今天剖析一篇文章题目为(Identification of an immune gene expression signature associated with favorable clinical features in Treg-enriched patient tumor samples )文章题目要充分理解这篇文章,需要三篇补充材料参考文献17:Charoentong, P. et al. Pan-cancer immunogenomic analyses reveal genotypeimmunophenotype relationships and predictors of response to checkpoint blockade. Cell Rep. 18, 248–262 (2017). 参考文献18:Newman, A. M. et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods 12, 453–457 (2015). 参考文献19:Patel, S. J. et al. Identification of essential genes for cancer immunotherapy. Nature 548, 537–542 (2017). 方法学workflow流程图筛选TCGA中负荷筛选标准的患者
聚类分析
免疫细胞评价
a patient’s IPS can be derived in an unbiased manner using machine learning by considering the four major categories of genes that determine immunogenicity (effector cells, immunosuppressive cells, MHC molecules, and immunomodulators) by the gene expression of the cell types these comprise (e.g., activated CD4+ T cells, activated CD8+ T cells, effector memory CD4+ T cells, Tregs, MDSCs). The IPS is calculated on a 0–10 scale based on representative cell type gene expression z-scores, where higher scores are associated with increased immunogenicity.
DNA可及性分析:结果结果一很简单:对135进行聚类,再拆分不同的癌肿进行聚类结果一其中cluster1 和cluster2能够很好的反应sens组和res组。卡方检验P=0.0007 图b-f只有SKCM和STAD两种癌症的卡方值P<0.05 结果二也很简单A为cluster1和cluster2的生存分析,B为cluster1中res的患者和cluster2中res的患者。 结果二 说明了这种32个基因的expression signature可以较好的区分不同临床表现的患者 结果三:a-e比较cluster1 和cluster2中CD8A和CD8B,HLA-A,PRF1的表达量还有比较两组cibersore免疫细胞abandance的结果。结果三表一是对cibersort图片的补充。表一f-j比较cluster1中res的患者和cluster2中res的患者的CD8A和CD8B,HLA-A,PRF1的表达量还有比较两组cibersore免疫细胞abandance的结果。结果三-2结果四:验证队列OS的比较,结果全部重现一遍结果四结果五:与免疫治疗marker相关的分析A是IPS评分, 结果五-1B-C是PD-1和CTLA4的表达, 结果五-2 D:使用参考文献19的18个免疫治疗相关的基因再次进行聚类分析kmeans(K=2),对比32个基因的聚类分析的结果,发现异质性=0.54.E:在这18个基因中cluster1中高表达的占了12个。热图体现。 结果五-3 文章结论这个就自己体会了 our results reveal a gene signature able to produce unsupervised clusters of Treg-enriched patients, with one cluster of patients uniquely representative of an immunogenic tumor microenvironment. Ultimately, these results support the proposed gene signature as a putative biomarker to identify certain Treg-enriched patients with immunogenic tumors that are more likely to be associated with features of favorable clinical outcome. |
|