转录组
仿形(计算机编程)
膀胱癌
癌症研究
计算生物学
生物
医学
癌症
计算机科学
内科学
基因
基因表达
操作系统
遗传学
作者
Zhenduo Shi,Zhuo Sun,Zuobin Zhu,Xing Liu,Jun‐Zhi Chen,Lin Hao,Jiefei Zhu,Kun Pang,Di Wu,Yang Dong,Yufei Liu,Weihua Chen,Qing Liang,Shichao Zhuo,Conghui Han
摘要
Abstract Background Recurrent bladder cancer is the most common type of urinary tract malignancy; nevertheless, the mechanistic basis for its recurrence is uncertain. Innovative technologies such as single‐cell transcriptomics and spatial transcriptomics (ST) offer new avenues for studying recurrent tumour progression at the single‐cell level while preserving spatial data. Method This study integrated single‐cell RNA (scRNA) sequencing and ST profiling to examine the tumour microenvironment (TME) of six bladder cancer tissues (three from primary tumours and three from recurrent tumours). Findings scRNA data‐based ST deconvolution analysis revealed a much higher tumour heterogeneity along with TME in recurrent tumours than in primary tumours. High‐resolution ST analysis further identified that while the overall natural killer/T cell and malignant cell count or the ratio of total cells was similar or even lower in the recurrent tumours, a higher interaction between epithelial and immune cells was detected. Moreover, the analysis of spatial communication reveals a marked increase in activity between cancer‐associated fibroblasts (CAFs) and malignant cells, as well as other immune cells in recurrent tumours. Interpretation We observed an enhanced interplay between CAFs and malignant cells in bladder recurrent tumours. These findings were first observed at the spatial level.
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