Evidence map›Paper›PMID 37596597›Full record

ArticleBMC medical genomics2023

m6A genotypes and prognostic signature for assessing the prognosis of patients with acute myeloid leukemia.

Caizhu Fu, Ruirui Kou, Jie Meng, Duanfeng Jiang, Ruilan Zhong, Min Dong

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 22% of its field
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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

5 citing papers in PubMed, 7 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Caizhu Fu *Hematology, the Second Affiliated Hospital of Hainan Medical University, Haikou, 570000, China.
Ruirui Kou *Hematology, the Second Affiliated Hospital of Hainan Medical University, Haikou, 570000, China.
Jie MengHematology, the Second Affiliated Hospital of Hainan Medical University, Haikou, 570000, China.
Duanfeng JiangHematology, the Second Affiliated Hospital of Hainan Medical University, Haikou, 570000, China.
Ruilan ZhongHematology, the Second Affiliated Hospital of Hainan Medical University, Haikou, 570000, China.
Min DongHematology, the Second Affiliated Hospital of Hainan Medical University, Haikou, 570000, China. mindonghn@hainmc.edu.cn.
Hainan Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundN6-methyladenosine (m6A) has been confirmed to function critically in acute myeloid leukemia (AML) progression. Hitherto, the subtyping and prognostic predictive significance of m6A-correlated genes in AML is unclear.

methodFrom The Cancer Genome Atlas (TCGA-LAML), Therapeutically Applicable Research to Generate Effective Treatments (TARGET-AML) and Gene Expression Omnibus (GEO, GSE71014) databases, we collected the sequencing data of AML patients. The batch effect was removed via limma package for TCGA-LAML and TARGET-AML, and the aggregated samples were AML cohorts. Samples in the AML cohort identified m6A models in AML by consensus clustering based on 23-m6A-related modulators. M6A-related differentially expressed genes (m6ARDEGs) influencing the overall survival (OS) of AML were determined by performing differential expression analysis and univariate COX analysis, and consensus-based clustering was utilized to access AML molecular subtypes. LASSO and multivariate COX analyses were performed to obtain the optimized m6ARDEGs to construct the m6A Prognostic Risk Score (m6APR_Score). Whether the model was robust was evaluated according to Kaplan-Meier (K-M) and receiver operator characteristic (ROC) curves. Further, the abundance of immune cell infiltration was explored in different m6A modification patterns and molecular subtypes and m6APR_Score groupings. Finally, nomogram was constructed to predict OS in AML. Quantitative real-time polymerase chain reaction (RT-qPCR) and cell counting kit-8 (CCK-8) assay were used to validate the genes in m6APR_Score in AML cells.

resultsThe m6A models (m6AM1, m6AM2, m6AM3) and molecular subtypes (C1, C2, C3) were identified in the AML cohort, exhibiting different prognosis and immunoreactivity. We recognized novel prognostic biomarkers of AML such as CD83, NRIP1, ACSL1, METTL7B, OGT, and C4orf48. AML patients were grouped into high-m6APR_Score and low-m6APR_Score groups, with the later group showing a better prognosis than former one. Both the AML cohort and the validation cohort GSE71014 demonstrated excellent prediction. Finally, the nomogram accurately predicted the survival of patients suffering from AML. Further, the decision curves showed that both nomogram and m6APR_Score showed excellent prediction. It was confirmed in vitro experiments that mRNA expressions of NRIP1, ACSL1, METTL7B and OGT were elevated, while CD83 and C4orf48 mRNA expressions downregulated in AML cells. A significant increase in the viability of U937 and THP-1 cell lines after inhibition of CD83, while siMETTL7B had contrast results.

conclusionOur study demonstrated that m6APR_Score and CD83, NRIP1, ACSL1, METTL7B, OGT, and C4orf48 potentially provided novel and promising prognostic support for AML patients.

Indexed as

Leukemia, Myeloid, AcuteCluster AnalysisGenotypeHumansPrognosisRNA, MessengerRNA, MessengerAcute myeloid leukemiaImmuneN6-methyladenosinePrognosticTCGA

Identifiers

PMID37596597
PMCPMC10436408
OpenAlexW4385981713

What Socratic holds

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LicenceCC BY
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Registered trials

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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.