Construction method of unified diagnosis-prognosis-recurrence model for patients with hepatocellular carcinoma

Abstract

The invention discloses a construction method of a unified diagnosis-prognosis-recurrence model for patients with hepatocellular carcinoma. The method comprises the following steps: step 1) collectinggene expression data and DNA methylation data of hepatocellular carcinoma; step 2) analyzing the gene expression data and the DNA methylation data of the hepatocellular carcinoma, and identifying DNAmethylation driver genes in hepatocellular carcinoma; and step 3) establishing a diagnosis-prognosis-recurrence model for the patients with hepatocellular carcinoma through single-factor Cox regression, minimum absolute constriction and selection operator regression analysis and multi-factor Cox regression analysis on the DNA methylation driver genes in the hepatocellular carcinoma. The unified diagnosis-prognosis-recurrence model composed of the three DNA methylation driver genes is found and verified, so a novel research direction is provided for screening of hepatocellular carcinoma biomarkers, and new possibility is provided for individualized treatment of the patients with hepatocellular carcinoma.

Description

technical field [0001] The invention relates to the field of biology, in particular to a method for constructing a unified model for the diagnosis, prognosis and recurrence of hepatocellular carcinoma (HCC). Background technique [0002] Hepatocellular carcinoma (HCC) is the most common type of liver cancer, the third leading cause of cancer-related death, and the leading aggressive malignancy worldwide. Liver cancer is a multistep and complex disease involving a series of genetic and epigenetic alterations, including genomic deletions, amplifications, mutations and / or insertions. Early diagnosis and interventional therapy, as well as the development of therapeutic and surgical approaches, have led to major advances in the treatment of this cancer. However, the vast majority of patients with advanced HCC have a poor prognosis when diagnosed. Therefore, there is an urgent need to better understand the functional pathways and molecular mechanisms of HCC, as well as to develo...

AI Technical Summary

Problems solved by technology

However, most studies mainly focused on methylation or gene expression data, and joint analyzes were not performed

Thus, a comprehensive understanding of the cellular and molecular mechanisms driving HCC is lacking, limiting therapeutic strategies

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