Identification and Validation of a lipid metabolism-Immune-Based Prognostic Multiomics Signature for Oral Squamous Cell Carcinoma

Abstract

Abstract Oral squamous cell carcinoma (OSCC) is one of the common oral cancers. This research is designed to establish a lipid metabolism-Immune-Based Prognostic Multiomics signature for OSCC and clarify the immune function, immune characteristics, the advantages of immune therapy, and pan-cancer analysis in the model-defined subgroups of OSCC. Based on lipid-metabolism-related genes and ESTIMATEScore, clustering analysis was applied to divide 373 OSCC samples into 21 high-immunity-lipid metabolism specimens and 172 low-immunity-lipid metabolism specimens. Through R packages “limma”, differential expression of mRNA, micro-RNA and DNA Methylation were identified. Then, the least absolute shrinkage and selection operator (LASSO) was applied to construct an 8-Multiomics Signature for predicting recurrence after surgery, and the risk model was validated in the TCGA-test and TCGA-train dataset. Afterward, the immune characteristics, immune function, and the advantages of ICI therapy in 8-Multiomics Signature subgroups were analyzed. Finally, the Pan-cancer analysis of eight symbols in the risk model was analyzed. In conclusion, 8-Multiomics Signature is a promising biomarker to distinguish the prognosis, the immune characteristics, and the immune benefit from immune therapy in OSCC.