Evidence map›Paper›PMID 39975548›Full record

ArticleFrontiers in immunology2025

Polymorphisms in immunosuppression-related genes are associated with AML.

Mingying Li, Jingjing Ye, Mengyuan Chang, Lei Feng, Tingting Liu, Di Zhang, Yuyan Wu, Yuechan Ma, Guangqiang Meng, Chunyan Ji and 1 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Clinical significance of CD45 and CD200 expression in newly diagnosed multiple myeloma patients.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025
    Article
  6. Review
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

11 authors.

Mingying Li *Department of Hematology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Jingjing Ye *Department of Hematology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Mengyuan ChangDepartment of Hematology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Lei FengDepartment of Hematology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Tingting LiuDepartment of Hematology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Di ZhangDepartment of Hematology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Yuyan WuDepartment of Hematology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Yuechan MaDepartment of Hematology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Guangqiang MengDepartment of Hematology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Chunyan JiDepartment of Hematology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Tao SunDepartment of Hematology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Acute myeloid leukemia (AML) is a hematologic malignancy with poor overall survival (OS). The immunosuppressive microenvironment significantly impacts AML development and chemoresistance. Despite new immunotherapeutic strategies entering standard clinical care for various tumors, progress in AML remains poor. Multi-omics analyses, such as single-cell transcriptomics, have revealed many potential new targets to improve AML prognosis from an immunological perspective. Methods: DNA from 307 AML patients and 316 healthy individuals were extracted. We detected nine single nucleotide polymorphisms (SNPs) in five immunosuppression-related genes (CIITA, CD200, CD163, MRC1 and LILRB4) in these samples. SNP genotyping was performed on the MassARRAY platform. We then analyzed the relationship between these SNPs and AML susceptibility, treatment response, and prognosis. Results: Our findings indicated that rs4883263 in the CD163 gene is a protective factor for AML susceptibility and chromosomal karyotype abnormalities. Additionally, rs4883263 in CD163 was related to low PLT count at diagnosis, while rs2272022 in CD200 was protective against low PLT count. rs4780335 in CIITA was associated with high WBC count at diagnosis and worse OS. Furthermore, rs1048801 in LILRB4 was linked to worse AML treatment response, lower OS, and may be an independent prognostic risk factor for AML. Lastly, expressions of CD163, CIITA, LILRB4, and CD200 were higher in AML patients than that in normal controls. Conclusions: Our findings on SNP associations in AML immunosuppression-related genes provide important reference points for predicting treatment outcomes in AML patients.

Indexed as

Immune ToleranceLeukemia, Myeloid, AcutePolymorphism, Single NucleotideAdolescentAdultAgedAntigens, CDAntigens, Differentiation, MyelomonocyticCase-Control StudiesCD163 AntigenFemaleGenetic Predisposition to DiseaseGenotypeHumansMaleMembrane GlycoproteinsAntigens, CDantigens, CD200Antigens, Differentiation, MyelomonocyticCD163 AntigenLILRB4 protein, humanMembrane GlycoproteinsReceptors, Cell SurfaceReceptors, ImmunologicAMLimmunosuppression-related genesprognosisSNPstreatment response

Identifiers

PMID39975548
PMCPMC11835863

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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.