A novel prognostic model based on migrasome-related LncRNAs for gastric cancer DOI Creative Commons
Wenhao Jiang,

Jiaying Shi,

Yingchuan Zhu

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 25, 2025

Abstract Gastric cancer (GC) represents a substantial public health challenge, characterized by elevated morbidity and mortality rates. Migrasomes, newly discovered type of extracellular vesicle, have been highlighted as important contributors to progression, though their specific role in GC remains unclear. To address this issue, we developed the first prognostic model utilizing migrasome-related long non-coding RNAs (MRLs). This aims deepen understanding pathogenesis improve patient outcomes. Clinical transcriptional data for 407 patients from TCGA were classified training testing sets. Through Pearson correlation analysis, 537 MRLs recognized, LASSO Cox regression analyses further refined list four key lncRNAs (AC012055.1, LINC01150, AC053503.4, AC107021.2) constructing model. Kaplan-Meier survival analysis indicated significantly poorer prognosis high-risk group. PCA confirmed model’s robustness, univariate multivariate validated it an independent predictor clinical The ROC curve C-index evaluations affirmed predictive power. We nomogram combining signature with parameters enhance accuracy. GO, KEGG GSEA performed on genes associated GC. Furthermore, exhibited increased immune cell infiltration reduced tumor mutation burden, both Additionally, twenty-nine potential therapeutic agents identified. novel MRLs-based provides crucial insights into biology valuable tool improving management strategies.

Language: Английский

A novel prognostic model based on migrasome-related LncRNAs for gastric cancer DOI Creative Commons
Wenhao Jiang,

Jiaying Shi,

Yingchuan Zhu

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 25, 2025

Abstract Gastric cancer (GC) represents a substantial public health challenge, characterized by elevated morbidity and mortality rates. Migrasomes, newly discovered type of extracellular vesicle, have been highlighted as important contributors to progression, though their specific role in GC remains unclear. To address this issue, we developed the first prognostic model utilizing migrasome-related long non-coding RNAs (MRLs). This aims deepen understanding pathogenesis improve patient outcomes. Clinical transcriptional data for 407 patients from TCGA were classified training testing sets. Through Pearson correlation analysis, 537 MRLs recognized, LASSO Cox regression analyses further refined list four key lncRNAs (AC012055.1, LINC01150, AC053503.4, AC107021.2) constructing model. Kaplan-Meier survival analysis indicated significantly poorer prognosis high-risk group. PCA confirmed model’s robustness, univariate multivariate validated it an independent predictor clinical The ROC curve C-index evaluations affirmed predictive power. We nomogram combining signature with parameters enhance accuracy. GO, KEGG GSEA performed on genes associated GC. Furthermore, exhibited increased immune cell infiltration reduced tumor mutation burden, both Additionally, twenty-nine potential therapeutic agents identified. novel MRLs-based provides crucial insights into biology valuable tool improving management strategies.

Language: Английский

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