Open Access

Disulfidptosis‑related lncRNA prognosis model to predict survival therapeutic response prediction in lung adenocarcinoma

  • Authors:
    • Xiaoming Sun
    • Jia Li
    • Xuedi Gao
    • Yubin Huang
    • Zhanyue Pang
    • Lin Lv
    • Hao Li
    • Haibo Liu
    • Liangming Zhu
  • View Affiliations

  • Published online on: May 29, 2024     https://doi.org/10.3892/ol.2024.14476
  • Article Number: 342
  • Copyright: © Sun et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, and disulfidptosis is a newly discovered mechanism of programmed cell death. However, the effects of disulfidptosis‑related lncRNAs (DR‑lncRNAs) in LUAD have yet to be fully elucidated. The aim of the present study was to identify and validate a novel lncRNA‑based prognostic marker that was associated with disulfidptosis. RNA‑sequencing and associated clinical data were obtained from The Cancer Genome Atlas database. Univariate Cox regression and lasso algorithm analyses were used to identify DR‑lncRNAs and to establish a prognostic model. Kaplan‑Meier curves, receiver operating characteristic curves, principal component analysis, Cox regression, nomograms and calibration curves were used to assess the reliability of the prognostic model. Functional enrichment analysis, immune infiltration analysis, somatic mutation analysis, tumor microenvironment and drug predictions were applied to the risk model. Reverse transcription‑quantitative PCR was subsequently performed to validate the mRNA expression levels of the lncRNAs in normal cells and tumor cells. These analyses enabled a DR‑lncRNA prognosis signature to be constructed, consisting of nine lncRNAs; U91328.1, LINC00426, MIR1915HG, TMPO‑AS1, TDRKH‑AS1, AL157895.1, AL512363.1, AC010615.2 and GCC2‑AS1. This risk model could serve as an independent prognostic tool for patients with LUAD. Numerous immune evaluation algorithms indicated that the low‑risk group may exhibit a more robust and active immune response against the tumor. Moreover, the tumor immune dysfunction exclusion algorithm suggested that immunotherapy would be more effective in patients in the low‑risk group. The drug‑sensitivity results showed that patients in the high‑risk group were more sensitive to treatment with crizotinib, erlotinib or savolitinib. Finally, the expression levels of AL157895.1 were found to be lower in A549. In summary, a novel DR‑lncRNA signature was constructed, which provided a new index to predict the efficacy of therapeutic interventions and the prognosis of patients with LUAD.
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August-2024
Volume 28 Issue 2

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Copy and paste a formatted citation
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Spandidos Publications style
Sun X, Li J, Gao X, Huang Y, Pang Z, Lv L, Li H, Liu H and Zhu L: Disulfidptosis‑related lncRNA prognosis model to predict survival therapeutic response prediction in lung adenocarcinoma. Oncol Lett 28: 342, 2024
APA
Sun, X., Li, J., Gao, X., Huang, Y., Pang, Z., Lv, L. ... Zhu, L. (2024). Disulfidptosis‑related lncRNA prognosis model to predict survival therapeutic response prediction in lung adenocarcinoma. Oncology Letters, 28, 342. https://doi.org/10.3892/ol.2024.14476
MLA
Sun, X., Li, J., Gao, X., Huang, Y., Pang, Z., Lv, L., Li, H., Liu, H., Zhu, L."Disulfidptosis‑related lncRNA prognosis model to predict survival therapeutic response prediction in lung adenocarcinoma". Oncology Letters 28.2 (2024): 342.
Chicago
Sun, X., Li, J., Gao, X., Huang, Y., Pang, Z., Lv, L., Li, H., Liu, H., Zhu, L."Disulfidptosis‑related lncRNA prognosis model to predict survival therapeutic response prediction in lung adenocarcinoma". Oncology Letters 28, no. 2 (2024): 342. https://doi.org/10.3892/ol.2024.14476