Development and validation of a LRP1B mutation-associated prognostic model for hepatocellular carcinoma

Abstract Purpose: To develop a LRP1B gene mutation based prognostic model for hepatocellular carcinoma (HCC) patients risk prediction. Methods: The LRP1B gene mutation rate was calculated from HCC patient samples. Meanwhile, differentially expressed genes according to LRP1B mutant were screened out for prognostic model establishment. Based on this innovative model, HCC patients were categoried into high and low-risk group. The immune status including immune cell infiltration ratio and checkpoints have been explored in two groups. Results: It can be shown here 11 genes demonstrate significant differences according to LRP1B status, which can better predict HCC patient prognosis. The accuracy of the model prediction is evaluated and approved by the AUC value. From the immune cell infiltration ratio analysis, there is a significant difference in the infiltration degree of 7 types of immune cells and 2 immune checkpoints between high and low-risk HCC patients. Meanwhile, LRP1B was tested as a prognostic marker in clinic to predict different stages for HCC with satisfied accurancy. Conclusion: This study has explored a potential prognostic biomarker and developed a novel LRP1B mutation-associated prognostic model for hepatocellular carcinoma, which provides a systematic reference for future better understanding of clinical research.