Identification of Somatic Mutation-Driven Immune Cells by Integrating Genomic and Transcriptome Data - Jiang, Ying; Zheng, Baotong; Yang, Yang; Li, Xiangmei; Han, Junwei (Frontiers in Cell and Developmental Biology, 2021)
Tumor somatic mutations in protein-coding regions may generate neoantigens which may trigger antitumor immune cell response. Increasing evidence supports that the immune cell response may profoundly influence tumor progression. However, there are no calculated tools to systematically identify the immune cells driven by specific somatic mutations. It is urgent to develop a calculated method to comprehensive detect tumor-infiltrating immune cells driven by the specific somatic mutations in cancer. We developed a novel software package (SMDIC) that enables automated identification of Somatic Mutation-Driven Immune Cell. SMDIC provides a novel pipeline to discover the mutation-specific immune cells by integrating genomic and transcriptome data. The operation modes include inference of the relative abundance matrix of tumor-infiltrating immune cells, detection of differential abundance immune cells with respect to the gene mutation status, conversion of the abundance matrix of significantly dysregulated cells into two binary matrices (one for up-regulated and one for down-regulated cells), identification of somatic mutation-driven immune cells by comparing the gene mutation status with each immune cell in the binary matrices across all samples, and visualization of immune cell abundance of samples in different mutation status for each gene. SMDIC provides a user-friendly tool to identify somatic mutation-specific immune cell response. SMDIC may contribute to understand the mechanisms underlying the anticancer immune response and find targets for cancer immunotherapy. The package is implemented in R and available under GPL-2 license from the CRAN website (https://CRAN.R-project.org/package=SMDIC).