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(MPS)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反应的抵抗，现在公认的是抑制受体如 PD1在抑制T细胞对肿瘤的反应中起关键作用。因此，阻断抗PD1的治疗 单抗已成为治疗黑色素瘤最有效的方法之一，可延长临床治疗时间。 受益于30%-40%的高级议员。有强有力的证据表明，预先存在的CD8+肿瘤浸润性T细胞 与临床对PD1阻滞剂的抗肿瘤反应有关。然而，并不是所有T细胞发炎的肿瘤都对 PD1阻断，并不是所有的黑色素瘤都发炎。因此，支持反应或抵抗的机制 对PD1的封锁仍有待准确确定。两项研究表明，肠道微生物群在 调节CTLA4和PD1阻断对小鼠黑色素瘤模型的临床反应。此外，还有两项研究 在非小细胞肺癌和肾癌(RC)以及黑色素瘤患者(MPS)中，分别表明 某些共生体的存在与PD1阻断后较好的临床结果相关。粪便微生物区系 PD1反应者(PD1Rs)在荷黑色素瘤的GF小鼠体内的移植(FMT)显著减少肿瘤 与来自PD1无响应者(PD1NR)的FMT相比增长。我们观察到增加了 与PD1NRs相比，PD1R粪便中某些细菌共生体的丰度，尽管显著 与最近发表的不同。我们的发现与最近的研究结果之间的显著差异 考虑到更大的复杂性和个体之间的差异，发表的研究并不完全令人惊讶 人体肠道微生物区系对许多寄主依赖变量的可变性。因此，这一点至关重要。 使用最先进的组学方法(元基因组学)将这些研究扩展到更多的MPS中，并 系统生物学评估共生细菌和临床结果之间的直接因果关系。在这里，我们 建议测试肠道微生物组是否调节对PD1阻断的免疫和临床反应 背景一项新的临床试验，从PD1Rs获得的FMT与PD1NRs中的PD1阻断相结合。这 该项目将测试新的假设：1)PD1R在多样性方面表现出不同的肠道微生物区系特征， 与PD1NRs相比，随着时间的推移，PD1R的丰度和动态；2)单一PD1R来源的给药 对PD1NRs的FMT联合PD1阻断可促进临床抗肿瘤反应；3) 经FMT和PD1阻断治疗的MPS的临床反应与T细胞对黑色素瘤的反应相关。 这项提议将利用调查员在#年的成熟和跨学科专业知识。 黑色素瘤、人类癌症免疫学、肠道微生物组和代谢组学、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.