Recently, several molecular subtypes with different prognosis have been found in lung adenocarcinoma (LUAD). However, the characteristics of the ferroptosis molecular subtypes and the associated tumor microenvironment (TME) cell infiltration have not been fully studied in LUAD. Using 1160 lung adenocarcinoma samples, we explored the molecular subtypes mediated by ferroptosis-related genes, along with the associated TME cell infiltration. The ferroptosis score was constructed using the least absolute shrinkage and selection operator regression (LASSO) method to quantify the ferroptosis characteristics of a single tumor. Three different molecular subtypes related to ferroptosis, with different prognoses, were identified in LUAD. Analysis of TME cell infiltration revealed immune heterogeneity among the three subtypes. Cluster A was characterized by immunosuppression and was associated with stromal activation. Cluster C was characterized by a large number of immune cells infiltrating the TME, promoting tumor immune response, and it was significantly enriched in immune activation-related signaling pathways. Relatively less infiltration of immune cells was a feature of cluster B. The ferroptosis score can predict tumor subtype, immunity and prognosis. A low ferroptosis score was characterized by immune activation and good prognosis, as seen in the cluster C subtype. Relative immunosuppression and poor prognosis were the characteristics of a high ferroptosis score, as seen in cluster A and B subtypes. At the same time, the anti-PD-1/L1 immunotherapy cohort demonstrated that a low ferroptosis score was associated with higher efficacy of immunotherapy. The ferroptosis score is a promising biomarker that could be of great significance to determine the prognosis, molecular subtypes, TME cell infiltration characteristics and immunotherapy effects in patients with LUAD.

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Background Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death. This study aimed to develop and validate reliable prognostic biomarkers and signature. Methods Differentially expressed genes were identified based on three Gene Expression Omnibus (GEO) datasets. Based on 1052 samples’ data from our cohort, GEO and The Cancer Genome Atlas, we explored the relationship of clinicopathological features and NEIL3 expression to determine clinical effect of NEIL3 in LUAD. Western blotting (22 pairs of tumor and normal tissues), Real-time quantitative PCR (19 pairs of tumor and normal tissues), and immunohistochemical analyses (406-tumor tissues subjected to microarray) were conducted. TIMER and ImmuCellAI analyzed relationship between NEIL3 expression and the abundance of tumor-infiltrating immune cells in LUAD. The co-expressed-gene prognostic signature was established based on the Cox regression analysis. Results This study identified 502 common differentially expressed genes and confirmed that NEIL3 was significantly overexpressed in LUAD samples (P < 0.001). Increased NEIL3 expression was related to advanced stage, larger tumor size and poor overall survival (p < 0.001) in three LUAD cohorts. The proportions of natural T regulatory cells and induced T regulatory cells increased in the high NEIL3 group, whereas those of B cells, Th17 cells and dendritic cells decreased. Gene set enrichment analysis indicated that NEIL3 may activate cell cycle progression and P53 signaling pathway, leading to poor outcomes. We identified nine prognosis-associated hub genes among 370 genes co-expressed with NEIL3. A 10-gene prognostic signature including NEIL3 and nine key co-expressed genes was constructed. Higher risk-score was correlated with more advanced stage, larger tumor size and worse outcome (p < 0.05). Finally, the signature was verified in test cohort (GSE50081) with superior diagnostic accuracy. Conclusions This study suggested that NEIL3 has the potential to be an immune-related therapeutic target and an independent predictor of LUAD prognosis. We also developed a prognostic signature for LUAD with a precise diagnostic accuracy.

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