Construction and validation of prognostic risk model for hepatocellular carcinoma based on biological analysis of palmitoyl-associated enzyme long-chain non-coding RNA

doi:10.3969/j.issn.1674-8115.2023.06.011

Abstract

Abstract:

Objective ·To explore the effect of screening the expression of long non-coding RNA (lncRNA) related to palmitoylation on prognosis of liver cancer based on The Cancer Genome Atlas (TCGA) database and construct a risk prediction model in liver cancer. Methods ·The sequencing data and the corresponding clinical information of 374 liver cancer tissues and 50 normal tissue samples were downloaded from TCGA database. The differential zinc finger aspartate-histidine-histidine-cysteine domain (ZDHHC) between liver cancer tissues and normal tissues was used to construct the expression profile of lncRNA related to ZDHHC. Furthermore, the prediction model was constructed by LASSO regression algorithm and the validity of the model prediction was verified to analyze the relationship between high-risk and low-risk groups and immune function and to predict the response to immunotherapy. Results ·There were 20 differentially expressed ZDHHCs in hepatocellular carcinoma, among which 656 lncRNAs were correlated with differential ZDHHCs (all P<0.05). Univariate COX analysis showed that 22 lncRNAs were associated with the prognosis of hepatocellular carcinoma (HR 1.47?13.05, all P<0.05), and LASSO regression analysis included 3 lncRNAs to construct a risk model. The risk score=0.662 6×AC026356.1+0.213 9×AC026401.3+0.405 6×POLH-AS1. In the model, the overall survival (OS) and progression-free survival (PFS) of patients in the high-risk group were significantly lower than those in the low-risk group (all P<0.05). Multivariate COX regression analysis showed that the model as a risk factor was an independent factor affecting survival (HR=1.375, 95%CI 1.208?1.566). In the risk model, there were significant differences between high-risk and low-risk immune function pathways, and the response level of high-risk patients to immunotherapy was lower (P<0.05). Conclusion ·The use of a risk model based on palm acylation related lncRNA expression can independently predict the survival period of liver cancer patients, providing reference for patients receiving immunotherapy.

Key words: hepatocellular carcinoma (HCC), long non-coding RNA (lncRNA), palmitoylation, risk model, immune therapy

CLC Number:

R730.7

YU Li, SU Xiandu, ZHANG Min, LI Yahui, WANG Le. Construction and validation of prognostic risk model for hepatocellular carcinoma based on biological analysis of palmitoyl-associated enzyme long-chain non-coding RNA[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2023, 43(6): 747-754.

Figures/Tables 5

Fig 1 Univariate analysis of associated lncRNAs affecting prognosis in patients with hepatocellular carcinoma

Fig 2 Construction of a risk model for liver cancer patients based on ZDHHC-related lncRNA

Fig 3 Single factor and multiple regression analysis

Fig 4 Column chart creation and prognostic prediction calibration

Fig 5 Analysis of pathways related to immune response in high-risk and low-risk groups

TrendMD

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