AIM: To identify discriminating protein patterns in serum samples among non-small cell lung cancer (NSCLC), chronic obstructive pulmonary disease (COPD), pneumonia, and healthy controls. To discover specific low molecular weight (LMW) serum peptidome biomarkers and establish a diagnostic pattern for NSCLCby using proteomic technology. METHODS: We used magnetic bead-based separation followed by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) to identify patients with NSCLC, COPD, and pneumonia. A total of 154 serum samples were analyzed in this study, among which there were 60 serum samples from NSCLC patients, 30 from patients with other lung-related diseases (16 pneumonia patients and 14 patients with COPD) as disease controls, and 64 from healthy volunteers as healthy control. The mass spectra, analyzed using ClinProTools software, distinguished between cancer patients and healthy individuals based on GA algorithm model. RESULTS: In this study, we generated numerous discriminating m/z peaks as well as disease-specific discrimination peaks. A set of five potential biomarkers (m/z: 7,763.24, 1,012.61, 4,153.16, 1,450.55, and 2,878.89) could be used as the diagnostic biomarkers to distinguish NSCLCpatients from healthy controls. In the training set, patients with NSCLC could be identified with sensitivity of 97.5% and specificity of 98.8%. Similar results were obtained in the testing set, showing 80.7% sensitivity and 91.2% specificity. CONCLUSION: Our study demonstrated that a combined application of magnetic beads with MALDI-TOF MS technique was suitable for identification of serum biomarkers for NSCLC.
AIM: To identify discriminating protein patterns in serum samples among non-small cell lung cancer (NSCLC), chronic obstructive pulmonary disease (COPD), pneumonia, and healthy controls. To discover specific low molecular weight (LMW) serum peptidome biomarkers and establish a diagnostic pattern for NSCLCby using proteomic technology. METHODS: We used magnetic bead-based separation followed by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) to identify patients with NSCLC, COPD, and pneumonia. A total of 154 serum samples were analyzed in this study, among which there were 60 serum samples from NSCLCpatients, 30 from patients with other lung-related diseases (16 pneumoniapatients and 14 patients with COPD) as disease controls, and 64 from healthy volunteers as healthy control. The mass spectra, analyzed using ClinProTools software, distinguished between cancerpatients and healthy individuals based on GA algorithm model. RESULTS: In this study, we generated numerous discriminating m/z peaks as well as disease-specific discrimination peaks. A set of five potential biomarkers (m/z: 7,763.24, 1,012.61, 4,153.16, 1,450.55, and 2,878.89) could be used as the diagnostic biomarkers to distinguish NSCLCpatients from healthy controls. In the training set, patients with NSCLC could be identified with sensitivity of 97.5% and specificity of 98.8%. Similar results were obtained in the testing set, showing 80.7% sensitivity and 91.2% specificity. CONCLUSION: Our study demonstrated that a combined application of magnetic beads with MALDI-TOF MS technique was suitable for identification of serum biomarkers for NSCLC.
Authors: Georg Martin Fiedler; Sven Baumann; Alexander Leichtle; Anke Oltmann; Julia Kase; Joachim Thiery; Uta Ceglarek Journal: Clin Chem Date: 2007-02-01 Impact factor: 8.327
Authors: Nicholas P Schaub; Kimberly J Jones; Julius O Nyalwidhe; Lisa H Cazares; Izabela D Karbassi; O John Semmes; Eric C Feliberti; Roger R Perry; Richard R Drake Journal: J Am Coll Surg Date: 2009-03-26 Impact factor: 6.113
Authors: A M Rodríguez-Piñeiro; S Blanco-Prieto; N Sánchez-Otero; F J Rodríguez-Berrocal; M Páez de la Cadena Journal: J Proteomics Date: 2010-03-15 Impact factor: 4.044
Authors: Edward F Patz; Michael J Campa; Elizabeth B Gottlin; Irina Kusmartseva; Xiang Rong Guan; James E Herndon Journal: J Clin Oncol Date: 2007-12-10 Impact factor: 44.544