Construction of a risk and prognostic model for migrasome-associated lncRNAs in renal cell carcinoma

Abstract The migrasome, a recently identified cellular organelle, is closely associated with cell migration and plays a critical role in various physiological and pathological processes. The relationship between migrasomes and the prognosis of kidney cancer patients remains unclear. We utilized leas...

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Bibliographic Details
Main Authors: Liangwei Zhao, Fengjiao Geng, Xiaomin Ji, Chaoqun Geng, Tian Liu
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-10630-w
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Summary:Abstract The migrasome, a recently identified cellular organelle, is closely associated with cell migration and plays a critical role in various physiological and pathological processes. The relationship between migrasomes and the prognosis of kidney cancer patients remains unclear. We utilized least absolute shrinkage and selection operator (LASSO) Cox regression analysis on data from The Cancer Genome Atlas- kidney renal clear cell carcinoma (TCGA-KIRC) dataset to identify migrasome-related long non-coding RNAs (lncRNAs) with prognostic significance in KIRC. We then developed and validated a prognostic risk model based on these lncRNAs. In addition, to identify potential immunotherapeutic agents, we analyzed tumor immune dysfunction and exclusion scores; we also conducted immune cell infiltration profiling. Risk score analysis identified 12 migrasome-related lncRNAs significantly associated with the prognosis of TCGA-KIRC patients. Kaplan–Meier survival analysis demonstrated that the prognostic model effectively stratified patients into high- and low-risk groups; the high-risk group showed a significantly worse prognosis relative to the low-risk group. Importantly, higher risk scores were associated with increased immune cell infiltration. This prognostic model underscores the importance of migrasome-related lncRNAs in KIRC and provides a novel tool for predicting patient prognosis and immune response in KIRC.
ISSN:2045-2322