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Classification by Mass Spectrometry Can Accurately and Reliably Predict Outcome in Patients with Non-small Cell Lung Cancer Treated with Erlotinib-Containing Regimen

Classification by Mass Spectrometry Can Accurately and Reliably Predict Outcome in Patients with... ORIGINAL ARTICLE Classification by Mass Spectrometry Can Accurately and Reliably Predict Outcome in Patients with Non-small Cell Lung Cancer Treated with Erlotinib-Containing Regimen Stuart Salmon, MD,* Heidi Chen, PhD,† Shuo Chen, PhD,† Roy Herbst, MD, PhD,‡ Anne Tsao, MD,‡ Hai Tran, PharmD,‡ Alan Sandler, MD,† Dean Billheimer, PhD,§ Yu Shyr, PhD,† Ju-Whei Lee, PhD, Pierre Massion, MD,† Julie Brahmer, MD,¶ Joan Schiller, MD,# David Carbone, MD, PhD,† and Thao P. Dang, MD† Key Words: Lung cancer, Biomarkers, Proteomics. Purpose: Although many lung cancers express the epidermal growth factor receptor and the vascular endothelial growth factor, (J Thorac Oncol. 2009;4: 689–696) 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, ecent advances in our understanding of cancer biology have potentially allowing the selection of patients who may benefit from Rled to the development of therapeutics that target pathways important for tumor growth and survival. One such pathway such therapies. Here, we use a matrix-assisted laser desorption/ involves epidermal growth factor receptors (EGFRs). High ionization MS proteomic algorithm developed from a small dataset of erlotinib-bevacizumab treated patients to predict the clinical EGFR expression is http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Thoracic Oncology Wolters Kluwer Health

Classification by Mass Spectrometry Can Accurately and Reliably Predict Outcome in Patients with Non-small Cell Lung Cancer Treated with Erlotinib-Containing Regimen

Dang, Thao P.
Journal of Thoracic Oncology , Volume 4 (6) – Jun 1, 2009
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ISSN
1556-0864
DOI
10.1097/JTO.0b013e3181a526b3
pmid
19404214
Publisher site
See Article on Publisher Site

Abstract

ORIGINAL ARTICLE Classification by Mass Spectrometry Can Accurately and Reliably Predict Outcome in Patients with Non-small Cell Lung Cancer Treated with Erlotinib-Containing Regimen Stuart Salmon, MD,* Heidi Chen, PhD,† Shuo Chen, PhD,† Roy Herbst, MD, PhD,‡ Anne Tsao, MD,‡ Hai Tran, PharmD,‡ Alan Sandler, MD,† Dean Billheimer, PhD,§ Yu Shyr, PhD,† Ju-Whei Lee, PhD, Pierre Massion, MD,† Julie Brahmer, MD,¶ Joan Schiller, MD,# David Carbone, MD, PhD,† and Thao P. Dang, MD† Key Words: Lung cancer, Biomarkers, Proteomics. Purpose: Although many lung cancers express the epidermal growth factor receptor and the vascular endothelial growth factor, (J Thorac Oncol. 2009;4: 689–696) 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, ecent advances in our understanding of cancer biology have potentially allowing the selection of patients who may benefit from Rled to the development of therapeutics that target pathways important for tumor growth and survival. One such pathway such therapies. Here, we use a matrix-assisted laser desorption/ involves epidermal growth factor receptors (EGFRs). High ionization MS proteomic algorithm developed from a small dataset of erlotinib-bevacizumab treated patients to predict the clinical EGFR expression is

Journal

Journal of Thoracic Oncology – Wolters Kluwer Health

Published: Jun 1, 2009

References

  • Erlotinib in previously treated non-small-cell lung cancer
    Shepherd
  • Angiogenesis and lung cancer: prognostic and therapeutic implications
    Herbst
  • Paclitaxel-carboplatin alone or with bevacizumab for non-small-cell lung cancer
    Sandler