Detection of Tumor Epidermal Growth Factor Receptor Pathway Dependence by Serum Mass Spectrometry in Cancer Patients

Overview

Journal Cancer Epidemiol Biomarkers Prev

Specialties Biochemistry
Oncology
Public Health

Date 2010 Jan 21

PMID 20086114

Citations 29

Authors

Christine H Chung

Erin H Seeley

Heinrich Roder

Julia Grigorieva

Maxim Tsypin

Joanna Roder

Barbara A Burtness

Athanassios Argiris

Arlene A Forastiere

Jill Gilbert

Barbara Murphy

Richard M Caprioli

David P Carbone

Ezra E W Cohen

Affiliations

Soon will be listed here.

Abstract

Background: We hypothesized that a serum proteomic profile predictive of survival benefit in non-small cell lung cancer patients treated with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKI) reflects tumor EGFR dependency regardless of site of origin or class of therapeutic agent.

Methods: Pretreatment serum or plasma from 230 patients treated with cetuximab, EGFR-TKIs, or chemotherapy for recurrent/metastatic head and neck squamous cell carcinoma (HNSCC) or colorectal cancer (CRC) were analyzed by mass spectrometry. Each sample was classified into "good" or "poor" groups using VeriStrat, and survival analyses of each cohort were done based on this classification. For the CRC cohort, this classification was correlated with the tumor EGFR ligand levels and KRAS mutation status.

Results: In the EGFR inhibitor-treated cohorts, the classification predicted survival (HNSCC: gefitinib, P = 0.007 and erlotinib/bevacizumab, P = 0.02; CRC: cetuximab, P = 0.0065) whereas the chemotherapy cohort showed no survival difference. For CRC patients, tumor EGFR ligand RNA levels were significantly associated with the proteomic classification, and combined KRAS and proteomic classification provided improved survival classification.

Conclusions: Serum proteomic profiling can detect clinically significant tumor dependence on the EGFR pathway in non-small cell lung cancer, HNSCC, and CRC patients treated with either EGFR-TKIs or cetuximab. This classification is correlated with tumor EGFR ligand levels and provides a clinically practical way to identify patients with diverse cancer types most likely to benefit from EGFR inhibitors. Prospective studies are necessary to confirm these findings.

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