Background Protein S-palmitoylation is a reversible posttranslational modification widely involved in tumor progression. Nevertheless, the function of palmitoylation metabolism in prognosis and tumor microenvironment characteristics in liver hepatocellular carcinoma (LIHC) patients is not fully understood. Methods mRNA and clinical data of LIHC patients were obtained from the TCGA and ICGC databases. Consensus clustering was used to construct palmitoylation metabolism-related clusters. Univariate Cox and Lasso regression analyses were employed to establish a palmitoylation metabolism-related signature (PMS). ssGSEA was applied to evaluate the immune cell score in each LIHC sample. Functional enrichments were accessed through GO, KEGG and GSVA. Drug sensitivity data were downloaded from the GDSC database. Results Three palmitoylation metabolism-related clusters with different prognostic and immune infiltration characteristics were constructed in LIHC. We identified PMS with distinct survival, clinical, and tumor immune microenvironment characteristics. The high PMS group had a poorer prognosis, higher infiltration of immunosuppressive cells and higher expression of immune checkpoints. ZDHHC20 exerted a tumor-promoting role in LIHC and was significantly associated with immunosuppressive cells and immunosuppressive checkpoints. Additionally, in HepG-2 and SMCC-7721 cells, si-ZDHHC20 boosted apoptosis but decreased proliferation and migration when compared to si-NC. Conclusion Our research revealed that PMS may accurately predict the prognosis and immune characteristics of LIHC patients. ZDHHC20 has significant clinical and immune relevance in LIHC and may contribute to the formulation of new targets for LIHC immunotherapy.
Home>Identification and validation of palmitoylation metabolism-related signature for liver hepatocellular carcinoma
Identification and validation of palmitoylation metabolism-related signature for liver hepatocellular carcinoma
- Impact factors: 2.65
- Publication: Evidence-based Complementary and Alternative Medicine
- Author:Xingcai Zhang, Wei Zhang, Xianhai Chen, Yuli Cai
- DOI citation-doi:10.1155/2023/1973163
- Date:2023-01-24T00:00:00.000Z