Evidence map›Paper›PMID 34733970›Full record

ArticleAnnals of translational medicine2021

Classification and immune invasion analysis of breast cancer based on m6A genes.

Qiang Qin, Da Lang Fang, Weijie Zhou, Yuhua Meng, Jie Wei

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2021. 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
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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. The cellular landscape of druggable RNA-binding proteins.Nature reviews. Drug discovery · 2026
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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

5 authors at 3 institutions in 1 country.

Qiang QinDepartment of Hematology, Baise People's Hospital, Baise, China.
Da Lang FangDepartment of Breast and Thyroid Surgery, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China.
Weijie ZhouClinical Laboratory, Baise People's Hospital, Baise, China.
Yuhua MengDepartment of Pathology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, China.
Jie WeiDepartment of Hematology, Baise People's Hospital, Baise, China.
Affiliated Hospital of Youjiang Medical University for Nationalities · CNBaise University · CNThe First People's Hospital of Shunde · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer (BRCA) shows genetic, epigenetic, and phenotypic diversity. Methylation of N6-methyladenosine (m6A) affects the occurrence, development, and therapeutic efficacy of BRCA. However, the characteristics and prognostic value of m6A in BRCA remain unclear. We aimed to classify and construct a scoring system for the m6A regulatory gene in BRCA, and to explore its potential mechanisms.

methodsIn this study, we selected 23 m6A regulatory genes and analyzed their genetic variation in BRCA, including copy number variation (CNV) data, expression differences, mutations, gene types, and correlations between genes. Survival curves were drawn by the Kaplan-Meier method, and a log-rank P<0.05 was considered statistically significant. The partitioning around medoids (PAM) algorithm was used for molecular subtype analysis of m6A, single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm was used to quantify the relative infiltration levels of various immune cell subgroups, and a scoring system was built based on principal component analysis (PCA).

resultsIn BRCA, m6A regulatory gene mutation frequency is not high, while that of CNV mutation is high, which is related to gene expression and closely related to prognosis. In this study, we identified 3 different m6A subtypes, which are closely related to the level of immune cell infiltration. We further constructed an m6A score system, in which lower scores were correlated with low tumor mutation burden (TMB), later clinical staging, programmed cell death 1 ligand 1 (PD-L1) expression, and triple-negative breast cancer (TNBC).

conclusionsThis study highlights the diversity and complexity of the role of m6A in BRCA. The classification of BRCA based on the m6A regulatory gene can help us understand the characteristics of BRCA and help develop individualized immunotherapy regimens.

Indexed as

Breast cancerimmune characteristicsmolecular subtypeN6-methyladenosine (m6A)

Identifiers

PMID34733970
PMCPMC8506726
OpenAlexW3197244531

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LicenceCC BY-NC-ND
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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.