title: A metabolomic approach to lung cancer.
abstract: Lung cancer is one of the most common cancers in the world, but no good clinical markers that can be used to diagnose the disease at an early stage and predict its prognosis have been found. Therefore, the discovery of novel clinical markers is required. In this study, metabolomic analysis of lung cancer patients was performed using gas chromatography mass spectrometry. Serum samples from 29 healthy volunteers and 33 lung cancer patients with adenocarcinoma (n=12), squamous cell carcinoma (n=11), or small cell carcinoma (n=10) ranging from stage I to stage IV disease and lung tissue samples from 7 lung cancer patients including the tumor tissue and its surrounding normal tissue were used. A total of 58 metabolites (57 individual metabolites) were detected in serum, and 71 metabolites were detected in the lung tissue. The levels of 23 of the 58 serum metabolites were significantly changed in all lung cancer patients compared with healthy volunteers, and the levels of 48 of the 71 metabolites were significantly changed in the tumor tissue compared with the non-tumor tissue. Partial least squares discriminant analysis, which is a form of multiple classification analysis, was performed using the serum sample data, and metabolites that had characteristic alterations in each histological subtype and disease stage were determined. Our results demonstrate that changes in metabolite pattern are useful for assessing the clinical characteristics of lung cancer. Our results will hopefully lead to the establishment of novel diagnostic tools.
authors.affiliation: Division of Respiratory Medicine, Kobe University Graduate School of Medicine, Japan.
authors.forename: Suya
authors.initials: S
authors.lastname: Hori
authors.forename: Shin
authors.initials: S
authors.lastname: Nishiumi
authors.forename: Kazuyuki
authors.initials: K
authors.lastname: Kobayashi
authors.forename: Masakazu
authors.initials: M
authors.lastname: Shinohara
authors.forename: Yukihisa
authors.initials: Y
authors.lastname: Hatakeyama
authors.forename: Yoshikazu
authors.initials: Y
authors.lastname: Kotani
authors.forename: Naoya
authors.initials: N
authors.lastname: Hatano
authors.forename: Yoshimasa
authors.initials: Y
authors.lastname: Maniwa
authors.forename: Wataru
authors.initials: W
authors.lastname: Nishio
authors.forename: Takeshi
authors.initials: T
authors.lastname: Bamba
authors.forename: Eiichiro
authors.initials: E
authors.lastname: Fukusaki
authors.forename: Takeshi
authors.initials: T
authors.lastname: Azuma
authors.forename: Tadaomi
authors.initials: T
authors.lastname: Takenawa
authors.forename: Yoshihiro
authors.initials: Y
authors.lastname: Nishimura
authors.forename: Masaru
authors.initials: M
authors.lastname: Yoshida
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000378:metabolism*; D002289:Carcinoma, Non-Small-Cell Lung / Q000175:diagnosis* / Q000473:pathology / Q000503:physiopathology; D055088:Early Detection of Cancer; D005240:Feasibility Studies; D005260:Female; D008401:Gas Chromatography-Mass Spectrometry; D006801:Humans; D008168:Lung / Q000378:metabolism* / Q000473:pathology; D008175:Lung Neoplasms / Q000175:diagnosis* / Q000473:pathology / Q000503:physiopathology; D008297:Male; D055432:Metabolomics / Q000379:methods; D008875:Middle Aged; D009367:Neoplasm Staging; D011379:Prognosis; D044967:Serum / Q000378:metabolism*; D012907:Smoking; D055815:Young Adult
chemical_list: D014408:Biomarkers, Tumor