Published online Sep 26, 2023. doi: 10.12998/wjcc.v11.i27.6383
Peer-review started: June 22, 2023
First decision: July 17, 2023
Revised: August 2, 2023
Accepted: August 23, 2023
Article in press: August 23, 2023
Published online: September 26, 2023
Processing time: 90 Days and 4.1 Hours
Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. With highly invasive biological characteristics and a lack of obvious clinical manifestations, HCC usually has a poor prognosis and ranks fourth in cancer mortality. The aetiology and exact molecular mechanism of primary HCC are still unclear.
To explore genomic characteristics between different grades of HCC.
To select the characteristic genes that are significantly associated with the prognosis of HCC patients and construct a prognosis model of this malignancy.
By comparing gene expression levels of patients with different cancer grades of HCC, we screened out differentially expressed genes associated with tumour grade. By PPI network analysis, we obtained the top 2 protein-protein interaction networks and hub genes from these differentially expressed genes. By using least absolute shrinkage and selection operator Cox regression, 13 prognostic genes were selected for feature extraction, and a prognostic risk model of HCC was established.
The model had significant prognostic ability in HCC. We also analysed the biological functions of these prognostic genes. These prognostic genes and the prognostic model based on these genes can be used in clinical practice.
By comparing the gene profiles of patients with different stages of HCC, we have constructed a prognostic model based on 13 genes. This model has good application value and can be explained clinically.
The component genes of the prognostic model are expected to be candidate targets for liver cancer treatment in future clinical therapy.