Article http://dx.doi.org/10.26855/ijcemr.2024.01.030

Disulfidptosis-related lncRNAs Predict Prognosis and Immune Landscape in Endometrial Cancer


Yu Zhang1, Yaping Wang1,2, Xiabing Li1, Qimin Jin1, Hongjian Zhang1, Hai Zhu1, Qing Liu1, Hongyu Li1,2,*

1Gynecologic Oncology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.

2Zhengzhou Key Laboratory of Gynecological Oncology, Zhengzhou, Henan, China.

*Corresponding author: Hongyu Li

Published: March 12,2024


Background: Recently, a novel form of cell death called disulfidptosis was identified. It is characterized by rapid cell death caused by disulfide stress resulting from excessive cystine accumulation within cells. Disulfidptosis holds promise as a potential target for intervention in tumor treatment. However, the roles and prognostic value of disulfidptosis-related lncRNAs (DRLs) in EC remain largely unknown. Therefore, the objective of this study is to develop a prediction model based on DRLs to forecast the prognosis and assess the immunotherapy response in EC patients, as well as identify potential chemotherapy drugs for treatment. Methods: We constructed a model by screening DRLs associated with EC prognosis through bioinformatics methods and validated it. Furthermore, enrichment analysis was conducted to explore functional differences between different risk populations. Additionally, we examined the associations between the risk score and tumor mutational burden (TMB), tumor microenvironment (TME), tumor immune dysfunction and exclusion (TIDE), and drug sensitivity. Finally, we validated this using quantitative reverse transcription polymerase chain reaction (qRT-PCR). Results: We identified 8 DRLs (Z69733.1, AL158071.4, AC022960.1 AC005034.2, AC003086.1, AC024230.1, AL499602.1, RAB11B-AS1) and constructed a robust risk model. Further analysis revealed that the low-risk group had superior overall survival (OS), immunotherapy response, and drug sensitivity compared to the high-risk group. Conclusion: Our risk model provides an accurate prediction of prognosis and immunotherapy response in EC patients, offering significant clinical implications and novel insights for clinicians in the treatment of EC.


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How to cite this paper

Disulfidptosis-related lncRNAs Predict Prognosis and Immune Landscape in Endometrial Cancer

How to cite this paper: Yu Zhang, Yaping Wang, Xiabing Li, Qimin Jin, Hongjian Zhang, Hai Zhu, Qing Liu, Hongyu Li. (2024) Disulfidptosis-related lncRNAs Predict Prognosis and Immune Landscape in Endometrial CancerInternational Journal of Clinical and Experimental Medicine Research8(1), 165-179.

DOI: http://dx.doi.org/10.26855/ijcemr.2024.01.030