Loch Florian N, Klein Oliver, Beyer Katharina, Klauschen Frederick, Schineis Christian, Lauscher Johannes C, Margonis Georgios A, Degro Claudius E, Rayya Wael, Kamphues Carsten
Department of Surgery, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Hindenburgdamm 30, 12203 Berlin, Germany.
Berlin Institute of Health, Charité-Universitätsmedizin Berlin, Center for Regenerative Therapies BCRT, Charitéplatz 1, 10117 Berlin, Germany.
Biology (Basel). 2021 Oct 12;10(10):1033. doi: 10.3390/biology10101033.
Despite the overall poor prognosis of pancreatic cancer there is heterogeneity in clinical courses of tumors not assessed by conventional risk stratification. This yields the need of additional markers for proper assessment of prognosis and multimodal clinical management. We provide a proof of concept study evaluating the feasibility of Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to identify specific peptide signatures linked to prognostic parameters of pancreatic cancer. On 18 patients with exocrine pancreatic cancer after tumor resection, MALDI imaging analysis was performed additional to histopathological assessment. Principal component analysis (PCA) was used to explore discrimination of peptide signatures of prognostic histopathological features and receiver operator characteristic (ROC) to identify which specific / values are the most discriminative between the prognostic subgroups of patients. Out of 557 aligned / values discriminate peptide signatures for the prognostic histopathological features lymphatic vessel invasion (pL, 16 / values, eight proteins), nodal metastasis (pN, two / values, one protein) and angioinvasion (pV, 4 / values, two proteins) were identified. These results yield proof of concept that MALDI-MSI of pancreatic cancer tissue is feasible to identify peptide signatures of prognostic relevance and can augment risk assessment.
尽管胰腺癌的总体预后较差,但肿瘤的临床病程存在异质性,这是传统风险分层无法评估的。因此,需要额外的标志物来准确评估预后和进行多模式临床管理。我们提供了一项概念验证研究,评估基质辅助激光解吸/电离(MALDI)质谱成像(MSI)识别与胰腺癌预后参数相关的特定肽谱的可行性。对18例胰腺外分泌癌患者进行肿瘤切除后,除了组织病理学评估外,还进行了MALDI成像分析。主成分分析(PCA)用于探索预后组织病理学特征的肽谱差异,受试者操作特征曲线(ROC)用于确定哪些特定的/值在患者预后亚组之间具有最大的区分度。在557个比对的/值中,识别出了与预后组织病理学特征淋巴管浸润(pL,16个/值,8种蛋白质)、淋巴结转移(pN,2个/值,1种蛋白质)和血管浸润(pV,4个/值,2种蛋白质)相关的肽谱。这些结果证明了胰腺癌组织的MALDI-MSI识别具有预后相关性的肽谱并增强风险评估的概念验证。