title: Differential combinatorial regulatory network analysis related to venous metastasis of hepatocellular carcinoma.
abstract: BACKGROUND
  Hepatocellular carcinoma (HCC) is one of the most fatal cancers in the world, and metastasis is a significant cause to the high mortality in patients with HCC. However, the molecular mechanism behind HCC metastasis is not fully understood. Study of regulatory networks may help investigate HCC metastasis in the way of systems biology profiling.
  
  
  METHODS
  By utilizing both sequence information and parallel microRNA(miRNA) and mRNA expression data on the same cohort of HBV related HCC patients without or with venous metastasis, we constructed combinatorial regulatory networks of non-metastatic and metastatic HCC which contain transcription factor(TF) regulation and miRNA regulation. Differential regulation patterns, classifying marker modules, and key regulatory miRNAs were analyzed by comparing non-metastatic and metastatic networks.
  
  
  RESULTS
  Globally TFs accounted for the main part of regulation while miRNAs for the minor part of regulation. However miRNAs displayed a more active role in the metastatic network than in the non-metastatic one. Seventeen differential regulatory modules discriminative of the metastatic status were identified as cumulative-module classifier, which could also distinguish survival time. MiR-16, miR-30a, Let-7e and miR-204 were identified as key miRNA regulators contributed to HCC metastasis.
  
  
  CONCLUSIONS
  In this work we demonstrated an integrative approach to conduct differential combinatorial regulatory network analysis in the specific context venous metastasis of HBV-HCC. Our results proposed possible transcriptional regulatory patterns underlying the different metastatic subgroups of HCC. The workflow in this study can be applied in similar context of cancer research and could also be extended to other clinical topics.
authors.affiliation: School of Life Science and Technology, Tongji University, Shanghai 200092, PR China.
authors.forename: Lingyao
authors.initials: L
authors.lastname: Zeng
authors.forename: Jian
authors.initials: J
authors.lastname: Yu
authors.forename: Tao
authors.initials: T
authors.lastname: Huang
authors.forename: Huliang
authors.initials: H
authors.lastname: Jia
authors.forename: Qiongzhu
authors.initials: Q
authors.lastname: Dong
authors.forename: Fei
authors.initials: F
authors.lastname: He
authors.forename: Weilan
authors.initials: W
authors.lastname: Yuan
authors.forename: Lunxiu
authors.initials: L
authors.lastname: Qin
authors.forename: Yixue
authors.initials: Y
authors.lastname: Li
authors.forename: Lu
authors.initials: L
authors.lastname: Xie
mesh_terms: D006528:Carcinoma, Hepatocellular / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D015331:Cohort Studies; D053263:Gene Regulatory Networks; D006515:Hepatitis B virus; D006801:Humans; D008113:Liver Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D035683:MicroRNAs / Q000378:metabolism; D009362:Neoplasm Metastasis / Q000235:genetics*; D011237:Predictive Value of Tests; D011379:Prognosis; D014157:Transcription Factors / Q000235:genetics / Q000378:metabolism
chemical_list: D035683:MicroRNAs; D014157:Transcription Factors