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Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA

Abstract

Cancers acquire resistance to systemic treatment as a result of clonal evolution and selection1,2. Repeat biopsies to study genomic evolution as a result of therapy are difficult, invasive and may be confounded by intra-tumour heterogeneity3,4. Recent studies have shown that genomic alterations in solid cancers can be characterized by massively parallel sequencing of circulating cell-free tumour DNA released from cancer cells into plasma, representing a non-invasive liquid biopsy5,6,7. Here we report sequencing of cancer exomes in serial plasma samples to track genomic evolution of metastatic cancers in response to therapy. Six patients with advanced breast, ovarian and lung cancers were followed over 1–2 years. For each case, exome sequencing was performed on 2–5 plasma samples (19 in total) spanning multiple courses of treatment, at selected time points when the allele fraction of tumour mutations in plasma was high, allowing improved sensitivity. For two cases, synchronous biopsies were also analysed, confirming genome-wide representation of the tumour genome in plasma. Quantification of allele fractions in plasma identified increased representation of mutant alleles in association with emergence of therapy resistance. These included an activating mutation in PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha) following treatment with paclitaxel8; a truncating mutation in RB1 (retinoblastoma 1) following treatment with cisplatin9; a truncating mutation in MED1 (mediator complex subunit 1) following treatment with tamoxifen and trastuzumab10,11, and following subsequent treatment with lapatinib12,13, a splicing mutation in GAS6 (growth arrest-specific 6) in the same patient; and a resistance-conferring mutation in EGFR (epidermal growth factor receptor; T790M) following treatment with gefitinib14. These results establish proof of principle that exome-wide analysis of circulating tumour DNA could complement current invasive biopsy approaches to identify mutations associated with acquired drug resistance in advanced cancers. Serial analysis of cancer genomes in plasma constitutes a new paradigm for the study of clonal evolution in human cancers.

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Figure 1: Identification of treatment-associated mutational changes from exome sequencing of serial plasma samples.
Figure 2: Mutations showing evidence of genomic tumour evolution.
Figure 3: Genome-wide concordance between plasma DNA and tumour DNA.

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Acknowledgements

We thank J. Langmore and K. Solomon (Rubicon Genomics) for early access to library preparation products. We thank L. Jones, S. Richardson, C. Hodgkin and H. Biggs for recruiting patients into the DETECT and CTCR-OVO4 studies, all medical and ancillary staff in the breast and gynaecological cancer clinic and patients for consenting to participate. We thank the Human Research Tissue Bank at Addenbrooke’s Hospital which is supported by the NIHR Cambridge Biomedical Research Centre. We thank the Cancer Science Institute, National University of Singapore, and the Hematology-Oncology Research Group, National University Health System, Singapore for their support. We acknowledge the support of Cancer Research UK, the University of Cambridge, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Experimental Cancer Medicine Centre, Hutchison Whampoa Limited, and the National Medical Research Council, Singapore. S.-J.D. is supported by an Australian NHMRC/RG Menzies Early Career Fellowship that is administered through the Peter MacCallum Cancer Centre, Victoria, Australia.

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Authors

Contributions

M.M., S.-J.D., T.F., D.W.Y.T., D.G., J.D.B., C.C. and N.R. designed the study. M.M., D.W.Y.T. and T.F. developed methods. S.-J.D., C.P., A.S.C.W., T.M.C., J.D.B. and C.C. designed and conducted the prospective clinical studies. M.M., S.-J.D., D.W.Y.T., D.G., T.F. and A.M.P. generated data. Z.K., S.H. and D.B. contributed sequencing data. M.M., F.M. and N.R. analysed sequencing data. S.-F.C. and J.H. contributed to experiments and data analysis. M.M., S.-J.D., D.W.Y.T., T.M.C., J.D.B., C.C. and N.R. interpreted data. M.M. and N.R. wrote the paper with assistance from S.-J.D., D.W.Y.T., C.C., J.D.B. and other authors. All authors approved the final manuscript. J.D.B., C.C. and N.R. are the project co-leaders and joint senior authors.

Corresponding authors

Correspondence to James D. Brenton, Carlos Caldas or Nitzan Rosenfeld.

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Competing interests

Z.K., S.H. and D.B. are full-time employees of Illumina, Inc., providers of the sequencing technology used in this study; the other authors declare no competing financial interests.

Supplementary information

Supplementary Information

This file contains Supplementary Text, Supplementary Figures 1-8 and Supplementary Tables 1-3. (PDF 2709 kb)

Supplementary Tables

This file contains Supplementary Tables 4-9, which contain a list of mutations with increased representation in plasma over the course of treatment for Cases 1-6. (XLSX 103 kb)

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Murtaza, M., Dawson, SJ., Tsui, D. et al. Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature 497, 108–112 (2013). https://doi.org/10.1038/nature12065

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