Single-cell sequencing in bladder cancer: new insights from tumor cell diversity to individualized treatment strategies

Bladder cancer (BCa) is a prevalent malignancy and major cause of cancer-related mortality in men, with clinical outcomes still varying despite advances in personalized treatments. High inter- and intra-tumor heterogeneity significantly contributes to this variability. While traditional high-throughput sequencing has provided insights into BCa mechanisms, driver genes, and clinical strategies, it falls short in completely elucidating cellular heterogeneity. Recently, single-cell sequencing (SCS) technologies have substantially enhanced the detection of tumor heterogeneity by improving sensitivity, accuracy, and efficiency. Single-cell transcriptome sequencing offers unbiased, high-resolution analysis of gene expression patterns at the single-cell level, offering essential insights into BCa pathogenesis. This article reviews advancements in SCS technology and its applications in evaluating tumor heterogeneity, the tumor microenvironment, metastasis, and treatment resistance, offering new perspectives for future BCa research.

Authors

Institutions

Publication Details

Journal
Cancer Cell International
Published
2025-12-03
DOI
https://doi.org/10.1186/s12935-025-04094-1
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Single-cell sequencing in bladder cancer: new insights from tumor cell diversity to individualized treatment strategies

Yan Wang, Cong Yin, Shuai Ye, Jiahao Jiang et al.
Cancer Cell International
Single-cell and spatial transcriptomics
article

Single-cell sequencing in bladder cancer: new insights from tumor cell diversity to individualized treatment strategies

Yan Wang, Cong Yin, Shuai Ye, Jiahao Jiang, Cen Liufu, Tao Zhu, Bentao Shi
article en

Abstract

Bladder cancer (BCa) is a prevalent malignancy and major cause of cancer-related mortality in men, with clinical outcomes still varying despite advances in personalized treatments. High inter- and intra-tumor heterogeneity significantly contributes to this variability. While traditional high-throughput sequencing has provided insights into BCa mechanisms, driver genes, and clinical strategies, it falls short in completely elucidating cellular heterogeneity. Recently, single-cell sequencing (SCS) technologies have substantially enhanced the detection of tumor heterogeneity by improving sensitivity, accuracy, and efficiency. Single-cell transcriptome sequencing offers unbiased, high-resolution analysis of gene expression patterns at the single-cell level, offering essential insights into BCa pathogenesis. This article reviews advancements in SCS technology and its applications in evaluating tumor heterogeneity, the tumor microenvironment, metastasis, and treatment resistance, offering new perspectives for future BCa research.

Cancer Cell InternationalVol. 26(1)
Anhui Medical University (CN), Shantou University (CN), Longgang Central Hospital (CN), Shantou University Medical College (CN), Peking University Shenzhen Hospital (CN), University of Hong Kong - Shenzhen Hospital (CN), Shenzhen University Health Science Center (CN), Second Affiliated Hospital of Anhui Medical University (CN), Shenzhen Second People's Hospital (CN)
Openalex Percentile: Top 66%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Single-cell sequencing in bladder cancer: new insights from tumor cell diversity to individualized treatment strategies — Yan Wang, Cong Yin, et al. · Cancer Cell International (2025) | TGRS Research Map | TGRS