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Development and validation of a ferroptosis-related prognostic model in pancreatic cancer

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Summary

Background: The purpose of this study was to identify ferroptosis-related genes (FRGs) associated with the prognosis of pancreatic cancer and to construct a prognostic model based on FRGs. Methods: Based on pancreatic cancer data obtained from The Cancer Genome Atlas database, we established a prognostic model from 232 FRGs. A nomogram was constructed by combining the prognostic model and clinicopathological features. Gene Expression Omnibus datasets and tissue samples obtained from our center were utilized to validate the model. The relationship between risk score and immune cell infiltration was explored by CIBERSORT and TIMER. Results: The prognostic model was established based on four FRGs (ENPP2, ATG4D, SLC2A1 and MAP3K5), and the risk score was demonstrated to be an independent risk factor in pancreatic cancer (HR 1.648, 95% CI 1.335–2.035, p < 0.001). Based on the median risk score, patients were divided into a high-risk group and a low-risk group. The low-risk group had a better prognosis than the high-risk group. In the high-risk group, patients treated with chemotherapy had a better prognosis. The nomogram showed that the model was the most important element. Gene set enrichment analysis identified three key pathways, namely, TGFβ signaling, HIF signaling pathway and the adherens junction. The prognostic model may be associated with infiltration of immune cells such as M0 macrophages, M1 macrophages, CD4 + T cells and CD8 + T cells. Conclusion: The ferroptosis-related prognostic model can be employed to predict the prognosis of pancreatic cancer. Ferroptosis is an important marker, and immunotherapy may be a potential therapeutic target for pancreatic cancer.

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Data availability

All data generated or analyzed during this study are included in this published article and supplementary information files.

Abbreviations

FRG:

Ferroptosis-related genes

DE-FRG:

Differentially expressed ferroptosis-related genes

TCGA:

The Cancer Genome Atlas

LASSO:

Least absolute shrinkage and selection operator

GEO:

Gene Expression Omnibus

OS:

Overall survival

GSEA:

Gene set enrichment analysis

ROS:

Reactive oxygen species

GO:

Gene Ontology

KEGG:

Kyoto Encyclopedia of Genes and Genomes

BP:

Biological processes

CC:

Cellular components

MF:

Molecular functions

PPI:

Protein–protein interaction

KM:

Kaplan-Meier

ROC:

Receiver operating characteristic

AUC:

The area under the curve;

RT-qPCR:

Real-time quantitative polymerase chain reaction

FDR:

False discovery rate

SCNA:

Somatic number alteration

TIMER:

Tumor Immune Estimation Resource

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Acknowledgements

We thank the staff from the pancreas center of the First Affiliated Hospital of Nanjing Medical University who gave us support throughout the experiments.

Funding

This work was supported by the Wu Jieping Medical Foundation (Grant/Award Number: 320.2710.1802).

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Authors

Contributions

Chen-jie Qiu and Xue-bing Wang performed the experimental design and data analysis. Zi-ruo Zheng wrote the manuscript. All authors read and approved the final manuscript.

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Correspondence to Kui-rong Jiang or Wen-tao Gao.

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The study was approved by the Ethics Committee of the First Affiliated Hospital of Nanjing Medical University.

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Qiu, Cj., Wang, Xb., Zheng, Zr. et al. Development and validation of a ferroptosis-related prognostic model in pancreatic cancer. Invest New Drugs 39, 1507–1522 (2021). https://doi.org/10.1007/s10637-021-01114-5

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