Group of liver cancer prognostic markers and application thereof

Abstract

The invention discloses a gene set for predicting prognosis of liver cancer patients and targeting treatment of the liver cancer. As enough biomarkers to predict prognosis of a liver cancer patient are lacked in the prior art, especially for a patient with an advanced liver cancer, traditional treatment methods such as liver transplantation, surgical hepatic resection, early radio frequency treatment and the like have limitations, the exploration of the novel biomarker is crucial to the treatment target of the liver cancer. Genes related to liver cancer prognosis in a G2M checkpoint gene set are further screened out through COX survival analysis, a liver cancer patient prognosis influencing model is constructed through multi-factor COX survival analysis, the accuracy and the specificity ofthe model are verified through a K-M plot curve, an ROC curve and the survival time and the survival state of the patient, and therefore, the prediction model has important significance in prognosisand targeted therapy of the liver cancer patient.

Description

[0001] field of invention [0002] The invention belongs to the field of biomedicine, relates to a liver cancer prognostic marker and its application, and specifically relates to a group of mRNAs related to a new cell cycle G2M checkpoint, and the gene set can be used as a liver cancer prognostic marker. Background technique [0003] Liver cancer is one of the deadliest cancers in the world. According to statistics from 2003 to 2018, the mortality rate of liver cancer among all cancers has risen sharply. The therapeutic effect of HCC largely depends on the time interval from diagnosis to treatment, especially for patients with early-stage HCC. Although liver transplantation, surgical hepatectomy, early radiofrequency therapy and other treatment methods have been improved, however, more than 70% of liver cancer patients are diagnosed at an advanced stage, which limits the application of traditional therapies. [0004] Genome instability is an important hallmark of cancer and ...

AI Technical Summary

Problems solved by technology

However, there is currently a lack of systematic studies on G2 / M checkpoint-related genes in liver cancer

[0005] In view of the lack of sufficient biomarkers in the existing technology to predict the prognosis of liver cancer patients, especially for patients with advanced liver cancer, traditional treatment methods such as liver transplantation, surgical liver resection, and early radiofrequency therapy have been limited

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