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| Status |
Public on Jun 01, 2014 |
| Title |
An EGFR-mutation signature reveals features of the EGFR-dependent phenotype and identifies MACC1 as an EGFR-associated regulator of MET. |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by array
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| Summary |
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.
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| Overall design |
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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| Contributor(s) |
Saintigny P, Wistuba II, Heymach JV, Kim ES, Lippman SM, Herbst RS, Hong WK, Lee JJ, Coombes KR, Mao L |
| Citation missing |
Has this study been published? Please login to update or notify GEO. |
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| Submission date |
Sep 02, 2011 |
| Last update date |
Jul 26, 2018 |
| Contact name |
Pierre Saintigny |
| E-mail(s) |
[email protected]
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| Organization name |
The University of Texas M.D. Anderson Cancer Center
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| Department |
Thoracic / Head and Neck Medical Oncology
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| Street address |
1515 Holcombe
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| City |
Houston |
| ZIP/Postal code |
77030 |
| Country |
USA |
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| Platforms (1) |
| GPL6244 |
[HuGene-1_0-st] Affymetrix Human Gene 1.0 ST Array [transcript (gene) version] |
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| Samples (124)
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| Relations |
| BioProject |
PRJNA155255 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE31852_RAW.tar |
562.4 Mb |
(http)(custom) |
TAR (of CEL) |
| Processed data included within Sample table |
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