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Will the real mutation please stand up?

When a patient is diagnosed with cancer, a sample of the tumor is often analyzed to look for mutations that might guide the approach to targeted treatment of the disease. Jones et al. analyzed samples from more than 800 patients with 15 different cancer types and showed that this standard approach is not necessarily accurate without also analyzing a matched sample of normal DNA from the same patient. The authors found that, compared to analysis of paired samples, the standard tumor-only sequencing approach frequently identified mutations that were present in the patient’s normal tissues and were therefore not suitable for targeted therapy or, conversely, missed useful new mutations in the tumor.

Abstract

Massively parallel sequencing approaches are beginning to be used clinically to characterize individual patient tumors and to select therapies based on the identified mutations. A major question in these analyses is the extent to which these methods identify clinically actionable alterations and whether the examination of the tumor tissue alone is sufficient or whether matched normal DNA should also be analyzed to accurately identify tumor-specific (somatic) alterations. To address these issues, we comprehensively evaluated 815 tumor-normal paired samples from patients of 15 tumor types. We identified genomic alterations using next-generation sequencing of whole exomes or 111 targeted genes that were validated with sensitivities >95% and >99%, respectively, and specificities >99.99%. These analyses revealed an average of 140 and 4.3 somatic mutations per exome and targeted analysis, respectively. More than 75% of cases had somatic alterations in genes associated with known therapies or current clinical trials. Analyses of matched normal DNA identified germline alterations in cancer-predisposing genes in 3% of patients with apparently sporadic cancers. In contrast, a tumor-only sequencing approach could not definitively identify germline changes in cancer-predisposing genes and led to additional false-positive findings comprising 31% and 65% of alterations identified in targeted and exome analyses, respectively, including in potentially actionable genes. These data suggest that matched tumor-normal sequencing analyses are essential for precise identification and interpretation of somatic and germline alterations and have important implications for the diagnostic and therapeutic management of cancer patients.
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Supplementary Material

Summary

Fig. S1. Bioinformatic approach to classify somatic and germline mutations on the basis of the consequence of the alteration.
Fig. S2. Bioinformatic approach to classify somatic and germline mutations based on the affected protein domain.
Table S1. Genes analyzed in the targeted approach (provided in a separate Excel file).
Table S2. Summary of sequencing statistics (provided in a separate Excel file).
Table S3. Summary of performance characteristics of whole-exome and targeted analyses (provided in a separate Excel file).
Table S4. Characteristics of the tumor and normal samples (provided in a separate Excel file).
Table S5. Fraction of cases with somatic mutations in actionable genes (provided in a separate Excel file).
Table S6. Fraction of cases with evidence for clinical actionability in different tumor types (provided in a separate Excel file).
Table S7. Hereditary cancer predisposition genes (provided in a separate Excel file).
Table S8. Putative germline predisposing mutations (provided in a separate Excel file).
Table S9. Germline false-positive mutations in actionable genes (provided in a separate Excel file).

Resources

File (7-283ra53_sm.pdf)
File (7-283ra53_tables_s1_to_s9.zip)

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Published In

Science Translational Medicine
Volume 7 | Issue 283
April 2015

Submission history

Received: 18 January 2015
Accepted: 6 March 2015

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Acknowledgments

We thank V. Adleff and L. D. Wood for technical assistance and J. R. Eshelman, R. H. Hruban, and members of our laboratories for helpful discussions. Funding: This work was supported in part by the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation, the Commonwealth Foundation, American Association for Cancer Research Stand Up To Cancer–Dream Team Translational Cancer Research grant, John G. Ballenger Trust, FasterCures Research Acceleration Award, Swim Across America, and U.S. NIH grant CA121113. Author contributions: S.J. designed the study, performed analyses, and wrote the paper. V.A., K.L., S.P.-L., M.N., D.R.R., M.K., E.P., K.G.G., D.M., and T.Z. performed analyses; M.S. and S.V.A. performed analyses and wrote the paper. M.S., B.C., and L.K. performed experiments. L.A.D. and V.E.V. designed the study, performed analyses, provided funding, and wrote the paper. Competing interests: Some of the work described in this publication is included in a pending patent application. L.A.D. and V.E.V. are cofounders of Personal Genome Diagnostics and are members of its Scientific Advisory Board and Board of Directors. L.A.D. and V.E.V. own Personal Genome Diagnostics stock, which is subject to certain restrictions under university policy. The terms of these arrangements are managed by the Johns Hopkins University in accordance with its conflict of interest policies.

Authors

Affiliations

Siân Jones
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Valsamo Anagnostou
The Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Karli Lytle
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Sonya Parpart-Li
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Monica Nesselbush
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
David R. Riley
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Manish Shukla
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Bryan Chesnick
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Maura Kadan
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Eniko Papp
The Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Kevin G. Galens
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Derek Murphy
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Theresa Zhang
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Lisa Kann
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Mark Sausen
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Samuel V. Angiuoli
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Luis A. Diaz, Jr.
The Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Victor E. Velculescu* [email protected]
The Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.

Notes

*Corresponding author. E-mail: [email protected]

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