Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 6 Grunwaldzka Street, 60-780 Poznan, Poland.
Gynecologic Oncology Department, Poznan University of Medical Sciences, 33 Polna Street, 60-535 Poznan, Poland.
Life Sci. 2019 Apr 1;222:235-244. doi: 10.1016/j.lfs.2019.03.004. Epub 2019 Mar 7.
Despite of almost a hundred years of research on cancer metabolism, the biological background of cancerogenesis and cancer-related reprogramming of metabolism remains not fully understood. In order to comprehensively and effectively diagnose and treat the deadliest diseases, the mechanisms underlying these diseases have to be discovered urgently. Among the gynecological malignancies, ovarian cancer is the most common cause of death. The aim of the study was to search for potential cancer-related differences in concentrations of metabolites and interactions between them in serum of women with ovarian cancer and benign ovarian tumor in comparison with healthy controls using targeted metabolomics. These metabolites might serve as biomarkers in the future.
We used wide spectrum targeted metabolomics to evaluate serum concentrations of metabolites related to ovarian cancer and compared them against benign ovarian tumors and healthy controls. The measurements were performed using high performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry technique in highly-selective multiple reaction monitoring mode.
In this study we confirmed our previous findings about the role of histidine and citrulline in ovarian cancer as well as we indicated new lipid compounds (lysoPC a C16:1, PC aa C32:2, PC aa C34:4 and PC aa C 36:6) potentially involved in cancer metabolism.
We indicated interesting interactions between metabolites for further in-depth research which could potentially serve as clinically useful biomarkers in future. Moreover, the presented work attempts to visualize a possible 3D-network of relationships between the molecules found to be related to ovarian malignancy.
尽管癌症代谢的研究已经进行了近一百年，但癌症发生和与癌症相关的代谢重编程的生物学背景仍未完全被理解。为了全面有效地诊断和治疗这些最致命的疾病，必须紧急发现这些疾病的机制。在妇科恶性肿瘤中，卵巢癌是最常见的死亡原因。本研究旨在通过靶向代谢组学，寻找卵巢癌患者和良性卵巢肿瘤患者与健康对照者血清中潜在的与癌症相关的代谢物浓度差异及其相互作用。这些代谢物在未来可能作为生物标志物。
我们使用广谱靶向代谢组学来评估与卵巢癌相关的代谢物在血清中的浓度，并将其与良性卵巢肿瘤和健康对照进行比较。使用高效液相色谱-三重四极杆串联质谱技术在高度选择性的多重反应监测模式下进行测量。
在这项研究中，我们证实了我们之前关于组氨酸和瓜氨酸在卵巢癌中的作用的发现，并且我们还指出了新的脂质化合物（lysoPC a C16:1、PC aa C32:2、PC aa C34:4 和 PC aa C 36:6）可能参与了癌症代谢。
我们指出了代谢物之间有趣的相互作用，以供进一步深入研究，这些相互作用可能在未来成为有临床应用价值的生物标志物。此外，本研究试图可视化与卵巢恶性肿瘤相关的分子之间可能存在的 3D 关系网络。
