In addition to tumor cells, a large number of immune cells are found in the tumor microenvironment (TME) of cancer patients. Tumor-infiltrating immune cells play an important role in tumor progression and patient outcome. We improved the relative proportion estimation algorithm of immune cells based on RNA-seq gene expression profiling and solved the multiple linear regression model by support vector regression ([Formula: see text]-SVR). These steps resulted in increased robustness of the algorithm and more accurate calculation of the relative proportion of different immune cells in cancer tissues. This method was applied to the analysis of infiltrating immune cells based on 41 pairs of colorectal cancer tissues and normal solid tissues. Specifically, we compared the relative fractions of six types of immune cells in colorectal cancer tissues to those found in normal solid tissue samples. We found that tumor tissues contained a higher proportion of CD8 T cells and neutrophils, while B cells and monocytes were relatively low. Our pipeline for calculating immune cell proportion using gene expression profile data can be freely accessed from GitHub at https://github.com/gutmicrobes/EICS.git.

中文翻译：

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基于支持向量回归的批量肿瘤基因表达谱计算免疫细胞比例

除了肿瘤细胞，在癌症患者的肿瘤微环境（TME）中还发现了大量的免疫细胞。肿瘤浸润性免疫细胞在肿瘤进展和患者预后中起重要作用。我们改进了基于RNA-seq基因表达谱的免疫细胞相对比例估计算法，并通过支持向量回归（[公式：见正文]-SVR）求解了多元线性回归模型。这些步骤提高了算法的稳健性，并更准确地计算了癌组织中不同免疫细胞的相对比例。该方法应用于基于41对结直肠癌组织和正常实体组织的浸润性免疫细胞分析。具体来说，我们将结直肠癌组织中六种免疫细胞的相对比例与正常实体组织样本中发现的比例进行了比较。我们发现肿瘤组织含有较高比例的 CD8 T 细胞和中性粒细胞，而 B 细胞和单核细胞相对较低。我们使用基因表达谱数据计算免疫细胞比例的管道可以从 GitHub 上免费访问，网址为 https://github.com/gutmicrobes/EICS.git。