ReviewGenes & development2025
Deciphering normal and cancer stem cell niches by spatial transcriptomics: opportunities and challenges.
Review in Genes & development, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed.
- Current therapeutic interventions to target cancer stem cells for metastasis.International journal of clinical oncology · 2026Review
- Review
- Molecular mechanisms of KMT2C alterations in gastrointestinal cancers: enhancer network destabilization, lineage plasticity, and clinical translation.Frontiers in immunology · 2026Review
- Targeting tumor transition windows.Exploration of targeted anti-tumor therapy · 2026Review
- Research Progress on the Adaptation Law and Core Mechanism of Animal Models for Exercise Intervention in Inflammatory Bowel Disease: A Systematic Review.Clinical and experimental gastroenterology · 2026Review
- Biology of stem cell paradox: a double-edged sword-implications for cancer therapy.Cancer cell international · 2025Review
- Single-cell multi-omics and machine learning for dissecting stemness in cancer.Briefings in bioinformatics · 2025Review
- DSG2 promotes pancreatic cancer stem cell maintenance via support of tumour and macrophage cellular cross-talk.Cell death & disease · 2025Article
- Cancer stem cells: Bridging microenvironmental interactions and clinical therapy.Clinical and translational medicine · 2025Review
- Refinement strategies for Tangram for reliable single-cell to spatial mapping.Bioinformatics (Oxford, England) · 2025Article
- Single-cell transcriptomics in metastatic breast cancer: mapping tumor evolution and therapeutic resistance.Frontiers in genetics · 2025Review
- Cancer stem cells in hepatocellular carcinoma: therapy resistance and emerging treatments.Frontiers in immunology · 2025Review
- Application of artificial intelligence-based stemness index in cancer.Frontiers in oncology · 2025Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer stem cells (CSCs) often exhibit stem-like attributes that depend on an intricate stemness-promoting cellular ecosystem within their niche. The interplay between CSCs and their niche has been implicated in tumor heterogeneity and therapeutic resistance. Normal stem cells (NSCs) and CSCs share stemness features and common microenvironmental components, displaying significant phenotypic and functional plasticity. Investigating these properties across diverse organs during normal development and tumorigenesis is of paramount research interest and translational potential. Advancements in next-generation sequencing (NGS), single-cell transcriptomics, and spatial transcriptomics have ushered in a new era in cancer research, providing high-resolution and comprehensive molecular maps of diseased tissues. Various spatial technologies, with their unique ability to measure the location and molecular profile of a cell within tissue, have enabled studies on intratumoral architecture and cellular cross-talk within the specific niches. Moreover, delineation of spatial patterns for niche-specific properties such as hypoxia, glucose deprivation, and other microenvironmental remodeling are revealed through multilevel spatial sequencing. This tremendous progress in technology has also been paired with the advent of computational tools to mitigate technology-specific bottlenecks. Here we discuss how different spatial technologies are used to identify NSCs and CSCs, as well as their associated niches. Additionally, by exploring related public data sets, we review the current challenges in characterizing such niches, which are often hindered by technological limitations, and the computational solutions used to address them.
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Registered trials
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