Abstract
BACKGROUND: Given the differential expression and biological functions of protein arginine methylation (PAM) regulators in lung adenocarcinoma (LUAD), it may be of great value in the diagnosis, prognosis, and treatment of LUAD. However, the expression and function of PAM regulators in LUAD and its relationship with prognosis are unclear. METHODS: 8 datasets including 1798 LUAD patients were selected. During the bioinformatic study in LUAD, we performed (i) consensus clustering to identify clusters based on 9 PAM regulators related expression profile data, (ii) to identify hub genes between the 2 clusters, (iii) principal component analysis to construct a PAM.score based on above genes, and (iv) evaluation of the effect of PAM.score on the deconstruction of tumor microenvironment and guidance of immunotherapy. RESULTS: We identified two different clusters and a robust and clinically practicable prognostic scoring system. Meanwhile, a higher PAM.score subgroup showed poorer prognosis, and was validated by multiple cohorts. Its prognostic effect was validated by ROC (Receiver operating characteristic curve) curve and found to have a relatively good prediction efficacy. High PAM.score group exhibited lower immune score, which associated with an immunosuppressive microenvironment in LUAD. Finally, patients exhibiting a lower PAM.score presented noteworthy therapeutic benefits and clinical advantages. CONCLUSION: Our PAM.score model can help clinicians to select personalized therapy for LUAD patients, and PAM.score may act a part in the development of LUAD.