RATIONALE: Studying samples of tissue from patients with cancer in the laboratory may help doctors learn more about changes that occur in DNA and identify biomarkers related to cancer. It may also help doctors predict how patients respond to treatment with erlotinib. PURPOSE: This laboratory study is developing a model to predict progression-free survival after erlotinib in patients with non-small cell lung cancer.
OBJECTIVES: * Assess mesenchymal and epithelial markers in tissues from patients with non-small cell lung cancer treated with erlotinib hydrochloride on clinical trial ECOG-E3503. * Determine the loss of epithelial markers (E-cadherin) and gain of mesenchymal markers (vimentin/cytokeratin co-expression) in these patients. * Assess whether mesenchymal and epithelial markers are predictive of progression-free survival (PFS) of these patients. * Identify a single nucleotide polymorphism profile via whole genome mapping and other known biomarkers to predict PFS of these patients. OUTLINE: Tissue samples are analyzed by whole genome mapping for single nucleotide polymorphism (SNP) rate and by signal detection rate and by quantitative immunohistochemistry for mesenchymal (vimentin/cytokeratin) and epithelial (E-cadherin) marker transitions. After biomarker identification and gene mapping are complete, a model to predict progression-free survival in these patients is developed. PROJECTED ACCRUAL: A total of 137 samples will be accrued for this study.
Study Type
OBSERVATIONAL
Enrollment
137
Mesenchymal and epithelial markers
Mesenchymal and epithelial markers
Time frame: 1 month
Loss of epithelial markers (E-cadherin) and gain of mesenchymal markers (vimentin/cytokeratin co-expression)
Loss of epithelial markers (E-cadherin) and gain of mesenchymal markers
Time frame: 1 month
Correlation of progression-free survival (PFS) by mesenchymal and epithelial markers
Correlation of progression-free survival (PFS) by mesenchymal and epithelial markers
Time frame: 1 month
Identification of a single nucleotide polymorphism profile via whole genome mapping and other known biomarkers to predict PFS
Identification of a single nucleotide polymorphism profile via whole genome mapping and other known biomarkers to predict PFS
Time frame: 1 month
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