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A novel immunogenic cell death-related genes signature for predicting prognosis, immune landscape and immunotherapy effect in hepatocellular carcinoma

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Abstract

Objective

Immunogenic cell death (ICD) has emerged as a promising strategy to activate the adaptive immune response, modulate the tumor microenvironment (TME) and enhance the efficacy of immune therapy. However, the relationship between ICD and TME reprogramming in hepatocellular carcinoma (HCC) remains poorly understood.

Methods

Transcriptional profiles and clinical spectrum of 486 HCC patients were obtained from TCGA and GEO databases. We utilized consensus clustering analysis to construct two distinct molecular subtypes and established an ICD-based scoring system (named ICD score) via WGCNA and LASSO Cox regression to predict the prognosis of the HCC cohort. Then we employed CIBERSORT and ESTIMATE methods to analyze the immune landscape of ICD score in HCC. Subsequently, the immunophenoscore (IPS) and tumor immune dysfunction and rejection (TIDE) analyses were performed to determine whether the ICD score could influence the immune therapeutic effect. Based on the ICD scoring system, a novel nomogram was generated to provide a numerical probability of HCC patients’ overall survival (OS).

Results

We identified two independent ICD clusters (cluster A/B), and cluster B possessed a worse prognosis and higher immune cell infiltration. Using ICD scoring system, the HCC patients were divided into high- and low-ICD-score groups. Through integrative analyses, the high-ICD cohort owned advanced TNM stage, high pathologic grade and increased suppressive immune cell enrichment. We developed a nomogram containing the ICD score, demonstrating a high predictive accuracy with a C-index of 0.703. We further discovered that PSMD2 and PSMD14 could serve as ICD-associated prognostic biomarkers and therapeutic targets in HCC.

Conclusion

The ICD score exhibits a high degree of reliability for predicting prognosis and may provide valuable guidance for the selection of immunotherapy for HCC patients. This novel scoring system enables the estimation of clinical immunotherapy response for HCC patients, offering new opportunities for personalized immunotherapy.

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Data availability

The data used to support the findings of this study are available from the public databases, including TCGA database (https://gdcportal.nci.nih.gov/) and GEO database (http://www.ncbi.nlm.nih.gov/geo/, containing datasets of GSE76427).

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Funding

This work was supported by the Science Technology Department of Zhejiang Province (2023C03063), Huadong Medicine Joint Funds of the Zhejiang Provincial Natural Science Foundation of China (LHDMD22H310005), the Health Commission of Zhejiang Province (JBZX-202004 and 2023RC013) and National Natural Science Foundation of China Grant (NO. 82073144 and NO. 82202974).

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Author notes

  1. Guangming Xu and Yifan Jiang first two authors contributed equally to this work.

Authors and Affiliations

  1. Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang Province, Hangzhou, 310003, China

    Guangming Xu, Yifan Jiang, Yu Li, Jiangzhen Ge, Xiaofeng Xu, Diyu Chen & Jian Wu

  2. NHC Key Laboratory of Combined Multi-Organ Transplantation, Zhejiang Province, Hangzhou, 310003, China

    Jian Wu

  3. Key Laboratory of the Diagnosis and Treatment of Organ Transplantation, Research Unit of Collaborative Diagnosis and Treatment For Hepatobiliary and Pancreatic Cancer, Chinese Academy of Medical Sciences (2019RU019), Zhejiang Province, Hangzhou, 310003, China

    Jian Wu

  4. Key Laboratory of Organ Transplantation, Research Center for Diagnosis and Treatment of Hepatobiliary Diseases, Zhejiang Province, Hangzhou, 310003, China

    Diyu Chen & Jian Wu

Authors
  1. Guangming Xu
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Contributions

JW, DYC and GMX designed/planned the study. GMX, YFJ, YL, JZG and XFX acquired and analyzed data, performed computational modeling. GMX, YFJ, DYC and JW wrote and revised the manuscript. DYC and JW supervised the study. All authors participated in imaging analysis and discussion of related data and approved the submitted version.

Corresponding authors

Correspondence to Diyu Chen or Jian Wu.

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Supplementary Information

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Supplementary file1 (PDF 50 KB) Supplement Table 1 List of 33 ICD-related genes

Supplementary file2 (PDF 77 KB) Supplement Figure 1 Work flow of this study

432_2023_5370_MOESM3_ESM.jpg

Supplementary file3 (JPG 2464 KB) Supplement Figure 2 We conducted a univariate COX regression analysis of the 33 ICD-related genes and found that 23 genes were associated with the prognosis of HCC

432_2023_5370_MOESM4_ESM.jpg

Supplementary file4 (JPG 2103 KB) Supplement Figure 3 Based on the K–M analyses, we observed that the OS of five hub mRNA and lncRNA was significantly lower in the high-expression group than in the low-expression group

432_2023_5370_MOESM5_ESM.jpg

Supplementary file5 (JPG 1231 KB) Supplement Figure 4 Validation of the stability of the ICD score model. (a) We conducted the PCA analysis of ICD score, revealing that two ICD score clusters could distinguish HCC patients, vividly. A (blue) and B (yellow). (b) The Kaplan–Meier curves showed the high-ICD-score group had a worse OS. (c) An alluvial diagram was created to depict the relationship between the ICD clusters, ICD score and living status. (d) The diagram demonstrated a significant correlation between the ICD score and T and B cells. (e) The boxplot indicated that patients in ICD cluster A had a higher ICD score

432_2023_5370_MOESM6_ESM.jpg

Supplementary file6 (JPG 653 KB) Supplement Figure 5 We performed differential analyses of ten genes resulted from PPI analysis between HCC samples and normal individuals obtained from the GEPIA database, revealing that PSMD2 and PSMD14 were significantly up-regulated in HCC patients

432_2023_5370_MOESM7_ESM.jpg

Supplementary file7 (JPG 1584 KB) Supplement Figure 6 The K–M curves showed that patients with low expressions of PSMD2 and PSMD14 had significantly better overall survival (OS) rate

432_2023_5370_MOESM8_ESM.jpg

Supplementary file8 (JPG 921 KB) Supplement Figure 7 PSMD2 had good relationship with the mainly ICD-related genes consisting of CALR, CASP1, CASP8, HMGB2 and HSP90AA1 as well as PSMD14

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Xu, G., Jiang, Y., Li, Y. et al. A novel immunogenic cell death-related genes signature for predicting prognosis, immune landscape and immunotherapy effect in hepatocellular carcinoma. J Cancer Res Clin Oncol 149, 16261–16277 (2023). https://doi.org/10.1007/s00432-023-05370-1

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