Inference of infiltrating cells in the tumor microenvironment

To evaluate the abundance of TIICs in the CRC samples, we employed the LM22 gene signature and the CIBERSORT algorithm, which could sensitively and specifically discriminate 22 human immune cell phenotypes (B cells, T cells, NK cells, macrophages, DCs, and myeloid subsets).⁶⁹ CIBERSORT is a deconvolution algorithm based on support vector regression, which uses a set of reference gene-expression values corresponding to a minimal representation for each cell type to infer cell type proportions in data from bulk tumor samples with mixed cell types. The CIBERSORT algorithm can, in particular, be used to derive the proportion of cells in complex microarray data.¹⁷ Using Monte Carlo sampling, CIBERSORT calculates the empirical p value of the deconvolution to indicate the accuracy of the results, while a p value of <0.05 indicates that the inferred cell composition is highly reliable.²⁹ Therefore, we only retained CRC samples with CIBERSORT p values <0.05 for subsequent analysis.