Novel application of the ferroptosis-related genes risk model associated with disulfidptosis in hepatocellular carcinoma prognosis and immune infiltration

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Bioinformatics and Genomics

Main article text

 

Introduction

Materials and Methods

Data acquisition

Analysis of differentially expressed genes

Enrichment analysis of DEGs

Unsupervised cluster analysis

Analysis of biological behavior and tumor microenvironment (TME) on phenotypes of DRG-FRGs

Construction and validation of a risk prognostic model based on DRG-FRGs

Decision curve analysis and model comparison

Analysis of gene mutation and tumor mutation burden

Gene set enrichment analysis (GSEA)

Analysis of tumor microenvironment

Analysis of response to drug therapy

Analysis of cancer stem cell infiltration

Single-cell analysis

Analysis of immune checkpoints and antigen presentation

Validation of signature genes in databases

Immunohistochemistry (IHC)

Statistical analysis

Results

Identification and analysis of differentially expressed ferroptosis genes associated with disulfidptosis

Unsupervised cluster analysis

Construction and validation of risk prognostic model based on DRG-FRGs

Evaluation of the risk prognostic model based on DRG-FRGs

Analysis of gene mutation and tumor mutation burden

Analysis of immune features and antigen presentation

Gene set enrichment analysis

Drug sensitivity analysis

Analysis of cancer stem cell infiltration

Single-cell analysis of signature genes

Validation of signature genes in databases

Validation of signature genes in protein level

Discussion

Supplemental Information

Supplementary material.

DOI: 10.7717/peerj.16819/supp-1

Additional Information and Declarations

Competing Interests

The authors declare that they have no competing interests.

Author Contributions

Jiayan Wei conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the article, and approved the final draft.

Jinsong Wang conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the article, and approved the final draft.

Xinyi Chen performed the experiments, prepared figures and/or tables, authored or reviewed drafts of the article, and approved the final draft.

Li Zhang conceived and designed the experiments, authored or reviewed drafts of the article, and approved the final draft.

Min Peng conceived and designed the experiments, authored or reviewed drafts of the article, and approved the final draft.

Data Availability

The following information was supplied regarding data availability:

The data is available at figshare and the following sites: 魏, 家燕 (2024). Ferroptosis-Related Genes Risk Model Associated with Disulfidptosis in Hepatocellular Carcinoma Prognosis. figshare. Dataset. https://doi.org/10.6084/m9.figshare.24971169.v1.

TCGA: TCGA-LIHC, https://www.cancer.gov/ccg/research/genome-sequencing/tcga;

GEO: GSE14520;

ICGC: LIRI-JP, https://dcc.icgc.org;

FerrDb: Driver+Suppressor+Marker genes:259, http://www.zhounan.org/ferrdb/legacy/operations/download.html;

GDSC: GDSC2-LIHC, https://www.cancerrxgene.org;

UCSC Xena: TCGA Liver Cancer (LIHC), http://xena.ucsc.edu;

STRING: http://string.embl.de;

TIMER 2.0: http://timer.cistrome.org;

CIBERSORT: https://cibersortx.stanford.edu;

cBioPortal: http://www.cbioportal.org;

MSigDB: https://www.gsea-msigdb.org/gsea/msigdb;

TISCH: http://tisch.comp-genomics.org;

HPA: https://www.proteinatlas.org;

CCLE: http://www.broadinstitute.org/ccle.

Funding

This work was supported by grants from the National Science Foundation of China (No. 81770169), The Hubei Science Foundation for Distinguished Young Scholars (2023AFA079), The Interdisciplinary Innovative Talents Foundation from Renmin Hospital of Wuhan University (JCRCFZ-2022-025), the Beijing Science and Innovation Medical Development Foundation (KC2021-JX-0186-18), the China primary healthcare foundation (cphcf-2022-183), and the China Zhongguancun Precision Medicine Science and Technology Foundation (ZLXGBXKYXM-030-02). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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