Optimized algorithm for Sanger sequencing-based EGFR mutation analyses in NSCLC biopsies.

摘要

Pulmonary adenocarcinoma patients harboring EGFR mutations can benefit from tyrosine kinase inhibitor therapy. Reliable molecular analyses and precise pathological reporting of the EGFR mutational status are factors essential for patient treatment and outcome. More than 70?% of all EGFR mutation analyses are performed on non-small cell lung cancer (NSCLC) biopsies. However, biopsies may not be sufficient for mutation analysis due to low tumor content and admixture with non-neoplastic cells. To define the minimal concentration of tumor cells required for reliable EGFR mutational diagnostics by Sanger sequencing and to develop an algorithm for routine diagnostics on biopsy material, we determined total numbers of tumor and non-tumor cells, calculated the tumor cell concentration and serially diluted DNA from EGFR-mutated NSCLC by adding DNA of non-tumor cells from the same section. A counted tumor cell concentration of 30?%, which refers to a histologically estimated concentration of 40?%, is necessary for reliable detection of all mutations. Based on these data, we developed an algorithm for evidence-based EGFR mutation analysis by Sanger sequencing in biopsy specimens, which was subsequently applied to 461 diagnostic cases. Optimized diagnostic testing results in 80?% reliable EGFR mutation analyses of biopsy specimens, while in 20?% of cases re-biopsies had to be recommended.