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Whole–genome characterization of chemoresistant ovarian cancer

A Corrigendum to this article was published on 21 October 2015

Abstract

Patients with high-grade serous ovarian cancer (HGSC) have experienced little improvement in overall survival, and standard treatment has not advanced beyond platinum-based combination chemotherapy, during the past 30 years. To understand the drivers of clinical phenotypes better, here we use whole-genome sequencing of tumour and germline DNA samples from 92 patients with primary refractory, resistant, sensitive and matched acquired resistant disease. We show that gene breakage commonly inactivates the tumour suppressors RB1, NF1, RAD51B and PTEN in HGSC, and contributes to acquired chemotherapy resistance. CCNE1 amplification was common in primary resistant and refractory disease. We observed several molecular events associated with acquired resistance, including multiple independent reversions of germline BRCA1 or BRCA2 mutations in individual patients, loss of BRCA1 promoter methylation, an alteration in molecular subtype, and recurrent promoter fusion associated with overexpression of the drug efflux pump MDR1.

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Figure 1: Genomic features of HGSC.
Figure 2: Mutational signatures of primary high-grade serous ovarian cancer.
Figure 3: Somatic mutational patterns in acquired resistant cohort.
Figure 4: Molecular changes associated with acquired resistance.

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Gene Expression Omnibus

Data deposits

The whole genome and transcriptome sequencing data have been deposited in the European Genome-phenome Archive (EGA) repository under the accession code EGAD00001000877. Genotyping, methylation and miRNA data sets have been submitted into the Gene Expression Omnibus (GEO) accession GSE65821. A complete list of the AOCS Study Group can be found at http://www.aocstudy.org.

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Acknowledgements

The AOCS gratefully acknowledge the cooperation of the participating institutions in Australia, and also acknowledge the contribution of the study nurses, research assistants and all clinical and scientific collaborators including L. Galletta, C. Emmanuel, L. Bowes and J. Hallo. The authors acknowledge assistance from C. Anderson and D. Gwynne. The CASCADE investigators would like to thank the CASCADE Management Committee, all staff at the Victorian Institute of Forensic Medicine, D. Stevens and Tobin Brothers Funerals. The investigators would like to thank the Australia New Zealand Gynaecological Oncology Group (ANZGOG) and the women, and their families, who participated in these research programs. This work was supported by the National Health and Medical Research Council of Australia (NHMRC ID631701), Worldwide Cancer Research (09-0676) and Cancer Australia (1004673). The Australian Ovarian Cancer Study was supported by the US Army Medical Research and Materiel Command under DAMD17-01-1-0729, The Cancer Council Victoria, Queensland Cancer Fund, The Cancer Council New South Wales, The Cancer Council South Australia, The Cancer Foundation of Western Australia, The Cancer Council Tasmania and the National Health and Medical Research Council of Australia (NHMRC; ID400413, ID400281). The AOCS gratefully acknowledges additional support from S. Boldeman, the Agar family, Ovarian Cancer Australia and Ovarian Cancer Action (UK). The Gynaecological Oncology Biobank at Westmead, a member of the Australasian Biospecimen Network-Oncology group, was supported by grants from the NHMRC (ID 310670, ID 628903) and the Cancer Institute of New South Wales. The CASCADE study was supported by the Peter MacCallum Cancer Centre Foundation, and in kind by the Victorian Institute of Forensic Medicine and Tobin Brothers Funerals.

Author information

Authors and Affiliations

Authors

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Contributions

Project supervision: J.V.P., Nicola.W., A.D.F., S.M.G., D.D.L.B. Study design: A.M.P., E.L.C., D.E., D.W.G., S.F., P.C., Nicola.W., A.D.F., S.M.G., D.D.L.B. Sample acquisition: S.F., K.A., A.O.C.S., A.H., L.M., O.M.N., C.K., J.H., Y.E.C., P.H., M.F., M.Q., J.P., S.C., P.O.B., J.L., P.W., N.T., H.T., M.S., R.D., E.S., H.G., A.J., O.M.N., E.L., A.D.F., D.D.L.B. Sample preparation: E.L.C., D.E., D.W.G., P.C., Y.E.C., P.H., C.M., J.H. Data acquisition: E.L.C., D.E., D.W.G., S.F., D.K.M., G.M.A., T.P.H., T.S., I.H., C.N., E.N., S.M., S.I., T.J.C.B., A.N.C. Performed patient autopsy: G.Y., K.S. Sequence data management, alignment and mutation identification: A.M.P., K.N., F.N., S.K., O.H., M.A., C.L., S.W., Q.X., J.L.F., Nick.W., S.H.N., P.J.W., J.V.P., S.M.G. Genome informatics, software tool development: A.M.P., P.J.B., K.S.K., F.N., S.K., B.P., O.H., M.A., C.L., S.W., D.F.T., Q.X., J.L.F., Nick.W., J.V.P., Nicola.W. Data analysis: A.M.P., E.L.C., D.E., D.W.G., J.G., K.N., P.J.B., K.S.K., M.C.JQ., K.Q., C.W.B., E.C., H.S.L., G.A.Y., W.A., R.W.T., A.L., N.H., R.B., J.E., M.D., R.V., C.S., J.V.P., Nicola.W., S.M.G. Perform molecular/verification analysis: E.L.C., K.N., S.M., E.M. Wrote the manuscript: A.M.P., E.L.C., D.E., D.W.G., Nicola.W., A.D.F., S.M.G., D.D.L.B.

Corresponding author

Correspondence to David D. L. Bowtell.

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The authors declare no competing financial interests.

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Extended data figures and tables

Extended Data Figure 1 Patient cohort.

a, Summary of whole-genome sequenced patients (n = 92) and samples (n = 114). b, Clinical characteristics of patients by clinical response group and acquired resistant cases without matching primary tumour material. *Primary tumour ungraded; diagnosis from ascites or pleural fluid. ^Time to progression or death measured from diagnosis. aKruskal–Wallis, bFisher or clog-rank test P values comparing primary tumour clinical groups reported. Median follow up time of cohort was 97.3 months.

Extended Data Figure 2 Structural variants and somatic mutations.

a, b, Scatter plot shows that the number of structural variants (a) and SNVs (b) detected per sample was not dependent on the purity of primary tumours (n = 80, grey) and ascites/relapse samples (n = 34, black). Spearman correlation P values indicated. c, Number of structural variants detected in primary tumours (n = 80) grouped by homologous recombination (HR) mutation status: HR wild-type, BRCA1/2 altered, and HR deficient (lines indicate mean; ****P < 0.0001, Kolmogorov–Smirnov test). d, e, Whole-genome (d) and coding mutations (e) per megabase for samples (n = 79) stratified by BRCA1, BRCA2 or homologous recombination pathway mutation status (lines indicate mean; **P < 0.01, ***P < 0.001, Kolmogorov–Smirnov test). Sample AOCS-166 with germline mismatch repair mutation excluded from analysis (see Supplementary Information section 4.3).

Extended Data Figure 3 Chromothripsis and breakage-fusion-bridge.

a, Chromothripsis affecting chromosome 13, including the BRCA2 locus (arrow), for a primary chemotherapy-resistant tumour. A high number of breakpoints (structural variants) are observed with oscillations of copy number (CNA and LOGRR) indicating regions of retained heterozygosity (BAF) for a single haplotype. b, Breakage-fusion-bridge amplification is observed on chromosome 1 for a primary chemotherapy-resistant tumour. A cluster of breakpoints (structural variants), mostly inversions, on the distal p arm are associated with blocks of amplification (CNA). IGV review of the tumour WGS confirms that the telomere region has been lost.

Extended Data Figure 4 Expression of genes altered by structural variation.

Scatter graphs show expression of RB1, NF1, PTEN and RAD51B plotted against copy number in primary tumours (n = 79; Spearman correlation analysis). Boxplots summarize expression by mutation type; lines indicate median and whiskers show range (two-tailed Mann-Whitney test; *P < 0.05, ***P < 0.001). Samples with somatic interrupting structural variants and truncating mutations are indicated. Not all structural variants are associated with DNA loss and translocations can be observed to produce high expression counts for non-functional transcripts. Expression values lower than the median value for tumours and controls was observed for the majority of samples with structural variant events in RB1, NF1, PTEN and RAD51B.

Extended Data Figure 5 Molecular characteristics of primary tumours.

Clinical and molecular characteristics of primary tumours sorted by BRCA signature contribution (n = 80).

Extended Data Figure 6 Mutational signature associations.

a, b, Age mutational signature association with age at diagnosis (a) and CCNE1 copy number (b) (Spearman correlation P value reported, n = 80). c, d, BRCA mutational signature association with BRCA1/2 and other homologous recombination pathway mutations (c) and primary treatment response (d) (lines indicate mean; Kolmogorov–Smirnov **P < 0.01, ***P < 0.001, ****P < 0.0001; n = 80).

Extended Data Figure 7 Molecular drivers and clinical associations.

a, Percentage (n) of primary tumours (total n = 80) affected by homologous recombination pathway mutations and CCNE1 copy number gains. One driver mutation counted for samples with more than one change, ranking mutations in BRCA1/2, followed by other germline, somatic, amplification, deletion and methylation events respectively. b, Association of driver mutation subgroup with overall survival in AOCS and TCGA cohorts (Kaplan–Meier analysis, P value calculated by Mantel–Cox log-rank test). c, d, Whole genome (c) and coding mutations (d) per megabase for samples stratified by primary clinical response group (lines indicate mean). Kruskal–Wallis test P value reported (*P < 0.05, **P < 0.01, Kolmogorov–Smirnov test). e, Boxplots summarize CCNE1 expression in different driver mutation subgroups (****P < 0.0001, unpaired two-tailed t-test). Middle bar, median; whiskers, data range. f, Proportions of gene expression molecular subtypes between driver mutation subgroups. HR/CCNE1− subgroup has no detected homologous recombination pathway mutations or CCNE1 copy number changes.

Extended Data Figure 8 Analysis of acquired resistance cases.

a, b, Matched primary ascites share most variants with primary tumour samples across the whole genome (a) and for non-silent coding mutations (b). c, d, Significant correlations are observed between the time between collection of the primary and relapse samples and the number of lines of platinum treatment the patient received (Pearson correlation, P = 0.0232, two-tailed) (c), and between the number of non-silent coding mutations unique to the relapse samples and the number of lines of platinum treatment the patient received (Pearson correlation, P = 0.0456, two-tailed) (d). e, Genes with recurrent non-silent coding mutations that are unique to the second sample in the acquired resistance cohort or that are driver genes reported previously55.

Extended Data Figure 9 BRCA1/2 reversion events.

a, BRCA1 and BRCA2 mutations are indicated by sample for acquired resistance cases (n = 23). Of the ten cases with germline mutations, five show secondary somatic mutations in the relapse-resistant samples that are proposed to restore gene function (that is, reversion). b, Two independent point mutations revert the BRCA1 nonsense mutation in AOCS-034. c, CA125 serum marker profile for case AOCS-167. d, Schematic of 12 high confidence reversion events identified in AOCS-167. e, Allele frequency of fifteen BRCA2 reversion events identified in deep amplicon sequencing across 18 relapse samples from case AOCS-167. Reversions observed in single deposits at low allele frequencies (≤0.001) were considered low confidence events.

Extended Data Figure 10 SLC25A40-ABCB1 fusion transcript.

a, Schematic showing the locations of structural variants identified upstream or internal to ABCB1 from WGS. b, ABCB1 and SLC25A40 expression levels in sensitive and resistant samples of AOCS-092 and AOCS-150. c, RT–PCR verification of SLC25A40-ABCB1 fusion transcript expression in AOCS-092 and schematic of expected RT–PCR products. d, RT–PCR results from a validation cohort of relapse ascites identifying four additional samples with the fusion transcript (n = 51). e, ABCB1 and SLC25A40 expression levels compared to the SKOV3 cell line by qRT–PCR in the validation cohort and selected cases. Relapse samples with the fusion are indicated by open squares and the matched primary samples indicated by closed squares; validation cases with the fusion are indicated by ‘+’; the median plus median absolute deviation expression level is indicated by the dotted line (n = 56).

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Supplementary Information

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Patch, AM., Christie, E., Etemadmoghadam, D. et al. Whole–genome characterization of chemoresistant ovarian cancer. Nature 521, 489–494 (2015). https://doi.org/10.1038/nature14410

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