. and A.L. performed BH3 profiling experiments. S.S., S.L.C., R.B. and G.G. contributed methodology and analysis review. A.R. and E.M.V. performed biological review of genomic findings. S.G. performed sequencing assays. A.T.-W., T.Z., K.L., C.T. and E.M.V. performed genomic analysis of validation cohort. M.H. performed pathology and histological evaluation of clinical samples. A.T.-W., T.Z., B.B., C.S. and E.M.V. prepared manuscript and figures.
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The authors declare no competing financial interests.
Additional information
Reviewer Information Nature thanks K. Nathanson and the other anonymous reviewer(s) for their contribution to the peer review of this work.
Extended data figures and tables
Extended Data Figure 1 Mutational significance and copy number meta-analysis.
a, Mutational significance meta-analysis of discovery and ICR cohorts identify KRAS, KIT and RPL5 as significantly mutated in TGCT, with a spectrum of mutation rates. In this plot, each column represents a patient WES. Asterisk denotes the hypermutated PMGCT (DFCI_17). b, RLOH distribution by histology in discovery cohort. c, RLOH distribution by histology in ICR cohort. d, RLOH distribution in the meta-analysis, consistent with both subsets.
Extended Data Figure 2 Genomic reads for KRAS loci in two patient cases.
a, Integrative genomics viewer snapshot of KRAS p.G12A mutation in DFCI_55 GCNIS and seminoma. The mutation is present in the primary tumour but absent from the GCNIS. b, Integrative genomics viewer snapshot of KRAS p.G12A mutation in DFCI_61 GCNIS and seminoma. The mutation is present in the primary tumour but absent from the GCNIS.
Extended Data Figure 3 Allelic copy number heat map of the discovery cohort.
Each tumour sample is a row, and chromosomes are listed as columns. Blue regions note deletions, and red regions denote amplifications.
Extended Data Figure 4 Testes tumours of different cell types.
Allelic copy number data from testes tumours of different cell types are shown. These three tumours do not contain the same level of arm level chromosomal events as GCTs.
Extended Data Figure 5 Phylogenetic analysis of DFCI_4.
Histology proportion is indicated by pie charts within each phylogenetic tree. Phylogenetic trees were constructed using allelic copy number deconstructions. Branch lengths are proportional to the number of deconstructed copy number events. Branches leading to primary samples are red, and branches leading to metastases are purple. The dotted branch indicates deconstructions which may be impacted by FFPE sample degradation, limiting discrete branch length estimation.
Supplementary information
Supplementary Table 1
Clinical and genomic overview of GCT cohort. This table lists histological subclass, vital status, mutation load, and location of the primary and initially sequenced metastases shown in figure 1. (XLSX 45 kb)
Supplementary Table 2
Summary clinical data. This table lists aggregate summary phenotypic data, including therapies and response, for this cohort. (XLSX 10 kb)
Supplementary Table 3
Mutation significance analysis. Table of significant (q < 0.2) genes uncovered with MutSigCV run on the discovery cohort. (XLSX 34 kb)
Supplementary Table 4
Mutation data for all samples. All mutations and small insertions and deletions called in this cohort. (XLSX 486 kb)
Supplementary Table 5
ABSOLUTE allelic segmented copy-number data. Allelic copy number data used to perform deconstructions and construct phylogenetic trees. (TXT 1236 kb)
Supplementary Table 6
ABSOLUTE purity and ploidy solutions. This table lists purity, ploidy and genome doubling status of each tumor as assessed by ABSOLUTE. (XLS 21 kb)
Supplementary Table 7
Gene expression data. This table has transcript per million expression values by sample for TP53, NANOG and POU5F1. (XLSX 46 kb)
Supplementary Table 8
Detailed clinical annotations for multi-regional sampling subset. This table lists treatment regimen, location, and histological subtype of each sample in figure 4. (XLSX 36 kb)
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Taylor-Weiner, A., Zack, T., O’Donnell, E. et al. Genomic evolution and chemoresistance in germ-cell tumours. Nature 540, 114–118 (2016). https://doi.org/10.1038/nature20596
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DOI: https://doi.org/10.1038/nature20596
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