Disulfidptosis-related immune patterns predict prognosis and characterize the tumor microenvironment in oral squamous cell carcinoma

Abstract Background Establishing a prognostic risk model based on immunological and disulfidptosis signatures enables precise prognosis prediction of oral squamous cell carcinoma (OSCC). Methods Differentially expressed immune and disulfidptosis genes were identified in OSCC and normal tissues. We e...

Full description

Saved in:
Bibliographic Details
Main Authors: Xuechen Wu, Boxin Liu, Shi-Zhou Deng, Tengteng Xiong, Lin Dai, Bo Cheng
Format: Article
Language:English
Published: BMC 2025-02-01
Series:BMC Oral Health
Subjects:
Online Access:https://doi.org/10.1186/s12903-024-05279-2
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Abstract Background Establishing a prognostic risk model based on immunological and disulfidptosis signatures enables precise prognosis prediction of oral squamous cell carcinoma (OSCC). Methods Differentially expressed immune and disulfidptosis genes were identified in OSCC and normal tissues. We examined the model’s clinical applicability and its relationship to immune cell infiltration. Additionally, the risk score, ssGSEA, ESTIMATE, and CIBERSORT were used to evaluate the intrinsic molecular subtypes, immunological checkpoints, abundances of tumor-infiltrating immune cell types and proportions between the two risk groups. GO-KEGG and GSVA analyses were performed to identify enriched pathways. Results We analyzed the correlation immune genes based on the 14 disulfidptosis-related genes, and found 379 disulfidptosis-related immune genes (DRIGs). After univariate Cox regression we obtained 30 DRIGs and least absolute shrinkage and selection operator (LASSO) regression to reduce the number of genes to 16. Finally we created a nine-DRIGs risk model, of which four were upregulated and five were downregulated. The analysis results showed that disulfidptosis was tightly related to immune cells, immunological-related pathways, the tumor microenvironment (TME), immune checkpoints, human leukocyte antigen (HLA), and tumor mutational burden (TMB). The nomogram, integrating the risk score and clinical factors, accurately predicted overall survival. Conclusions This novel risk model highlights the role of disulfidptosis-related immune genes in OSCC prognosis. With this model, we can more accurately predict the prognosis of patients with OSCC, as well as assess the potential effects of their TME and immunotherapy.
ISSN:1472-6831