Title:Prediction of the Prognosis and Treatment Responses Based on the Characteristics of Disulfidptosis-Related Genes in Patients with Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma
Volume: 26
Issue: 1
Author(s): Min Kang, Sha Jiang, Huihui Chen, Youhua Xu*Hui Mo*
Affiliation:
- Faculty of Chinese Medicine and State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Macau, 999078, China
- Faculty of Chinese Medicine and State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Macau, 999078, China
Keywords:
Disulfidptosis-related gene, risk model, tumor microenvironment, cervical squamous cell carcinoma and endocervical adenocarcinoma, immune infiltration, drug sensitivity.
Abstract:
Background: Disulfidptosis is a new type of regulatory cell death (RCD), but the pathophysiological
functions and mechanisms of disulfidptosis-related genes (DRGs) in cervical squamous
cell carcinoma and endocervical adenocarcinoma (CESC) remain to be examined.
Aims: This study explored the mutation status of DRGs in CESC.
Objective: After analyzing the mutation profiles of DRGs in CESC, this study established a prognostic
model for CESC and also explored the differences in immune infiltration (accumulation of
immune system cells in tissues or organs), related enriched pathways, and drug sensitivity between
high-risk and low-risk CESC groups.
Methods: The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) were accessed
to source related data. The mutation profiles of DRGs in CESC were analyzed using Mutect2
software, and disulfidptosis scores were calculated by ssGSEA. WGCNA was performed to
identify modular genes, which were further filtered and used to formulate a risk model by applying
the survival and glmnet packages. Low- and high-risk groups of CESC patients were classified
using the survminer package. GSEA was performed to conduct pathway analysis, and immune infiltration
was assessed using the MCPcounter package, ESTIMATE, and TIMER algorithms. Finally,
immunotherapy response and drug sensitivity were analyzed using the TIDE method and
the pRRophetic package, respectively.
Results: Except for NDUFA11, ARL6IP5, EPM2AIP1, GBE1, RBM38, ULK4, and ZBTB47 were
found to be the DRGs significantly mutated in CESC. The six genes were integrated to develop a
RiskScore model with a relatively high Area Under the Curve (AUC) value. Significant differences
between the two risk groups were determined, indicating that the model was highly reliable.
Notably, the low-risk group was enriched in energy metabolism-correlated pathways, while the
high-risk group was primarily enriched in immune-correlated pathways. The high-risk group
showed higher immune cell activity, higher TIDE score, and more B cells than the low-risk group.
Drug sensitivity study revealed that the high-risk group was more sensitive to chemotherapy
drugs.
Conclusion: This study provides novel insights into CESC prognosis, immunotherapy, and drug
development, contributing to the clinical treatment for CESC.
