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鼻咽癌中记忆B细胞与肿瘤细胞之间的细胞信号串扰不容忽视:它们在肿瘤进展和治疗策略中的作用重大。

The cellular signaling crosstalk between memory B cells and tumor cells in nasopharyngeal carcinoma cannot be overlooked: Their involvement in tumor progression and treatment strategy is significant.

作者信息

Li Haiyu, Bian Yanjie, Xiahou Zhikai, Zhao Zhijie, Zhao Fu, Zhang Qinghan

机构信息

Department of Clinical Laboratory, Songjiang Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Xinxiang Medical University, Xinxiang, China.

出版信息

J Cancer. 2025 Jan 1;16(1):288-314. doi: 10.7150/jca.101420. eCollection 2025.

Abstract

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. 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. 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. 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.

摘要

鼻咽癌(NPC)是指发生于鼻咽腔顶壁及侧壁的恶性肿瘤。通常情况下,患者往往在病情已显著进展时才被诊断出该病,而晚期鼻咽癌患者在靶向治疗的反应率和总体临床生存率方面往往预后不佳。人们已经探索了多种分子机制,包括髓源性抑制细胞和PD-L1等因子,以改善鼻咽癌的治疗效果。然而,在早期识别症状、准确预测癌症复发和扩散的可能性以及设计成功的治疗方法方面,仍存在挑战。B细胞及其相应通路的激活为开发增强免疫治疗策略提供了潜力。然而,对B细胞与NPC肿瘤细胞之间复杂关联的全面理解仍不完整。因此,本研究采用单细胞多组学分析来研究与人类NPC中B细胞亚群相关的分子生物标志物和预后因素,同时探究其潜在机制。基因表达综合数据库提供了从鼻咽癌患者获取的肿瘤和血液样本。随后,我们对这些单细胞数据进行了分析。在评估NPC样本质量后,我们使用R包“Harmony”,利用主成分分析结果来减少批次差异。通过基因本体分析、基因集富集分析和京都基因与基因组百科全书分析,研究NPC肿瘤B细胞亚群中的差异表达基因。使用Monocle和Slingshot软件工具研究NPC中B细胞的拟时间轨迹。此外,利用CellChat包预测B细胞不同亚群与癌细胞之间细胞间通讯的发生率。此外,我们使用单变量Cox回归、LASSO和多变量Cox回归分析来构建预后模型。使用ESTIMATE、CIBERSORT和xCell评估肿瘤组织中的免疫细胞浸润情况。此外,利用infercnv评估NPC细胞中拷贝数变异的程度。为预测特定肿瘤样本对化疗的潜在反应,使用了名为“pRRophetic”的R包。单细胞RNA测序有效地识别了NPC中的各种细胞亚群,包括T/NK细胞、B细胞、浆细胞、髓样细胞、肥大细胞和恶性细胞。对B细胞亚群的全面检查显示它们分为13个不同组,每组具有独特的特征和功能。富集分析表明,C4 CD86 + 记忆B细胞可能在抑制病毒入侵和活性中发挥作用。通过轨迹分析,我们绘制了B细胞的分化途径,发现C4 CD86 + 记忆B细胞代表了这一分化过程的最终阶段。此外,信号通讯分析表明,C4 CD86 + 记忆B细胞有可能通过CD99 - CD99、SEMA4 - PLXNB2,尤其是CD46 - JAG1信号通路与恶性细胞启动相互作用。为构建CD86 + 记忆B评分,我们使用单变量Cox回归分析、LASSO回归分析和多变量Cox回归分析,基于C4 CD86 + 记忆B细胞的前100个标记基因筛选出14个基因。结果表明,C4 CD86 + 记忆B细胞可能对NPC中的病毒活性具有抑制作用。然而,CD86 + 记忆B评分较高亚组的患者预后较差。这可能归因于C4 CD86 + 记忆B细胞通过CD46 - JAG1信号通路在肿瘤细胞的增殖和分化中起关键作用。这些发现为鼻咽癌发生的基本机制提供了重要见解。此外,这些因素极大地影响了这种特定类型癌症患者的预后,并为未来治疗方法的发展提供了关键视角。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b72b/11660138/84ff526bb17d/jcav16p0288g001.jpg

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