Evidence map›Paper›PMID 42310765›Full record

ArticleJournal of translational medicine2026

SP-printer: reconstruction of tumor stage-specific microenvironments via phenotype-integrated spatial transcriptomics.

Weihao Deng, Yantao Shi, Hui Tang

Abstract read
In one paragraph

Article in Journal of 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

3 authors.

Weihao Deng *School of Mathematics, Foshan University, Foshan, China.
Yantao Shi *School of Mathematics, Foshan University, Foshan, China.
Hui TangSchool of Mathematics, Foshan University, Foshan, China. tanghui@fosu.edu.cn.ORCID 0000-0002-7306-0501

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2025A1515011988National Natural Science Foundation of China 12301619National Natural Science Foundation of China 12501670
6 · The paper itself

Abstract

backgroundSpatial transcriptomics (ST) technologies have rapidly advanced the investigation of tumor microenvironment (TME) mechanisms by enabling high-resolution mapping of mRNA molecules within their native spatial context. However, existing methods often overlook phenotypic indices like malignancy status, limiting their interpretability within the tumor microenvironment.

methodsThis work proposes SP-printer (Spatial-Phenotype printer), a flexible integrating approach that integrates phenotypic and spatial data to quantify stage-specific malignancy levels at each spot. SP-printer first identifies stage-specific metagenes from bulk RNA-seq datasets by using a S-score strategy. These metagenes are then projected onto ST data at pixel level via an information-enhanced mapping strategy, generating spatially resolved stage phenotypes. Finally, the pixel-level mappings are aggregated to spot resolution, enabling compatibility with standard ST workflows and supporting downstream analyses.

resultsSP-printer outperforms state-of-the-art methods in identifying malignant regions across diverse tumor tissues. Specifically, we identified early microenvironment diagnostic markers for primary liver cancer and liver metastasis and evaluated the effects of seven drugs on the tumor microenvironment, providing a comprehensive assessment of their therapeutic potential.

conclusionsSP-printer offers a unified framework to dissect the tumor spatial microenvironment and bridge the gap between cellular context and phenotypic outcomes, thereby enhancing the precision of tumor microenvironment analysis and facilitating informed clinical decision-making.

Indexed as

Spatial TranscriptomicsTumor MicroenvironmentHumansLiver NeoplasmsPhenotype

Identifiers

PMID42310765
PMCPMC13523258

What OpenQuestion 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 OpenQuestion graph.