Evidence map›Paper›PMID 35365599›Full record

ReviewSignal transduction and targeted therapy2022

Clinical and translational values of spatial transcriptomics.

Linlin Zhang, Dongsheng Chen, Dongli Song, Xiaoxia Liu, Yanan Zhang, Xun Xu, Xiangdong Wang

Abstract readReview
In one paragraph

Review in Signal transduction and targeted therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 125 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
125citing papers in PubMed, 1 pooled it
–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

125 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Insights Into Spatial Transcriptomics: Exploring Recent Technical Developments and Their Diverse Applications.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
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65 more citing papers are in PubMed but not listed here.

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

7 authors.

Linlin Zhang *Zhongshan Hospital, Department of Pulmonary and Critical Care Medicine, Institute for Clinical Science, Shanghai Institute of Clinical Bioinformatics, Shanghai Engineering Research for AI Technology for Cardiopulmonary Diseases, Shanghai, 200000, China.
Dongsheng Chen *Suzhou Institute of Systems Medicine, Suzhou, 215123, Jiangsu, China.
Dongli Song *Zhongshan Hospital, Department of Pulmonary and Critical Care Medicine, Institute for Clinical Science, Shanghai Institute of Clinical Bioinformatics, Shanghai Engineering Research for AI Technology for Cardiopulmonary Diseases, Shanghai, 200000, China.
Xiaoxia LiuZhongshan Hospital, Department of Pulmonary and Critical Care Medicine, Institute for Clinical Science, Shanghai Institute of Clinical Bioinformatics, Shanghai Engineering Research for AI Technology for Cardiopulmonary Diseases, Shanghai, 200000, China.
Yanan ZhangTsinghua-Berkeley Shenzhen Institute (TBSI), Tsinghua University, Shenzhen, 518055, China.
Xun XuBGI-Shenzhen, Shenzhen, 518083, China. xuxun@genomics.cn.
Xiangdong WangZhongshan Hospital, Department of Pulmonary and Critical Care Medicine, Institute for Clinical Science, Shanghai Institute of Clinical Bioinformatics, Shanghai Engineering Research for AI Technology for Cardiopulmonary Diseases, Shanghai, 200000, China. xdwang@fuccb.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The combination of spatial transcriptomics (ST) and single cell RNA sequencing (scRNA-seq) acts as a pivotal component to bridge the pathological phenomes of human tissues with molecular alterations, defining in situ intercellular molecular communications and knowledge on spatiotemporal molecular medicine. The present article overviews the development of ST and aims to evaluate clinical and translational values for understanding molecular pathogenesis and uncovering disease-specific biomarkers. We compare the advantages and disadvantages of sequencing- and imaging-based technologies and highlight opportunities and challenges of ST. We also describe the bioinformatics tools necessary on dissecting spatial patterns of gene expression and cellular interactions and the potential applications of ST in human diseases for clinical practice as one of important issues in clinical and translational medicine, including neurology, embryo development, oncology, and inflammation. Thus, clear clinical objectives, designs, optimizations of sampling procedure and protocol, repeatability of ST, as well as simplifications of analysis and interpretation are the key to translate ST from bench to clinic.

Indexed as

Computational BiologyTranscriptomeHumansSequence Analysis, RNA

Identifiers

PMID35365599
PMCPMC8972902

What OpenQuestion holds

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LicenceCC BY
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 OpenQuestion graph.