Evidence map›Paper›PMID 42860711›Full record

ReviewClinical and translational medicine2026

Spatiotemporal transcriptomics for tumour microenvironment remodelling in cancer progression and therapy.

Ying Kang, Qinjing Wang, Siqi Xu, Jiming Guo, Yue Ming, Weixing Chen, Min Wang, Zhijie Huang, Yisheng Huang, Bo Jia

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Clinical and translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ying Kang *Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China.
Qinjing Wang *Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China.
Siqi XuStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China.
Jiming GuoStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China.
Yue MingSchool of Materials Science and Engineering, East China University of Science and Technology, Shanghai, China.
Weixing ChenSchool of Materials Science and Engineering, East China University of Science and Technology, Shanghai, China.
Min WangStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China.ORCID https://orcid.org/0009-0005-2798-8607
Zhijie HuangStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China.ORCID https://orcid.org/0000-0002-7312-4982
Yisheng HuangStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China.ORCID https://orcid.org/0000-0002-3654-6561
Bo JiaStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China.ORCID https://orcid.org/0000-0002-7178-424X

Funding

Beijing Xiangzan International Trading Co., Ltd. NYKQ-JG(HX)-202402Clinical New Technology Project of Southern Medical University Stomatological Hospital NTP202304Guangzhou Science and Technology Program Project in Agriculture and Social Development 2025B03J0107Key Project of Guangdong Province General Higher Education in Key Areas 2023ZDZX2009Science research cultivation program of Southern Medical University Stomatological Hospital PY2022015The Health Talent Project of the Eighth Batch of "Guangdong Special Support Program" 0820250219Zhuhai Hiyamei Biotechnology Co. NYKQ-JG(HX)-202401
6 · The paper itself

Abstract

backgroundSpatiotemporal transcriptomics (STT) integrates spatially resolved gene expression with temporal information derived from staged samples, paired treatment specimens, or computational inference, providing a framework for reconstructing tissue-level dynamics. In the tumour microenvironment (TME), STT extends static molecular and cellular maps by revealing how cellular neighbourhoods and functional niches are reorganised during tumour evolution. MAIN TEXT: This review examines how STT characterises TME remodelling during malignant transformation, invasion, metastasis, ageing, and treatment response. We discuss strategies for resolving temporal dynamics, including stage-stratified sampling, paired or serial specimens, pseudotime and trajectory inference, and complementary intravital imaging. We further consider how spatiotemporal analyses can connect changes in cellular states, spatial organisation, and intercellular interactions with clinically relevant tumour phenotypes.

conclusionBy linking the spatial organisation of the TME with stage- and treatment-associated molecular changes, STT may improve the prioritisation of candidate targets, treatment stratification, and the development of precision oncology strategies.

Indexed as

NeoplasmsTumor MicroenvironmentAnimalsDisease ProgressionHumansSpatial TranscriptomicsSpatio-Temporal Analysisprecision treatmentspatial heterogeneityspatiotemporal transcriptomicstime‐series analysistumour microenvironment

Identifiers

PMID42860711
PMCPMC13655377

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.