Front Immunol. 2026 ;17
1782717
Migrasomes, recently discovered extracellular organelles, are implicated in cancer progression and immune regulation. Nevertheless, their roles in cancer immunotherapy resistance remain poorly understood. To address this gap, we integrated cutting-edge computational engines to identify migrasome-associated targets modulating cancer immunotherapy. Using the Cancer Immunology Data Engine (CIDE) covering 5,957 patients across 17 tumor types, TSPAN6 was identified as significantly associated with adverse immunotherapy outcomes. Pan-cancer validation across the TCGA, ICGC, and CPTAC cohorts confirmed that elevated TSPAN6 expression significantly correlates with adverse prognosis. Using the pan-cancer atlas of over 4.4 million cells, we revealed the specific expression of TSPAN6 in malignant cells. Additionally, TSPAN6-high malignant cells significantly up-regulate immune checkpoint genes including CD274, NECTIN2, and LGALS9, thereby enhancing immunosuppressive interactions with exhausted T cells. Genetic ablation of TSPAN6 in co-culture models enhanced anti-tumor immunity, functionally validating this mechanism. Spatial transcriptomics further demonstrated TSPAN6 enrichment in tumor cores and its significant downregulation in immunotherapy responders compared to non-responders. In our validation cohorts, paired serum samples from 44 cancer patients showed significantly decreased TSPAN6 levels following immunotherapy. To overcome TSPAN6-mediated resistance, we computationally screened 1,615 FDA-approved compounds for inhibiting TSPAN6. Among these drugs, mitoxantrone demonstrated high-affinity binding to TSPAN6 through hydrogen bonding and hydrophobic interactions with TSPAN6. Collectively, our findings establish TSPAN6 as a migrasome-related regulator driving adverse immunotherapy outcomes and responses. Targeting TSPAN6, potentially with mitoxantrone, presents a potential strategy to enhance immunotherapy efficacy.
Keywords: bioinformatics; immunotherapy; microenvironment; migrasome; multi-omics