Evidence map›Paper›PMID 36109402›Full record

ArticleJournal of cancer research and clinical oncology2023

Prognostic value of comprehensive typing based on m6A and gene cluster in TNBC.

Haoming Wu, Jikun Feng, Jundong Wu, Wenjing Zhong, Xiazi Zouxu, Weiling Huang, Xinjian Huang, Jiarong Yi, Xi Wang

Open access · greenAbstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Epigenetic Modulation of Estrogen Receptor Signaling in Ovarian Cancer.International journal of molecular sciences · 2024
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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

9 authors at 3 institutions in 1 country.

Haoming Wu *The Breast Center, Guangdong Provincial Key Laboratory of Breast Cancer Diagnosis and Treatment, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Jikun Feng *Department of Breast Oncology, The State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China.
Jundong WuThe Breast Center, Guangdong Provincial Key Laboratory of Breast Cancer Diagnosis and Treatment, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Wenjing ZhongDepartment of Breast Oncology, The State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China.
Xiazi ZouxuDepartment of Breast Oncology, The State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China.
Weiling HuangDepartment of Breast Oncology, The State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China.
Xinjian HuangDepartment of Breast Oncology, The State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China.
Jiarong YiDepartment of Breast Oncology, The State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China. yijr@sysucc.org.cn.
Xi WangDepartment of Breast Oncology, The State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China. yijr@sysucc.org.cn.
Sun Yat-sen University Cancer Center · CNSun Yat-sen University · CNShantou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTriple-negative breast cancer (TNBC) is resistant to targeted therapy with HER2 monoclonal antibodies and endocrine therapy, because it lacks the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). TNBC is a subtype of breast cancer with the worst prognosis and the highest mortality rate compared to other subtypes. N6-methyladenosine (m6A) modification is significant in cancer and metastasis, because it can alter gene expression and function at numerous levels, such as RNA splicing, stability, translocation, and translation. There are limited investigations into the connection between TNBC and m6A. MATERIALS AND

methodsBreast cancer-related data were retrieved from the Cancer Genome Atlas (TCGA) database, and 116 triple-negative breast cancer cases were identified from the data. The GSE31519 data set, which included 68 cases of TNBC, was obtained from the Gene Expression Omnibus (GEO) database. Survival analysis was used to determine the prognosis of distinct m6A types based on their m6A group, gene group, and m6A score. To investigate the potential mechanism, GO and KEGG analyses were performed on the differentially expressed genes.

resultsThe expression of m6A-related genes and their impact on prognosis in TNBC patients were studied. According to the findings, m6A was crucial in determining the prognosis of TNBC patients, and the major m6A-linked genes in this process were YTHDF2, RBM15B, IGFBP3, and WTAP. YTHDF2, RBM15B and IGFBP3 are associated with poor prognosis, while WTAP is associated with good prognosis. By cluster analysis, the gene cluster and the m6A cluster were beneficial in predicting the prognosis of TNBC patients. The m6A score based on m6A and gene clusters was more effective in predicting the prognosis of TNBC patients. Furthermore, the tumor microenvironment may play an important role in the process of m6A, influencing TNBC prognosis.

conclusionsN6-adenylic acid methylation (m6A) was important in altering the prognosis of TNBC patients, and the key m6A-associated genes in this process were YTHDF2, RBM15B, IGFBP3, and WTAP. Furthermore, the comprehensive typing based on m6A and gene clusters was useful in predicting TNBC patients' prognosis, showing potential as valuable evaluating tools for TNBC.

Indexed as

Triple Negative Breast NeoplasmsBreastHumansMultigene FamilyPrognosisTranscription FactorsTumor MicroenvironmentTranscription FactorsGEOM6APrognosisTCGATNBCTyping

Identifiers

PMID36109402
PMCPMC11798311
OpenAlexW4296032991

What OpenQuestion holds

Textmetadata
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.