title: Identifying susceptibility networks for drug-induced non-immune neutropenia.
abstract: Systems toxicology, a branch of toxicology that studies drug effects at the level of biological systems, offers exciting opportunities to discover toxicity-related sub-networks using high-throughput technologies. This paper takes a computational approach to systems toxicology and investigates the use of automated signalling path detection for discovery of potential biomarkers of drug-induced non-immune neutropenia. The algorithm utilises a gene expression change measure to mine a large protein interaction network and identify chemical-toxicity signalling paths. Cytoscape-based analysis of detected signalling paths with statistically significant path expression scores reveals 'hub' proteins and a smaller sub-network of path proteins. The importance of 'hub' and drug-toxicity signalling path proteins in haematological and apoptotic signal transduction networks is investigated in order to understand the value of automated signalling path detection approach.
authors.forename: Kaushal
authors.initials: K
authors.lastname: Desai
authors.forename: David
authors.initials: D
authors.lastname: Brott
authors.forename: Xiaohua
authors.initials: X
authors.lastname: Hu
authors.forename: Anastasia
authors.initials: A
authors.lastname: Christianson
mesh_terms: D000465:Algorithms; D000970:Antineoplastic Agents / Q000008:administration & dosage / Q000493:pharmacokinetics*; D064146:Chemotherapy-Induced Febrile Neutropenia / Q000235:genetics / Q000378:metabolism*; D016207:Cytokines / Q000378:metabolism*; D004198:Disease Susceptibility; D020869:Gene Expression Profiling / Q000379:methods; D006801:Humans; D009369:Neoplasms / Q000188:drug therapy / Q000235:genetics / Q000378:metabolism*; D025941:Protein Interaction Mapping / Q000379:methods; D015398:Signal Transduction
chemical_list: D000970:Antineoplastic Agents; D016207:Cytokines