The glucose‐deprivation network counteracts lapatinib‐induced toxicity in resistant ErbB2‐positive breast cancer cells
| Autor: | Deepak Nagrath, Prahlad T. Ram, Kakajan Komurov, Jen Te Tseng, Melissa Muller, Elena G. Seviour, Tyler J. Moss, Lifeng Yang |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Receptor
ErbB-2 Glucose uptake medicine.medical_treatment Cellular homeostasis Pharmacology Targeted therapy computational methods 0302 clinical medicine metabolic and regulatory networks Molecular Targeted Therapy skin and connective tissue diseases 0303 health sciences Applied Mathematics bioinformatics Genomics Flow Cytometry Metformin 3. Good health Computational Theory and Mathematics 030220 oncology & carcinogenesis Female Macrolides General Agricultural and Biological Sciences functional genomics Signal Transduction Information Systems medicine.drug Antineoplastic Agents Breast Neoplasms Biology Lapatinib Models Biological Glucagon Article General Biochemistry Genetics and Molecular Biology 03 medical and health sciences Cell Line Tumor medicine Humans Hypoglycemic Agents News and Views 030304 developmental biology General Immunology and Microbiology Gene Expression Profiling Cancer medicine.disease Glucose Drug Resistance Neoplasm Quinazolines Unfolded protein response |
| Zdroj: | Molecular Systems Biology |
| ISSN: | 1744-4292 |
| Popis: | This study implicates the glucose deprivation response in breast cancer cell resistance to lapatinib and high relapse rates in Her2-positive patients. Identification of these compensatory networks suggests novel strategies to target cancer signaling and metabolism. Increased expression of the glucose deprivation response network, including glucagon signaling, glucose uptake, gluconeogenesis and unfolded protein response genes is found in breast cancer cells with acquired resistance to lapatinib. The glucose deprivation response gene network correlated significantly with high clinical relapse rates in ErbB2-positive breast cancer patients. Chemical genomics bioinformatics data mining identified drugs that target the glucose deprivation response networks to reduced survival of resistant cells. 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Plný text