Evidence map›Paper›PMID 41888163›Full record

ArticleScientific data2026

Integrated single-cell transcriptomic atlas of human gastric and colorectal tissues across diverse phenotypes.

Yunjin Go, Aki Uesugi, Dakeun Lee, Su Bin Lim

Abstract readDataset
In one paragraph

Article in Scientific data, 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

4 authors.

Yunjin Go *Department of Biochemistry & Molecular Biology, Ajou University School of Medicine, Suwon, 16499, South Korea.
Aki Uesugi *Department of Biochemistry & Molecular Biology, Ajou University School of Medicine, Suwon, 16499, South Korea.ORCID http://orcid.org/0009-0002-1251-5485
Dakeun LeeDepartment of Biomedical Sciences, Graduate School of Ajou University, Suwon, 16499, Korea.ORCID http://orcid.org/0000-0003-1604-2961
Su Bin LimDepartment of Biochemistry & Molecular Biology, Ajou University School of Medicine, Suwon, 16499, South Korea. sblim@ajou.ac.kr.ORCID http://orcid.org/0000-0003-1752-7039

Funding

Ministry of Health and Welfare (Ministry of Health, Welfare and Family Affairs) HR22C1734National Research Foundation of Korea (NRF) 2020M3A9D8037604National Research Foundation of Korea (NRF) 2020R1A6A1A03043539National Research Foundation of Korea (NRF) 2022R1C1C1004756National Research Foundation of Korea (NRF) RS-2020-NR046270National Research Foundation of Korea (NRF) RS-2020-NR049588
6 · The paper itself

Abstract

Gastrointestinal cancer is one of the most burdensome health threats worldwide, accounting for approximately one-quarter of all cancer incidences. Gastric and colorectal cancers are among the most prevalent and lethal malignancies of the gastrointestinal tract globally. Despite steadily rising incidence, the complex cellular landscape comprising the tumor microenvironment and accelerating tumorigenesis remains insufficiently explored. Although single-cell transcriptomics has been employed to investigate this complexity, previous studies are limited by the small number of cells analyzed. In this study, we present a comprehensive single-cell transcriptomic atlas comprising 574,532 cells across 70 cell types from 229 human stomach tissues and 479,629 cells across 70 cell types from 220 human colorectal tissues, spanning diverse phenotypes. Data quality and cell type annotations were rigorous validated utilizing multiple computational tools. Additionally, standardized cell type definitions and annotated clinical information facilitate the usability of this dataset, enabling analysis across clinical subtypes and metastatic states. This resource provides a valuable foundation for meta-analyses of gastric and colorectal cancers at single-cell resolution.

Indexed as

Colorectal NeoplasmsSingle-Cell Gene Expression AnalysisStomach NeoplasmsTranscriptomeHumansPhenotypeTumor Microenvironment

Identifiers

PMID41888163
PMCPMC13184354

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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.