title: Mass spectrometry-based metabolic profiling of gemcitabine-sensitive and gemcitabine-resistant pancreatic cancer cells.
abstract: OBJECTIVE
  Gemcitabine resistance (GR) is one of the critical issues for therapy for pancreatic cancer, but the mechanism still remains unclear. Our aim was to increase the understanding of GR by metabolic profiling approach.
  
  
  METHODS
  To establish GR cells, 2 human pancreatic cancer cell lines, SUIT-2 and CAPAN-1, were exposed to increasing concentration of gemcitabine. Both parental and chemoresistant cells obtained by this treatment were subjected to metabolic profiling based on liquid chromatography-mass spectrometry.
  
  
  RESULTS
  Multivariate statistical analyses, both principal component analysis and orthogonal partial least squares discriminant analysis, distinguished metabolic signature of responsiveness and resistance to gemcitabine in both SUIT-2 and CAPAN-1 cells. Among significantly different (P < 0.005) metabolite peaks between parental and GR cells, we identified metabolites related to several metabolic pathways such as amino acid, nucleotide, energy, cofactor, and vitamin pathways. Decreases in glutamine and proline levels as well as increases in aspartate, hydroxyproline, creatine, and creatinine levels were observed in chemoresistant cells from both cell lines.
  
  
  CONCLUSIONS
  These results suggest that metabolic profiling can isolate distinct features of pancreatic cancer in the metabolome of gemcitabine-sensitive and GR cells. These findings may contribute to the biomarker discovery and an enhanced understanding of GR in pancreatic cancer.
authors: From the *Innovation Center for Medical Redox Navigation; †Departments of Surgery and Oncology, Graduate School of Medical Sciences; ‡Department of Advanced Medical Initiatives, Graduate School of Medical Sciences; §Faculty of Agriculture; ∥Bio-Architecture Center, Kyushu University, Fukuoka, Japan; and ¶Kyushu University Hospital Cancer Center, Fukuoka, Japan.
authors: Yoshinori
authors: Y
authors: Fujimura
authors: Naoki
authors: N
authors: Ikenaga
authors: Kenoki
authors: K
authors: Ohuchida
authors: Daiki
authors: D
authors: Setoyama
authors: Miho
authors: M
authors: Irie
authors: Daisuke
authors: D
authors: Miura
authors: Hiroyuki
authors: H
authors: Wariishi
authors: Masaharu
authors: M
authors: Murata
authors: Kazuhiro
authors: K
authors: Mizumoto
authors: Makoto
authors: M
authors: Hashizume
authors: Masao
authors: M
authors: Tanaka
mesh_terms: D000964:Antimetabolites, Antineoplastic / Q000494:pharmacology; D045744:Cell Line, Tumor; D003841:Deoxycytidine / Q000031:analogs & derivatives* / Q000494:pharmacology; D016002:Discriminant Analysis; D019008:Drug Resistance, Neoplasm; D006801:Humans; D016018:Least-Squares Analysis; D013058:Mass Spectrometry / Q000379:methods*; D053858:Metabolic Networks and Pathways / Q000187:drug effects; D055442:Metabolome / Q000187:drug effects*; D055432:Metabolomics / Q000379:methods*; D010190:Pancreatic Neoplasms / Q000378:metabolism / Q000473:pathology; D025341:Principal Component Analysis; D000093542:Gemcitabine
chemical_list: D000964:Antimetabolites, Antineoplastic; D003841:Deoxycytidine; D000093542:Gemcitabine