Fecal Microbiota Transplant and PD-1 blockade in Melanoma

摘要 有充分的证据表明，黑色素瘤患者（MP）会产生针对肿瘤的免疫反应， 相关抗原。然而，高频率的肿瘤抗原特异性细胞毒性T淋巴细胞（CTL）通常 不能诱导肿瘤排斥反应。在肿瘤诱导的免疫抑制的众多机制中， 有助于肿瘤对CTL应答的抗性，现在已经确定抑制性受体如 PD 1在抑制T细胞对肿瘤的反应中起关键作用。因此，使用阻断性抗PD 1抗体的治疗 单克隆抗体已经成为黑色素瘤最有效的治疗方法之一， 30-40%的高级议员受益。有强有力的证据表明，预先存在的CD 8+肿瘤浸润性T细胞 与对PD 1阻断的临床抗肿瘤反应相关。然而，并不是所有的T细胞炎症肿瘤都对 PD 1阻断，并不是所有的黑色素瘤都会发炎。因此，支持反应或抵抗的机制 对PD 1的阻断作用仍有待精确测定。两项研究表明，肠道微生物组在 在鼠黑素瘤模型中调节对CTLA 4和PD 1阻断的临床应答。此外，两项研究 在NSCLC和肾癌（RC）和黑色素瘤患者（MP）中，分别显示， 某些药物的存在与PD 1阻断后更好的临床结果相关。粪便微生物群 在携带黑色素瘤的GF小鼠中，来自PD 1应答者（PD 1 R）的移植物（FMT）显著减少了肿瘤 与来自PD 1无应答者（PD 1 NRs）的FMT相比的生长。我们观察到， 与PD 1 NR相比，PD 1 R粪便中某些细菌的丰度，尽管显著 与最近出版的不同。我们的研究结果与最近的研究结果之间的显著差异 当人们考虑到更大的复杂性和个体间的差异时， 人类肠道微生物群的变异性取决于许多宿主依赖性变量。因此， 使用最先进的组学方法（宏基因组学）在大量MP中扩展这些研究， 系统生物学评价肠道细菌与临床结局之间的直接因果关系。这里我们 建议测试肠道微生物组是否调节免疫和临床对PD 1阻断的反应， 背景是一项新的临床试验，FMT从PD 1 Rs中获得，与PD 1 NR中的PD 1阻断相结合。这 该项目将测试以下新假设：1）PD 1 R在多样性方面表现出不同的肠道微生物群特征， 与PD 1 NRs相比，随着时间的推移的丰度和动力学; 2）施用单一PD 1 R衍生的 针对PD 1 NR的FMT与PD 1阻断一起促进临床抗肿瘤应答;和3） 用FMT和PD 1阻断剂治疗的MP的临床应答与T细胞对黑素瘤的应答相关。 这一提议将利用调查员在以下方面的成熟和跨学科的专门知识： 黑色素瘤，人类癌症免疫学，肠道微生物组和元组学，生物统计学和系统生物学。

Abstract There is ample evidence that melanoma patients (MPs) develop immune responses directed against tumor- associated antigens. However, high frequencies of tumor antigen-specific cytotoxic T-lymphocytes (CTL) often fail to induce tumor rejection. Among the numerous mechanisms of tumor-induced immunosuppression that contribute to the resistance of tumors to CTL responses, it is now well established that inhibitory receptors like PD1 play a critical role in dampening T cell responses to tumors. As a result, therapy with blocking anti-PD1 monoclonal antibodies has become one of the most potent therapies of melanoma, providing prolonged clinical benefits to 30-40% advanced MPs. There is strong evidence that pre-existing CD8+ tumor-infiltrating T cells correlate with clinical antitumor response to PD1 blockade. However, not all T cell-inflamed tumors respond to PD1 blockade and not all melanomas are inflamed. Hence, the mechanisms supporting response or resistance to PD1 blockade remain to be precisely determined. Two studies have shown the role of the gut microbiome in regulating clinical responses to CTLA4 and PD1 blockade in murine melanoma model. In addition, two studies in NSCLCs and renal cancers (RC), and melanoma patients (MPs), respectively, have shown that the presence of certain commensals correlated with better clinical outcome upon PD1 blockade. Fecal microbiota transplant (FMT) from PD1 responders (PD1Rs) in melanoma-bearing GF mice reduced significantly tumor growth as compared to FMT from PD1 non-responders (PD1NRs). We have observed the increased abundance of certain bacterial commensals in stools of PD1Rs as compared to PD1NRs, albeit significantly different from the ones recently published. The striking differences between our findings and the recent published study are not totally surprising when one considers the greater complexity and inter-individual variability of the human gut microbiota upon many host-dependent variables. It is therefore critically important to expand these studies in a larger number of MPs using state-of-the-art omic approach (metagenomics) and Systems Biology to evaluate the direct causality between commensal bacteria and clinical outcome. Here, we propose to test whether the gut microbiome modulates immune and clinical responses to PD1 blockade in the context a novel clinical trial with FMT obtained from PD1Rs combined with PD1 blockade in PD1NRs. This project will test the novel hypotheses that: 1) PD1Rs exhibit distinct gut microbiota profiles in terms of diversity, abundance and dynamics over time compared with PD1NRs; 2) the administration of single PD1R-derived FMT to a PD1NRs together with PD1 blockade promotes clinical antitumor response; and 3) the occurrence of clinical responses in MPs treated with FMT and PD1 blockade correlates with T cell responses to melanoma. This proposal will take advantage of the well-established and cross-disciplinary expertise of the investigators in melanoma, human cancer immunology, gut microbiome and metaomics, biostatistics, and systems biology.