Expression and prognostic value of AIM1L in esophageal squamous cell carcinoma

Abstract

Background: Absent in melanoma 1-like (AIM1L), also known as crystalline beta gamma domain containing 2. The relationship between AIM1L and tumors has not been fully investigated, and the biological function of AIM1L in different tumors is unknown, so we bioinformatically explored a possible relationship between AIM1L and esophageal squamous cell carcinoma (ESCC). Methods: AIM1L mRNA expression was detected by the Gene Expression Omnibus database (GSE20347, GSE161533, and GSE53625), and protein level expression was detected by immunohistochemistry. The correlation between AIM1L expression and clinical pathological characteristics was evaluated by the Wilcoxon signed rank test or chi-square test. Kaplan–Meier analysis and Cox proportional risk regression model were used to determine the prognostic value of AIM1L in ESCC patients and establish and verify a nomogram. Find genes highly related to the expression of AIM1L, conduct GO and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, and conduct GSEA analysis on the gene set. The “CIBERSORT” R package was used to explore the relationship between AIM1L and immune infiltration, and the “OncoPredict” R package was used to explore the relationship between AIM1L and drug sensitivity. Results: Compared with the matched adjacent non-cancer tissues, the expression of AIM1L was down-regulated in ESCC tissues, and correlated with tumor grade. Kaplan–Meier survival analysis and Cox analysis showed that the low expression of AIM1L was related to the poor prognosis of ESCC patients. Enrichment analysis explained the possible function of AIM1L, GSEA determined the highly correlated signal pathway of AIM1L low expression phenotype, immune infiltration analysis determined that AIM1L was related to activated NK cells and macrophage M2, and drug sensitivity analysis determined that the low expression of AIM1L might be related to EGFR targeted drug resistance. Conclusion: AIM1L may be a candidate tumor suppressor gene for ESCC and an independent molecular biomarker for the prognosis of ESCC patients.