Journal Article10.1002/ctm2.1338
Integrated single‐cell and spatial transcriptomic profiling reveals higher intratumour heterogeneity and epithelial–fibroblast interactions in recurrent bladder cancer
Zhenjun Shi,Zhuo Sun,Zuo-bin Zhu,Xing Liu,Jun-Zhi Chen,Lin Hao,Jie-Fei Zhu,Kun Pang,Di Wu,Yang Dong,Yufei Liu,Wei-hua Chen,Qing Liang,Shichao Zhuo,Cong Han +14 more
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TL;DR: An enhanced interplay between CAFs and malignant cells in bladder recurrent tumours is observed, and a marked increase in activity between cancer‐associated fibroblasts andmalignant cells, as well as other immune cells in recurrent tumour tissues.
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Abstract: 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.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).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.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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Citations
Relationship between clonal evolution and drug resistance in bladder cancer: A genomic research review
Zhouting Tuo,Ying Zhang,D X Li,Yetong Wang,Ruicheng Wu,Jie Wang,Qingxin Yu,Luxia Ye,Fanglin Shao,Dilinaer Wusiman,Yubo Yang,Koo Han Yoo,Mang Ke,Uzoamaka Okoli,William C. Cho,Susan Heavey,Wuran Wei,Dechao Feng +17 more
TL;DR: This genomic review explores the relationship between clonal evolution and drug resistance in bladder cancer, highlighting how clonal heterogeneity and dynamic transformations within tumor cells drive therapy resistance and disease progression.
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Spatial transcriptomics in cancer research and potential clinical impact: a narrative review
Michael A. Cilento,Christopher J. Sweeney,Lisa M. Butler +2 more
TL;DR: Spatial transcriptomics provides novel insights into the tumor microenvironment and has the potential to improve cancer diagnosis and treatment.
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Crosstalk between bladder cancer and the tumor microenvironment: Molecular mechanisms and targeted therapy
Xiaole Lu,Liang Cheng,Chenwei Yang,Jian Huang,Xu Chen +4 more
TL;DR: This study reviews the molecular mechanisms of bladder cancer's crosstalk with the tumor microenvironment, highlighting key cellular components and epigenetic factors driving metastasis, treatment resistance, and tumorigenesis, and discusses targeted therapies and future perspectives.
Single-cell RNA sequencing and spatial transcriptomics of bladder Ewing sarcoma
Weipu Mao,Kangjie Xu,Keyi Wang,Houliang Zhang,Jie Ji,Jiang Geng,Si Sun,Chaoming Gu,Atrayee Bhattacharya,Fang Cheng,Tao Tao,Ming Chen,Jian Wu,Shuqiu Chen,Chao Sun,Bing Xu +15 more
TL;DR: This study employs single-cell RNA sequencing and spatial transcriptomics to investigate bladder Ewing sarcoma's pathogenesis, revealing specialized epithelial and mast cells, and identifying TNFRSF12A upregulation and a potential therapeutic target, Enavatuzumab.
Integrating Multi-Modal Transcriptomics Identifies Cellular Subtypes with Distinct Roles in PDAC Progression
Jun Wu,Tenghui Dai,Ziyue Li,Meng Pan,Wei Zhang,Hao Chen,Guansheng Zheng,Li Qiao,Qizhou Lian,Yang Liu,Jierong Chen +10 more
TL;DR: This study integrates multi-modal transcriptomics to identify distinct cellular subtypes in pancreatic ductal adenocarcinoma (PDAC) microenvironment, revealing six fibroblast and eight macrophage subtypes with prognostic significance, and highlighting potential therapeutic targets.
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