Profiling critical cancer gene mutations in clinical tumor samples.

PloS One
Laura E MacConaillLevi A Garraway

Abstract

Detection of critical cancer gene mutations in clinical tumor specimens may predict patient outcomes and inform treatment options; however, high-throughput mutation profiling remains underdeveloped as a diagnostic approach. We report the implementation of a genotyping and validation algorithm that enables robust tumor mutation profiling in the clinical setting. We developed and implemented an optimized mutation profiling platform ("OncoMap") to interrogate approximately 400 mutations in 33 known oncogenes and tumor suppressors, many of which are known to predict response or resistance to targeted therapies. The performance of OncoMap was analyzed using DNA derived from both frozen and FFPE clinical material in a diverse set of cancer types. A subsequent in-depth analysis was conducted on histologically and clinically annotated pediatric gliomas. The sensitivity and specificity of OncoMap were 93.8% and 100% in fresh frozen tissue; and 89.3% and 99.4% in FFPE-derived DNA. We detected known mutations at the expected frequencies in common cancers, as well as novel mutations in adult and pediatric cancers that are likely to predict heightened response or resistance to existing or developmental cancer therapies. OncoMap profiles als...Continue Reading

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Methods Mentioned

BETA
biopsy
genotyping
Assay
dissection
laser-capture microdissection
PCR
Illumina sequencing

Software Mentioned

OncoMapâsupported
OncoMap

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