Evidence map›Paper›PMID 41685311›Full record

ArticleFrontiers in immunology2026

Prognostic gene screening and experimental validation in renal clear cell carcinoma based on spatial transcriptomics and single-cell sequencing.

Cong Fu, Lin Sun, Tong Zhou, Yanzhi Bi

Abstract read
In one paragraph

Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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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.

Cong Fu *Department of Oncology, Changzhou Cancer (Fourth People's) Hospital, Changzhou, China.
Lin Sun *Department of Oncology, Affiliated Hospital of Soochow University, Changzhou, China.
Tong ZhouDepartment of Oncology, Changzhou Cancer (Fourth People's) Hospital, Changzhou, China.
Yanzhi BiDepartment of Oncology, Changzhou Cancer (Fourth People's) Hospital, Changzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Clear cell renal cell carcinoma (ccRCC) is characterized by high recurrence and metastatic potential, leading to poor clinical outcomes. There is a critical need to identify reliable prognostic biomarkers and therapeutic targets to improve patient stratification and personalized treatment. Methods: This study integrated single-cell RNA sequencing (scRNA-seq) data and spatial transcriptomics (ST) data to identify prognostic genes and therapeutic targets. Prognostic modeling and validation were performed using The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. In addition, functional analyses were conducted to explore the biological roles of candidate genes. Results: Seven prognostic genes (CYFIP2, MPPED2, HHLA2, ADAM8, ATP1A1, ARC, and MXD3) were identified and used to construct a risk model that stratified patients into high- and low-risk groups. The high-risk group exhibited significantly poorer survival, a finding validated in both TCGA and ICGC datasets. A nomogram incorporating risk score and age improved survival prediction accuracy, with Area Under the Curve (AUC) values of 0.79, 0.75, and 0.78 at 1, 3, and 5 years, respectively. ATP1A1 was highly expressed in endothelial cells and was significantly associated with M1 macrophages; thus, it was selected as a potential therapeutic target. Functional analyses revealed its role in angiogenesis inhibition and M1 macrophage polarization. Discussion: The risk model and nomogram demonstrate strong prognostic value and may aid in clinical risk stratification for ccRCC. ATP1A1 emerges as a potential therapeutic target, with functional implications in angiogenesis and immune modulation. These findings highlight the clinical relevance of the identified gene signatures and support the development of personalized treatment strategies for ccRCC patients.

Indexed as

Biomarkers, TumorCarcinoma, Renal CellKidney NeoplasmsGene Expression ProfilingGene Expression Regulation, NeoplasticHumansNomogramsPrognosisSingle-Cell AnalysisSingle-Cell Gene Expression AnalysisSpatial TranscriptomicsTranscriptomeBiomarkers, TumorATP1A1clear cell renal cell carcinomaepithelial cellsnomogramprognostic genessingle-cell RNA sequencingspatial transcriptomics RNA sequencing

Identifiers

PMID41685311
PMCPMC12891194

What Socratic holds

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LicenceCC BY
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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 Socratic graph.