Disulfidptosis-associated LncRNA signature predicts prognosis and immune response in kidney renal clear cell carcinoma

被引:0
作者
Xu, Kangjie [1 ]
Li, Dongling [2 ]
Ji, Kangkang [1 ]
Zhang, Yanhua [3 ]
Zhang, Minglei [4 ]
Zhou, Hai [5 ]
Hou, Xuefeng [1 ]
Jiang, Jian [1 ]
Zhang, Zihang [6 ]
Dai, Hua [7 ]
Sun, Hang [8 ]
机构
[1] Yangzhou Univ, Binhai Cty Peoples Hosp, Clin Med Coll, Cent Lab Dept, Yancheng, Peoples R China
[2] Binhai Cty Peoples Hosp, Nephrol Dept, Yancheng, Peoples R China
[3] Binhai Cty Peoples Hosp, Obstet & Gynecol Dept, Yancheng, Peoples R China
[4] Binhai Cty Peoples Hosp, Oncol Dept, Yancheng, Peoples R China
[5] Binhai Cty Peoples Hosp, Sci & Educ Dept, Yancheng, Peoples R China
[6] Binhai Cty Peoples Hosp, Pathol Dept, Yancheng, Peoples R China
[7] Yangzhou Univ, Clin Med Coll, Jiangsu Key Lab Expt & Translat Noncoding RNA Res, Yangzhou, Peoples R China
[8] Binhai Cty Peoples Hosp, Urol Dept, Yancheng, Peoples R China
关键词
Kidney renal clear cell carcinoma (KIRC); Disulfidptosis-related lncRNAs (DRlncRNAs); Prognostic model; Gene set enrichment analysis (GSEA); Immune infiltration; COLORECTAL-CANCER; ACTIN; IDENTIFICATION; CYTOSKELETON; SPINT1-AS1; EXPRESSION; APOPTOSIS;
D O I
10.1186/s13062-024-00517-7
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
BackgroundKidney renal clear cell carcinoma (KIRC) represents a significant proportion of renal cell carcinomas and is characterized by high aggressiveness and poor prognosis despite advancements in immunotherapy. Disulfidptosis, a novel cell death pathway, has emerged as a critical mechanism in various cellular processes, including cancer. This study leverages machine learning to identify disulfidptosis-related long noncoding RNAs (DRlncRNAs) as potential prognostic biomarkers in KIRC, offering new insights into tumor pathogenesis and treatment avenues.ResultsOur analysis of data from The Cancer Genome Atlas (TCGA) led to the identification of 431 DRlncRNAs correlated with disulfidptosis-related genes. Five key DRlncRNAs (SPINT1-AS1, AL161782.1, OVCH1-AS1, AC131009.3, and AC108673.3) were used to develop a prognostic model that effectively distinguished between low- and high-risk patients with significant differences in overall survival and progression-free survival. The low-risk group had a favorable prognosis associated with a protective immune microenvironment and a better response to targeted drugs. Conversely, the high-risk group displayed aggressive tumor features and poor immunotherapy outcomes. Validation through qRT-PCR confirmed the differential expression of these DRlncRNAs in KIRC cells compared to normal kidney cells, underscoring their potential functional significance in tumor biology.ConclusionsThis study established a robust link between disulfidptosis-related lncRNAs and patient prognosis in KIRC, underscoring their potential as prognostic biomarkers and therapeutic targets. The differential expression of these lncRNAs in tumor versus normal tissue further highlights their relevance in KIRC pathogenesis. The predictive model not only enhances our understanding of KIRC biology but also provides a novel stratification tool for precision medicine approaches, improving treatment personalization and outcomes in KIRC patients.
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页数:18
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