Development of a Serum Proteomic Classifier for the Prediction of Benefit From Bevacizumab in Combination With Carboplatin and Paclitaxel
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Lung Cancer
- Sponsor
- ECOG-ACRIN Cancer Research Group
- Enrollment
- 90
- Primary Endpoint
- Survival
- Status
- Completed
- Last Updated
- 8 years ago
Overview
Brief Summary
RATIONALE: Studying samples of blood in the laboratory from patients undergoing treatment for non-small cell lung cancer may help doctors predict how patients will respond to treatment.
PURPOSE: This laboratory study is looking at proteomic patterns in stored blood samples from patients undergoing treatment for non-small cell lung cancer.
Detailed Description
OBJECTIVES: Primary * To develop a serum proteomic classifier using matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry analysis of blood samples from patients with non-squamous cell non-small cell lung cancer to predict benefit, in terms of survival and time to progression, from treatment with bevacizumab in combination with carboplatin and paclitaxel. Secondary * To better quantitate candidate biomarkers by using more advanced mass spectrometric technologies, including multiple-reaction monitoring and heavy-labeled peptides. OUTLINE: Previously collected pre-treatment samples of serum or plasma are randomly selected from patients enrolled on protocol ECOG-4599 (i.e., 60 from the bevacizumab arm and 30 from the control arm). Samples are analyzed by matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry to identify patterns from protein spectra that correlate with patient survival.
Investigators
Eligibility Criteria
Inclusion Criteria
- Not provided
Exclusion Criteria
- Not provided
Outcomes
Primary Outcomes
Survival
Time Frame: 1 day