Establishing method and application for multi-gene liver cancer prognosis grading system

Abstract

The invention discloses an establishing method and application for a multi-gene liver cancer prognosis grading system. The system can be used to predict survival time and recurrence probability of patients with liver cancer after surgery, regardless of the ages and tumor sizes of the patients. Samples come from a total of 378 clinical liver cancer surgery patients in a hospital affiliated to Zhejiang University School of Medicine in 2012-2018, after strict quality control of the samples, through a multi-gene quantitative real time polymerase chain reaction (qRT-PCR), the correlation between each gene and the survival time is further analyzed, and finally high-risk genes related to prognosis of the clinical liver cancer surgery patients are screened to establish the prognosis grading system. The method has the following beneficial effects: the prognosis grading system capable of predicting the survival time and recurrence probability of the clinical liver cancer patients after the surgery is established, regardless of the ages and tumor sizes of the patients, and the system can be used for postoperative survival time assessment of the liver cancer surgery patients, and assist in formulation of a postoperative treatment plan for the patients.

Description

technical field [0001] The invention relates to the field of prognosis grading system for patients undergoing clinical liver cancer surgery, and mainly relates to a method for establishing a polygenic liver cancer prognosis grading system and its application. Background technique [0002] The number of patients with liver cancer in my country accounts for more than half of the world. Liver cancer has a high degree of malignancy and poor prognosis. The current 5-year survival rate of liver cancer is only 16.8%. [1,2] . Surgical resection remains the mainstay of treatment for liver cancer [3] . There is significant tumor heterogeneity in different liver cancer patients, so whether surgical resection can benefit patients is still unknown. A series of grading systems that can be used to predict individual recurrence and prognosis risk have been discovered so far. Most of them are consistent with the clinical characteristics of liver cancer, such as Liver function grade, AFP, ...

AI Technical Summary

Problems solved by technology

There is significant tumor heterogeneity in different liver cancer patients, so whether surgical resection can benefit patients is still unknown. A series of grading systems that can be used to predict individual recurrence and prognosis risk have been discovered so far. Most of them are consistent with the clinical characteristics of liver cancer, such as Liver function grade, AFP, tumor size, and location are related, but due to the complexity of individual patient information and human errors in follow-up data, the reliability of the prediction grading system is greatly reduced

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