Background
RNA modifications, including adenosine-to-inosine RNA editing, alternative polyadenylation, m1A and m6A, play a significant role in tumorigenesis and tumor immunity. However, the functions of RNA modification enzymes (writers) in immunotherapy and tumor microenvironment (TME) remain unknown.
Methods
Nonnegative matrix factorization clustering was applied to identify RNA modification clusters in lung adenocarcinoma, one of the most prevalent subtypes of non-small cell lung cancer (NSCLC). CIBERSORT and ESTIMATE algorithms were performed to depict TME characteristics. Additionally, a scoring system called Writer-Score was established to quantify RNA modification patterns and subsequently predict clinical outcomes. We subsequently used RNA sequencing, targeted DNA sequencing and multiplex immunofluorescence to further evaluate the efficacy of Writer-Score in NSCLC patients receiving neoadjuvant immunotherapy. Findings: We identified three distinct RNA modification clusters and two DEGclusters, which were shown to be strongly associated with a variety of TME features and biological processes. Additionally, the Writer-Score served as an important factor in post-transcriptional events and immunotherapy. The Writer-Score was capable of properly predicting the prognosis of NSCLC patients receiving neoadjuvant PD-1 inhibitor therapy. Interpretation: Our work systematically analyzed four types of RNA modifications and constructed a scoring system to guide neoadjuvant immunotherapy in NSCLC, which highlighted the writers' roles in post-transcriptional events, TME and neoadjuvant immunotherapy. Funding: A full list of funding bodies that supported this study can be found in the Acknowledgements section.