Development and validation of a three-immune-related gene signature prognostic risk model in papillary thyroid carcinoma

Journal of Endocrinological Investigation (2021)Cite this article

Abstract

Purpose

Increasing evidence indicates that there is a correlation between papillary thyroid carcinoma (PTC) prognosis and the immune signature. Our goal was to construct a new prognostic tool based on immune genes to achieve more accurate prognosis predictions and earlier diagnoses of PTC.

Methods

The 493 PTCs samples and 58 tumor-adjacent normal tissues were obtained from The Cancer Genome Atlas database (TCGA). Immune genes were obtained from the ImmPort database. First, this cohort was randomly divided into training cohort and testing cohort. Second, the differentially expressed (DE) immune genes from the training set were used to construct the prognostic model. Then, the testing and entire data cohorts were used to validate the model, and the data were analyzed to determine the correlation of the clinical prognostic model with immune cell infiltration and expression profiles of human leukocyte antigen (HLA) genes. Finally, an analysis of the gene ontology (GO) annotation was performed.

Results

A total of 189 upregulated and 128 downregulated DE immune genes were identified. We developed and validated a three-immune gene model for PTC that includes Hsp70, NOX5, and FGF23. This model was demonstrated to be an independent prognostic variable. In addition, the overall immune activity of the high-risk group was higher than that of the low-risk group.

Conclusions

We developed and validated a three-immune gene model for PTC that includes HSPA1A, NOX5, and FGF23. This model can be used as a validated tool to predict outcomes in PTC.

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Abbreviations

PTC:

Papillary thyroid carcinoma

TCGA:

The Cancer Genome Atlas database

HLA:

Human leukocyte antigen

GO:

Gene ontology

TC:

Thyroid cancer

IRGs:

Immune-related gene signature

DE:

Differentially expressed

TF:

Transcription factors

GSEA:

The Gene set enrichment analysis

KM:

Kaplan–Meier analyses

ROC:

Receiver-operating characteristic

AUC:

Area under the ROC curve

TME:

Tumor microenvironment

OS:

Overall survival

HSPA1A:

Heat shock protein family A (Hsp70) member 1A

NOX5:

NADPH oxidase 5

FGF23:

Fibroblast growth factor 23

TIM:

Tumor immune microenvironment

DC:

Dendritic cells

TAMs:

Tumor-associated macrophages

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Acknowledgements

Thanks to Professor Bo Xu for this design.

Funding

This research was supported by Guangzhou medicine and healthcare technology projects (20141A011011, 20151A011007, and 20161A011008).

Author information

Author notes

  1. X. Gan, M. Guo, and Z. Chen share the first authorships.

Affiliations

  1. Department of Thyroid Surgery, Guangzhou First People’s Hospital, Guangzhou Medical University, Guangzhou, China

    X. Gan, M. Guo, F. Shen, J. Feng, W. Cai & B. Xu

  2. Department of Thyroid Surgery, School of Medicine, Guangzhou First People’s Hospital, South China University of Technology, Guangzhou, Guangdong, China

    X. Gan, Z. Chen, Y. Li, F. Shen, J. Feng, W. Cai & B. Xu

Authors
  1. X. Gan
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  2. M. Guo
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  3. Z. Chen
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  4. Y. Li
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  5. F. Shen
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  6. J. Feng
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  8. B. Xu
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Contributions

Conception: XG and BX. Design and revise the manuscript: XG, JF, and FS. Analysis and interpretation of data: XG, FS, JF, WC, ZC, MG, and YL.

Corresponding author

Correspondence to B. Xu.

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Conflict of interest

The authors reported no proprietary or commercial interest in any product mentioned or concept discussed in this article.

Ethical approval

All data of the study were obtained from The Cancer Genome Atlas (TCGA) database and have obtained ethical approval.

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Cite this article

Gan, X., Guo, M., Chen, Z. et al. Development and validation of a three-immune-related gene signature prognostic risk model in papillary thyroid carcinoma. J Endocrinol Invest (2021). https://doi.org/10.1007/s40618-021-01514-7

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Keywords

  • Immune gene
  • Prognosis
  • Risk model
  • Papillary thyroid carcinoma
  • TCGA