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Molecular correlates and therapeutic targets in T cell-inflamed versus non-T cell-inflamed tumors across cancer types

机译:在癌症类型的T细胞发炎与非T细胞发炎的肿瘤中的分子相关和治疗靶标

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The T cell-inflamed tumor microenvironment, characterized by CD8 T cells and type I/II interferon transcripts, is an important cancer immunotherapy biomarker. Tumor mutational burden (TMB) may also dictate response, and some oncogenes (i.e., WNT/β-catenin) are known to mediate immunosuppression. We performed an integrated multi-omic analysis of human cancer including 11,607 tumors across multiple databases and patients treated with anti-PD1. After adjusting for TMB, we correlated the T cell-inflamed gene expression signature with somatic mutations, transcriptional programs, and relevant proteome for different immune phenotypes, by tumor type and across cancers. Strong correlations were noted between mutations in oncogenes and tumor suppressor genes and non-T cell-inflamed tumors with examples including IDH1 and GNAQ as well as less well-known genes including KDM6A, CD11c, and genes with unknown functions. Conversely, we observe genes associating with the T cell-inflamed phenotype including VHL and PBRM1. Analyzing gene expression patterns, we identify oncogenic mediators of immune exclusion across cancer types (HIF1A and MYC) as well as novel examples in specific tumors such as sonic hedgehog signaling, hormone signaling and transcription factors. Using network analysis, somatic and transcriptomic events were integrated. In contrast to previous reports of individual tumor types such as melanoma, integrative pan-cancer analysis demonstrates that most non-T cell-inflamed tumors are influenced by multiple signaling pathways and that increasing numbers of co-activated pathways leads to more highly non-T cell-inflamed tumors. Validating these analyses, we observe highly consistent inverse relationships between pathway protein levels and the T cell-inflamed gene expression across cancers. Finally, we integrate available databases for drugs that might overcome or augment the identified mechanisms. These results nominate molecular targets and drugs potentially available for further study and potential immediate translation into clinical trials for patients with cancer.
机译:T细胞发炎的肿瘤微环境,其特征在于CD8 T细胞和I / II型干扰素转录物,是重要的癌症免疫治疗生物标志物。肿瘤突变负荷(TMB)也可以决定反应,并且已知一些癌基因(即,Wnt /β-catenin)介导免疫抑制。我们对人类癌症进行了综合的多环境分析,包括跨多个数据库的11,607个肿瘤,并用抗PD1治疗患者。调整TMB后,我们将T细胞发炎的基因表达签名与细胞突变,转录程序和相关蛋白质组相关,以通过肿瘤类型和癌症进行不同免疫表型。癌肠和肿瘤抑制基因的突变和非T细胞发炎的肿瘤之间的突变与包含IDH1和GNAQ的实例的突变以及包括KDM6A,CD11c和具有未知功能的基因的较少的众所周知的基因之间的强相关性。相反,我们观察与包括VHL和PBRM1的T细胞发炎的表型相关的基因。分析基因表达模式,鉴定癌症类型(HIF1A和MYC)的免疫排除的致癌介质以及在特定肿瘤中的新实例,如声音刺猬信号传导,激素信号传导和转录因子。使用网络分析,整合了体细胞和转录组事件。与先前的单个肿瘤类型如黑色素瘤的报道相反,综合性泛癌分析表明,大多数非T细胞发炎的肿瘤受到多个信号通路的影响,并且越来越多的共激的途径导致更高度的非T.细胞发炎的肿瘤。验证这些分析,我们观察途径蛋白水平与癌症的T细胞发炎的基因表达之间的高度一致的反相。最后,我们整合了可能克服或增强所确定的机制的药物的可用数据库。这些结果提名分子靶点和药物可能可用于进一步研究和潜在的癌症临床试验中的临床试验。

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