Evidence map›Paper›PMID 42374231›Full record

ArticleBMC cancer2026

Integrated multi-omics analysis reveals folate metabolism-related genes as prognostic markers and therapeutic targets in clear cell renal cell carcinoma.

Jinkang Lin, Sheng Li, Yunxin Zhou, Zecao Han, Weilin Chen, Huanhui Zheng, Shun Liu, Jiabiao Dai, Wei Cheng, Chen Fu and 3 more

Abstract read
In one paragraph

Article in BMC cancer, 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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0citing papers in PubMed
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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

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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

13 authors.

Jinkang Lin *Department of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.ORCID http://orcid.org/0009-0002-8821-745X
Sheng Li *Department of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.ORCID http://orcid.org/0000-0002-6964-7625
Yunxin Zhou *Department of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.ORCID http://orcid.org/0009-0002-6803-9131
Zecao HanDepartment of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.ORCID http://orcid.org/0009-0001-5972-7576
Weilin ChenDepartment of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.ORCID http://orcid.org/0009-0002-7134-7047
Huanhui ZhengDepartment of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.ORCID http://orcid.org/0009-0004-1248-8960
Shun LiuDepartment of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.ORCID http://orcid.org/0009-0001-8846-0110
Jiabiao DaiDepartment of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.ORCID http://orcid.org/0009-0006-2005-3478
Wei ChengDepartment of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.ORCID http://orcid.org/0009-0002-9994-0950
Chen FuDepartment of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.ORCID http://orcid.org/0009-0004-5640-9398
Wen DengDepartment of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.ORCID http://orcid.org/0000-0001-5991-7807
Haibo XiDepartment of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.ORCID http://orcid.org/0000-0001-9120-759X
Jin ZengDepartment of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China. zengjin_31217@ncu.edu.cn.ORCID http://orcid.org/0009-0001-9119-0529

Funding

National Natural Science Foundation of China No. 82203365Natural Science Foundation of Jiangxi Province No. 20232BAB206090
6 · The paper itself

Abstract

backgroundClear cell renal cell carcinoma (ccRCC) is an aggressive tumor with high metastatic potential and therapeutic resistance, yet the role of folate metabolism in its pathogenesis and immune evasion remains unclear. This study aims to develop and validate a folate metabolism-related gene (FMRG) scoring system to stratify patients by prognostic risk and immune phenotypes, and to explore the functional role of key FMRGs in ccRCC progression.

methodsUsing transcriptomic and clinical data from The Cancer Genome Atlas (TCGA), we developed a folate metabolism-related gene (FMRG) scoring system via integrative machine learning and validated it in an external cohort. We analyzed associations of the FMRG score with clinicopathological features, biological pathways, immune infiltration, therapeutic responsiveness, and drug sensitivity. Single-cell RNA sequencing and spatial transcriptomics mapped candidate gene expression, and in vitro experiments validated the functional role of NGF.

resultsA ten-gene prognostic model based on the FMRG score stratified ccRCC patients into groups with distinct clinical outcomes, immune profiles, and therapeutic responses. NGF was upregulated in ccRCC, with heterogeneous spatial expression. Functional assays showed that NGF enhances proliferation, migration, and invasion.

conclusionsThis folate metabolism-based scoring framework facilitates prognostic stratification, tumor microenvironment characterization, and prediction of immunotherapy response in ccRCC. NGF is identified as a functional mediator of tumor progression, offering potential therapeutic targets and insights into metabolic-immune crosstalk.

Indexed as

Biomarkers, TumorCarcinoma, Renal CellFolic AcidKidney NeoplasmsGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMultiomicsPrognosisTumor MicroenvironmentBiomarkers, TumorFolic AcidClear cell renal cell carcinomaFolate metabolismImmunotherapyMulti-omicsPrognostic signatureTumor microenvironment

Identifiers

PMID42374231
PMCPMC13584470

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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.