Metabolite biomarker discovery for pancreatic neuroendocrine tumors using metabolomic approach

A. Jannin, A.F. Dessein, S. Dabo, A. Descat, M.C. Vantyghem, B. Chevalier, C. Cardot-Bauters, M. El Amrani, S. Dominguez, C. Marciniak, I. Van Seuningen, C. Do Cao, N. Jonckheere, L. Coppin
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Abstract

Metabolic flexibility is one of the key hallmarks of cancer and metabolites are the final products of this adaptation, reflecting the tumors’ aberrant changes. However, the metabolic plasticity of pancreatic neuroendocrine tumors (pNET) is still unknown. pNETs are heterogeneous which makes their diagnosis and therapeutic management difficult. We aimed to assess the metabolomic profile of pNETs patients to understand metabolic deregulation and identify novel biomarkers. Plasma samples from 45 pNETs and 10 controls were profiled by LC−MS/MS and FIA-MS/MS targeted metabolomics analysis (Biocrates AbsoluteIDQp180kit). Explanatory multivariate statistical and unsupervised learning analysis were performed to evaluate metabolomic profiles. Finally, nonparametric comparison analysis was performed to select metabolites biomarker. As compared to controls we identified an increase of sugars, phosphatidylcholine and a decrease of carnitine levels in pNETs. An increase in phosphatidylcholine, phenylalanine, glutamine and a decrease of carnitine levels was observed for pNETs patients with MEN1 mutation as compared with MEN1 WT patients. Similarly, metastatic pNETs patients had an increased in glutamine, proline, ornithine aa, PC, glucogenic aa, spermine, putrescine and a decrease in PUFA/SFA and carnitine levels as compared to patients without metastasis. Regarding patients with pNETs G2 as compared to G1, an increase in phenylalanine, ornithine, proline aa, carnitine, sphingomyeline and spermidine was observed. For the first time, a precise comprehensive metabolic profile of pNET patients was established and different metabolic plasmatic signatures were defined depending on patient characteristics. This will be confirmed in a validation cohort currently being recruited.
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利用代谢组学方法发现胰腺神经内分泌肿瘤的代谢物生物标志物
代谢灵活性是癌症的关键标志之一,代谢物是这种适应的最终产物,反映了肿瘤的异常变化。然而,胰腺神经内分泌肿瘤(pNET)的代谢可塑性尚不清楚。pNETs的异质性使其诊断和治疗变得困难。我们旨在评估pNETs患者的代谢组学特征,以了解代谢失调并识别新的生物标志物。通过LC -MS/MS和FIA-MS/MS靶向代谢组学分析(Biocrates AbsoluteIDQp180kit)对45例pNETs和10例对照的血浆样本进行分析。使用解释性多变量统计和无监督学习分析来评估代谢组学特征。最后进行非参数比较分析,选择代谢物生物标志物。与对照组相比,我们发现pNETs中糖、磷脂酰胆碱增加,肉毒碱水平降低。与MEN1 WT患者相比,MEN1突变的pNETs患者的磷脂酰胆碱、苯丙氨酸、谷氨酰胺水平升高,肉碱水平降低。同样,与没有转移的患者相比,转移性pNETs患者的谷氨酰胺、脯氨酸、鸟氨酸aa、PC、糖原性aa、精胺、腐胺水平升高,PUFA/SFA和肉毒碱水平下降。pNETs G2患者与G1相比,苯丙氨酸、鸟氨酸、脯氨酸aa、肉毒碱、鞘磷脂和亚精胺均升高。首次建立了pNET患者的精确综合代谢谱,并根据患者特征定义了不同的代谢血浆特征。这将在目前正在招募的验证队列中得到证实。
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