代谢组学
体内
离体
胰腺癌
糖酵解
乳酸脱氢酶
癌症
癌症研究
厌氧糖酵解
医学
核磁共振波谱
化学
生物
新陈代谢
内科学
生物化学
生物信息学
酶
生物技术
有机化学
作者
Prasanta Dutta,Mayrim Rios Perez,Jae-Hyuk Lee,Ya’an Kang,Michael F. Pratt,Travis C. Salzillo,Joseph Weygand,Niki M. Zacharias,Seth T. Gammon,Eugene J. Koay,Michael P. Kim,Florencia McAllister,Subrata Sen,Anirban Maitra,David Piwnica‐Worms,Jason B. Fleming,Pratip K. Bhattacharya
标识
DOI:10.1021/acs.jproteome.9b00132
摘要
Pancreatic ductal adenocarcinoma (PDAC) is a deadly cancer that progresses without any symptom, and oftentimes, it is detected at an advanced stage. The lack of prior symptoms and effective treatments have created a knowledge gap in the management of this lethal disease. This issue can be addressed by developing novel noninvasive imaging-based biomarkers in PDAC. We explored in vivo hyperpolarized (HP) 13C MRS of pyruvate to lactate conversion and ex vivo 1H NMR spectroscopy in a panel of well-annotated patient-derived PDAC xenograft (PDXs) model and investigated the correlation between aberrant glycolytic metabolism and aggressiveness of the tumor. Real-time metabolic imaging data demonstrate the immediate intracellular conversion of HP 13C pyruvate to lactate after intravenous injection interrogating upregulated lactate dehydrogenase (LDH) activity in aggressive PDXs. Total ex vivo lactate measurement by 1H NMR spectroscopy showed a direct correlation with in vivo dynamic pyruvate-to-lactate conversion and demonstrated the potential of dynamic metabolic flux as a biomarker of total lactate concentration and aggressiveness of the tumor. Furthermore, the metabolite concentrations were very distinct among all four tumor types analyzed in this study. Overexpression of LDH-A and hypoxia-inducible factor (HIF-1α) plays a significant role in the conversion kinetics of HP pyruvate-to-lactate in tumors. Collectively, these data identified aberrant metabolic characteristics of pancreatic cancer PDXs and could potentially delineate metabolic targets for therapeutic intervention. Metabolic imaging with HP pyruvate and NMR metabolomics may enable identification and classification of aggressive subtypes of patient-derived xenografts. Translation of this real-time metabolic technique to the clinic may have the potential to improve the management of patients at high risk of developing pancreatic diseases.
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