Evidence map›Paper›PMID 39496456›Full record

ReviewGenes & development2025

Deciphering normal and cancer stem cell niches by spatial transcriptomics: opportunities and challenges.

Hirak Sarkar, Eunmi Lee, Sereno L Lopez-Darwin, Yibin Kang

Abstract readReview
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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.

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

13 citing papers in PubMed.

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  4. Targeting tumor transition windows.Exploration of targeted anti-tumor therapy · 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

4 authors.

Hirak Sarkar *Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA.
Eunmi Lee *Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA.
Sereno L Lopez-DarwinLewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA.
Yibin KangDepartment of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA; ykang@princeton.edu.ORCID 0000-0002-1626-6730

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Neoplastic Stem CellsStem Cell NicheTranscriptomeAnimalsGene Expression ProfilingHumansNeoplasmsTumor Microenvironmentcancer stem cellcell-to-cell interactiondeconvolutionnext-generation sequencingnormal stem cellsegmentationspatial transcriptomicsstem cell niche

Identifiers

PMID39496456
PMCPMC11789490

What OpenQuestion holds

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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.