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Chinese Journal of Lung Diseases(Electronic Edition) ›› 2026, Vol. 19 ›› Issue (05): 779-785. doi: 10.3877/cma.j.issn.1674-6902.2026.05.010

• Original Article • Previous Articles    

Exploring the expression characteristics and prognostic value of SFN in lung adenocarcinoma based on bioinformatics

Yandong Nan†(), Yujuan Li, Miaomiao Liu, Teng Ren   

  1. Department of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Air Force Medical University, Xi′an 710038, China
  • Received:2025-12-23 Online:2026-10-25 Published:2026-11-13
  • Contact: Yandong Nan

Abstract:

Objective

To systematically evaluate the expression characteristics, diagnostic and prognostic value of stratifin in lung adenocarcinoma based on bioinformatics methods, and to analyze its correlation with immune cell infiltration.

Methods

RNAseq data from 538 lung adenocarcinoma tissues and 58 adjacent normal tissues were obtained from the TCGA database, and immunohistochemical data for SFN protein were retrieved from the HPA database. The Kruskal Wallis test and paired sample ttest were used to compare the differential expression of SFN mRNA between tumour and normal tissues. Diagnostic performance was assessed using receiver operating characteristic (ROC) curves. Prognostic value was evaluated by Kaplan-Meier survival analysis and Cox regression analysis. The ssGSEA algorithm and Spearman correlation analysis were employed to assess the correlations between SFN expression and the infiltration levels of 24 immune cell types.

Results

SFN mRNA was significantly overexpressed in lung adenocarcinoma tissues (unpaired comparison P<0.001; paired comparison P<0.001), and the immunohistochemical results from HPA were consistent. SFN expression levels were significantly associated with T stage (P=0.012), N stage (P=0.008), pathological stage (P=0.015), and overall survival (OS)(P=0.021), but not with age, sex, race, smoking status, or treatment outcome (P>0.05). The area under the ROC curve (AUC) was 0.755, indicating moderate diagnostic capability. Kaplan-Meier analysis showed that the high SFN expression group had significantly shorter progressionfree survival (PFS)(P=0.004) and OS (P=0.009) than the low expression group. Multivariate Cox regression identified residual tumour, T stage, N stage, M stage, and primary therapy outcome as independent risk factors (all P<0.05). Immune infiltration analysis revealed that SFN expression was significantly positively correlated with NK cells (R=0.157, P<0.001), immature dendritic cells (iDC, R=0.155, P<0.001), and Th17 cells (R=0.135, P<0.001), while it was significantly negatively correlated with central memory T cells (Tcm, R=0.306, P<0.001) and helper T cells (Th, R=0.250, P<0.001).

Conclusion

SFN is significantly overexpressed in lung adenocarcinoma and shows good diagnostic efficacy. Its high expression is closely associated with poor prognosis and a specific pattern of immune cell infiltration. SFN may participate in lung adenocarcinoma progression through immune regulation and holds promise as a potential target for early diagnosis and personalised treatment.

Key words: Adenocarcinoma of the lung, Stratifin, Bioinformatics, Early diagnosis, Immune cell infiltration

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