title: Quantitative proteomic approach to understand metabolic adaptation in non-small cell lung cancer.
abstract: KRAS mutations in non-small cell lung cancer (NSCLC) are a predictor of resistance to EGFR-targeted therapies. Because approaches to target RAS signaling have been unsuccessful, targeting lung cancer metabolism might help to develop a new strategy that could overcome drug resistance in such cancer. In this study, we applied a large screening quantitative proteomic analysis to evidence key enzymes involved in metabolic adaptations in lung cancer. We carried out the proteomic analysis of two KRAS-mutated NSCLC cell lines (A549 and NCI-H460) and a non tumoral bronchial cell line (BEAS-2B) using an iTRAQ (isobaric tags for relative and absolute quantitation) approach combined with two-dimensional fractionation (OFFGEL/RP nanoLC) and MALDI-TOF/TOF mass spectrometry analysis. Protein targets identified by our iTRAQ approach were validated by Western blotting analysis. Among 1038 proteins identified and 834 proteins quantified, 49 and 82 proteins were respectively found differently expressed in A549 and NCI-H460 cells compared to the BEAS-2B non tumoral cell line. Regarding the metabolic pathways, enzymes involved in glycolysis (GAPDH/PKM2/LDH-A/LDH-B) and pentose phosphate pathway (PPP) (G6PD/TKT/6PGD) were up-regulated. The up-regulation of enzyme expression in PPP is correlated to their enzyme activity and will be further investigated to confirm those enzymes as promising metabolic targets for the development of new therapeutic treatments or biomarker assay for NSCLC.
authors.affiliation: Department of Biochemistry and Molecular Biology, IBUB, Faculty of Biology, Universitat de Barcelona and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) , 08007 Barcelona, Spain.
authors.forename: Alfonso
authors.initials: A
authors.lastname: Martín-Bernabé
authors.forename: Roldán
authors.initials: R
authors.lastname: Cortés
authors.forename: Sylvia G
authors.initials: SG
authors.lastname: Lehmann
authors.forename: Michel
authors.initials: M
authors.lastname: Seve
authors.forename: Marta
authors.initials: M
authors.lastname: Cascante
authors.forename: Sandrine
authors.initials: S
authors.lastname: Bourgoin-Voillard
mesh_terms: D015153:Blotting, Western; D002289:Carcinoma, Non-Small-Cell Lung / Q000188:drug therapy / Q000235:genetics / Q000378:metabolism*; D045744:Cell Line, Tumor; D002853:Chromatography, Liquid; D019008:Drug Resistance, Neoplasm / Q000235:genetics*; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics / Q000502:physiology*; D006019:Glycolysis / Q000235:genetics / Q000502:physiology; D057166:High-Throughput Screening Assays; D006801:Humans; D053858:Metabolic Networks and Pathways / Q000235:genetics / Q000502:physiology*; D010427:Pentose Phosphate Pathway / Q000235:genetics / Q000502:physiology; D040901:Proteomics / Q000379:methods*; D011518:Proto-Oncogene Proteins / Q000235:genetics*; D016283:Proto-Oncogene Proteins p21(ras); D053719:Tandem Mass Spectrometry; D018631:ras Proteins / Q000235:genetics*
chemical_list: C117307:KRAS protein, human; D011518:Proto-Oncogene Proteins; D016283:Proto-Oncogene Proteins p21(ras); D018631:ras Proteins
keywords: NSCLC; cancer metabolism; drug resistance; iTRAQ quantitative proteomic approach