Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Department of Biochemistry and Molecular Biology, Harbin Medical University, Harbin, China.
Front Immunol. 2021 May 14;12:672031. doi: 10.3389/fimmu.2021.672031. eCollection 2021.
Tumor-infiltrating immune cells are important components in the tumor microenvironment (TME) and different types of these cells exert different effects on tumor development and progression; these effects depend upon the type of cancer involved. Several methods have been developed for estimating the proportion of immune cells using bulk transcriptome data. However, there is a distinct lack of methods that are capable of predicting the immune contexture in specific types of cancer. Furthermore, the existing methods are based on absolute gene expression and are susceptible to experimental batch effects, thus resulting in incomparability across different datasets. In this study, we considered two common neoplasms as examples (colorectal cancer [CRC] and melanoma) and introduced the Tumor-infiltrating Immune Cell Proportion Estimator (TICPE), a cancer-specific qualitative method for estimating the proportion of tumor-infiltrating immune cells. The TICPE was based on the relative expression orderings (REOs) of gene pairs within a sample and is notably insensitive to batch effects. Performance evaluation using public expression data with mRNA mixtures, single-cell RNA-Seq (scRNA-Seq) data, immunohistochemistry data, and simulated bulk RNA-seq samples, indicated that the TICPE can estimate the proportion of immune cells with levels of accuracy that are clearly superior to other methods. Furthermore, we showed that the TICPE could effectively detect prognostic signals in patients with tumors and changes in the fractions of immune cells during immunotherapy in melanoma. In conclusion, our work presented a unique novel method, TICPE, to estimate the proportion of immune cells in specific cancer types and explore the effect of the infiltration of immune cells on the efficacy of immunotherapy and the prognosis of cancer. The source code for TICPE is available at https://github.com/huitingxiao/TICPE.
肿瘤浸润免疫细胞是肿瘤微环境（TME）的重要组成部分，不同类型的免疫细胞对肿瘤的发展和进展有不同的影响；这些影响取决于所涉及的癌症类型。已经开发了几种使用批量转录组数据估计免疫细胞比例的方法。然而，目前缺乏能够预测特定类型癌症免疫结构的方法。此外，现有的方法基于绝对基因表达，容易受到实验批次效应的影响，因此导致不同数据集之间的不可比性。在本研究中，我们以两种常见的肿瘤（结直肠癌[CRC]和黑色素瘤）为例，并引入了肿瘤浸润免疫细胞比例估计器（TICPE），这是一种用于估计肿瘤浸润免疫细胞比例的癌症特异性定性方法。TICPE 基于样本内基因对的相对表达顺序（REO），并且对批次效应不敏感。使用公共表达数据与 mRNA 混合物、单细胞 RNA-Seq（scRNA-Seq）数据、免疫组织化学数据和模拟批量 RNA-seq 样本进行性能评估表明，TICPE 可以以明显优于其他方法的准确度来估计免疫细胞的比例。此外，我们表明 TICPE 可以有效地检测肿瘤患者的预后信号以及黑色素瘤免疫治疗过程中免疫细胞分数的变化。总之，我们的工作提出了一种独特的新方法 TICPE，用于估计特定癌症类型中免疫细胞的比例，并探索免疫细胞浸润对免疫治疗效果和癌症预后的影响。TICPE 的源代码可在 https://github.com/huitingxiao/TICPE 上获得。
