摘要：

Background: Nasopharyngeal carcinoma (NPC) refers to a cancerous tumor that develops in the upper and side walls of the nasopharyngeal cavity. Typically, individuals are often diagnosed with the disease when it has already progressed significantly, and those with advanced NPC tend to have an unfavorable outlook in terms of response rate to targeted treatments and overall clinical survival. Various molecular mechanisms, including Myeloid-derived suppressor cells and factors like PD-L1, have been explored to enhance the outcome of NPC. However, there are still challenges to be addressed in terms of identifying symptoms at an early stage, making precise predictions about the chances of cancer returning and spreading, and devising successful approaches for treatment. The activation of B cells and their corresponding pathways holds potential for developing enhanced immune therapeutic strategies. Nevertheless, the comprehensive understanding of the intricate association between B cells and NPC tumor cells remains incomplete. Hence, this study employed single-cell multi-omics analysis to investigate the molecular biomarkers and prognostic factors linked to B cell subpopulations in human NPC while examining the underlying mechanisms. Materials and Methods: The Gene Expression Omnibus database provided tumor and blood samples obtained from patients diagnosed with NPC. Subsequently, we analyzed these single-cell data. Following the assessment of NPC sample quality, we employed the R package 'Harmony' to mitigate batch discrepancies using PCA outcomes. The analysis of Gene Ontology, Gene Set Enrichment Analysis, and Kyoto Encyclopedia of Genes and Genomes was used to examine differentially expressed genes in B cell subpopulations of NPC tumors. The pseudo-temporal trajectories of B cells in NPC were studied using the Monocle and Slingshot software tools. In addition, the CellChat package was utilized to predict the incidence of intercellular communication between different subpopulations of B cells and cancerous cells. Furthermore, we utilized univariate Cox regression, LASSO, and multivariate Cox regression analysis to construct prognostic models. The immune cell infiltration was evaluated in tumor tissues using ESTIMATE, CIBERSORT, and xCell. Furthermore, the infercnv was employed to assess the extent of copy number variation in NPC cells. To forecast the potential reaction of particular tumor samples to chemotherapy, the R package called 'pRRophetic' was utilized. Results: Single-cell RNA sequencing effectively identified various cell subgroups in NPC, including T/NK cells, B cells, plasma cells, myeloid cells, mast cells, and malignant cells. A comprehensive examination of the B cell subgroups revealed their division into 13 distinct groups, each with unique characteristics and functions. Enrichment analysis indicated that C4 CD86+ Memory B cells may play a role in inhibiting viral invasion and activity. Through trajectory analysis, we mapped the differentiation pathways of B cells and found that C4 CD86+ Memory B cells represent the final stage of this differentiation process. Furthermore, signal communication analysis revealed that C4 CD86+ Memory B cells have the potential to initiate interactions with malignant cells via the CD99-CD99, SEMA4-PLXNB2, and notably the CD46-JAG1 signaling pathways. To construct the CD86+ Memory B score, we employed univariate Cox regression analysis, LASSO regression analysis, and multivariate Cox regression analysis to screen 14 genes based on the top 100 marker genes of C4 CD86+ Memory B cells. Conclusion: The results indicate that the C4 CD86+ Memory B cells may have a suppressive impact on viral activity in NPC. However, patients with a higher subgroup of CD86+Memory B scores exhibited a worse prognosis. This could be attributed to the crucial involvement of C4 CD86+ Memory B cells in the proliferation and differentiation of tumor cells, which occurs through the CD46-JAG1 signaling pathway. The discoveries provide significant insights into the fundamental mechanisms of developing NPC. Moreover, these factors greatly influence the prognosis of individuals suffering from this specific type of cancer and offer crucial perspectives for the advancement of future treatment approaches.

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