EGFR Gene Signature May Predict Prognosis and Guide Treatment in Lung Cancer
EGFR Gene Signature May Predict Prognosis and Guide Treatment in Lung Cancer
Oncogenically mutated epidermal growth-factor receptor (EGFR) is a validated therapeutic target for nonsmall-cell lung cancer (NSCLC). Researchers now report that they have identified a 93-gene signature that is significantly associated with EGFR mutations in NSCLC patients.
The study results suggest that the gene signature might provide “predictive value and biological insights” into EGFR inhibitor responses in lung adenocarcinomas, researchers told meeting attendees here at the American Association for Cancer Research-International Association for the Study of Lung Cancer Joint Conference on Molecular Origins of Lung Cancer: Prospects for Personalized Prevention and Therapy.
“The mutation signature may be able to help guide medical treatment decisions in the future and provide prognostic information beyond just EGFR mutation status,” said lead author Pierre Saintigny, MD, PhD, a research scientist at the University of Texas M.D. Anderson Cancer Center in Houston, in an interview.
The signature also correlated with sensitivity to erlotinib and gefitinib, which target EGFR, he said, adding that it might also help identify patients who might benefit from EGFR-targeted treatments, regardless of their mutation status.
There is currently a great deal of interest in this field; clinical data have shown that erlotinib and gefitinib work best in NSCLC patients with EGFR mutations, but questions have been raised over the practicality of testing for these mutations in clinical practice, as reported recently by Medscape Oncology.
Testing of Lung Cancer Samples
In this study, Dr. Saintigny and colleagues evaluated messenger (m)RNA expression in 195 lung adenocarcinoma samples using several microarray platforms, and then conducted a similar analysis on 53 NSCLC cell lines. The tumor sets used for developing the EGFR-mutation signature came from the University of Hong Kong, the University of Michigan Comprehensive Cancer Center, Memorial Sloan-Kettering Cancer Center, and the University of Texas M.D. Anderson Cancer Center.
The samples from M.D. Anderson were derived from the ongoing Biomarker-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE I) trial.
The tumor samples used in the training set came primarily from patients with early stage I to II disease (78%), and just over half (57%) were former/current smokers. In all, 54% of the cohort had the EGFR mutation, and all patients were treatment-naive.
The researchers also examined gefitinib and erlotinib drug-response phenotypes in the NSCLC lines, and training and testing sets and cross-validation were used to test and evaluate the mRNA signature model.
The 93-gene signature was developed using the 3 training sets, and was consistently associated with EGFR mutations in different datasets. The validation study was conducted using 99 samples from patients with chemotherapy-refractory advanced-stage NSCLC who are participating in the BATTLE I trial.
Associated With Survival
The validation trial showed that the signature had an accuracy of 67%, which was significantly associated with EGFR mutations in an independent cohort (P = .014). The prediction accuracy of the signature was further analyzed with receiver operating characteristic curves and, for the NSCLC cell lines (53 samples), the area under the curve was 0.95 (P = 2.2e–06).
The gene signature was found to be associated with survival in a separate dataset of 442 early-stage adenocarcinomas (hazard ratio, 0.85; P = 3.73e–03). The researchers also found the gene sets associated with endocytosis and vesicle recycling to be upregulated in EGFR-mutant tumors, whereas mitotic-related genes were downregulated.
The BATTLE I trial is part of a set of studies that are examining the genetic profiles of individual tumors and then assigning therapies that offer the best benefits on the basis of the tumor’s unique characteristics. “The EGFR-mutation signature will be evaluated as a predictor of response in the BATTLE I trial,” said Dr. Saintigny, adding that they will be presenting those results later this year at the annual meeting of the American Society of Clinical Oncology.
