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Identification and development of a novel risk model based on cuproptosis-associated RNA methylation regulators for predicting prognosis and characterizing immune status in hepatocellular carcinoma

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Abstract

Background

Cuproptosis, a novel cell death caused by excess copper, is quite obscure in hepatocellular carcinoma (HCC) and needs more investigation.

Methods

RNA-seq and clinical data of HCC patients TCGA database were analyzed to establish a predictive model through LASSO Cox regression analysis. External dataset ICGC was used for the verification. GSEA and CIBERSORT were applied to investigate the molecular mechanisms and immune microenvironment of HCC. Cuproptosis induced by elesclomol was confirmed via various in vitro experiments. The expression of prognostic genes was verified in HCC tissues using qRT-PCR analysis.

Results

Initially, 18 cuproptosis-associated RNA methylation regulators (CARMRs) were selected for prognostic analysis. A nine-gene signature was created by applying the LASSO Cox regression method. Survival and ROC assays were carried out to validate the model using TCGA and ICGC database. Moreover, there exhibited obvious differences in drug sensitivity in terms of common drugs. A higher tumor mutation burden was shown in the high-risk group. Additionally, significant discrepancies were found between the two groups in metabolic pathways and RNA processing via GSEA analysis. Meanwhile, CIBERSORT analysis indicated different infiltrating levels of various immune cells between the two groups. Elesclomol treatment caused a unique form of programmed cell death accompanied by loss of lipoylated mitochondrial proteins and Fe–S cluster protein. The results of qRT-PCR indicated that most prognostic genes were differentially expressed in the HCC tissues.

Conclusion

Overall, our predictive signature displayed potential value in the prediction of overall survival of HCC patients and might provide valuable clues for personalized therapies.

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Availability of data and materials

Most of the datasets used and analyzed in the study are publicly available data from TCGA and ICGC database. Further inquiries can be directed to the corresponding authors.

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Funding

This work was supported by National Key Research and Development Project (2017YFC0110802), Zhejiang province Key Research and Development Project (2020C01059), National Natural Science Foundation of China (81872297, and 81874059), Zhejiang Engineering Research Center of Cognitive Healthcare (2017E10011), National Natural Science Foundation of China (82102105), Natural Science Foundation of Zhejiang Province (LQ22H160017) and China Postdoctoral Science Foundation (2021M702825).

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Author notes

  1. Duguang Li, Zhaoqi Shi and Xiaolong Liu contributed equally.

Authors and Affiliations

  1. Department of General Surgery, School of Medicine, Sir Run Run Shaw Hospital, Zhejiang University, 3 East Qingchun Rd, Hangzhou, 310016, People’s Republic of China

    Duguang Li, Zhaoqi Shi, Xiaolong Liu, Shengxi Jin, Peng Chen, Yiyin Zhang, Guoqiao Chen, Xiaoxiao Fan, Jing Yang & Hui Lin

  2. Zhejiang Engineering Research Center of Cognitive Healthcare, School of Medicine, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, People’s Republic of China

    Hui Lin

  3. College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, People’s Republic of China

    Hui Lin

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  1. Duguang Li
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Contributions

HL, JY, and XXF conceived and designed the analysis. SXJ, PC, YYZ, and GQC collected the data. DGL, ZQS, and XLL performed analysis. DGL, ZQS, and XLL wrote the paper. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Xiaoxiao Fan, Jing Yang or Hui Lin.

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Conflict of interest

Duguang Li, Zhaoqi Shi, Xiaolong Liu, Shengxi Jin, Peng Chen, Yiyin Zhang, Guoqiao Chen, Xiaoxiao Fan, Jing Yang and Hui Lin have no relevant financial or non-financial interests to disclose.

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki, and was approved by the Institutional Review Board of SRRSH (ethical code: 20210729-282) and written informed consent was obtained from all patients.

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Li, D., Shi, Z., Liu, X. et al. Identification and development of a novel risk model based on cuproptosis-associated RNA methylation regulators for predicting prognosis and characterizing immune status in hepatocellular carcinoma. Hepatol Int 17, 112–130 (2023). https://doi.org/10.1007/s12072-022-10460-2

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