title: The glucose-deprivation network counteracts lapatinib-induced toxicity in resistant ErbB2-positive breast cancer cells.
abstract: Dynamic interactions between intracellular networks regulate cellular homeostasis and responses to perturbations. Targeted therapy is aimed at perturbing oncogene addiction pathways in cancer, however, development of acquired resistance to these drugs is a significant clinical problem. A network-based computational analysis of global gene expression data from matched sensitive and acquired drug-resistant cells to lapatinib, an EGFR/ErbB2 inhibitor, revealed an increased expression of the glucose deprivation response network, including glucagon signaling, glucose uptake, gluconeogenesis and unfolded protein response in the resistant cells. Importantly, the glucose deprivation response markers correlated significantly with high clinical relapse rates in ErbB2-positive breast cancer patients. Further, forcing drug-sensitive cells into glucose deprivation rendered them more resistant to lapatinib. Using a chemical genomics bioinformatics mining of the CMAP database, we identified drugs that specifically target the glucose deprivation response networks to overcome the resistant phenotype and reduced survival of resistant cells. This study implicates the chronic activation of cellular compensatory networks in response to targeted therapy and suggests novel combinations targeting signaling and metabolic networks in tumors with acquired resistance.
authors.affiliation: Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77045, USA.
authors.forename: Kakajan
authors.initials: K
authors.lastname: Komurov
authors.forename: Jen-Te
authors.initials: JT
authors.lastname: Tseng
authors.forename: Melissa
authors.initials: M
authors.lastname: Muller
authors.forename: Elena G
authors.initials: EG
authors.lastname: Seviour
authors.forename: Tyler J
authors.initials: TJ
authors.lastname: Moss
authors.forename: Lifeng
authors.initials: L
authors.lastname: Yang
authors.forename: Deepak
authors.initials: D
authors.lastname: Nagrath
authors.forename: Prahlad T
authors.initials: PT
authors.lastname: Ram
mesh_terms: D000970:Antineoplastic Agents / Q000494:pharmacology*; D001943:Breast Neoplasms / Q000235:genetics / Q000378:metabolism; D045744:Cell Line, Tumor; D019008:Drug Resistance, Neoplasm / Q000187:drug effects* / Q000235:genetics; D005260:Female; D005434:Flow Cytometry; D020869:Gene Expression Profiling / Q000379:methods*; D023281:Genomics / Q000379:methods; D005947:Glucose / Q000378:metabolism; D006801:Humans; D007004:Hypoglycemic Agents / Q000494:pharmacology; D000077341:Lapatinib; D018942:Macrolides / Q000494:pharmacology; D008687:Metformin / Q000494:pharmacology; D008954:Models, Biological; D058990:Molecular Targeted Therapy; D011799:Quinazolines / Q000494:pharmacology*; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000037:antagonists & inhibitors / Q000235:genetics / Q000378:metabolism; D015398:Signal Transduction / Q000187:drug effects* / Q000235:genetics
chemical_list: D000970:Antineoplastic Agents; D005947:Glucose; D007004:Hypoglycemic Agents; D000077341:Lapatinib; D018942:Macrolides; D008687:Metformin; D011799:Quinazolines; D018719:Erb-b2 Receptor Tyrosine Kinases; C057620:bafilomycin A