Molecular Cancer Research · 2014 · 116 citations · 27 references
MedicineGeneticsOncologyCancer GeneticsGenomicsMolecular OncologyCancer GenomicsMalignant NeoplasmsMolecular Tumor ProfilingNext-generation Sequencing In OncologySquamous Cell CarcinomaExome SequencingGenomic Dna AnalysisPik3ca MutationsTumor Exome SequencingTumor Mutation AnalysisTumor ProfilingWhole Exome Sequencing StudiesWhole-exome Sequencing Analysis
UNLABELLED: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common type of cancer worldwide. The increasing amount of genomic information on human tumors and cell lines provides more biologic data to design preclinical studies. We and others previously reported whole-exome sequencing data of 106 HNSCC primary tumors. In 2012, high-throughput genomic data and pharmacologic profiling of anticancer drugs of hundreds of cancer cell lines were reported. Here, we compared the genomic data of 39 HNSCC cell lines with the genomic findings in 106 HNSCC tumors. Amplification of eight genes (PIK3CA, EGFR, CCND2, KDM5A, ERBB2, PMS1, FGFR1, and WHSCIL1) and deletion of five genes (CDKN2A, SMAD4, NOTCH2, NRAS, and TRIM33) were found in both HNSCC cell lines and tumors. Seventeen genes were only mutated in HNSCC cell lines (>10%), suggesting that these mutations may arise through immortalization in tissue culture. Conversely, 11 genes were only mutated in >10% of human HNSCC tumors. Several mutant genes in the EGF receptor (EGFR) pathway are shared both in cell lines and in tumors. Pharmacologic profiling of eight anticancer agents in six HNSCC cell lines suggested that PIK3CA mutation may serve as a predictive biomarker for the drugs targeting the EGFR/PI3K pathway. These findings suggest that a correlation of gene mutations between HNSCC cell lines and human tumors may be used to guide the selection of preclinical models for translational research. IMPLICATIONS: These findings suggest that a correlation of gene mutations between HNSCC cell lines and human tumors may be used to guide the selection of preclinical models for translational research.
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