Migrasomes are a newly discovered type of extracellular vesicle (EV) formed during cell migration, playing a pivotal role in intercellular communication. These vesicles are generated by retracting fibers of migrating cells and encapsulate various molecules, such as proteins, lipids, and RNA, allowing the transfer of biochemical signals to neighboring cells. Current evidence suggests that migrasomes are involved in a wide range of physiological processes such as embryogenesis, angiogenesis, immune modulation, and mitochondrial quality control. Moreover, migrasomes are implicated in pathological conditions, including cancer metastasis, cardiovascular diseases, and viral infections. To fully understand their significance, it is critical to first explore the molecular mechanisms underlying their formation and function. Recent studies have shed light on the biogenesis, release, and biological properties of migrasomes, all of which are key to understanding their role in cell-to-cell communication. In this review, we provide an up-to-date summary of migrasome biogenesis, release, characterization, and their biological activities in intercellular communication, while also proposing potential new functions for these vesicles.

Prostate cancer (PCa), with high heterogeneity and poor prognosis, is one of the most common malignant tumors in men. Circular RNAs (circRNAs) have been identified in tumor progression and resistance to medication in numerous studies. However, the role of circ_0001047 in PCa is unclear. In this research, we found that circ_0001047 had low expression in PCa cells and tissues and was negatively correlated with testosterone secretion in vivo. Overexpression of circ_0001047 inhibited the proliferation, migration, invasion, and anti-apoptotic abilities of human PCa cells in vitro. Mechanistically, circ_0001047 promoted the expression of FKBP5 through sponge adsorption of miR-122-5p and then inhibited the proliferation, anti-apoptotic migration, and invasion abilities of PCa cells. In addition, overexpression of circ_0001047 enhanced the sensitivity of PCa cells to abiraterone by inhibiting AKT phosphorylation activation through upregulation of FKBP5/PHLPP1. This study revealed a novel mechanism by which circ_0001047 regulates PCa progression and treatment sensitivity via the miR-122-5p/FKBP5/PHLPP1/AKT axis. These findings deepen our comprehension of the molecular mechanisms in latent PCa progression and treatment resistance. Graphical Abstract

Plant derived exosome-like nanoparticles (PELNs) are emerging as a powerful tool for treating cancers. Among them, PELNs derived from traditional Chinese m

Bladder cancer (BLCA) is a prevalent malignancy with substantial consequences for patient health. This study aimed to elucidate the underlying mechanisms of BLCA through integrated multi-omics analysis. Tumor and adjacent tissues from BLCA patients underwent transcriptomic, whole-exome sequencing, metabolomic, and intratumoral microbiome analyses. These data were integrated with public datasets to identify key genes, metabolites, and microorganisms. Molecular subtypes were defined by key gene expression and compared for pathways, immune profiles, mutations, immunotherapy response, and drug sensitivity. Prognostic relevance was validated in external cohorts. Single-cell sequencing was applied to reveal cellular localization of key genes. Three key genes (AHNAK, CSPG4, NCAM1), 90 metabolites, and two microbes (Sphingomonas koreensis, Rhodospirillaceae) were identified. Key genes negatively correlated with metabolites but not with microbes. BLCA samples were classified into two molecular clusters with distinct ECM organization, metabolic features, immune checkpoint expression, and therapeutic sensitivity. NCAM1 correlated positively with γδ T cells and negatively with M0 macrophages. Single-cell analysis revealed nine major cell types, with fibroblasts displaying the highest expression of key genes, particularly elevated AHNAK in specific fibroblast subtypes. Drug prediction and docking identified candidate compounds targeting these genes with stable binding potential. This comprehensive multi-omics analysis links key genes, metabolites, and microbes to BLCA pathogenesis. Fibroblasts emerge as central regulators, while identified gene-metabolite interactions and microbial associations provide novel insights into tumor heterogeneity. These findings highlight potential biomarkers and therapeutic targets to support precision treatment in BLCA.

Introduction: Bladder cancer (BCa) is one of the top ten most common cancers, yet its underlying mechanisms remain unclear. This study aimed to explore the potential molecular mechanisms of BCa using multi-omics and single-cell analysis. Methods: First, differential analysis of transcriptome data related to BCa from public databases was performed, and a risk model was then developed using 101 different machine learning algorithms to determine prognostic genes, followed by independent prognostic analysis to construct a nomogram. Immune infiltration analysis was performed to explore the impact of prognostic genes on the tumor microenvironment. Metabolomics, proteomics, and post-translational modification data from BCa tumor and adjacent non-tumor tissues were used to explore the relationships between prognostic genes and various omics levels. Finally, single-cell analysis identified key cells involved in BCa pathogenesis, and in vitro experiments validated the expression and function of key genes. Results: The risk model constructed by 8 prognostic genes identified using 101 algorithms effectively predicted the survival outcomes of BCa patients. Furthermore, risk scores, pathological T stage, and pathological N stage were confirmed as independent prognostic factors for the nomogram construction. Interestingly, high-risk patients showed a significantly lower response to PD-L1 treatment, with higher TIDE scores. Omics analysis revealed a close relationship between prognostic genes and proteomics, metabolomics, and post-translational modifications. Specifically, FLNC and MYH11 may influence BCa progression through phosphorylation and succinylation. Single-cell analysis identified fibroblasts as key cells in BCa. Functional experiments showed that MYH11 knockdown promoted cell proliferation, migration, and invasion. Conclusion: This study identified 8 prognostic genes to construct a risk model, and suggest that MYH11 is a potential diagnostic and prognostic biomarker for BCa.

Background: Bladder cancer (BLCA) is a common malignant tumor whose pathogenesis has not yet been fully elucidated. This study analyzed prognostic genes in BLCA by integrating transcriptomics and proteomics data, and established prognostic models, aiming to offer novel insights for BLCA therapy.