ICeD-T Provides Accurate Estimates of Immune Cell Abundance in Tumor Samples by Allowing for Aberrant Gene Expression Patterns
ICeD-T Provides Accurate Estimates of Immune Cell Abundance in Tumor Samples by Allowing for Aberrant Gene Expression Patterns
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ICeD-T 通过允许异常基因表达模式来准确估计肿瘤样本中的免疫细胞丰度
DOI：
10.1101/326421
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Wei Sun
中科院分区：
文献类型：
--
作者：
Douglas R. Wilson;J. Ibrahim;Wei Sun
免疫疗法在癌症的治疗方面取得了惊人的成功，并承诺在不久的将来取得更多的突破。了解免疫疗法的潜在机制并开发精确的免疫疗法方案的需求激发了人们对表征肿瘤微环境中免疫细胞组成的极大兴趣。已经开发了几种方法来使用来自大体肿瘤样品的基因表达数据估算免疫细胞组成。但是，这些方法的灵活性不足以处理基因表达数据的异常模式，例如，纯化的参考样品与肿瘤样品中这种细胞类型之间的细胞类型特异性基因表达不一致。在本文中，我们提出了一种用于表达反卷积的新型统计模型，称为ICED-T（肿瘤组织中的免疫细胞反卷积），该模型通过对数正态分布进行基因表达对基因表达进行建模，该分布适用于微阵列和RNA-seq数据。 ICED-T自动确定其表达与反卷积模型不一致的异常基因，并且对细胞类型丰度估计的贡献下降。我们在模拟研究和几个实际数据分析中评估了ICED-T与现有方法的性能。与这些竞争方法相比，冰茶表现出可比性或优越的性能。 ICED-T应用这些方法评估免疫疗法反应与免疫细胞组成之间的关系，能够识别其竞争对手错过的重要关联。
Immunotherapies have achieved phenomenal success in the treatment of cancer and promise even more breakthroughs in the near future. The need to understand the underlying mechanisms of immunotherapies and to develop precision immunotherapy regimens has spurred great interest in characterizing immune cell composition within the tumor microenvironment. Several methods have been developed to estimate immune cell composition using gene expression data from bulk tumor samples. However, these methods are not flexible enough to handle aberrant patterns of gene expression data, e.g., inconsistent cell type-specific gene expression between purified reference samples and this cell type in tumor samples. In this paper, we present a novel statistical model for expression deconvolution called ICeD-T (Immune Cell Deconvolution in Tumor tissues), which models gene expression by a log-normal distribution that is appropriate for both microarray and RNA-seq data. ICeD-T automatically identifies aberrant genes whose expressions are inconsistent with the deconvolution model and down-weights their contributions to cell type abundance estimates. We evaluated the performance of ICeD-T versus existing methods in simulation studies and several real data analyses. ICeD-T displayed comparable or superior performance to these competing methods. Applying these methods to assess the relationship between immunotherapy response and immune cell composition, ICeD-T is able to identify significant associations that are missed by its competitors.
来自两个条件 48 次重复实验的 RNA-seq 数据的统计模型
DOI：
10.48550/arxiv.1505.00588
发表时间：
2015
期刊：
--
影响因子：
--
作者：
Gierlinski M
通讯作者：
Gierlinski M
影响因子：
32.4
作者：
Bindea, Gabriela;Mlecnik, Bernhard;Galon, Jerome
通讯作者：
Galon, Jerome