Evidence map›Paper›PMID 35967408›Full record

ArticleFrontiers in immunology2022

m6A-related metabolism molecular classification with distinct prognosis and immunotherapy response in soft tissue sarcoma.

Zhen-Dong Huang, Yong-Cheng Fu, Shu-Yan Liu, Ya-Juan Mao, Yan Zhang, Chao Hu, Ren-Xiong Wei

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 52% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. 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

7 authors at 2 institutions in 1 country.

Zhen-Dong HuangDepartment of Spine and Orthopedic Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Yong-Cheng FuThe Third Clinical School, Hubei University of Medicine, Shiyan, China.
Shu-Yan LiuThe Third Clinical School, Hubei University of Medicine, Shiyan, China.
Ya-Juan MaoThe Third Clinical School, Hubei University of Medicine, Shiyan, China.
Yan ZhangThe Third Clinical School, Hubei University of Medicine, Shiyan, China.
Chao HuDepartment of Spine and Orthopedic Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Ren-Xiong WeiDepartment of Spine and Orthopedic Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Hubei University of Medicine · CNZhongnan Hospital of Wuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

N6-methyladenosine (m6A) methylation, one of the most crucial RNA modifications, has been proven to play a key role that affect prognosis of soft tissue sarcoma (STS). However, m6A methylation potential role in STS metabolic processes remains unknown. We comprehensively estimated the m6A metabolic molecular subtypes and corresponding survival, immunity, genomic and stemness characteristics based on 568 STS samples and m6A related metabolic pathways. Then, to quantify the m6A metabolic subtypes, machine learning algorithms were used to develop the m6A-metabolic Scores of individual patients. Finally, two distinct m6A metabolic subtypes (Cluster A and Cluster B) among the STS patients were identified. Compared to Cluster B subtype, the Cluster A subtype was mainly characterized by better survival advantages, activated anti-tumor immune microenvironment, lower gene mutation frequency and higher anti-PD-1 immunotherapy response rates. We also found that the m6A-metabolic Scores could accurately predict the molecular subtype of STS, prognosis, the abundance of immune cell infiltration, tumor metastasis status, sensitivity to chemotherapeutics and immunotherapy response. In general, this study revealed that m6A-regulated tumor metabolism processes played a key role in terms of prognosis of STS, tumor progression, and immune microenvironment. The identification of metabolic molecular subtypes and the construction of m6A-metabolic Score will help to more effectively guide immunotherapy, metabolic therapy and chemotherapy in STS.

Indexed as

SarcomaAdenosineHumansImmunotherapyMethylationPrognosisTumor MicroenvironmentAdenosinecancer metabolismimmunotherapym6A modificationmachine learningmolecular classificationtumor microenvironment

Identifiers

PMID35967408
PMCPMC9374037
OpenAlexW4288723208

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.