Evidence map›Paper›PMID 42502300›Full record

ArticleHuman mutation2026

Single-Cell and Machine Learning Analyses Identify MYDGF as an Immune-Related Biomarker Associated With the Tumor Microenvironment in Clear Cell Renal Cell Carcinoma.

Yingkun Xu, Guandu Li, Xinxiu Ren, Xiaochen Qi, Guangzhen Wu

Abstract read
In one paragraph

Article in Human mutation, 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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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

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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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Yingkun XuDepartment of General Surgery, Qilu Hospital of Shandong University, Jinan, China, qiluhospital.com.ORCID https://orcid.org/0000-0002-0100-9117
Guandu LiDepartment of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian, China, dlmedu.edu.cn.
Xinxiu RenDepartment of Cell Biology, College of Basic Medical Science, Dalian Medical University, Dalian, China, dlmedu.edu.cn.
Xiaochen QiDepartment of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian, China, dlmedu.edu.cn.
Guangzhen WuDepartment of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian, China, dlmedu.edu.cn.ORCID https://orcid.org/0009-0001-9007-151X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell transcriptomics and machine learning methods are increasingly used to identify immune-related biomarkers in solid tumors, yet their combined application to microenvironment-related drivers of therapeutic resistance in clear cell renal cell carcinoma (ccRCC) is still limited. Here, we investigated the biological and clinical significance of myeloid-derived growth factor (MYDGF) through an integrative strategy spanning single-cell profiling, bulk multiomics, and functional validation. Analysis of scRNA-seq data (GSE156632) revealed that MYDGF is preferentially detected in malignant epithelial subpopulations and associated with the composition of myeloid and lymphoid compartments. Integration with TCGA-KIRC transcriptomic and clinical datasets demonstrated strong associations between MYDGF expression and immune-checkpoint activation, immune dysfunction signatures, and PI3K/AKT-MAPK pathway activity. Tumors with high MYDGF expression exhibited an immune-infiltrated yet functionally impaired microenvironment and were predicted to show reduced responsiveness to immune checkpoint blockade. Differential expression and enrichment analyses further highlighted MYDGF-associated genes involved in inflammatory, extracellular, and receptor-binding functions. A machine learning pipeline using LASSO Cox regression identified a preliminary 19-gene MYDGF-related prognostic gene set that requires further validation. Functional experiments confirmed that MYDGF knockdown suppressed proliferation, migration, and invasion in ccRCC cells. Overall, our analyses characterize MYDGF as a microenvironment-related biomarker linked to immune-associated features, signaling-associated alterations, and adverse prognosis in ccRCC. These results nominate MYDGF as a candidate prognostic biomarker and show the value of pairing single-cell resolution with computational modeling for biomarker discovery in renal cancer.

Indexed as

Biomarkers, TumorCarcinoma, Renal CellKidney NeoplasmsMachine LearningSingle-Cell AnalysisTumor MicroenvironmentGene Expression ProfilingGene Expression Regulation, NeoplasticHumansSingle-Cell Gene Expression AnalysisBiomarkers, Tumorclear cell renal cell carcinomaimmune infiltrationmachine learningMYDGFprognosissingle-cell RNA sequencingtumor microenvironment

Identifiers

PMID42502300
PMCPMC13401162

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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.