MSKCC-A Primary Lung Cancer Specimens
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Luc Girard
PROVIDER: E-GEOD-31547 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:Develop an EGFR mutation gene expression signature to aid in predicting response and clinical outcome and to identify genes associated with the EGFR-dependent phenotype 30 primary lung adenocarcinomas and 20 adjacent normal lung controls were analyzed with Affymetrix U133B
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Project description:EGFR-mutated non-small cell lung cancers bear hallmarks including sensitivity to EGFR inhibitors, and low proliferation, and increased MET. However, the biology of EGFR dependence is still poorly understood. Using a training cohort of chemo-naive lung adenocarcinomas, we have developed a 72-gene signature that predicts (i) EGFR mutation status in four independent datasets; (ii) sensitivity to erlotinib in vitro; and (iii) improved survival, even in the wild-type EGFR subgroup. The signature includes differences associated with enhanced receptor tyrosine kinase (RTK) signaling, such as increased expression of endocytosis-related genes, decreased phosphatase levels, decreased expression of proliferation-related genes, increased folate receptor-1 (FOLR1) (a determinant of pemetrexed response), and higher levels of MACC1 (which we identify as a regulator of MET in EGFR-mutant NSCLC). Those observations provide evidence that the EGFR-mutant phenotype is associated with alterations in the cellular machinery that links the EGFR and MET pathways and create a permissive environment for RTK signaling. We have developed a gene expression signature that predicts (i) EGFR mutation in chemo-naive and, to a lesser extent, in chemo-refractory NSCLC patients; (ii) EGFR TKI response in vitro; and (iii) survival in wild-type EGFR patients. The signature also identifies novel features of EGFR mutant NSCLC including increased levels of endocytosis-related genes and MACC1, which appears be an EGFR mutant associated regulator of MET. Gene expression profiles were measured in 124 core biopsies from patients with refractory non-small cell lung cancer in the Biomarker-integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) trial. We used the BATTLE dataset to test an EGFR-mutation gene expression signature trained in chemo-naive lung adenocarcinoma. The signature was computed as an index, called EGFR index.
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