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RATIONALE: DNA analysis of tumor tissue may help doctors predict how well patients will respond to treatment.
- To demonstrate that vascular endothelial growth factor-A (VEGFA) haplotypes that are associated with an increased VEGFA expression will predict superior outcome for patients with metastatic breast cancer receiving bevacizumab in ECOG-E2100 (but not for the control arm).
- To demonstrate that candidate single nucleotide polymorphisms (SNPs) will further improve the predictive capacity of outcome (efficacy and toxicity) in patients enrolled in ECOG-E2100.
- To demonstrate that tumor VEGFA amplification or borderline amplification (estimated 14% frequency) will predict superior outcome for patients with metastatic breast cancer receiving bevacizumab on ECOG-E2100 whereas those with VEGFA deletion (estimated 11% frequency) will predict inferior outcome.
- To demonstrate that VEGFA amplification/deletion will not predict outcome in the control arm of ECOG-E2100.
- To demonstrate that tumor VEGFA amplification will predict increased protein expression as ascertained by IHC.
- To demonstrate that a combined algorithm calculated from tumor-specific variability (VEGFA amplification/deletion) and host-specific variability (SNPs) will optimally predict outcome (efficacy) with bevacizumab in patients enrolled on ECOG-E2100.
OUTLINE: This is a multicenter study.
Previously collected tumor-derived DNA is analyzed for VEGFA amplification/deletion and haplotype as biomarkers for outcome after bevacizumab treatment. Gene expression, polymorphism, and protein expression analysis and immunohistochemistry are performed on the samples.
DNA analysis, gene expression analysis, polymorphism analysis, protein expression analysis, immunohistochemistry staining method, laboratory biomarker analysis
Not yet recruiting
National Cancer Institute (NCI)
Published on BioPortfolio: 2014-08-27T03:12:29-0400
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