Mehta Khyati Y, Wu Hung-Jen, Menon Smrithi S, Fallah Yassi, Zhong Xiaogang, Rizk Nasser, Unger Keith, Mapstone Mark, Fiandaca Massimo S, Federoff Howard J, Cheema Amrita K
Department of Oncology, Georgetown University Medical Center, Washington, DC, United States of America.
Department of Biochemistry and Molecular and Cellular Biology, Georgetown University Medical Center, Washington, DC, United States of America.
Oncotarget. 2017 Aug 18;8(40):68899-68915. doi: 10.18632/oncotarget.20324. eCollection 2017 Sep 15.
Pancreatic cancer (PC) is an aggressive disease with high mortality rates, however, there is no blood test for early detection and diagnosis of this disease. Several research groups have reported on metabolomics based clinical investigations to identify biomarkers of PC, however there is a lack of a centralized metabolite biomarker repository that can be used for meta-analysis and biomarker validation. Furthermore, since the incidence of PC is associated with metabolic syndrome and Type 2 diabetes mellitus (T2DM), there is a need to uncouple these common metabolic dysregulations that may otherwise diminish the clinical utility of metabolomic biosignatures. Here, we attempted to externally replicate proposed metabolite biomarkers of PC reported by several other groups in an independent group of PC subjects. Our study design included a T2DM cohort that was used as a non-cancer control and a separate cohort diagnosed with colorectal cancer (CRC), as a cancer disease control to eliminate possible generic biomarkers of cancer. We used targeted mass spectrometry for quantitation of literature-curated metabolite markers and identified a biomarker panel that discriminates between normal controls (NC) and PC patients with high accuracy. Further evaluation of our model with CRC, however, showed a drop in specificity for the PC biomarker panel. Taken together, our study underscores the need for a more robust study design for cancer biomarker studies so as to maximize the translational value and clinical implementation.
胰腺癌（PC）是一种侵袭性疾病，死亡率很高，然而，目前尚无用于早期检测和诊断该疾病的血液检测方法。几个研究小组报告了基于代谢组学的临床研究，以确定胰腺癌的生物标志物，然而，缺乏一个可用于荟萃分析和生物标志物验证的集中式代谢物生物标志物库。此外，由于胰腺癌的发病率与代谢综合征和2型糖尿病（T2DM）相关，因此有必要将这些常见的代谢失调区分开来，否则可能会降低代谢组学生物标志物的临床效用。在此，我们试图在一组独立的胰腺癌患者中对外复制其他几个小组报告的胰腺癌代谢物生物标志物。我们的研究设计包括一个用作非癌症对照的2型糖尿病队列和一个诊断为结直肠癌（CRC）的单独队列，作为癌症疾病对照，以消除可能的癌症通用生物标志物。我们使用靶向质谱法定量文献整理的代谢物标记物，并确定了一个能高精度区分正常对照（NC）和胰腺癌患者的生物标志物组。然而，用结直肠癌对我们的模型进行进一步评估时，结果显示胰腺癌生物标志物组的特异性有所下降。综上所述，我们的研究强调癌症生物标志物研究需要更稳健的研究设计，以最大限度地提高转化价值和临床应用。
