Interplay of mechanical properties of tissue microenvironment, oncogenic signaling, and metabolism in hepatopancreatic cancer

肝胰腺癌组织微环境机械特性、致癌信号传导和代谢的相互作用

• 批准号: 530848033
• 负责人: Privatdozent Dr. Nikolaus Berndt
• 金额: --
• 依托单位: Institut für Pathologie (CCM)
• 依托单位国家: 德国
• 项目类别: Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/530848033?language=en
• 关键词: Interplay; mechanical; properties; tissue; microenvironment

Oncogenic signaling pathways are the main drivers of cellular transformation and metabolic alterations and lead to cancer cell invasion and metastasis. Intracellular molecular adaptation processes in cancer cells following oncogenic transformation have been widely studied. However, the link between mechanical alterations induced by the growing tumor and the interaction with the surrounding tissue microenvironment remains incompletely understood. In A02, we will combine a comprehensive molecular investigation of pancreatic adenocarcinoma (PDAC) and hepatocellular carcinoma (HCC) samples at RNA, protein, and metabolite levels with the determination of viscoelastic properties of patient tumors in vivo and in vitro. Thus, within the research unit, A02 is central to the analysis of tumor-altered metabolism and signaling concerning mechanical niche properties. With the support of A01 and A03, we will establish and apply organoid-matrix mechanical assays, while tissue and in vivo mechanical parameters will be obtained from the B- and C projects. To gain insight into molecular processes coupled with distinct and patient-individual viscoelastic properties, we will first uncover the transcriptomic and metabolic profiles of tumor samples derived from patients undergoing surgery and previously tested using multifrequency MR elastography (mMRE). In addition to intracellular processes activated through oncogenes, elevated external solid stress and interstitial fluid pressure have been shown to generate stress signals within tumors. This can impact MAPK, YAP/TAZ, and TGFβ pathway activation. To test the hypothesis that oncogenic signaling and metabolic properties are influenced by the mechanical environment within a tumor sample and vice-versa, organoids will be established from patient tissue with distinct viscoelastic properties investigated by mMRE. Distinct matrix components will be added to modulate in vitro matrix stiffness. Alternatively, organoids will be grown on pancreas and liver decellularized extracellular matrix samples. Using these different environmental conditions, we will implement transcriptomic and CyTOF analyses for determining KRAS/MAPK, mTOR, insulin, and glucagon signaling of PDAC and HCC to link metabolic states with oncogenic signaling. Using molecular resolved kinetic modeling based on proteomic data from parenchyma/tumors of pancreas and livers obtained from surgical specimens and organoids, we will reveal the alterations in metabolic capacities of carbohydrate, fatty acid, and amino acid metabolism. We will compare in vivo and ex vivo viscoelastic properties of patients and differentially cultivated organoids. Combining these data, we will identify clusters of signaling, metabolic states/dynamics under varying matrix conditions, and viscoelastic properties from patients to be the first to uncover functional links that have the potential to improve diagnosis and help to identify new therapeutic targets in patients with PDAC and HCC.

致癌信号通路是细胞转化和代谢改变的主要驱动力，并导致癌细胞的侵袭和转移。癌变后癌细胞的细胞内分子适应过程已被广泛研究。然而，肿瘤生长引起的机械改变和与周围组织微环境的相互作用之间的联系仍不完全清楚。在A02会议上，我们将结合对胰腺癌(PDAC)和肝细胞癌(HCC)样本在RNA、蛋白质和代谢物水平上的全面分子研究，以及体内和体外患者肿瘤的粘弹性特性的确定。因此，在研究单位内，A02是分析肿瘤改变的新陈代谢和与机械生态位特性有关的信号的中心。在A01和A03的支持下，我们将建立和应用有机基质机械分析，而组织和体内的机械参数将从B-和C项目中获得。为了深入了解分子过程与独特的和患者个体的粘弹性特性相结合，我们将首先揭示来自手术患者的肿瘤样本的转录和代谢特征，并先前使用多频磁共振弹性成像(MMRE)进行测试。除了通过癌基因激活的细胞内过程外，外部固体压力和间质流体压力的增加也被证明在肿瘤内产生应力信号。这可能会影响MAPK、YAP/TAZ和转化生长因子β途径的激活。为了验证致癌信号和代谢特性受肿瘤样本中的机械环境影响以及反之亦然的假设，将从具有不同粘弹性特性的患者组织中建立有机类化合物，通过mMRE进行研究。将添加不同的基质成分来调节体外基质的硬度。或者，类有机物将在胰腺和肝脏脱细胞的细胞外基质样本上生长。利用这些不同的环境条件，我们将进行转录和细胞TOF分析，以确定PDAC和肝癌的KRAS/MAPK、mTOR、胰岛素和胰升糖素信号，从而将代谢状态与致癌信号联系起来。利用基于胰腺实质/肿瘤和肝脏蛋白质组数据的分子分辨动力学模型，我们将揭示碳水化合物、脂肪酸和氨基酸代谢能力的变化。我们将比较患者和不同培养的有机物质在体内和体外的粘弹性特性。结合这些数据，我们将识别来自患者的信号簇、在不同基质条件下的代谢状态/动力学以及粘弹性属性，从而率先发现有可能改善PDAC和肝细胞癌患者诊断并帮助确定新治疗靶点的功能联系。