title: Identification of transcription factors that may reprogram lung adenocarcinoma.
abstract: BACKGROUND
  Lung adenocarcinoma is one of most threatening disease to human health. Although many efforts have been devoted to its genetic study, few researches have been focused on the transcription factors which regulate tumor initiation and progression by affecting multiple downstream gene transcription. It is proved that proper transcription factors may mediate the direct reprogramming of cancer cells, and reverse the tumorigenesis on the epigenetic and transcription levels.
  
  
  METHODS
  In this paper, a computational method is proposed to identify the core transcription factors that can regulate as many as possible lung adenocarcinoma associated genes with as little as possible redundancy. A greedy strategy is applied to find the smallest collection of transcription factors that can cover the differentially expressed genes by its downstream targets. The optimal subset which is mostly enriched in the differentially expressed genes is then selected.
  
  
  RESULTS
  Seven core transcription factors (MCM4, VWF, ECT2, RBMS3, LIMCH1, MYBL2 and FBXL7) are detected, and have been reported to contribute to tumorigenesis of lung adenocarcinoma. The identification of the transcription factors provides a new insight into its oncogenic role in tumor initiation and progression, and benefits the discovery of functional core set that may reverse malignant transformation and reprogram cancer cells.
authors.affiliation: School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China. Electronic address: tocliu@126.com.
authors.forename: Chenglin
authors.initials: C
authors.lastname: Liu
authors.affiliation: Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, People's Republic of China. Electronic address: zhangyh825@163.com.
authors.forename: Yu-Hang
authors.initials: YH
authors.lastname: Zhang
authors.affiliation: Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, People's Republic of China. Electronic address: tohuangtao@126.com.
authors.forename: Tao
authors.initials: T
authors.lastname: Huang
authors.affiliation: School of Life Sciences, Shanghai University, Shanghai 200444, People's Republic of China. Electronic address: cai_yud@126.com.
authors.forename: Yudong
authors.initials: Y
authors.lastname: Cai
mesh_terms: D000230:Adenocarcinoma / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D000077192:Adenocarcinoma of Lung; D001185:Artificial Intelligence; D002471:Cell Transformation, Neoplastic / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D044127:Epigenesis, Genetic; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D006801:Humans; D008175:Lung Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D015398:Signal Transduction; D014157:Transcription Factors / Q000235:genetics* / Q000378:metabolism; D014158:Transcription, Genetic
chemical_list: D014157:Transcription Factors
keywords: Greedy algorithm; Lung adenocarcinoma; Transcription factor; Tumorigenesis