title: Support vector machines coupled with proteomics approaches for detecting             biomarkers predicting chemotherapy resistance in small cell lung cancer.
abstract: The aim of this study was to identify serum protein fingerprints of small             cell lung cancer (SCLC) and potential biomarkers related to chemotherapy resistance             of SCLC with surface enhanced laser desorption/ionization time of flight mass             spectrometry (SELDI-TOF MS). A total of 60 SCLC patients and 48 age- and sex-matched             healthy individuals were enrolled. The chemotherapy regimen was cisplatin plus             etoposide. All patients received two cycles of chemotherapy. Serum protein profiles             were detected using SELDI-TOF MS and the spectra were analyzed with support vector             machines (SVMs). Western blotting was performed to verify the results of SELDI-TOF             MS. Three top scored peaks, at m/z of 6269, 9043 and 13124 Da, were finally selected             as potential biomarkers for detection of SCLC. The SVM classifier separated the             SCLC from the healthy samples in the blind test, with a sensitivity of 92.4% and             a specificity of 92.5%. For the 56 eligible chemotherapy patients, 4 had a complete             response (7.14%), 39 patients had a partial response (69.6%), 9 patients had a             stable disease (16.1%) and 4 patients had a progressive disease (7.14%). The model             constructed using two protein peaks with m/z of 8830 and 10468 Da separated the             chemotherapy-resistant group from the chemotherapy-sensitive group with a sensitivity             of 80.0% and a specificity of 80.0%. Initial protein database searching identiﬁed             10468 Da as S100-A9 which was conﬁrmed by western blotting. The present results             suggest that the combination of SELDI-TOF MS with SVM may provide a useful means             in the search for serum biomarkers for predicting chemotherapy resistance in patients             with SCLC.
authors.affiliation: Cancer Therapy and Research Center, Shandong Provincial Hospital, Shandong University, Jinan 250021, PR China.
authors.forename: Mingyong
authors.initials: M
authors.lastname: Han
authors.forename: Jianjian
authors.initials: J
authors.lastname: Dai
authors.forename: Ying
authors.initials: Y
authors.lastname: Zhang
authors.forename: Qi
authors.initials: Q
authors.lastname: Lin
authors.forename: Man
authors.initials: M
authors.lastname: Jiang
authors.forename: Xiaoya
authors.initials: X
authors.lastname: Xu
authors.forename: Qi
authors.initials: Q
authors.lastname: Liu
authors.forename: Jihui
authors.initials: J
authors.lastname: Jia
mesh_terms: D000328:Adult; D000368:Aged; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use; D014408:Biomarkers, Tumor / Q000097:blood*; D001798:Blood Proteins / Q000032:analysis*; D002945:Cisplatin / Q000627:therapeutic use; D019008:Drug Resistance, Neoplasm; D005047:Etoposide / Q000627:therapeutic use; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000097:blood / Q000188:drug therapy; D008297:Male; D008875:Middle Aged; D040081:Protein Array Analysis; D040901:Proteomics; D055752:Small Cell Lung Carcinoma / Q000097:blood* / Q000188:drug therapy*; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; D060388:Support Vector Machine; D016896:Treatment Outcome
chemical_list: D014408:Biomarkers, Tumor; D001798:Blood Proteins; D005047:Etoposide; D002945:Cisplatin