Evidence map›Paper›PMID 34804925›Full record

ArticleFrontiers in oncology2021

Comprehensive Analysis of m6A RNA Methylation Regulators in the Prognosis and Immune Microenvironment of Multiple Myeloma.

Rui Liu, Ying Shen, Jinsong Hu, Xiaman Wang, Dong Wu, Meng Zhai, Ju Bai, Aili He

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.6field-weighted citation impact, top 35% 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

10 citing papers in PubMed, 9 citations in OpenAlex.

  1. Emerging roles of RNA mInternational journal of oncology · 2026
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Essential mJournal of oncology · 2022
    Article
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

8 authors at 2 institutions in 1 country.

Rui LiuDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Ying ShenDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Jinsong HuDepartment of Cell Biology and Genetics, The Institute of Infection and Immunity, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Xiaman WangDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Dong WuDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Meng ZhaiDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Ju BaiDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Aili HeDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Second Affiliated Hospital of Xi'an Jiaotong University · CNXi'an Jiaotong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundN6-methyladenosine is the most abundant RNA modification, which plays a prominent role in various biology processes, including tumorigenesis and immune regulation. Multiple myeloma (MM) is the second most frequent hematological malignancy. MATERIALS AND

methodsTwenty-two m6A RNA methylation regulators were analyzed between MM patients and normal samples. Kaplan-Meier survival analysis and least absolute shrinkage and selection operator (LASSO) Cox regression analysis were employed to construct the risk signature model. Receiver operation characteristic (ROC) curves were used to verify the prognostic and diagnostic efficiency. Immune infiltration level was evaluated by ESTIMATE algorithm and immune-related single-sample gene set enrichment analysis (ssGSEA).

resultsHigh expression of HNRNPC, HNRNPA2B1, and YTHDF2 and low expression of ZC3H13 were associated with poor survival. Based on these four genes, a prognostic risk signature model was established. Multivariate Cox regression analysis demonstrated that the risk score was an independent prognostic factor of MM. Enrichment analysis showed that cell cycle, immune response, MYC, proteasome, and unfold protein reaction were enriched in high-risk MM patients. Furthermore, patients with higher risk score exhibited lower immune scores and lower immune infiltration level.

conclusionThe m6A-based prognostic risk score accurately and robustly predicts the survival of MM patients and is associated with the immune infiltration level, which complements current prediction models and enhances our cognition of immune infiltration.

Indexed as

immune infiltrationm6A (N6-methyladenosine)multiple myelomaRNA methylationsurvival

Identifiers

PMID34804925
PMCPMC8599583
OpenAlexW3211637832

What OpenQuestion 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 OpenQuestion graph.