title: Predicting Diagnostic Gene Biomarkers for Non-Small-Cell Lung Cancer.
abstract: Lung cancer is the primary reason for death due to cancer worldwide, and non-small-cell lung cancer (NSCLC) is the most common subtype of lung cancer. Most patients die from complications of NSCLC due to poor diagnosis. In this paper, we aimed to predict gene biomarkers that may be of use for diagnosis of NSCLC by integrating differential gene expression analysis with functional association network analysis. We first constructed an NSCLC-specific functional association network by combining gene expression correlation with functional association. Then, we applied a network partition algorithm to divide the network into gene modules and identify the most NSCLC-specific gene modules based on their differential expression pattern in between normal and NSCLC samples. Finally, from these modules, we identified genes that exhibited the most impact on the expression of their functionally associated genes in between normal and NSCLC samples and predicted them as NSCLC biomarkers. Literature review of the top predicted gene biomarkers suggested that most of them were already considered critical for development of NSCLC.
authors: Department of Respiratory Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, Shandong 250021, China.
authors: Bin
authors: B
authors: Liang
authors: Department of Respiratory Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, Shandong 250021, China.
authors: Yang
authors: Y
authors: Shao
authors: Department of Respiratory Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, Shandong 250021, China.
authors: Fei
authors: F
authors: Long
authors: Department of Respiratory Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, Shandong 250021, China.
authors: Shu-Juan
authors: 0000-0003-3073-1931
authors: SJ
authors: Jiang
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000235:genetics / Q000378:metabolism*; D002289:Carcinoma, Non-Small-Cell Lung / Q000175:diagnosis* / Q000378:metabolism*; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D020869:Gene Expression Profiling / Q000379:methods*; D052138:Genes, Neoplasm / Q000235:genetics; D005819:Genetic Markers / Q000235:genetics; D006801:Humans; D008175:Lung Neoplasms / Q000175:diagnosis* / Q000235:genetics / Q000378:metabolism*; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D009363:Neoplasm Proteins / Q000235:genetics / Q000378:metabolism; D011379:Prognosis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor; D005819:Genetic Markers; D009363:Neoplasm Proteins