bims-migras 2025-12-14 papers

Issue of 2025–12–14
four papers selected by
Cliff Dominy

Cell Cycle. 2025 Dec 10. 1-22

Migrasomes: the "functional footprints" left by cell migration.

Yue Liu, Xingwen Chen, Jun Zhou, Qian Wang, Yongbin Ma, Kai Zhao.

Migrasomes are membrane-bound vesicles that form on the retraction fibers at the trailing edge of migrating cells and are deposited along the migration path upon the rupture of these fibers. As inherently signal-rich complexes enriched with diverse bioactive components, migrasomes not only mediate intercellular communication and microenvironmental regulation but also provide novel mechanisms and potential targets for understanding physiological and pathological processes. Although research on migrasome functions is still in its infancy, accumulating evidence suggests that they not only expand existing biological knowledge systems but also exhibit unique potential in elucidating disease mechanisms, developing diagnostic biomarkers, and exploring therapeutic targets. This review summarizes the discovery, biogenesis, biological functions, and methodological advances in migrasome research, with a particular focus on their emerging roles in disease. Additionally, we discuss prevailing challenges and future directions, concluding with a perspective on the clinical translation of migrasomes in diagnostics and therapeutics.

Keywords: Migrasomes; extracellular vesicles; physiological and pathological functions

DOI: https://doi.org/10.1080/15384101.2025.2601237

J Transl Med. 2025 Dec 08. 23(1): 1384

Hypoxic migrasomes drive colorectal cancer liver metastasis by mediating CD5L+ macrophage efferocytosis via NRP2/PROX1 axis.

Yuqi Luo, Yiwen Huang, Yaoxing Huang, Longzhen Chen.

OBJECTIVE: Migrasomes are a newly discovered class of extracellular vesicles, yet their roles in colorectal cancer (CRC) metastasis remain poorly understood. This study aimed to investigate the functional significance of CRC-derived migrasomes, particularly under hypoxic conditions, in promoting liver metastasis and modulating the tumor immune microenvironment.
METHODS: Migrasomes in CRC tissues and cells were characterized using transmission electron microscopy or immunofluorescence. A mouse liver metastasis model and single-cell RNA sequencing (scRNA-seq) were employed to explore functional outcomes and cellular interactions.
RESULTS: Migrasome structures were observed in both primary CRC and metastatic liver tissues, and live-cell imaging revealed hypoxic CRC cells released increased numbers of migrasomes. In vivo imaging demonstrated hepatic accumulation of hypoxic migrasomes and enhanced liver metastasis in mice. ScRNA-seq of liver metastases revealed that hypoxic migrasomes reprogrammed the tumor microenvironment, notably expanding a Tmem45a⁺ fibroblast subset with myofibroblast features and promoting CD5L⁺ macrophage differentiation with elevated efferocytic capacity. Mechanistically, NRP2, enriched in migrasomes derived from hypoxic CRC cells, was transferred to macrophages, binding with PROX1 to drive CD5L expression and upregulate of efferocytosis receptors. NRP2 knockdown in CRC cells abrogated migrasome-induced CD5L⁺ macrophage polarization and impaired apoptotic tumor cell clearance.
CONCLUSION: These findings demonstrate that hypoxic CRC-derived migrasomes facilitate liver metastasis by reprogramming stromal and immune compartments, particularly through NRP2/PROX1-mediated education of macrophages toward a pro-efferocytic CD5L⁺ phenotype. Our study reveals a previously unrecognized intercellular communication axis involving migrasomes in CRC progression and provides a potential therapeutic target for metastatic disease.

Keywords: Colorectal cancer liver metastasis; Hypoxic migrasome; Macrophage efferocytosis

DOI: https://doi.org/10.1186/s12967-025-07485-0

Sci Rep. 2025 Dec 11.

A novel migrasome-associated lncRNA model for clear cell renal cell carcinoma prognosis and immune response prediction.

Linlin Zhang, Longxin Dong, Tengzheng Tian, Jing Liu, Haozhe Zhang, Weitao Zhang.

The most common kind of kidney cancer, clear cell renal cell carcinoma (ccRCC), presents challenges in clinical management and prognosis. Although the roles of long non-coding RNAs (lncRNAs) and migrasomes in tumorigenesis and tumor development have gradually attracted attention, there is currently relatively little research on migrasomes in ccRCC. The objective of this research was to construct a migrasome-associated lncRNAs model and assess its predictive value for immune reactions and survival outcomes in patients with ccRCC. First, the Cancer Genome Atlas (TCGA) database was utilized to acquire transcriptome data and clinical information pertaining to ccRCC. Using this data, Pearson correlation identified migrasome-associated lncRNAs, and Cox regression analysis was utilized to build a prognostic model. Subsequently, the model's utility was validated against clinical characteristics from multiple perspectives. Enrichment results, immune infiltration analysis, Tumor Mutational Burden (TMB), and Tumor Immune Dysfunction and Exclusion (TIDE) analysis delineated differences in the tumor immune microenvironment. Quantitative real-time polymerase chain reaction (qPCR) confirmed the expression of key lncRNAs in the model. Finally, a interference plasmid for UBE2Q1-AS1 was constructed and transfected into 786-O cells. The CCK-8 assay and Transwell assay were then used to verify its effects on cell proliferation and migration. A prognostic model incorporating 12 migrasome-associated lncRNAs with independent prognostic value was developed, demonstrating robust predictive power across various clinical features. Enrichment and immune infiltration analyses revealed significant disparities in immune responses between groups. TMB and TIDE analyses indicated that high TMB groups had lower survival rates compared to low TMB groups, and TIDE scores were greater for high-risk groups than for low-risk groups. Additionally, the quantities of expression for migrasome-associated lncRNAs were validated in human ccRCC cell line. Cell experiments revealed that interference of UBE2Q1-AS1 significantly inhibited the proliferation and migration of 786-O cells. The migrasome-associated lncRNA model accurately predicts ccRCC patient prognosis, offering new insights for immunotherapy and clinical applications.

Keywords: Clear cell renal cell carcinoma; LncRNAs; Migrasome; Prognostic model

DOI: https://doi.org/10.1038/s41598-025-31455-7

Transl Androl Urol. 2025 Nov 30. 14(11): 3595-3612

Junming Huang, Juezhuo Huang, Jueling Wei, Jinji Chen, Shaohua Chen, Guanglin Yang.

Background: Clear cell renal cell carcinoma (ccRCC) represents the most common histological subtype of kidney cancer and constitutes a major global health burden. Despite increasing recognition of the roles of migrasome-related long non-coding RNAs (MRLs) in tumor biology, their prognostic relevance in ccRCC remains largely undefined. Therefore, this study aimed to systematically identify MRLs associated with ccRCC prognosis and construct a robust prognostic model to improve risk stratification and guide potential therapeutic strategies.
Methods: To identify MRLs, we initially performed a correlation analysis integrating transcriptomic profiles with clinical parameters of ccRCC patients from The Cancer Genome Atlas (TCGA). Leveraging the expression matrix of MRLs, we subsequently employed the least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic signature. A comprehensive assessment was carried out to determine the model's predictive robustness. At single-cell resolution, we delineated the cellular composition of ccRCC, capturing transcriptional heterogeneity across distinct cell populations. Ultimately, long non-coding RNAs (lncRNAs) derived from the prognostic model were experimentally validated in clinical specimens through reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and the landscape of migrasome-related genes (MRGs) was further defined using single-cell RNA sequencing (scRNA-seq) data.
Results: A prognostic signature comprising five MRLs-EMX2OS, AC106897.1, AC087645.2, AC121338.2, and C5orf66-was established to stratify patient risk. The derived risk score was subsequently validated as an independent predictor of overall survival (OS) in ccRCC patients. A nomogram integrating this score exhibited strong predictive capability. Immune landscape analysis uncovered marked differences in functional immune features between high- and low-risk cohorts defined by the lncRNA-based model. Notably, the high-risk group displayed enrichment of immune-related processes, whereas the low-risk group demonstrated enhanced predicted responsiveness to a spectrum of therapeutic compounds. scRNA-seq identified 17 distinct cellular subpopulations and highlighted the involvement of tumor cell-intrinsic vascular endothelial growth factor (VEGF) signaling in modulating migrasome-associated molecular programs.
Conclusions: This study emphasizes the prognostic utility of a signature comprising five MRLs for ccRCC, offering valuable insights for clinical risk stratification and therapeutic decision-making. Additionally, modulation of tumor cell migration and migrasome function via the VEGF signaling pathway offers a mechanistic basis for targeted intervention.

Keywords: Migrasome; clear cell renal cell carcinoma (ccRCC); immunology; long non-coding RNA (lncRNA); single-cell RNA sequencing (scRNA-seq)

DOI: https://doi.org/10.21037/tau-2025-541