Evidence map›Paper›PMID 38868768›Full record

ReviewFrontiers in immunology2024

A new perspective on hematological malignancies: m6A modification in immune microenvironment.

Shiyu Yang, Liping Xu, Haihui Zhuang, Fenglin Li, Ying Lu

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2024. 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. Review
  4. Review
  5. Epitranscriptomic RNA mAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
  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

5 authors.

Shiyu YangDepartment of Hematology, The Affiliated People's Hospital of Ningbo University, Ningbo, China.
Liping XuDepartment of Hematology, The Affiliated People's Hospital of Ningbo University, Ningbo, China.
Haihui ZhuangDepartment of Hematology, The Affiliated People's Hospital of Ningbo University, Ningbo, China.
Fenglin LiDepartment of Hematology, The Affiliated People's Hospital of Ningbo University, Ningbo, China.
Ying LuDepartment of Hematology, The Affiliated People's Hospital of Ningbo University, Ningbo, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immunotherapy for hematological malignancies is a rapidly advancing field that has gained momentum in recent years, primarily encompassing chimeric antigen receptor T-cell (CAR-T) therapies, immune checkpoint inhibitors, and other modalities. However, its clinical efficacy remains limited, and drug resistance poses a significant challenge. Therefore, novel immunotherapeutic targets and agents need to be identified. Recently, N6-methyladenosine (m6A), the most prevalent RNA epitope modification, has emerged as a pivotal factor in various malignancies. Reportedly, m6A mutations influence the immunological microenvironment of hematological malignancies, leading to immune evasion and compromising the anti-tumor immune response in hematological malignancies. In this review, we comprehensively summarize the roles of the currently identified m6A modifications in various hematological malignancies, with a particular focus on their impact on the immune microenvironment. Additionally, we provide an overview of the research progress made in developing m6A-targeted drugs for hematological tumor therapy, to offer novel clinical insights.

Indexed as

AdenosineHematologic NeoplasmsTumor MicroenvironmentAnimalsHumansImmunotherapyAdenosineN-methyladenosinehematological malignanciesimmune microenvironmentimmunotherapym6Atumor treatment resistance

Identifiers

PMID38868768
PMCPMC11168112

What OpenQuestion holds

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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 OpenQuestion graph.