Frontiers in Molecular Biosciences (Aug 2022)

Identification of immune-related ferroptosis prognostic marker and in-depth bioinformatics exploration of multi-omics mechanisms in thyroid cancer

  • Xin Fan,
  • Fei Xie,
  • Lingling Zhang,
  • Chang Tong,
  • Zhiyuan Zhang

DOI
https://doi.org/10.3389/fmolb.2022.961450
Journal volume & issue
Vol. 9

Abstract

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Background: Factors such as variations in thyroid carcinoma (THCA) gene characteristics could influence the clinical outcome. Ferroptosis and immunity have been verified to play an essential role in various cancers, and could affect the cancer patients’ prognosis. However, their relationship to the progression and prognosis of many types of THCA remains unclear.Methods: First, we extracted prognosis-related immune-related genes and ferroptosis-related genes from 2 databases for co-expression analysis to obtain prognosis-related differentially expressed immune-related ferroptosis genes (PR-DE-IRFeGs), and screened BID and CDKN2A for building a prognostic model. Subsequently, multiple validation methods were used to test the model’s performance and compare its performance with other 4 external models. Then, we explored the mechanism of immunity and ferroptosis in the occurrence, development and prognosis of THCA from the perspectives of anti-tumor immunity, CDKN2A-related competitive endogenous RNA regulatory, copy number variations and high frequency gene mutation. Finally, we evaluated this model’s clinical practice value.Results: BID and CDKN2A were identified as prognostic risk and protective factors, respectively. External data and qRT-PCR experiment also validated their differential expression. The model’s excellent performance has been repeatedly verified and outperformed other models. Risk scores were significantly associated with most immune cells/functions. Risk score/2 PR-DE-IRFeGs expression was strongly associated with BRAF/NRAS/HRAS mutation. Single copy number deletion of CDKN2A is associated with upregulation of CDKN2A expression and worse prognosis. The predicted regulatory network consisting of CYTOR, hsa-miRNA-873-5p and CDKN2A was shown to significantly affect prognosis. The model and corresponding nomogram have been shown to have excellent clinical practice value.Conclusion: The model can effectively predict the THCA patients’ prognosis and guide clinical treatment. Ferroptosis and immunity may be involved in the THCA’s progression through antitumor immunity and BRAF/NRAS/HRAS mutation. CYTOR-hsa-miRNA-873-5p-CDKN2A regulatory networks and single copy number deletion of CDKN2A may also affect THCA′ progression and prognosis.

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