title: Artificial neural networks and decision tree model analysis of liver cancer proteomes.
abstract: Hepatocellular carcinoma (HCC) is a heterogeneous cancer and usually diagnosed at late advanced tumor stages of high lethality. The present study attempted to obtain a proteome-wide analysis of HCC in comparison with adjacent non-tumor liver tissues, in order to facilitate biomarkers' discovery and to investigate the mechanisms of HCC development. A cohort of 66 Chinese patients with HCC was included for proteomic profiling study by two-dimensional gel electrophoresis (2-DE) analysis. Artificial neural network (ANN) and decision tree (CART) data-mining methods were employed to analyze the profiling data and to delineate significant patterns and trends for discriminating HCC from non-malignant liver tissues. Protein markers were identified by tandem MS/MS. A total of 132 proteome datasets were generated by 2-DE expression profiling analysis, and each with 230 consolidated protein expression intensities. Both the data-mining algorithms successfully distinguished the HCC phenotype from other non-malignant liver samples. The detection sensitivity and specificity of ANN were 96.97% and 87.88%, while those of CART were 81.82% and 78.79%, respectively. The three biological classifiers in the CART model were identified as cytochrome b5, heat shock 70 kDa protein 8 isoform 2, and cathepsin B. The 2-DE-based proteomic profiling approach combined with the ANN or CART algorithm yielded satisfactory performance on identifying HCC and revealed potential candidate cancer biomarkers.
authors.affiliation: Department of Surgery and Center for Cancer Research, Faculty of Medicine Building, 9/F, 21 Sassoon Road, University of Hong Kong, Pokfulam, Hong Kong. jmluk@hkucc.hku.hk
authors.forename: John M
authors.initials: JM
authors.lastname: Luk
authors.forename: Brian Y
authors.initials: BY
authors.lastname: Lam
authors.forename: Nikki P Y
authors.initials: NP
authors.lastname: Lee
authors.forename: David W
authors.initials: DW
authors.lastname: Ho
authors.forename: Pak C
authors.initials: PC
authors.lastname: Sham
authors.forename: Lei
authors.initials: L
authors.lastname: Chen
authors.forename: Jirun
authors.initials: J
authors.lastname: Peng
authors.forename: Xisheng
authors.initials: X
authors.lastname: Leng
authors.forename: Philip J
authors.initials: PJ
authors.lastname: Day
authors.forename: Sheung-Tat
authors.initials: ST
authors.lastname: Fan
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000032:analysis* / Q000145:classification; D006528:Carcinoma, Hepatocellular / Q000175:diagnosis*; D003663:Decision Trees; D015180:Electrophoresis, Gel, Two-Dimensional; D005260:Female; D006801:Humans; D008099:Liver; D008113:Liver Neoplasms / Q000175:diagnosis*; D008297:Male; D008875:Middle Aged; D009363:Neoplasm Proteins / Q000032:analysis* / Q000145:classification; D016571:Neural Networks, Computer; D020543:Proteome / Q000737:chemistry; D040901:Proteomics / Q000379:methods*; D053719:Tandem Mass Spectrometry
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins; D020543:Proteome