Multi-institutional Oncogenic Driver Mutation Analysis in Lung Adenocarcinoma: The Lung Cancer Mutation Consortium Experience

Abstract

Introduction: Molecular genetic analyses of lung adenocarcinoma have recently become standard of care for treatment selection. The Lung Cancer Mutation Consortium was formed to enable collaborative multi-institutional analyses of 10 potential oncogenic driver mutations. Technical aspects of testing and clinicopathologic correlations are presented.

Methods: Mutation testing in at least one of the eight genes (epidermal growth factor receptor [EGFR], KRAS, ERBB2, AKT1, BRAF, MEK1, NRAS, and PIK3CA) using SNaPshot, mass spectrometry, Sanger sequencing+/- peptide nucleic acid and/or sizing assays, along with anaplastic lymphoma kinase (ALK) and/or MET fluorescence in situ hybridization, were performed in six labs on 1007 patients from 14 institutions.

Results: In all, 1007 specimens had mutation analysis performed, and 733 specimens had all 10 genes analyzed. Mutation identification rates did not vary by analytic method. Biopsy and cytology specimens were inadequate for testing in 26% and 35% of cases compared with 5% of surgical specimens. Among the 1007 cases with mutation analysis performed, EGFR, KRAS, ALK, and ERBB2 alterations were detected in 22%, 25%, 8.5%, and 2.4% of cases, respectively. EGFR mutations were highly associated with female sex, Asian race, and never-smoking status; and less strongly associated with stage IV disease, presence of bone metastases, and absence of adrenal metastases. ALK rearrangements were strongly associated with never-smoking status and more weakly associated with presence of liver metastases. ERBB2 mutations were strongly associated with Asian race and never-smoking status. Two mutations were seen in 2.7% of samples, all but one of which involved one or more of PIK3CA, ALK, or MET.

Conclusion: Multi-institutional molecular analysis across multiple platforms, sample types, and institutions can yield consistent results and novel clinicopathological observations.

Figures

Figure 1. Mutations identified in the LCMC cohort

A pie chart is shown in which the size of each slice is proportional to the mutation frequency in the full genotyping set of 733 patients. Cases with two mutations are represented only once based on the mutation that primarily dictated clinical care in each patient. As a result the frequencies of ALK, MET, and PIK3CA alterations appear somewhat lower in this figure. (See Table 4 for details.) Frequencies presented here also differ slightly for some genes in comparison to frequencies for the any-genotyping group (n=1007). Please see details of the full-genotyping vs. any-genotyping cohorts, and a comprehensive breakdown of all mutations identified in our original paper on the LCMC experience, ref. 14).

Figure 2. Demographic and prognostic associations with any and individual specific mutations

Statistically significant and other notable associations are shown in the form of bar graphs for several mutation types. “Any” refers to any identified mutation. KRAS, EGFR, and ERBB2 consist of all point mutations occurring in those genes; ALK refers to translocations involving ALK, and MET refers to amplification of the MET locus, identified by FISH. More detailed demographic and prognostic association data are provided in Supplemental Table 7.