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Updated: Jun 2, 2026

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
Published on: April 6, 2016
Characterization of a serum protein pattern from NSCLC patients treated with Gefitinib
V M Garrisi1, I Bongarzone, A Mangia
1IRCCS National Cancer Centre Giovanni Paolo II, Department of Experimental Oncology, Bari, Italy. vmgarrisi@libero.it
Objectives:
The purpose of this study was to evaluate the efficacy of a protein-based pattern in serum previously determined by MALDI-TOF-MS (Matrix Assisted Laser Desorption Ionization-Time of Flight) and considered potentially useful for prediction of clinical outcome of EGFR (epidermal growth factor receptor) TKIs (tyrosine kinase inhibitors) treated patients.
Design And Methods:
We generated SELDI-TOF (Surface Enhanced Laser Desorption Ionization-Time of Flight) spectra in sera of 11 advanced NSCLC treated with Gefitinib. We detected the clusters with m/z 5843, 11445, 11529, 11685, 11759 and 11903 which were previously reported to be potential predictors of response to Gefitinib treatment.
Results:
Four cluster peaks with m/z 5843, 11445, 11529, 11685 corresponded to SAA (serum amyloid A) protein on the basis on their calculated molecular weight, peptide fingerprinting and antibodies recognition.
Conclusions:
We confirm that several proteins already reported were isoforms of SAA but further studies are in development in order to evaluate the predictive value of such algorithm.
