Abstract

e15181 Background: Tumor cell’s metabolism has been identified assisting immune evasion in tumor micro environment (TME), and it is very different from that of immune cells. Previous studies mostly focus on bulk or cell lines transcriptome; we aim to find the specific metabolic model of tumor cell based on vast single cell RNA-seq data. Methods: Public transcriptome of 7186 cells (SMART-Seq2) from 33 melanoma tumors in Benjamin’s study were collected from Single Cell Portal of Broad Institute, and metabolic genes were obtained from Human Metabolome Database (HMDB). Raw count data was preprocessed and analyzed using Seurat R package. Statistical analysis and data visualization were all carried out using R software. Results: Metabolic signature genes of malignant cells (Mals), CD8+ T cells, CD4+ T cells, B cells, natural killer (NK) cells, macrophages, cancer associated fibroblasts (CAFs), and endothelial cells (Endos) were extracted using Seurat. Mals, CAFs, Endos and macrophages shared similar metabolism patterns (high-level glycolysis, pyruvate metabolism, purine metabolism and specific proteoglycans profile compared to immune cells, p < 0.01). Glutathione metabolism activity in Mal was higher than that in immune cell, especially GPX1, GPX4 and GSTO1 genes were highly expressed in Mal ( fc > 2, p < 0.01). Compared to immune cells, genes participate in glycolysis, PFKL, ADH5, ENO2, G6PC3, PGM1, ALDH1B1, PFKM, ALDH7A1, GAPDHS, TPI1, PGK1, LDHA, GPI, PKM, LDHB, ENO1, ALDOA and GAPDH were highly expressed in Mals, CAFs and Endos ( fc > 2, p < 0.01). Noteworthily, LGALS1, an inducer of T-cell apoptosis, was highly expressed in Mals and CAF ( fc > 2, p < 0.01). Otherwise, proteoglycans (PGs) in cancer, which contribute to cancer pathogenesis, exhibited high variation from immune cells. Conclusions: We firstly highlight the differential metabolism between tumor and immune cells in TME. Mals, CAFs, endothelial cells and macrophages can assist in evading immune surveillance through reshaping their metabolic patterns at cell level. This study is helpful for exploring new target of metabolic based anti-cancer immunotherapy.

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