Evidence map›Paper›PMID 42294291›Full record

ArticleFrontiers in oncology2026

Identification of MTMR2 as an AML-associated candidate biomarker derived from lipid metabolism-related transcriptomic analysis.

Chenchen Liu, Yueyuan Pan, Minggui Chen, Songyu Li, Chong Zhang

Abstract read
In one paragraph

Article in Frontiers in oncology, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Chenchen LiuZhanjiang Institute of Clinical Medicine, Zhanjiang Central Hospital, Guangdong Medical University (Central People's Hospital of Zhanjiang), Zhanjiang, Guangdong, China.
Yueyuan PanZhanjiang Institute of Clinical Medicine, Zhanjiang Central Hospital, Guangdong Medical University (Central People's Hospital of Zhanjiang), Zhanjiang, Guangdong, China.
Minggui ChenPrecision Clinical Laboratory, Zhanjiang Central Hospital, Guangdong Medical University (Central People's Hospital of Zhanjiang), Zhanjiang, Guangdong, China.
Songyu LiZhanjiang Institute of Clinical Medicine, Zhanjiang Central Hospital, Guangdong Medical University (Central People's Hospital of Zhanjiang), Zhanjiang, Guangdong, China.
Chong ZhangZhanjiang Institute of Clinical Medicine, Zhanjiang Central Hospital, Guangdong Medical University (Central People's Hospital of Zhanjiang), Zhanjiang, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Acute myeloid leukemia (AML) is a diverse malignant hematologic disorder with poor clinical outcomes. Increasing evidence suggests that metabolic reprogramming, particularly lipid metabolism, contributes to AML progression and may offer new opportunities for biomarker discovery and therapeutic targeting. However, lipid metabolism-related hub genes with diagnostic and prognostic relevance in AML have not been systematically characterized. Methods: Expression profiles from GSE114868 and GSE9476 were analyzed to identify lipid metabolism-associated differentially expressed genes. Functional enrichment, single-sample gene set enrichment analysis (ssGSEA), weighted gene co-expression network analysis (WGCNA), machine-learning-based feature selection, diagnostic receiver operating characteristic (ROC) analysis, survival analysis, and immune infiltration analysis were performed. MTMR2 expression was further validated by RT-qPCR in an expanded clinical cohort of AML patients and healthy controls, and selected lipid-related clinical parameters were explored. Results: Lipid metabolism-related pathways were significantly altered in AML samples. Integration of differential expression analysis, WGCNA, LASSO regression, random forest analysis, and SVM-RFE identified MTMR2 as a candidate lipid metabolism-associated biomarker. MTMR2 was markedly upregulated in AML across independent datasets and showed good diagnostic performance. Kaplan-Meier analysis suggested an association between high MTMR2 expression and poorer overall survival. High MTMR2 expression was also associated with immune- and inflammation-related transcriptional features and with altered inferred immune-cell infiltration patterns. RT-qPCR analysis confirmed higher MTMR2 expression in AML samples, and exploratory clinical analysis showed lower ApoA1 and LDL-C levels and higher TG levels in AML patients than in healthy controls. Conclusion: This study identifies MTMR2 as a lipid metabolism-associated candidate biomarker in AML and provides preliminary clinical evidence supporting its increased expression and association with altered lipid-related parameters. These findings support further mechanistic and clinical validation of MTMR2 in larger independent AML cohorts.

Indexed as

acute myeloid leukemiaimmune infiltrationlipid metabolismmachine learningMTMR2prognosisROCssGSEA

Identifiers

PMID42294291
PMCPMC13259702

What Socratic holds

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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.