Bioinformatic analysis reveals cancer-associated lysine gene signatures as a poor prognostic factor and potential therapeutic target in esophageal squamous cell carcinoma

Abstract

Abstract Background:Esophageal squamous cell carcinoma is one of the most common malignant tumors of digestive tract. Due to the hidden onset of esophageal cancer, most patients with esophageal cancer have developed to the middle and late stages when diagnosed. Therefore, treatment failure, recurrence and metastasis are one of the main reasons for the high mortality of patients with esophageal cancer.Lysine functions as a biosynthetic molecule, energy source and antioxidant, but little is known about its pathological role in cancer.In this study, we aim to identify the cancer-associated lysine genes, which may increase the therapeutic success in esophageal squamous cell carcinoma. Methods: We downloaded the original expression data of esophageal squamous cell carcinoma mRNA from TCGA for limma differential expression analysis, and extracted lysine-related genes from GeneCards database for the crossover of differential genes. Then,We quantified lysine levels by ssGSEA and analyzed the differences in metabolic pathways between high and low lysine levels. Next,we used random survival forest machine learning algorithm for survival analysis to determine the genetic characteristics of lysine-related poor prognosis of esophageal cancer. Further analysis of immune cell infiltration and drug sensitivity were performed. Finally, we downloaded GSE196756 sample data from GEO database for single cell analysis to verify key lysine-related genes. Results: Our study revealed 84 lysine-related diferentially expressed genes (DEGs) in esophageal squamous cell carcinoma. Functional enrichment analysis showed that these lysine-related genes significantly enriched lysine-regulated pathways such as histone modification,histone lysine methylation and lysine degradation pathways.The ssGSEA analysis quantified lysine levels and showed that patients with high lysine metabolism may show enhanced activity in amino acid metabolism.Random survival forest analysis found that UBE4A and APOC1 were related to the survival of esophageal squamous cell carcinoma.Moreover, the the two lysine-related DGEs was an independent prognostic factor and a nomogram consisting of the two lysine-related DGEs and various clinical factors accurately predicted 1and 2 year survival time of esophageal squamous cell carcinoma patients.The search on drug databases revealed AICAR,BI.D1870, MS.275 and Lapatinib as the potential drugs for further investigation. Immunomicroenvironment infiltration analysis showed that UBE4A was positively correlated with T cells CD4 memory resting and negatively correlated with B cells memory. APOC1 was positively correlated with Macrophages M2, T cells CD4 memory activated and T cells CD8,and was negatively correlated with Dendritic cells activated, T cells CD4 memory resting and Eosinophils.We further performed single-cell analysis, and 21 subtypes were obtained by tSNE algorithm. Then, the R package SingleR was used to annotate each cluster. All clusters are annotated to T_cells, NK_cell, B_cell, Neutrophils, Monocyte, Smooth_muscle_cells, Epithelial_cells, Endothelial_cells, Tissue_s tem_cells and Neurons. Conclusions:Our study demonstrates the central role of lysine-related gene regulation in esophageal squamous cell carcinoma. The lysine-related genes we discovered in this study can be used as a predictive tool for poor prognosis of patients with esophageal squamous cell carcinoma, elucidate the possible mechanism of the poor prognosis caused by lysine-related genes, search for more effective molecular targeted drugs, and improve the success rate of treatment of esophageal squamous cell carcinoma.