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A systems biology approach to the study of cisplatin drug resistance in ovarian cancers

  • Jake Y. Chen*
  • , Zhong Yan
  • , Changyu Shen
  • , Dawn P.G. Fitzpatrick
  • , Mu Wang
  • *Corresponding author for this work
  • Indiana University-Purdue University Indianapolis
  • Indiana University Bloomington

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)

Abstract

Cisplatin-induced drug resistance is known to involve a complex set of cellular changes whose molecular mechanism details remain unclear. In this study, we developed a systems biology approach to examine proteomics- and network-level changes between cisplatin-resistant and cisplatin-sensitive cell lines. This approach involves experimental investigation of differential proteomics profiles and computational study of activated enriched proteins, protein interactions, and protein interaction networks. Our experimental platform is based on a Label-free liquid Chromatography/mass spectrometry proteomics platform. Our computational methods start with an initial list of 119 differentially expressed proteins. We expanded these proteins into a cisplatin-resistant activated sub-network using a database of human protein-protein interactions. An examination of network topology features revealed the activated responses in the network are closely coupled. By examining sub-network proteins using gene ontology categories, we found significant enrichment of proton-transporting ATPase and ATP synthase complexes activities in cisplatin-resistant cells in the form of cooperative down-regulations. Using two-dimensional visualization matrixes, we further found significant cascading of endogenous, abiotic, and stress-related signals. Using a visual representation of activated protein categorical sub-networks, we showed that molecular regulation of cell differentiation and development caused by responses to proteome-wide stress as a key signature to the acquired drug resistance.

Original languageEnglish
Pages (from-to)383-405
Number of pages23
JournalJournal of Bioinformatics and Computational Biology
Volume5
Issue number2 A
DOIs
Publication statusPublished - Apr 2007
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Gene ontology
  • Ovarian cancer
  • Protein interaction network
  • Proteomics
  • Systems biology
  • Visualization

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