A combination of ssGSEA and mass cytometry identifies immune microenvironment in muscle-invasive bladder cancer.

A combination of ssGSEA and mass cytometry identifies immune microenvironment in muscle-invasive bladder cancer.
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ssGSEA 和质谱流式分析相结合可识别肌肉浸润性膀胱癌的免疫微环境。

DOI:
10.1002/jcla.23754
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发表时间:
2021-05
影响因子:
2.7
通讯作者:
Li T
Li T
中科院分区:
医学4区
文献类型:
--
作者:
Wang X;Pan L;Lu Q;Huang H;Feng C;Tao Y;Li Z;Hu J;Lai Z;Wang Q;Tang Z;Xie Y;Li T

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肌层浸润性膀胱癌(MIBC)是一种异质性疾病,具有不同的临床病程和治疗反应。为了改善患者的预后,有必要了解这种异质性。我们使用单样本基因集富集分析将35例MIBC病例分为免疫高组和免疫低组。进行生物信息学分析以比较这些组之间的差异。最后,使用单细胞质谱仪(CyTOF)比较两组患者之间的免疫微环境特征。与免疫力低组患者相比,免疫力高组患者的肿瘤浸润免疫细胞数量更多,与抗肿瘤免疫活性相关的基因集富集程度更高。此外,阳性免疫应答相关途径在免疫力高组中更丰富。我们使用CyTOF鉴定了26种免疫细胞亚群,包括细胞毒性T细胞(Tcs)、辅助性T细胞(Ths)、调节性T细胞(Tcells)、B细胞、巨噬细胞、自然杀伤(NK)细胞和树突状细胞(DCs)。此外,在免疫力高组中,CD 45+淋巴细胞比例更高,一个Tc亚群富集。此外,M2巨噬细胞在免疫力低组中高度富集。最后,与免疫力高组相比,免疫力低组中Tcells上PD-1和Tim-3的表达更高,PD-1+ Tcells的比例也更高。总之,免疫力高和免疫力低的MIBC患者组的免疫微环境是异质的。具体而言,在免疫力低组患者的免疫微环境中观察到免疫抑制。在这项研究中,我们研究了MIBC患者的免疫浸润和癌症发展之间的关系。我们收集了35个MIBC癌样本,并使用其RNA谱数据,使用单样本基因集富集分析(ssGSEA)计算每个样本中29个免疫特征的评分。通过生物信息学分析,包括差异基因表达分析、GO分子功能富集分析、GSEA分析,研究免疫力高组和免疫力低组之间的差异。我们还使用单细胞质量细胞术分析了MIBC组织中浸润免疫细胞的组成和功能。我们的研究结果揭示了免疫微环境中异质性的存在,并为MIBC患者的治疗提供了指导。
Muscle‐invasive bladder cancer (MIBC) is a heterogeneous disease with varying clinical courses and responses to treatment. To improve the prognosis of patients, it is necessary to understand such heterogeneity. We used single‐sample gene set enrichment analysis to classify 35 MIBC cases into immunity‐high and immunity‐low groups. Bioinformatics analyses were conducted to compare the differences between these groups. Eventually, single‐cell mass cytometry (CyTOF) was used to compare the characteristics of the immune microenvironment between the patients in the two groups. Compared with patients in the immunity‐low group, patients in the immunity‐high group had a higher number of tumor‐infiltrating immune cells and greater enrichment of gene sets associated with antitumor immune activity. Furthermore, positive immune response‐related pathways were more enriched in the immunity‐high group. We identified 26 immune cell subsets, including cytotoxic T cells (Tcs), helper T cells (Ths), regulatory T cells (Tregs), B cells, macrophages, natural killer (NK) cells, and dendritic cells (DCs) using CyTOF. Furthermore, there was a higher proportion of CD45+ lymphocytes and enrichment of one Tc subset in the immunity‐high group. Additionally, M2 macrophages were highly enriched in the immunity‐low group. Finally, there was higher expression of PD‐1 and Tim‐3 on Tregs as well as a higher proportion of PD‐1+ Tregs in the immunity‐low group than in the immunity‐high group. In summary, the immune microenvironments of the immunity‐high and immunity‐low groups of patients with MIBC are heterogeneous. Specifically, immune suppression was observed in the immune microenvironment of the patients in the immunity‐low group. In this study, we investigated the relationship between immune infiltration and cancer development in MIBC patients. We collected 35 MIBC cancerous samples and used their RNA profile data to calculate the scores of 29 immune signatures in each sample using single sample gene set enrichment analysis (ssGSEA). Bioinformatics analyses including differential gene expression analysis, GO molecular function enrichment analysis, GSEA were performed to investigate the differences between the immunity‐high and immunity‐low groups. We also analyzed the composition and function of infiltrating immune cells in MIBC tissues using single‐cell mass cytometry. Our findings reveal the presence of heterogeneity in the immune micro‐environment and provides guidance for the therapy of patients with MIBC.
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