Low SLCO4C1 expression serves as an independent prognostic predictor in lung cancer

Abstract

Lung cancer is a significant global health concern, accounting for 18.4 percent of all cancer-related deaths, imposing substantial social and economic burdens. We explored SLCO4C1 as a potential prognostic marker in lung cancer. Analyzing The Cancer Genome Atlas (TCGA) data, we assessed SLCO4C1 expression using boxplot analyses. Chi-square and Fisher's test evaluated associations with clinicopathological features, and diagnostic capacity was determined the receiver-operating characteristic (ROC) curve analysis. Kaplan-Meier survival curves assessed survival differences based on SLCO4C1 levels. Cox regression models and subgroup analyses examined prognostic factors. Our findings reveal significant downregulation of SLCO4C1 in lung cancer tissues, with correlations to patient gender, histological type, and T classification. ROC analysis indicated moderate diagnostic potential. Survival analysis demonstrated lower overall and relapse-free survival rates in patients with low SLCO4C1 expression. Univariate and multivariate Cox regression analyses suggested SLCO4C1 as an independent prognostic predictor for lung cancer. In conclusion, low SLCO4C1 expression serves as an independent prognostic biomarker in lung cancer, offering promise for prognostic and therapeutic applications.