Classification by mass spectrometry can accurately and reliably predict outcome in patients with non-small cell lung cancer treated with erlotinib-containing regimen.

Salmon S, Chen H, Chen S, Herbst R, Tsao A, Tran H, Sandler A, Billheimer D, Shyr Y, Lee JW, Massion P, Brahmer J, Schiller J, Carbone D, Dang TP
J Thorac Oncol. 2009 4 (6): 689-96

PMID: 19404214 · PMCID: PMC3563261 · DOI:10.1097/JTO.0b013e3181a526b3

PURPOSE - Although many lung cancers express the epidermal growth factor receptor and the vascular endothelial growth factor, only a small fraction of patients will respond to inhibitors of these pathways. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MS) has shown promise in biomarker discovery, potentially allowing the selection of patients who may benefit from such therapies. Here, we use a matrix-assisted laser desorption/ionization MS proteomic algorithm developed from a small dataset of erlotinib-bevacizumab treated patients to predict the clinical outcome of patients treated with erlotinib alone.

METHODS - Pretreatment serum collected from patients in a phase I/II study of erlotinib in combination with bevacizumab for recurrent or refractory non-small cell lung cancer was used to develop a proteomic classifier. This classifier was validated using an independent treatment cohort and a control population.

RESULT - A proteomic profile based on 11 distinct m/z features was developed. This predictive algorithm was associated with outcome using the univariate Cox proportional hazard model in the training set (p = 0.0006 for overall survival; p = 0.0012 for progression-free survival). The signature also predicted overall survival and progression-free survival outcome when applied to a blinded test set of patients treated with erlotinib alone on Eastern Cooperative Oncology Group 3503 (n = 82, p < 0.0001 and p = 0.0018, respectively) but not when applied to a cohort of patients treated with chemotherapy alone (n = 61, p = 0.128).

CONCLUSION - The independently derived classifier supports the hypothesis that MS can reliably predict the outcome of patients treated with epidermal growth factor receptor kinase inhibitors.

MeSH Terms (25)

Adult Aged Aged, 80 and over Antibodies, Monoclonal Antibodies, Monoclonal, Humanized Antineoplastic Combined Chemotherapy Protocols Bevacizumab Biomarkers, Tumor Carcinoma, Non-Small-Cell Lung Case-Control Studies Cohort Studies Erlotinib Hydrochloride Female Humans Lung Neoplasms Male Middle Aged Neoplasm Recurrence, Local Pleural Effusion, Malignant Prognosis Quinazolines Reproducibility of Results Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Survival Rate Treatment Outcome

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