Core and specific network markers of carcinogenesis from multiple cancer samples

J Theor Biol. 2014 Dec 7:362:17-34. doi: 10.1016/j.jtbi.2014.05.045. Epub 2014 Jul 9.

Abstract

Cancer is the leading cause of death worldwide and is generally caused by mutations in multiple proteins or the dysregulation of pathways. Understanding the causes and the underlying carcinogenic mechanisms can help fight this disease. In this study, a systems biology approach was used to construct the protein-protein interaction (PPI) networks of four cancers and the non-cancers by their corresponding microarray data, PPI modeling and database-mining. By comparing PPI networks between cancer and non-cancer samples to find significant proteins with large PPI changes during carcinogenesis process, core and specific network markers were identified by the intersection and difference of significant proteins, respectively, with carcinogenesis relevance values (CRVs) for each cancer. A total of 28 significant proteins were identified as core network markers in the carcinogenesis of four types of cancer, two of which are novel cancer-related proteins (e.g., UBC and PSMA3). Moreover, seven crucial common pathways were found among these cancers based on their core network markers, and some specific pathways were particularly prominent based on the specific network markers of different cancers (e.g., the RIG-I-like receptor pathway in bladder cancer, the proteasome pathway and TCR pathway in liver cancer, and the HR pathway in lung cancer). Additional validation of these network markers using the literature and new tested datasets could strengthen our findings and confirm the proposed method. From these core and specific network markers, we could not only gain an insight into crucial common and specific pathways in the carcinogenesis, but also obtain a high promising PPI target for cancer therapy.

Keywords: Carcinogenesis relevance value; Network markers; Protein–protein interaction.

MeSH terms

  • Antineoplastic Agents / chemistry
  • Biomarkers, Tumor / metabolism
  • Carcinogenesis
  • Cell Cycle
  • Cell Proliferation
  • Cell Survival
  • Colorectal Neoplasms / metabolism
  • Databases, Protein
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic*
  • Humans
  • Liver Neoplasms / metabolism
  • Lung Neoplasms / metabolism
  • Neoplasms / metabolism*
  • Protein Interaction Mapping / methods*
  • Proteins / chemistry
  • Proteolysis
  • Signal Transduction
  • Systems Biology
  • Urinary Bladder Neoplasms / metabolism

Substances

  • Antineoplastic Agents
  • Biomarkers, Tumor
  • Proteins