Abstract

e21040 Background: Altered lipid metabolism exhibited by cancer cells, this study was conducted to explore the prognostic values of lipid metabolism-related genes and serum lipids for survival in non-small-cell lung cancer (NSCLC) patients. Methods: Differential expression of the lipid metabolism-related genes CD36, LDLR, ACLY, ACSS2, FASN, SCD, HMGCR, and SQLE in cancer tissues were conducted by tumor immune estimation resource (TIMER) analysis. The gene expression profiling interactive analysis (GEPIA) tool was used to confirm the differential gene expression levels of lipid metabolism-related genes in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Using a Kaplan-Meier plotter (K-M plotter), the prognostic value of lipid metabolism-related genes was assessed for LUAD and LUSC, including the hazard ratio (HR), 95% confidence interval (CI), and log-rank P-value. In addition, a retrospective study was conducted on patients with stage IV NSCLC diagnosed in Hubei Cancer Hospital. The optimal cutoff values for serum lipids were determined by X-Tile software. The chi-squared and Fisher’s exact probability tests were used to analyze count data. Survival curves were analyzed using the Kaplan-Meier, and the survival differences were assessed for statistical significance using the log-rank test. The Cox regression model was used to analyze the prognosis value of serum lipids. Data were analyzed using the SPSS 25.0 software, and P < 0.05 was considered statistically significant. Results: TIMER dataset showed that expressions of CD36, LDLR, ACSS2, FASN and SCD were relatively low in both LUAD and LUSC, whereas ACLY exhibited significantly elevated expression. The GEPIA tool identified CD36 and ACSS2 as having downregulated expression in both LUAD and LUSC. The results also indicated that LDLR expression was relatively low in LUAD. Interestingly, we observed that high expression of CD36 had positive impacted on OS in LUAD (P = 0.01, HR = 0.66 (0.49 – 0.91)), while a negative impact in LUSC was exhibited (P = 0.01, HR = 1.43 (1.09 – 1.87)). The results also confirmed the prognostic values of LDLR (LUAD: P = 0.05, HR = 1.34 (0.99 – 1.8); LUSC: P = 0.03, HR = 1.35 (1.03 – 1.77) and ASCC2 (LUAD: P = 0.04, HR = 0.73 (0.53 – 0.99); LUSC: P = 0.05, HR = 0.76 (0.58 – 0.99). According to the results of chi-square test and Fisher’s exact test, ApoA1 was significantly related to gender (P < 0.01), smoking status (P = 0.02), drinking status (P = 0.04), CHOL (P < 0.001), TG (P < 0.01), HDL-C (P < 0.001) and LP(a) (P < 0.001). High ApoA1 was associated with poor OS (ApoA1: 25.2 vs 31.2 months, P = 0.02) in univariate analysis. Multivariate Cox Regression model confirmed that ApoA1 was an independent prognostic factors for OS (P = 0.03, HR = 1.74, 95% CI: 1.07–2.83). Conclusions: These findings suggest that lipid metabolism-related genes and serum lipids can be used as prognostic biomarkers for determining prognosis in NSCLC.

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