Evidence map›Paper›PMID 39523319›Full record

ArticleJournal of translational medicine2024

Single cell analysis identified a basal cell transition state associated with the development and progression of bladder cancer.

Yang Li, Pengjie Shi, Yuhong Ding, Zhipeng Yao, Lilong Liu, Junyi Hu, Zhenghao Liu, Jinxu Li, Ke Chen, Yaxin Hou

Abstract read
In one paragraph

Article in Journal of translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Single-cell transcriptome analysis reveals DNMT1Journal of translational medicine · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yang Li *Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Pengjie ShiDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yuhong DingDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhipeng YaoDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Lilong LiuDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Junyi HuDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhenghao LiuDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Jinxu LiDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Ke ChenDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. shenke@hust.edu.cn.
Yaxin HouDepartment of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. 18351033626@163.com.ORCID 0000-0002-1330-6506

Funding

Fundamental Research Funds for the Central Universities YCJJ20241411Hebei Provincial Postdoctoral Science Foundation 2023M731199National Natural Science Foundation of China 82303623Postdoctoral Research Foundation of China GZB20230243Tongji Medical College, Huazhong University of Science and Technology 2021RCYJ005Tongji Medical College, Huazhong University of Science and Technology 2022YBJ018
6 · The paper itself

Abstract

backgroundBladder cancer (BC) is a prevalent malignancy characterized by significant cellular heterogeneity. While single-cell multi-omics studies have provided valuable insights, much of the existing data remains underexplored, limiting our understanding of BC's molecular mechanisms. Uncovering the pathogenesis of BC and finding new treatment methods are urgent problems to be solved. This study aims to address this gap by re-analyzing available single-cell datasets to uncover novel insights into BC.

methodsIn this study, we retrieved three single-cell transcriptome datasets by searching the Gene Expression Omnibus (GEO) database, focusing on single-cell sequencing of normal mouse bladder within the past 5 years. Through quality control and batch effect elimination, we obtained a total of 24,930 cells including epithelial, stromal, and immune cells. Subgroup analysis, pseudotemporal analysis, cell-cell communication, and transcription factor analysis were conducted specifically on epithelial cells to identify a transitional state during basal cell differentiation. We further compared the expression profiles of key transcription factors in cancer and normal tissues. In addition, we also performed immunohistochemical staining and survival analysis for key transcription factors.

resultsSubgroup analysis revealed multiple subtypes of epithelial cells, including basal, umbrella, and intermediate cells. Through pseudotemporal analysis, we discovered the developmental trajectory from basal cells to umbrella cells and further found that Basal_I is a transitional state for basal cell differentiation. Cell-to-cell communication analyses highlighted the pivotal role of Basal_I in cell-cell interactions, and key ligand-receptor pairs associated with cancer progression were also identified. Furthermore, elevated expression levels of key transcription factors in Basal_I were found to be closely associated with the stage and prognosis of BC. Immunohistochemical staining results further confirmed the upregulated expression of these transcription factors in BC.

conclusionsCollectively, we found a transitional state of basal cells in normal bladder epithelial cells in mice, which may be related to the occurrence and development of BC, providing important clues for further understanding of the pathogenesis of BC. Our study provided possible molecular mechanisms or target for the research and treatment of BC.

Indexed as

Disease ProgressionGene Expression Regulation, NeoplasticSingle-Cell AnalysisUrinary Bladder NeoplasmsAnimalsCell CommunicationCell DifferentiationEpithelial CellsGene Expression ProfilingHumansMiceTranscription FactorsTranscriptomeTranscription FactorsBasal cellBladder cancerscRNA-seq

Identifiers

PMID39523319
PMCPMC11550547

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.