Evidence map›Paper›PMID 41540415›Full record

ArticleJournal of translational medicine2026

Combining spatial and single-cell transcriptome data to analyze tertiary lymphoid structures in clear cell renal cell carcinoma reveals prognostic biomarkers.

Xuechao Li, Pu Liu, Man Li, Yongzhu Zhou, Tianwei Li, Tao Yang, Jinkai Dong, Chengwei Fu, Yunping Zhu, Lijun Chen and 2 more

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

12 authors.

Xuechao Li *Department of Urology, The Third Medical Centre, Chinese PLA General Hospital, Beijing, 100039, China.
Pu Liu *Chongqing International Institute for Immunology, Chongqing, 401338, China.
Man Li *Tianjin Normal University, Tianjin, 300387, China.
Yongzhu ZhouState Key Laboratory of Medical Proteomics, National Center for Protein Sciences (Beijing), Beijing, 102206, China.
Tianwei LiState Key Laboratory of Medical Proteomics, National Center for Protein Sciences (Beijing), Beijing, 102206, China.
Tao YangDepartment of Urology, The Third Medical Centre, Chinese PLA General Hospital, Beijing, 100039, China.
Jinkai DongDepartment of Urology, The Third Medical Centre, Chinese PLA General Hospital, Beijing, 100039, China.
Chengwei FuDepartment of Urology, The Third Medical Centre, Chinese PLA General Hospital, Beijing, 100039, China.
Yunping ZhuState Key Laboratory of Medical Proteomics, National Center for Protein Sciences (Beijing), Beijing, 102206, China.
Lijun ChenDepartment of Urology, The Third Medical Centre, Chinese PLA General Hospital, Beijing, 100039, China. chenlj829@163.com.
Jie MaState Key Laboratory of Medical Proteomics, National Center for Protein Sciences (Beijing), Beijing, 102206, China. majie@ncpsb.org.cn.
Wanlin LiuState Key Laboratory of Medical Proteomics, National Center for Protein Sciences (Beijing), Beijing, 102206, China. liuwanlin@ncpsb.org.cn.ORCID 0000-0002-4116-2597

Funding

Key Technologies Research and Development Program 2021YFA1301603National Natural Science Foundation of China 31870828National Natural Science Foundation of China 82173085Open Fund of State Key Laboratory of Medical Proteomics SKLP-O202204
6 · The paper itself

Abstract

backgroundAs the predominant and most aggressive subtype of renal cell carcinoma (RCC), clear cell RCC (ccRCC) represents the considerable heterogeneity present across RCC subtypes. Although tertiary lymphoid structures (TLS) are implicated in tumor immunity, their prognostic role and underlying mechanisms in ccRCC remain unclear. Characterizing TLS-associated genes may offer novel insights into disease progression and support improved risk stratification and personalized therapy.

methodsThe single-cell transcriptome and spatial transcriptome data were utilized to analyze the B-cell infiltration in ccRCC and to screen for differentially expressed genes within TLS of ccRCC. Next, consensus clustering and survival analysis based on Lasso-Cox regression were applied to identify TLS prognostic markers in ccRCC. Subsequently, a prognostic prediction model for ccRCC was established by integrating key clinical characteristics and these prognostic biomarkers. The immunofluorescence experiments were performed on ccRCC clinical specimens to validate the clinical relevance of proteins in candidate biomarkers for ccRCC.

resultsAberrant expression of three TLS-associated genes (CEMIP, PLA2G2A, and IGHGP) was associated with poor prognosis in ccRCC, identifying them as potential prognostic biomarkers. Then, the protein-coding biomarkers were validated in ccRCC pathological tissue samples by immunofluorescence. Mechanistically, aberrant expression underlies the functional transition in TLS from anti-tumor immunity to tumor promotion, potentially mediated by dysregulation of oncogenic processes via multi-pathway interactions. A prognostic model based on these biomarkers demonstrated high predictive accuracy.

conclusionsCombining single-cell analysis with spatial transcriptomic profiling identifies spatially-resolved functional heterogeneity in ccRCC-associated TLS, demonstrating their context-dependent immunomodulatory roles. Aberrant expression of specific TLS-associated proteins is associated with a functional transition from anti-tumor immunity to tumor promotion. CEMIP, PLA2G2A, and IGHGP may serve as potential prognostic biomarkers; derived models achieve high predictive accuracy, highlighting clinical potential. Immunofluorescence confirmed the enrichment of protein-level biomarkers within TLS in ccRCC clinical specimens. Our findings elucidate TLS-related genes regulating tumor-immune interactions, advancing understanding of ccRCC prognosis and providing tools for prediction and personalized therapy.

Indexed as

Biomarkers, TumorCarcinoma, Renal CellKidney NeoplasmsSingle-Cell AnalysisTertiary Lymphoid StructuresTranscriptomeGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimatePrognosisSingle-Cell Gene Expression AnalysisSpatial TranscriptomicsBiomarkers, TumorBiomarkerClear cell renal cell carcinomaPrediction modelPrognosisTertiary lymphoid structures

Identifiers

PMID41540415
PMCPMC12892582

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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.