Development of a Serum Proteomic Classifier for the Prediction of Benefit From Bevacizumab in Combination With Carboplatin and Paclitaxel
- 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.
- 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.
David P. Carbone, MD, PhD
Vanderbilt-Ingram Cancer Center