A migrasome-related LncRNA signatures for predicting prognosis and immunotherapeutic response in colorectal cancer

Migrasome has recently been reported to regulate cell-cell communication in tumor progression. But the function of migrasome in CRC, especially its prognostic potential and association with long non-coding RNAs and tumor microenvironment has yet to be fully explored. Migrasome-related lncRNAs were identified based on transcriptome data from 650 CRC patients in the TCGA COREAD cohort. A prognostic signature was developed via the least absolute shrinkage and selection operator algorithm and Cox regression. The multimodal predicting model for prognosis of CRC patients was constructed and validated through Kaplan-Meier survival, ROC curve analysis, and nomogram construction. Patients were divided into high- and low-risk groups according to their prognostic signature and functional enrichment, immune cell infiltration, immunotherapy efficacy, and drug sensitivity analyses were performed to characterize their variation. Ten migrasome-related lncRNAs were identified and used to construct a prognostic risk score that effectively stratified patients into high- and low-risk groups, demonstrating significant differences in overall survival (P < 0.001) and survival-related ROC curve analysis. A nomogram based on the multimodal predicting model was constructed with robust calibration curves. The transcriptional variation between high-risk and low-risk patients were mainly associated with signaling receptor activator activity, receptor ligand activity and cytokine-cytokine receptor interaction. High-risk patients exhibited reduced immune cell infiltration and higher potential for immune escape. In addition, drug sensitivity screening revealed that high-risk patients were more likely to resist current targeted drugs including PLX-4720 and JAK-8517 than low-risk patients. This study identifies a novel migrasome-related lncRNA signature as a reliable prognostic tool for CRC, highlighting its potential in patient stratification and personalized therapy.