Decoding the prognostic landscape of LUAD: the interplay between N-methyladenosine modification and immune microenvironment.

BACKGROUND

To determine the role of N-methyladenosine (mA) modification in the tumor immune microenvironment (TIME), as well as their association with lung adenocarcinoma (LUAD).

METHODS

Consensus clustering was performed to identify the subgroups with distinct immune or mA modification patterns using profiles from TCGA. A risk score model was constructed using least absolute shrinkage and selection operator regression and validated in two independent cohorts and LUAD tissue microarrays. For experimental validation, the regulation of METTL3/mA axis in the expression of candidate genes by RIP-qPCR assay in A549 and H460 cell lines. Co-culture experiments with human T cells were performed to evaluate the impact of METTL3 on the enhancement of anti-tumor immunity through experiments.

RESULTS

We identified 282 mA regulator genes and 955 immune-related genes, selecting seven key genes (SFTPC, CYP24A1, KRT6A, PTTG1, S100P, FAM83A, and ANLN) to develop a risk score model using Lasso regression. High-risk patients, determined by this model, exhibited poorer prognosis, increased immune infiltration, higher tumor mutational burden, more neoantigens, and elevated PD-L1 expression. These findings were validated by two independent databases and LUAD tissue microarrays. METTL3 was found to impact the mRNA expression of these genes, with METTL3 deficiency abolishing these interactions. Inhibition of METTL3 enhanced anti-tumor immunity, T cell activation, exhaustion, and infiltration .

CONCLUSION

This risk score system shows promise for prognostic prediction and the development of personalized treatment strategies for LUAD patients.