Abstract
BACKGROUND: Several studies have revealed that N6-methyladenosine (m6A) regulation is involved in various biological processes and cancer progression. Nevertheless, the potential effects of m6A modifications in the tumor immune microenvironment (TIME) and on immune regulation in pancreatic adenocarcinoma (PAAD) remains unclear. METHODS: A consensus clustering algorithm was used to identify different m6A modification patterns and construct an m6A-associated gene signature based on 23 m6A regulators in PAAD. The CIBERSORT and ssGSEA algorithms were used to estimate the components of the immune cells in each sample. The PCA algorithm was used to develop the m6Ascore system for the evaluation of m6A modification patterns in each sample. RESULTS: Two m6A modification patterns with different biological properties and prognoses were identified in 176 PAAD patient samples. The features of TIME between the two patterns were similar, with two definite immune phenotypes: immune-inflamed and immune-excluded. Based on the m6A phenotype-associated signature genes, we constructed an m6Ascore system to investigate the m6A modification pattern of each sample, profile the dissection of physiological processes, immune infiltration, clinical prognosis, immunotherapy, and genetic variation. Patients with low m6Ascore scores had better clinical outcomes, enhanced immune infiltration, and lower expression of immunotherapeutic drug targets, such as CD274 and PDCD1LG2. Further research indicated that the m6Ascore and tumor mutation burden were significantly correlated, and patients with low m6Ascore had higher mutation rates in SMAD4 and TTN. Moreover, TNFRSF21 was significantly upregulated in PAAD tumor tissues and cell lines. Lower expression of TNFRSF21 had a prominent advantage in survival and was correlated with a low level of immune infiltration. PAAD samples with different TNFRSF21 expression levels showed significantly distinct sensitivities to chemotherapeutic agents. CONCLUSIONS: This study revealed that m6A modification patterns could play an important role in the diversity and complexity of TIME, and the m6Ascore system could serve as an independent and powerful prognostic biomarker and is latently related to PAAD immunotherapies. Quantitative determination of m6A modification patterns in individual patients will be instrumental in mapping the TIME landscape and further optimizing precision immunotherapy.