Establishment of a ferroptosis-related gene signature for prognosis in lung adenocarcinoma patients

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Bioinformatics and Genomics

Main article text

 

Introduction

Materials & Methods

Databases

Collection of ferroptosis-related data

Identification of differentially expressed genes (DEGs)

Constructing and validating a prognostic ferroptosis-related gene signature

Nomogram generation

Biological pathway of ferroptosis-related prognostic genes

Statistical analysis

Results

Patient characteristics and DEGs

PPI analysis of DEGs

Construction and validation of a prognostic model in TCGA and GEO cohorts

Nomogram establishment

Assessment of independent prognostic value of risk score

Functional enrichment analysis in TCGA and GEO cohorts

Discussion

Conclusions

Supplemental Information

The relationship between the optimal cut-off expression of each gene and survival prognosis in TCGA cohort

DOI: 10.7717/peerj.11931/supp-1

The relationship between the optimal cut-off expression of each gene and survival prognosis in GSE68465 cohort

DOI: 10.7717/peerj.11931/supp-2

259 ferroptosis-related genes

DOI: 10.7717/peerj.11931/supp-3

The annotated gene set file used in ssGSEA

DOI: 10.7717/peerj.11931/supp-4

The list of DEGs

DOI: 10.7717/peerj.11931/supp-5

Additional Information and Declarations

Competing Interests

The authors declare there are no competing interests.

Author Contributions

Jingjing Cai and Chunyan Li conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft.

Hongsheng Li performed the experiments, prepared figures and/or tables, and approved the final draft.

Xiaoxiong Wang performed the experiments, analyzed the data, prepared figures and/or tables, and approved the final draft.

Yongchun Zhou analyzed the data, authored or reviewed drafts of the paper, and approved the final draft.

Data Availability

The following information was supplied regarding data availability:

The data is available at NCBI GEO: GSE68465 and at the TCGA: TCGA-LUAD.

Funding

This work was supported by the National Natural Science Foundation of China (Nos. 81860513). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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