Disulfidptosis classification of pancreatic carcinoma reveals correlation with clinical prognosis and immune profile.

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Tác giả: Jieqiong Lin, Jianwei Shen, Jiangmin Shi, Kai Wang, Liang Zhao

Ngôn ngữ: eng

Ký hiệu phân loại:

Thông tin xuất bản: England : Hereditas , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 581428

BACKGROUND: Disulfidptosis, a novel form of metabolism-related regulated cell death, is a promising intervention for cancer therapeutic intervention. Although aberrant expression of long-chain noncoding RNAs (lncRNAs) expression has been associated with pancreatic carcinoma (PC) development, the biological properties and prognostic potential of disulfidptosis-related lncRNAs (DRLs) remain unclear. METHODS: We obtained RNA-seq data, clinical data, and genomic mutations of PC from the TCGA database, and then determined DRLs. We developed a risk score model and analyzed the role of risk score in the predictive ability, immune cell infiltration, immunotherapy response, and drug sensitivity. RESULTS: We finally established a prognostic model including three DRLs (AP005233.2, FAM83A-AS1, and TRAF3IP2-AS1). According to Kaplan-Meier curve analysis, the survival time of patients in the low-risk group was significantly longer than that in the high-risk group. Based on enrichment analysis, significant associations between metabolic processes and differentially expressed genes were assessed in two risk groups. In addition, we observed significant differences in the tumor immune microenvironment landscape. Tumor Immune Dysfunction and Rejection (TIDE) analysis showed no statistically significant likelihood of immune evasion in both risk groups. Patients exhibiting both high risk and high tumor mutation burden (TMB) had the poorest survival times, while those falling into the low risk and low TMB categories showed the best prognosis. Moreover, the risk group identified by the 3-DRLs profile showed significant drug sensitivity. CONCLUSIONS: Our proposed 3-DRLs-based feature could serve as a promising tool for predicting the prognosis, immune landscape, and treatment response of PC patients, thus facilitating optimal clinical decision-making.
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