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Bobin Ning*, Xueguo Wang , Dongming Li and Lu Lu
Backgrounds: Hepatocellular Carcinoma (HCC) is the fourth-ranked malignant tumor with only 18% of 5-year Overall Survival (OS). Currently, the means of invasive detection for HCC patients are still inadequate. M6a methylation has been demonstrated to contribute to tumorigenesis and progression through the regulation of ncRNAs. Therefore, the construction of an asynchronous prediction pattern by m6A-lncRNA regardless of the expressed level is meaningful for HCC patients' diagnosis and potential mechanism study. Methods: We initially identified m6A-lncRNAs through Pearson correlation coefficients. After screening differential m6a-lncRNAs between the cancerous and paracancerous tissues, the lncRNA pairs were formed for further univariate analysis. Incorporate multi-clinical information, we determined 10 pairs of m6A-lncRNA into the prediction model by lasso regression analysis. Next, we determined the optimal cut-off value to distinguish high- and low-risk groups in HCC patients. Finally, we validated the model in terms of survival, clinicopathological characteristics, m6a genes, Tumor Microenvironment (TME), and chemotherapy. Results: Compared with clinical traits such as age, grades, and stages, the model composed of 10 pairs of DEm6A-lncRNA had a better prediction of HCC prognosis in patients. Moreover, it can serve as a risk factor for independent prognosis of HCC patients’ survival status (HR=1.38, p<0.001). Aggressive clinic-pathological characteristics, TME, differences of m6A-regulators, and chemotherapeutics sensitivity were also predictable and separatable according to the pair-model. Conclusion: The research suggests m6a-lncRNA pair-model is critical clinical meaningfulness for clinical prognosis and pathological characteristics, to the TME, and chemotherapeutic effect in HCC.