OBJECTIVES: 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.
OBJECTIVES: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 humanpancreatic 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: Shingo Matsumoto; Shun Kishimoto; Keita Saito; Yoichi Takakusagi; Jeeva P Munasinghe; Nallathamby Devasahayam; Charles P Hart; Robert J Gillies; James B Mitchell; Murali C Krishna Journal: Cancer Res Date: 2018-05-23 Impact factor: 12.701
Authors: Jia Fan; Qian Wei; Eugene J Koay; Yang Liu; Bo Ning; Paul W Bernard; Ning Zhang; Haiyong Han; Matthew H Katz; Zhen Zhao; Ye Hu Journal: Theranostics Date: 2018-11-13 Impact factor: 11.556