Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.] · 2025
Identification of A-to-I RNA editing profiles and their clinical relevance in pancreatic neuroendocrine neoplasms.
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Xu Yanling, He Na, Dai Guanqun, Zhou Ting, Ye Mujie, Tang Qiyun
Аннотация
BACKGROUND: Pancreatic neuroendocrine neoplasms (pNENs) exhibit significant clinical and molecular heterogeneity, complicating prognosis and treatment. This study aimed to characterize A-to-I RNA editing profiles in pNENs and evaluate their clinical relevance.
METHODS: Four RNA-seq datasets (EGAS00001005024, EGAS00001001732, GSE149395, GSE118014) were included in this study. A-to-I editing sites were identified using the GATK pipeline, filtered via REDIportal, and quantified by the Alu editing index (AEI). LASSO Cox regression was used to derive prognostic risk score from site-specific editing levels. A nomogram integrating editing signatures with TNM stage and G grade was developed and validated for survival prediction.
RESULTS: We identified 19,811 A-to-I editing sites, predominantly in noncoding regions (78.1 % intronic, 7.9 % intergenic) and Alu repeats (79.3 %). AEI was elevated in lymph node metastasis (p < 0.05) but not correlated with ADAR expression. Three key editing sites stratified patients into high- and low-risk groups, with significantly worse survival for high-risk patients (p < 0.001). The survival nomogram integrating RNA-editing signatures showed an area under the ROC curve (AUC)of 0.87 (95 % CI: 0.71-0.98), 0.87 (95 % CI: 0.74-0.97), and 0.92 (95 % CI: 0.77-1.13) at 3, 5, and 10 years in the training set, and 0.74 (95 % CI: 0.55-0.92), 0.75 (95 % CI: 0.53-0.93), and 0.79 (95 % CI: 0.60-1.00) at 3, 5, and 10 years in the validation set, demonstrating superior efficacy to conventional predictive indicators.
CONCLUSIONS: This study described the landscape of A-to-I RNA editing in pNENs and revealed its relationship with key clinical features including prognosis. The RNA editing-based nomogram provided a novel tool for prognostic prediction, highlighting the potential of RNA editing as a promising biomarker for risk assessment in pNEN patients.
METHODS: Four RNA-seq datasets (EGAS00001005024, EGAS00001001732, GSE149395, GSE118014) were included in this study. A-to-I editing sites were identified using the GATK pipeline, filtered via REDIportal, and quantified by the Alu editing index (AEI). LASSO Cox regression was used to derive prognostic risk score from site-specific editing levels. A nomogram integrating editing signatures with TNM stage and G grade was developed and validated for survival prediction.
RESULTS: We identified 19,811 A-to-I editing sites, predominantly in noncoding regions (78.1 % intronic, 7.9 % intergenic) and Alu repeats (79.3 %). AEI was elevated in lymph node metastasis (p < 0.05) but not correlated with ADAR expression. Three key editing sites stratified patients into high- and low-risk groups, with significantly worse survival for high-risk patients (p < 0.001). The survival nomogram integrating RNA-editing signatures showed an area under the ROC curve (AUC)of 0.87 (95 % CI: 0.71-0.98), 0.87 (95 % CI: 0.74-0.97), and 0.92 (95 % CI: 0.77-1.13) at 3, 5, and 10 years in the training set, and 0.74 (95 % CI: 0.55-0.92), 0.75 (95 % CI: 0.53-0.93), and 0.79 (95 % CI: 0.60-1.00) at 3, 5, and 10 years in the validation set, demonstrating superior efficacy to conventional predictive indicators.
CONCLUSIONS: This study described the landscape of A-to-I RNA editing in pNENs and revealed its relationship with key clinical features including prognosis. The RNA editing-based nomogram provided a novel tool for prognostic prediction, highlighting the potential of RNA editing as a promising biomarker for risk assessment in pNEN patients.