Evidence map›Paper›PMID 41229886›Full record

ArticleFrontiers in genetics2025

LDLRAD4 is a potential diagnostic and prognostic biomarker correlated with immune infiltration in myelodysplastic syndromes.

Mengjie Xu, Shihao Wu, Kaixiang Zhang, Lirong Nie, Qinghua Li, Jihong Zhong, Yuming Zhang, Honghua He

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Article in Frontiers in genetics, 2025. 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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5 · Who and what money

Authors and funding

8 authors.

Mengjie Xu *Department of Hematology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
Shihao Wu *Guangdong Medical University, Zhanjiang, China.
Kaixiang ZhangDepartment of Hematology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
Lirong NieDepartment of Hematology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
Qinghua LiDepartment of Hematology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
Jihong ZhongDepartment of Hematology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
Yuming ZhangDepartment of Hematology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
Honghua HeDepartment of Hematology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Myelodysplastic syndromes (MDS) are a group of hematological disorders that remain relatively under-explored, which are characterized by inconspicuous early symptoms and generally poor prognosis. Owing to the complex and variable pathogenesis of MDS, there is a relative paucity of available therapeutic options. Consequently, in-depth investigation into the pathogenesis of MDS and the search for effective targeted therapies have become urgent priorities. Methods: In this study, we leveraged the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) and conducted functional enrichment analysis. Utilizing three machine learning algorithms-Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine Recursive Feature Elimination (SVM-RFE), and Random Forest (RF)-we pinpointed hub genes. Furthermore, this study explored the relationship between hub gene expression levels and immune infiltration. Results: Our analysis identified three hub genes: LDLRAD4, FAM43A, and KCNK5, with LDLRAD4 showing a close association with TGF-β and MAPK signaling pathways. Furthermore, this study revealed a positive correlation between LDLRAD4 expression levels and immune infiltration, particularly with natural killer (NK) cells, offering a novel immunological perspective on LDLRAD4. Ultimately, we observed that the overexpression of LDLRAD4 can suppress the proliferative capacity of MDS cells, induce cell cycle arrest, and enhance apoptosis. Conclusion: We conclude that LDLRAD4, FAM43A, and KCNK5 are potential biomarkers for MDS. LDLRAD4's overexpression

Indexed as

biological markersimmune infiltrationLDLRAD4machine learningmyelodysplastic syndromes

Identifiers

PMID41229886
PMCPMC12604824

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