Prognostic effect of SERINC1 expression in lung cancer and its relationship with tumor immune infiltration
Objective This study aims to explore the role of SERINC1(serotonin transporter 1)in the prognosis of lung cancer.Methods Single-cell RNA sequencing(scRNA)data of lung cancer were download-ed from the GEO database and genes significantly expressed in epithelial cells were extracted.Concurrently,TCGA data were downloaded from the Xena database and subjected to differential analysis.The intersection of significantly expressed genes from both sources identified differential genes in epithelial cells.Intersection of multiple machine learning algorithms,including Lasso,Random Forest,GBM,and XGBoost,yielded six in-tersecting genes:FAM107A,SERINC1,MDK,GGCT,AVL9,and FEZ1.As the effect of SERINC1 in lung cancer has not been studied,a series of clinical correlation analyses were conducted on SERINC1,including di-agnostic ROC analysis,expression analysis,enrichment analysis,survival analysis,protein expression,pro-tein-protein interaction analysis,and immune infiltration analysis.Results The target gene SERINC1 was i-dentified through single-cell sequencing and machine learning.The AUC value of ROC analysis for SERINC1 was as high as 0.972,indicating a high diagnostic efficacy.The Kaplan-Meier curve indicated that patients with high SERINC1 expression had significantly better prognosis than those with low expression,with HR values of 0.71(95％CI:0.63～0.81)and 0.48(95％CI:0.39～0.61),suggesting that higher gene expression is asso-ciated with better prognosis.Immune infiltration analysis revealed that SERINC1 is related to various immune cells and is associated with marker gene-sets of various T cells.Conclusion SERINC1 is a promising prog-nostic marker for lung cancer and is related to immune infiltration.
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