Prognostic and therapeutic implications of the immune landscape in Mantle Cell Lymphoma

Abstract

Abstract Background The comprehensive immune landscape of mantle cell lymphoma (MCL) remains incompletely characterized. Immune cells within the tumor microenvironment (TME) critically influence tumor biology and treatment response, underscoring their research value. We therefore explored the tumor immune microenvironment (TIME) as a potential indicator for MCL prognosis and therapeutic guidance. Methods Gene expression profiles from 403 MCL samples across 8 independent GEO datasets were integrated. TIME composition was assessed using xCell, followed by hierarchical clustering to establish an immune-based classification. This classification was validated, and differences in immune gene expression, multi-omics profiles, clinical outcomes, and therapy responses were analyzed across datasets. Immune heterogeneity was further examined using single-cell transcriptomes from 8 MCL patients. Results We established a novel TIME classification system, stratifying MCL patients into three immune subtypes (IM1, IM2, IM3) with unique prognostic profiles. IM1 was defined by T-cell predominance, IM2 by B-cells, and IM3 by other cell types. IM1 demonstrated the most favorable prognosis, highest immune score, elevated immune checkpoint expression, and the greatest frequency of IGHV mutations. Conversely, IM3 exhibited pronounced genomic instability, resistance to ibrutinib, sensitivity to mirin, and enrichment in cell cycle pathways. Leveraging subtype-specific differentially expressed genes, we developed a prognostic model that effectively categorized patients into low- and high-risk groups with divergent outcomes. Conclusion Our research defines distinct MCL immune subtypes, revealing their significant impact on prognosis and treatment. Each subtype displays unique immunological and genetic features, clinical trajectories, and drug responses. We provide a user-friendly web tool (https://puh3.shinyapps.io/Immune_landscape_of_MCL/) for predicting immune subtypes and prognosis in MCL patients. These insights into the immune landscape may reveal new therapeutic strategies, potentially enhancing MCL management.