Research ArticleCancer

Personalized genomic analyses for cancer mutation discovery and interpretation

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Science Translational Medicine  15 Apr 2015:
Vol. 7, Issue 283, pp. 283ra53
DOI: 10.1126/scitranslmed.aaa7161

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.


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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