A multicentric translational clinical study on the role of the oro-intestinal microbiome in pancreatic cancer chemotherapy

胰腺导管腺癌(PDAC)是一种常见的癌症类型，但预后很差，5年总生存率仅为9%。大多数患者患有晚期疾病，需要全身化疗。目前的多种化疗方案可以提高总体生存率，但存在相当大的副作用和毒性，往往阻碍了它们在老年患者和/或功能状态较差的患者中的应用。由于目前缺乏能够预测PDAC治疗效果的生物标志物，我们不能可靠地将受益的患者与主要遭受毒性的患者进行分层。近年来，肠道微生物群已被发现用于预测和调节抗癌免疫治疗的疗效。目前，人们对其在实体瘤化疗系统治疗中的作用知之甚少。因此，在预测PDAC患者化疗关键结果的生物标记物方面存在大量未得到满足的医学需求，并调查微生物组特征是否与其相关，以便为未来的治疗干预开发微生物-癌症-治疗相互作用的机制假说和可用药靶点。在目前的研究方案中，我们的目标是对接受标准护理化疗的局部晚期和转移性PDAC患者的德国多中心队列进行微生物组元基因组测序。自2020年以来，我们前瞻性地招募患者(N=131)，并在确诊后收集连续唾液和粪便生物标本，直到系统治疗6个月。在这里，我们将研究治疗过程中口腔和粪便微生物组的纵向变化，并在最终的200名患者和总共800个微生物组样本中调查微生物组特征-物种、基因和代谢途径-与治疗反应、生存和毒性发展的关系，作为主要的临床结果。利用鸟枪元基因组测序，我们还将产生一个史无前例的数据集，说明化疗药物如何改变肠道微生物组的基因库，这可能会对肠道微生物动态平衡和微生物-宿主相互作用产生重大影响。最后，应用机器学习驱动的预测模型，我们将探索基于微生物组的分类器，并将在此包括临床特征和分子肿瘤特征，总体目标是为PDAC患者的治疗结果提出一个生物标志物。

Pancreatic ductal adenocarcinoma (PDAC) is a frequent cancer type, but with a miserable prognosis of a 5-year overall survival of only 9%. Most patients present with advanced stage disease and require systemic therapies with chemotherapy. Current poly-chemotherapeutic regimens can improve overall survival, but are associated with considerable side effects and toxicity, often preventing their application in elderly patients and/or patients with poor performance status. As biomarkers that can predict treatment efficacy against PDAC are currently lacking, we cannot reliably stratify patients in those who will benefit vs. those that will largely suffer from toxicity. In recent years, the gut microbiome has been identified to predict and modulate the efficacy of anticancer immunotherapies. Currently, little is known about its role in chemotherapy-based systemic treatments in solid tumors. Therefore, there is large unmet medical need on biomarkers predicting critical outcomes of chemotherapy in PDAC patients, and to investigate whether microbiome features are associated with it in order to develop mechanistic hypotheses on microbe-cancer-therapy interactions and on druggable targets for future therapeutic interventions. In the present research proposal, we aim to perform microbiome metagenome sequencing from a multicentric German cohort of locally advanced and metastatic PDAC patients receiving standard-of-care chemotherapies. Since 2020, we are prospectively recruiting patients (N = 131) and collecting serial saliva and stool biospecimens after diagnosis until 6 months of systemic therapy. Here, we will study longitudinal changes of the oral and fecal microbiome over the course of therapy and investigate associations of microbiome features – species, genes and metabolic pathways – with therapy response, survival and development of toxicities as major clinical outcomes in a final cohort of 200 patients and 800 microbiome samples in total. Utilizing shotgun metagenome sequencing, we will also generate an unprecedented data set on how chemotherapeutic agents modify the gene reservoir of the gut microbiome which may have drastic effects on gut microbial homeostasis and microbe-host interactions. Finally, applying machine-learning driven prediction models, we will explore microbiome-based classifiers and will include clinical features and molecular tumor characteristics herein with the overall goal to propose a biomarker for therapy outcomes in PDAC patients.