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 also support a new molecular stratification of pediatric low-grade gliomas based on BRAF mutations that may have immediate clinical impact.Our results demonstrate the clinical feasibility of high-throughput mutation profiling to query a large panel of "actionable" cancer gene mutations. In the future, this type of approach may be incorporated into both cancer epidemiologic studies and clinical decision making to specify the use of many targeted anticancer agents.
<p>GC PDXs are annotated for: CNV of HER2, EGFR, FGFR2, MET, KRAS ({greater than or equal to}8 gene copies); COSMIC Mutations/Frameshifts (Allelic frequency >0.3)</p>
Supplementary Data from Decreased Selenium-Binding Protein 1 in Esophageal Adenocarcinoma Results from Posttranscriptional and Epigenetic Regulation and Affects Chemosensitivity
<p>Supplementary Table 1. Tumor and sequencing information for Cohort 1, paired primary and metastatic gastric adenocarcinoma samples; Supplementary Table 2. 243-gene targeted panel used for sequencing of Cohort 2 samples; Supplementary Table 3: Wild type and mutant read counts for paired primary and metastatic samples in cohort 1; Supplementary Table 4. Clinical and pathologic characteristics of Cohort 2; Supplementary Table 5. Complete sequencing results of Cohort 2; Supplementary Table 6. Clinical characteristics of Cohort 3; Supplementary Table 7. Treatment assignment algorithm of PANGEA clinical trial; Supplementary Table 8. Clinical Characteristics and Response Data of evaluable patients in the PANGEA cohort (N = 21)</p>
