Migrasome-Related lncRNA Signature for Bladder Cancer Prognosis and Immune Landscape

A prognostic model based on migrasome-related long non-coding RNAs (lncRNAs) derived from transcriptomic and clinical data from The Cancer Genome Atlas (TCGA). The study, authored by Junlin Shen and last updated in April 2026, includes functional annotation, immune infiltration analysis, and experimental validation of a key lncRNA, SEC24B-AS1.

Use Cases

• Predicting patient survival outcomes based on the migrasome-related lncRNA risk signature.
• Analyzing tumor immune microenvironment features, such as immune cell infiltration and stromal scores, associated with the risk groups.
• Investigating drug sensitivity and identifying potential therapeutic compounds with differential responses between high- and low-risk patients.
• Exploring cellular heterogeneity and intercellular communication patterns within the bladder cancer microenvironment using single-cell RNA sequencing insights.

Strengths

• Includes experimental validation (qRT-PCR, CCK-8, colony formation, migration assays) for a key lncRNA, SEC24B-AS1.
• Analyses span multiple validation methods including Kaplan-Meier survival, ROC curves, PCA, and multivariate Cox regression.
• Integrates diverse data types: transcriptomic, clinical, immune profiling, tumor mutation burden, and single-cell RNA sequencing.

Limitations

• Row count and column-level documentation are unknown, which may limit suitability assessment.
• The primary data file is a 619.6 KB PDF, suggesting the dataset is a summary or research paper rather than raw data tables.
• Data may reflect bias inherent to the TCGA source cohort.

Provenance

Source

The Cancer Genome Atlas (TCGA)

Collection Method

Integrated transcriptomic and clinical data analysis, co-expression analysis, and regression modeling.

Time Range

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Freshness

Last updated 2026-04-16 05:16:37.

Geography

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