Mutation-specific antibodies for the detection of EGFR mutations in non-small-cell lung cancer.

PURPOSE: Activating mutations within the tyrosine kinase domain of epidermal growth factor receptor (EGFR) are found in approximately 10% to 20% of non-small-cell lung cancer (NSCLC) patients and are associated with response to EGFR inhibitors. The most common NSCLC-associated EGFR mutations are deletions in exon 19 and L858R mutation in exon 21, together accounting for 90% of EGFR mutations. To develop a simple, sensitive, and reliable clinical assay for the identification of EGFR mutations in NSCLC patients, we generated mutation-specific rabbit monoclonal antibodies against each of these two most common EGFR mutations and aimed to evaluate the detection of EGFR mutations in NSCLC patients by immunohistochemistry. EXPERIMENTAL DESIGN: We tested mutation-specific antibodies by Western blot, immunofluorescence, and immunohistochemistry. In addition, we stained 40 EGFR genotyped NSCLC tumor samples by immunohistochemistry with these antibodies. Finally, with a panel of four antibodies, we screened a large set of NSCLC patient samples with unknown genotype and confirmed the immunohistochemistry results by DNA sequencing. RESULTS: These two antibodies specifically detect the corresponding mutant form of EGFR by Western blotting, immunofluorescence, and immunohistochemistry. Screening a panel of 340 paraffin-embedded NSCLC tumor samples with these antibodies showed that the sensitivity of the immunohistochemistry assay is 92%, with a specificity of 99% as compared with direct and mass spectrometry-based DNA sequencing. CONCLUSIONS: This simple assay for detection of EGFR mutations in diagnostic human tissues provides a rapid, sensitive, specific, and cost-effective method to identify lung cancer patients responsive to EGFR-based therapies.

Global survey of phosphotyrosine signaling identifies oncogenic kinases in lung cancer.

Despite the success of tyrosine kinase-based cancer therapeutics, for most solid tumors the tyrosine kinases that drive disease remain unknown, limiting our ability to identify drug targets and predict response. Here we present the first large-scale survey of tyrosine kinase activity in lung cancer. Using a phosphoproteomic approach, we characterize tyrosine kinase signaling across 41 non-small cell lung cancer (NSCLC) cell lines and over 150 NSCLC tumors. Profiles of phosphotyrosine signaling are generated and analyzed to identify known oncogenic kinases such as EGFR and c-Met as well as novel ALK and ROS fusion proteins. Other activated tyrosine kinases such as PDGFRalpha and DDR1 not previously implicated in the genesis of NSCLC are also identified. By focusing on activated cell circuitry, the approach outlined here provides insight into cancer biology not available at the chromosomal and transcriptional levels and can be applied broadly across all human cancers.

Evaluation of CML model cell lines and imatinib mesylate response: determinants of signaling profiles.

Our understanding of the mechanisms by which BCR-ABL drives CML is based, in part, on the use of model cell lines such as the K562 cell line. However, the BCR-ABL translocation may occur via a number of different junction points. In addition, CML is a disease of hematopoietic stem cells and, as a result, can give rise to multiple lineages of tumor cells. In this study, we examined the cellular signaling profiles following imatinib mesylate treatment of eight model CML and ALL cell lines that encompass three BCR-ABL junction points and multiple lineages. We used phosphorylation-specific antibodies and flow cytometry to determine the kinase and pathway activation states with each of the cell lines before and after imatinib mesylate exposure. The comparisons of signaling response profiles, junction points and lineages indicate that cell line lineage rather than BCR-ABL junction point may determine cellular response to imatinib mesylate. The large amount of variation observed among the cell lines suggests that further analysis is required to understand the complex signaling profiles present in CML patients.