Erlmeier Franziska, Sun Na, Shen Jian, Feuchtinger Annette, Buck Achim, Prade Verena M, Kunzke Thomas, Schraml Peter, Moch Holger, Autenrieth Michael, Weichert Wilko, Hartmann Arndt, Walch Axel
Institute of Pathology, University Hospital Erlangen-Nuremberg, 91054 Erlangen, Germany.
Research Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany.
Cancers (Basel). 2022 Mar 30;14(7):1763. doi: 10.3390/cancers14071763.
High mass resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a suitable method for biomarker detection for several tumor entities. Renal cell carcinoma (RCC) is the seventh most common cancer type and accounts for more than 80% of all renal tumors. Prognostic biomarkers for RCC are still missing. Therefore, we analyzed a large, multicenter cohort including the three most common RCC subtypes (clear cell RCC (ccRCC), papillary RCC (pRCC) and chromophobe RCC (chRCC)) by MALDI for prognostic biomarker detection. MALDI-Fourier-transform ion cyclotron resonance (FT-ICR)-MSI analysis was performed for renal carcinoma tissue sections from 782 patients. SPACiAL pipeline was integrated for automated co-registration of histological and molecular features. Kaplan-Meier analyses with overall survival as endpoint were executed to determine the metabolic features associated with clinical outcome. We detected several pathways and metabolites with prognostic power for RCC in general and also for different RCC subtypes.
高质量分辨率基质辅助激光解吸/电离（MALDI）质谱成像（MSI）是检测多种肿瘤实体生物标志物的合适方法。肾细胞癌（RCC）是第七大常见癌症类型，占所有肾肿瘤的80%以上。RCC的预后生物标志物仍然缺失。因此，我们通过MALDI分析了一个大型多中心队列，包括三种最常见的RCC亚型（透明细胞RCC（ccRCC）、乳头状RCC（pRCC）和嫌色细胞RCC（chRCC）），以检测预后生物标志物。对782例患者的肾癌组织切片进行了MALDI-傅里叶变换离子回旋共振（FT-ICR）-MSI分析。整合了SPACiAL管道以实现组织学和分子特征的自动共配准。以总生存为终点进行Kaplan-Meier分析，以确定与临床结果相关的代谢特征。我们检测到了一些对RCC总体以及不同RCC亚型具有预后能力的通路和代谢物。
