title: Discovery of a set of biomarkers of human lung adenocarcinoma through cell-map proteomics and bioinformatics.
abstract: Carcinogenesis of lung adenocarcinoma remains unclear and very few biomarkers have been accepted for routine clinical use. In order to explore the pathogenesis and screen ideal biomarkers, we conducted cell-map proteomics study in human lung adenocarcinoma. Homogeneous lung adenocarcinoma cells were purified by laser capture microdissection (LCM). A high performance liquid chromatography (HPLC) system was used to separate the total solution proteins. The resulting MS/MS spectra were automatically searched for proteins against IPI human protein database using the TurboSEQUEST searching engine. Physico-chemical properties of the identified proteins, including molecular weight (MW), isoelectric point (PI), were described based on various proteomics web server and statistical analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were used to analyze function of expressed proteins and screen candidate biomarkers according to biological annotation. A total of 843 distinct proteins were identified and were categorized as 10 sorts of molecular function and 17 sorts of biological process based on GO annotation. Further searching against KEGG pathways found that six proteins were involved in WNT signaling pathway, apoptosis pathway, Erb-2 signaling pathway, p53 signaling pathway, ubiquitin-mediated proteolysis and were might be hopefully screened as candidate markers of lung adenocarcinoma. The present study through LCM and cell-map proteomics showed a full view on the expressed protein profiles of lung adenocarcinoma. Several candidate markers are hopeful to be used as molecular targets of diagnosis, treatment and prognosis of lung adenocarcinoma.
authors.affiliation: Department of Respiratory Disease, Tangdu Hospital, Fourth Military Medical University, 710038, Xi'an, Shaanxi Province, People's Republic of China.
authors.forename: Yandong
authors.initials: Y
authors.lastname: Nan
authors.forename: Faguang
authors.initials: F
authors.lastname: Jin
authors.forename: Shuanying
authors.initials: S
authors.lastname: Yang
authors.forename: Yingxuan
authors.initials: Y
authors.lastname: Tian
authors.forename: Yonghong
authors.initials: Y
authors.lastname: Xie
authors.forename: Enqing
authors.initials: E
authors.lastname: Fu
authors.forename: Hong
authors.initials: H
authors.lastname: Yu
mesh_terms: D000368:Aged; D014408:Biomarkers, Tumor / Q000378:metabolism*; D002851:Chromatography, High Pressure Liquid; D019295:Computational Biology; D030562:Databases, Protein; D005260:Female; D006801:Humans; D007834:Lasers; D008175:Lung Neoplasms / Q000378:metabolism* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D009363:Neoplasm Proteins / Q000378:metabolism*; D011379:Prognosis; D040901:Proteomics; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins