本篇文献题目为《An Immunogram for the Cancer-Immunity Cycel_ Towards Personalized Immunotherapy of Lung Cancer》
为《A novel scoring method basedon RNA-Seq immunograms describing individual cancerimmunity interaction》同一团队所作,且此文章发表在前( accepted 4 January 2017);IF=13+
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此文章选取了8个Axis:
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IGS 1 , existence of T-cell immunity in the tumor;
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IGS 2 , tumor antigenicity;
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IGS 3 , priming and activation;
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IGS 4 , trafficking and infiltration;
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IGS 5 , recognition of tumor antigens;
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IGS 6 to IGS 8 , suppressive factors preventing killing of cancer cells
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方法
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多数利用RNA-Seq 的GSEA 算出得分(Normalized Enrichment Score,NES),转为Z-Score,再转为 immunogram score (IGS):IGS = 3+1.5*Z
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有的是利用WES 测得neoantigen load,然后再将neoantigen load转为Z-Score,进而转为IGS
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RNA-seq数据进行GSEA的时候,涉及到Gene Sets 选取,个别是有前文报道可参考,无据可依的,则是作者自行选取和定义的gene sets
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有的Axis算出IGS后,还对相应患者做了IHC,IHC的结果能够印证IGS
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结果
- Figure1,不赘述 image
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Figure2
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IGS1: Antitumor T-Cell Immunity的情况:86 gene sets来自于参考文献26-27;依据该结果分为了 9个T细胞炎症型,5个中间型,6个豁免型
- 还进一步利用CD8和CD3抗体做了IHC,对IGS1分析的结果进行了实验验证:NES与CD3-positive area和 CD8-positive area显著正相关 image
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Figure 3
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IGS2:Tumor Antigenicity。利用number of candidate neoantigens and imCG antigens---Z-Score---IGS2
- Figure3A: T细胞炎症型的肿瘤中,neoantigens and imCG antigens的中位数均较低,但最终的IGS得分,T细胞炎症型,中间型和豁免型之间似乎未见显著差别
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IGS3:T-Cell Priming and Activation。GSEA所用53基因来自于参考文献26-27.
- Figure3B: T细胞炎症型的肿瘤中,树突状细胞(抗原递呈)的IGS3是显著高于非炎症型的
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IGS6:absence of inhibitory cells。
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