Institute of Pathology, School of Medicine, Technical University of Munich, Trogerstraße 18, 81675 Munich, Germany.
German Cancer Consortium (DKTK), Partner Site Munich, 81675 Munich, Germany.
Molecules. 2022 Jul 27;27(15):4811. doi: 10.3390/molecules27154811.
Cancer-related deaths are very commonly attributed to complications from metastases to neighboring as well as distant organs. Dissociate response in the treatment of pancreatic adenocarcinoma is one of the main causes of low treatment success and low survival rates. This behavior could not be explained by transcriptomics or genomics; however, differences in the composition at the protein level could be observed. We have characterized the proteomic composition of primary pancreatic adenocarcinoma and distant metastasis directly in human tissue samples, utilizing mass spectrometry imaging. The mass spectrometry data was used to train and validate machine learning models that could distinguish both tissue entities with an accuracy above 90%. Model validation on samples from another collection yielded a correct classification of both entities. Tentative identification of the discriminative molecular features showed that collagen fragments (COL1A1, COL1A2, and COL3A1) play a fundamental role in tumor development. From the analysis of the receiver operating characteristic, we could further advance some potential targets, such as histone and histone variations, that could provide a better understanding of tumor development, and consequently, more effective treatments.
癌症相关的死亡通常归因于转移到邻近和远处器官的并发症。胰腺腺癌治疗中的分离反应是治疗成功率低和生存率低的主要原因之一。这种行为不能用转录组学或基因组学来解释；然而，在蛋白质水平上可以观察到组成上的差异。我们利用质谱成像技术，直接在人类组织样本中对原发性胰腺腺癌和远处转移的蛋白质组组成进行了特征描述。质谱数据用于训练和验证机器学习模型，这些模型可以区分这两种组织实体，准确率超过 90%。对来自另一个样本集的样本进行模型验证，得到了对这两种实体的正确分类。对有区别的分子特征的初步鉴定表明，胶原片段（COL1A1、COL1A2 和 COL3A1）在肿瘤发展中起着重要作用。从接收者操作特征的分析中，我们可以进一步提出一些潜在的靶点，如组蛋白和组蛋白变体，这可以更好地了解肿瘤的发展，并因此提供更有效的治疗方法。
