title: Optimally discriminative subnetwork markers predict response to chemotherapy.
abstract: BACKGROUND
  Molecular profiles of tumour samples have been widely and successfully used for classification problems. A number of algorithms have been proposed to predict classes of tumor samples based on expression profiles with relatively high performance. However, prediction of response to cancer treatment has proved to be more challenging and novel approaches with improved generalizability are still highly needed. Recent studies have clearly demonstrated the advantages of integrating protein-protein interaction (PPI) data with gene expression profiles for the development of subnetwork markers in classification problems.
  
  
  RESULTS
  We describe a novel network-based classification algorithm (OptDis) using color coding technique to identify optimally discriminative subnetwork markers. Focusing on PPI networks, we apply our algorithm to drug response studies: we evaluate our algorithm using published cohorts of breast cancer patients treated with combination chemotherapy. We show that our OptDis method improves over previously published subnetwork methods and provides better and more stable performance compared with other subnetwork and single gene methods. We also show that our subnetwork method produces predictive markers that are more reproducible across independent cohorts and offer valuable insight into biological processes underlying response to therapy.
  
  
  BACKGROUND
  The implementation is available at: http://www.cs.sfu.ca/~pdao/personal/OptDis.html
  
  
  BACKGROUND
  cenk@cs.sfu.ca; alapuk@prostatecentre.com; ccollins@prostatecentre.com.
authors.affiliation: School of Computing Science, Simon Fraser University.
authors.forename: Phuong
authors.initials: P
authors.lastname: Dao
authors.forename: Kendric
authors.initials: K
authors.lastname: Wang
authors.forename: Colin
authors.initials: C
authors.lastname: Collins
authors.forename: Martin
authors.initials: M
authors.lastname: Ester
authors.forename: Anna
authors.initials: A
authors.lastname: Lapuk
authors.forename: S Cenk
authors.initials: SC
authors.lastname: Sahinalp
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000378:metabolism; D001943:Breast Neoplasms / Q000188:drug therapy* / Q000235:genetics; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans
chemical_list: D014408:Biomarkers, Tumor