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用于肝癌早期诊断的拉曼光谱无损分子成像与基质辅助激光解吸电离成像质谱标记物检测的对比

Nondestructive molecular imaging by Raman spectroscopy vs. marker detection by MALDI IMS for an early diagnosis of HCC.

作者信息

Kirchberger-Tolstik Tatiana, Ryabchykov Oleg, Bocklitz Thomas, Dirsch Olaf, Settmacher Utz, Popp Juergen, Stallmach Andreas

机构信息

Jena University Hospital, Department of Internal Medicine IV, Gastroenterology, Hepatology, Infectious Disease, Am Klinikum, 1, 07747 Jena, Germany.

出版信息

Analyst. 2021 Feb 21;146(4):1239-1252. doi: 10.1039/d0an01555e. Epub 2020 Dec 14.

Abstract

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide with a steadily increasing mortality rate. Fast diagnosis at early stages of HCC is of key importance for the improvement of patient survival rates. In this regard, we combined two imaging techniques with high potential for HCC diagnosis in order to improve the prediction of liver cancer. In detail, Raman spectroscopic imaging and matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI IMS) were applied for the diagnosis of 36 HCC tissue samples. The data were analyzed using multivariate methods, and the results revealed that Raman spectroscopy alone showed a good capability for HCC tumor identification (sensitivity of 88% and specificity of 80%), which could not be improved by combining the Raman data with MALDI IMS. In addition, it could be shown that the two methods in combination can differentiate between well-, moderately- and poorly-differentiated HCC using a linear classification model. MALDI IMS not only classified the HCC grades with a sensitivity of 100% and a specificity of 80%, but also showed significant differences in the expression of glycerophospholipids and fatty acyls during HCC differentiation. Furthermore, important differences in the protein, lipid and collagen compositions of differentiated HCC were detected using the model coefficients of a Raman based classification model. Both Raman and MALDI IMS, as well as their combination showed high potential for resolving concrete questions in liver cancer diagnosis.

摘要

肝细胞癌(HCC)是全球癌症相关死亡的主要原因,死亡率呈稳步上升趋势。HCC早期的快速诊断对于提高患者生存率至关重要。在这方面,我们结合了两种对HCC诊断具有高潜力的成像技术,以改善肝癌的预测。具体而言,拉曼光谱成像和基质辅助激光解吸电离成像质谱(MALDI IMS)被应用于36个HCC组织样本的诊断。使用多变量方法对数据进行分析,结果显示仅拉曼光谱对HCC肿瘤识别具有良好能力(灵敏度为88%,特异性为80%),将拉曼数据与MALDI IMS结合并不能提高该能力。此外,可以证明这两种方法结合使用线性分类模型能够区分高分化、中分化和低分化的HCC。MALDI IMS不仅以100%的灵敏度和80%的特异性对HCC分级进行分类,还显示出在HCC分化过程中甘油磷脂和脂肪酰基表达的显著差异。此外,使用基于拉曼的分类模型的模型系数检测到分化型HCC在蛋白质、脂质和胶原蛋白组成方面的重要差异。拉曼光谱和MALDI IMS及其组合在解决肝癌诊断中的具体问题方面均显示出很高的潜力。

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