Evidence map›Paper›PMID 39468216›Full record

ArticleScientific reports2024

A novel risk score model of lactate metabolism for predicting outcomes and immune signatures in acute myeloid leukemia.

Ze-Min Huang, Jing Wei, Xiao-Wen Pan, Xing-Biao Chen, Zi-Yuan Lu

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Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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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

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Ze-Min HuangDepartment of Hematology, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, China.
Jing WeiDepartment of Hematology, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, China.
Xiao-Wen PanDepartment of Hematology, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, China.
Xing-Biao ChenDepartment of Hematology, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, China.
Zi-Yuan LuDepartment of Hematology, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, China. lzo19880306@126.com.

Funding

the Elite Project Fund of The Third Affiliate Hospital of Guangzhou Medical University 2018001the Guangdong Basic and Applied Basic Research Foundation 2019A1515010390
6 · The paper itself

Abstract

Acute myeloid leukemia (AML) is a malignant tumor with high recurrence and refractory rates and low survival rates. Increased glycolysis is characteristic of metabolism in AML blast cells and is also associated with chemotherapy resistance. The purpose of this study was to use gene expression and clinical information from The Cancer Genome Atlas (TCGA) database to identify subtypes of AML associated with lactate metabolism. Two different subtypes linked to lactate metabolism, each with specific immunological features and consequences for prognosis, were identified in this study. Using the TCGA and International Cancer Genome Consortium (GEO) cohorts, a prognostic model composed of genes (LMNA, RETN and HK1) for the prognostic value of the lactate metabolism-related risk score prognostic model was created and validated, suggesting possible therapeutic uses. Additionally, the diagnostic value of the prognostic model genes was explored. LMNA and HK1 were ultimately identified as hub genes, and their roles in AML were determined through immune infiltration, GeneMANIA, GSEA, methylation analysis and single-cell analysis. LMNA was upregulated in AML associating with a poor prognosis while HK1 was downregulated in AML associating with a favorable prognosis. The findings underscore the noteworthy impact of genes linked to lactate metabolism in AML and illustrate the possible therapeutic usefulness of the lactate metabolism-related risk score and the hub lactate metabolism-related genes in guiding AML patients' treatment choices.

Indexed as

Lactic AcidLeukemia, Myeloid, AcuteBiomarkers, TumorFemaleGene Expression Regulation, LeukemicHumansMaleMiddle AgedPrognosisBiomarkers, TumorLactic AcidAcute myeloid leukemiaImmune signatureLactate metabolism-associated geneOSRisk model

Identifiers

PMID39468216
PMCPMC11519446

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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.