Construction and experimental validation of a signature for predicting prognosis and immune infiltration analysis of glioma based on disulfidptosis-related lncRNAs

Youwei Guo; Zhipeng Jiang; Quan Chen; Dongcheng Xie; Yi Zhou; Wen Yin; Zihan Wang; Binbin Wang; Caiping Ren; Xingjun Jiang

doi:10.3389/fimmu.2023.1291385

Construction and experimental validation of a signature for predicting prognosis and immune infiltration analysis of glioma based on disulfidptosis-related lncRNAs

Front Immunol. 2023 Nov 3:14:1291385. doi: 10.3389/fimmu.2023.1291385. eCollection 2023.

Authors

Youwei Guo^#^{1

2}, Zhipeng Jiang^#^{1

2}, Quan Chen^#^{1

2}, Dongcheng Xie^{1

2}, Yi Zhou^{1

2}, Wen Yin^{1

2}, Zihan Wang^{1

2}, Binbin Wang³, Caiping Ren^{4

5}, Xingjun Jiang^{1

2}

Affiliations

¹ Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China.
² National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China.
³ Department of Neurosurgery, the First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
⁴ Cancer Research Institute, Department of Neurosurgery, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China.
⁵ National Health Commission (NHC) Key Laboratory of Carcinogenesis and the Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, School of Basic Medical Science, Central South University, Changsha, Hunan, China.

^# Contributed equally.

Abstract

Backgrounds: Disulfidptosis, a newly discovered mechanism of programmed cell death, is believed to have a unique role in elucidating cancer progression and guiding cancer therapy strategies. However, no studies have yet explored this mechanism in glioma.

Methods: We downloaded data on glioma patients from online databases to address this gap. Subsequently, we identified disulfidptosis-related genes from published literature and verified the associated lncRNAs.

Results: Through univariate, multivariate, and least absolute shrinkage and selection operator (LASSO) regression algorithms analyses, we identified 10 lncRNAs. These were then utilized to construct prognostic prediction models, culminating in a risk-scoring signature. Reliability and validity tests demonstrated that the model effectively discerns glioma patients' prognosis outcomes. We also analyzed the relationship between the risk score and immune characteristics, and identified several drugs that may be effective for high-risk patients. In vitro experiments revealed that LINC02525 could enhances glioma cells' migration and invasion capacities. Additionally, knocking down LINC02525 was observed to promote glioma cell disulfidptosis.

Conclusion: This study delves into disulfidptosis-related lncRNAs in glioma, offering novel insights into glioma therapeutic strategies.

Keywords: bioinformatics; disulfidptosis; glioma; immune therapy; lncRNA.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Glioma* / genetics
Humans
Prognosis
RNA, Long Noncoding* / genetics
Reproducibility of Results

Substances

RNA, Long Noncoding

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This present study was supported by the Natural Science Foundation of Hunan Province [No. 2022JJ30931 (XJ)].