CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Pan-cancer single-cell and spatial transcriptomics analyses delineate response-associated heterogeneity and therapeutic targets of tumor-infiltrating B cells following immune checkpoint blockade.
Pan-cancer single-cell and spatial transcriptomics analyses delineate response-associated heterogeneity and therapeutic targets of tumor-infiltrating B cells following immune checkpoint blockade.
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肿瘤浸润B细胞(TIBs)正逐渐成为抗肿瘤免疫的核心调控者,但其生物学功能、空间生态位以及与TIL(肿瘤浸润淋巴细胞)的交互作用在不同癌症类型中差异很大,尤其是在癌症免疫治疗方面。
然而,一个将其转录谱与免疫检查点阻断(ICB)应答联系起来的泛癌图谱一直缺失。在此,我们呈现了泛癌ICB应答B细胞图谱,该图谱基于688个单细胞转录组(24种癌症类型,241,645个细胞)构建。鉴定出24个B细胞亚群,并揭示了它们在各种癌症中的比例动态变化和转录组特征。基于B细胞亚群比例的NMF分析鉴定出5种TIME亚型,其中TIME-Plasma和TIME-Memory表现出凋亡受抑、抗原呈递更高,且在应答者中富集,与多种癌症中更好的生存相关。伪时间轨迹描绘了两条保守的分化路径,它们在记忆B细胞节点处分叉,并与B细胞凋亡和ICB应答表现出不同的相关性。泛癌空间解卷积显示,包括浆细胞、记忆B细胞和活化B细胞在内的若干应答者来源B细胞亚群,相比非应答者来源B细胞亚群,更倾向于共出现。利用泛癌TCGA数据集,揭示了来自不同应答组的B细胞亚群的临床异质性。
我们构建了泛癌ICB应答Geneformer模型,并对所有基因进行了计算机扰动。鉴定出13个与B细胞ICB应答状态转换显著相关的候选基因。
总体而言,我们的研究阐明了TIBs的异质性,并增进了我们对肿瘤免疫治疗背景下癌症特异性B细胞亚群的理解。
Tumor-infiltrating B cells (TIBs) are emerging as central regulators of anti-tumor immunity, but their biological functions, spatial niches, and cross talk with tumor-infiltrating lymphocytes vary widely across cancer types, particularly with regard to cancer immunotherapies. Yet a pan-cancer atlas linking their transcriptional profile to the immune checkpoint blockade (ICB) response has been missing.
Here, we presented the pan-cancer ICB response B cell atlas, constructed from 688 single-cell transcriptomes (24 cancer types, 241,645 cells). Twenty-four B cell subsets were identified, and their proportion dynamics and transcriptomic features across cancers were revealed. B cell subsets proportion-based NMF analyses identified 5 TIME subtypes in which TIME-Plasma and TIME-Memory showing repressed apoptosis, higher antigen presentation, and enrichment in responders were correlated with better survival in several cancers.
Pseudo-time trajectories delineated two conserved differentiation pathways that branch at the memory B cell node and showed distinct correlations with B cell apoptosis and ICB response. Pan-cancer spatial deconvolution showed that several responder-derived B cell subsets including plasma cells, memory B cells, and activated B cells were more co-occurred compared to non-responder-derived B cell subsets. Utilizing pan-cancer TCGA datasets, the clinical heterogeneity of B cell subsets from distinct response groups was revealed.
We constructed a pan-cancer ICB response Geneformer model and in silico perturbed all genes. Thirteen candidate genes, which were significantly correlated with the B cell ICB response state transition, were identified.
Overall, our study illuminates the heterogeneity of TIBs and improves our understanding of cancer-specific B cell subsets within the context of tumor immunotherapies.
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