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. 2023 Oct 9:10:1749-1765.
doi: 10.2147/JHC.S417407. eCollection 2023.

Identification of a Novel Prognostic Signature Based on N-Linked Glycosylation and Its Correlation with Immunotherapy Response in Hepatocellular Carcinoma

Shusheng Lin #  1   2 , Yi Cao #  3 , Ke Zhu #  1   2   4 , Caini Yang  1   2 , Xiangping Zhu  2 , Honghua Zhang  1   2 , Rui Zhang  1   2
Affiliations

Identification of a Novel Prognostic Signature Based on N-Linked Glycosylation and Its Correlation with Immunotherapy Response in Hepatocellular Carcinoma

Shusheng Lin et al. J Hepatocell Carcinoma. .

Abstract

Background: The complex tumor microenvironment of hepatocellular carcinoma (HCC) has led to a low response to immune checkpoints inhibitors (ICIs) and a poor prognosis. PD-L1, as one of the indications for ICIs, is rich in glycosylation modifications, which result in untimely ICIs. Our study constructed a prognostic model based on N-linked glycosylation related genes for predicting the prognosis and the response to ICIs.

Methods: The list of N-linked glycosylation related genes is from the AmiGO2 database. The patients in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts were enrolled. The Cox regression was performed to develop a prognostic model and patients were divided into a low- and high-risk subgroups. The role of signature in HCC was well investigated by prognostic analysis, gene set enrichment analysis, and immune infiltration analysis. 21 recurrent HCC patients who received postoperative adjuvant ICIs were recruited to evaluate the relationship between immunotherapy response and the signature. In vitro studies were conducted to investigate the oncogenic effects of DDOST, STT3A and TMEM165 in HCC.

Results: 59 N-linked glycosylation related differentially expressed genes were screened from HCC and normal tissues in the TCGA cohort. The prognostic model was developed with DDOST, STT3A and TMEM165. The risk score could be an independent prognostic factor. Patients in the high-risk subgroup showed a worse prognosis than patients in the low-risk one. ssGSEA showed that patients in the low-risk subgroup tended to be in the immune-activated state, with higher levels of B cell and macrophage cell infiltrations and lower levels of regulatory T cell (Treg) infiltrations in both TCGC and GEO cohorts. Immunohistochemistry studies showed that DDOST, STT3A and TMEM165 are highly expressed in tumor tissues and patients with a high-risk score correlated with poor progression free survival and worse immunotherapeutic response. Furthermore, the proliferation of HCC cells was reduced after the knockdown of DDOST, as well as upon the knockdown of STT3A and TMEM165.

Conclusion: In this study, we establish that the risk model based on N-linked glycosylation related genes could efficiently predict the prognosis and tumor microenvironment immune state of HCC patients, and the risk score could serve as a novel indicator of immunotherapy.

Keywords: HCC; N-linked glycosylation; immune infiltration; immunotherapy; prognostic signature.

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Conflict of interest statement

The authors declare that they have no conflicts of interest in this work.

Figures

Figure 1
Figure 1
DEGs were identified in normal and tumor tissues to classify HCC patients.
Figure 2
Figure 2
Construction of risk model based on N-linked glycosylation related DEGs in TCGA dataset.
Figure 3
Figure 3
Validation of prognostic model.
Figure 4
Figure 4
Correlation of the HCC subgroups with immune infiltration.
Figure 5
Figure 5
Prognostic models are effective in predicting responses to immunotherapy.
Figure 6
Figure 6
Knockdown of the N-linked glycosylation prognostic model related genes suppresses the proliferation of HCC cell lines.
Figure 7
Figure 7
Flow diagram of this study.
See this image and copyright information in PMC

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