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Absolute quantification of somatic DNA alterations in human cancer

Nature Biotechnology volume 30, pages 413–421 (2012)Cite this article

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Abstract

We describe a computational method that infers tumor purity and malignant cell ploidy directly from analysis of somatic DNA alterations. The method, named ABSOLUTE, can detect subclonal heterogeneity and somatic homozygosity, and it can calculate statistical sensitivity for detection of specific aberrations. We used ABSOLUTE to analyze exome sequencing data from 214 ovarian carcinoma tumor-normal pairs. This analysis identified both pervasive subclonal somatic point-mutations and a small subset of predominantly clonal and homozygous mutations, which were overrepresented in the tumor suppressor genes TP53 and NF1 and in a candidate tumor suppressor gene CDK12. We also used ABSOLUTE to infer absolute allelic copy-number profiles from 3,155 diverse cancer specimens, revealing that genome-doubling events are common in human cancer, likely occur in cells that are already aneuploid, and influence pathways of tumor progression (for example, with recessive inactivation of NF1 being less common after genome doubling). ABSOLUTE will facilitate the design of clinical sequencing studies and studies of cancer genome evolution and intra-tumor heterogeneity.

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Figure 1: Overview of tumor DNA analysis using ABSOLUTE.
Figure 2: ABSOLUTE method validation and comparison.
Figure 3: Pan-cancer application of ABSOLUTE.
Figure 4: Characterization of subclonal evolution in ovarian cancer by integrative analysis of SNP array and whole-exome sequencing data.
Figure 5: Classification of somatic mutations by multiplicity analysis in 214 primary HGS-OvCa tumor samples.
Figure 6: Incidence and timing of whole-genome doubling events in primary cancers.
Figure 7: Genetic and clinical associations with genome doubling in primary HGS-OvCa samples.

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Acknowledgements

This work was supported by grants from the National Cancer Institute as part of The Cancer Genome Atlas project: U24CA126546 (M.M.), U24CA143867 (M.M.), and U24CA143845 (G.G.). S.L.C. and E.H. were supported by training grant T32 HG002295 from the National Human Genome Research Institute. In addition, D.P. was supported by the US National Institutes of Health (NIH) - 5R01 GM083299-14; D.A.L. by Department of Defense W81XWH-10-1-0222; T.Z. by NIH/National Institute of General Medical Sciences 5 T32 GM008313; R.B. by NIH K08CA122833 and U54CA143798. B.A.W. was supported by National Research Service Award grant F32CA113126.

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Author notes

  1. Kristian Cibulskis, Elena Helman, Aaron McKenna, Hui Shen and Travis Zack: These authors contributed equally to this work.

Authors and Affiliations

  1. The Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA

    Scott L Carter, Kristian Cibulskis, Elena Helman, Aaron McKenna, Robert C Onofrio, Wendy Winckler, Barbara A Weir, Rameen Beroukhim, Eric S Lander, Matthew Meyerson & Gad Getz

  2. Division of Health Sciences and Technology, MIT, Cambridge, Massachusetts, USA

    Scott L Carter & Elena Helman

  3. USC Epigenome Center, Keck School of Medicine, University of Southern California, Los Angeles, California, USA

    Hui Shen & Peter W Laird

  4. Biophysics Program, Harvard University, Cambridge, Massachusetts, USA

    Travis Zack

  5. Divisions of Medical Oncology and Cancer Biology and Center for Cancer Genome Discovery, Dana-Farber Cancer Institute, Boston, Massachusetts, USA

    Travis Zack, Rameen Beroukhim & Matthew Meyerson

  6. Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA

    Rameen Beroukhim

  7. Department of Pediatric Oncology, Department of Cell Biology, Howard Hughes Medical Institute, Dana-Farber Cancer Institute, Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA

    David Pellman

  8. Department of Surgery, Gynecology Service, Memorial Sloan-Kettering Cancer Center, New York, New York, USA

    Douglas A Levine

  9. Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA

    Eric S Lander

  10. MIT Department of Biology, Cambridge, Massachusetts, USA

    Eric S Lander

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Contributions

M.M. posed the concept of using allelic copy number analysis to assess tumor genomic purity. G.G. and S.L.C. conceived and designed the analysis. S.L.C. designed and implemented the ABSOLUTE algorithm, and performed data analysis. K.C. assisted with mutation calling and validation. E.H. performed analysis with ASCAT and assisted with multiplicity analysis. A.M. assisted with the determination of statistical power for the ovarian cancer data. T.Z. assisted with analysis of the SCNA length distribution versus genome doubling. R.C.O. and W.W. processed the SNP array experiments. W.W. designed and executed the DNA mixing experiment. H.S. and P.W.L. conceived and executed the leukocyte methylation signature analysis. B.A.W. contributed insight into allelic analysis of SNP array data. D.A.L. managed the FACS analysis of specimens for ploidy determination. All authors contributed to the final manuscript. D.P. and R.B. provided critical review of the manuscript. S.L.C., M.M., G.G. and E.S.L. wrote the manuscript. R.B., M.M. and G.G. provided leadership for the project.

Corresponding authors

Correspondence to Scott L Carter or Gad Getz.

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Competing interests

M.M. is an equity holder in and consultant for Foundation Medicine, and is a consultant for, and receives research support from, Novartis.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–12 and Supplementary Note (PDF 3420 kb)

Supplementary Table 1

Pan-cancer analysis: sample characteristics and predicted purity / ploidy values (TXT 658 kb)

Supplementary Table 2

Pan-cancer analysis: segmented absolute allelic copy numbers (TXT 27073 kb)

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Carter, S., Cibulskis, K., Helman, E. et al. Absolute quantification of somatic DNA alterations in human cancer. Nat Biotechnol 30, 413–421 (2012). https://doi.org/10.1038/nbt.2203

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