Evidence map›Paper›PMID 37457713›Full record

ArticleFrontiers in immunology2023

Mitochondrial DNA methylation is a predictor of immunotherapy response and prognosis in breast cancer: scRNA-seq and bulk-seq data insights.

Yixuan Ma, Juan Du, Meini Chen, Ning Gao, Sijia Wang, Zhikuan Mi, Xiaoli Wei, Jumei Zhao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

14 citing papers in PubMed, 12 citations in OpenAlex.

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  12. Mitochondrial epigenetic mechanisms in cancer: an updated overview.Frontiers in cell and developmental biology · 2025
    Review
  13. Review
  14. CD8Frontiers in immunology · 2024
    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

8 authors at 1 institution in 1 country.

Yixuan MaShaanbei Key Laboratory for Cancer Prevention of Yan'an, Medical College, Yan'an University, Yan'an, China.
Juan DuShaanbei Key Laboratory for Cancer Prevention of Yan'an, Medical College, Yan'an University, Yan'an, China.
Meini ChenShaanbei Key Laboratory for Cancer Prevention of Yan'an, Medical College, Yan'an University, Yan'an, China.
Ning GaoShaanbei Key Laboratory for Cancer Prevention of Yan'an, Medical College, Yan'an University, Yan'an, China.
Sijia WangShaanbei Key Laboratory for Cancer Prevention of Yan'an, Medical College, Yan'an University, Yan'an, China.
Zhikuan MiShaanbei Key Laboratory for Cancer Prevention of Yan'an, Medical College, Yan'an University, Yan'an, China.
Xiaoli WeiShaanbei Key Laboratory for Cancer Prevention of Yan'an, Medical College, Yan'an University, Yan'an, China.
Jumei ZhaoShaanbei Key Laboratory for Cancer Prevention of Yan'an, Medical College, Yan'an University, Yan'an, China.
Yan'an University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Alterations in Mitochondrial DNA methylation (MTDM) exist in many tumors, but their role in breast cancer (BC) development remains unclear. Methods: We analyzed BC patient data by combining scRNA-seq and bulk sequencing. Weighted co-expression network analysis (WGCNA) of TCGA data identified mitochondrial DNA methylation (MTDM)-associated genes in BC. COX regression and LASSO regression were used to build prognostic models. The biological function of MTDM was assessed using various methods, such as signaling pathway enrichment analysis, copynumber karyotyping analysis, and quantitative analysis of the cell proliferation rate. We also evaluated MTDM-mediated alterations in the immune microenvironment using immune microenvironment, microsatellite instability, mutation, unsupervised clustering, malignant cell subtype differentiation, immune cell subtype differentiation, and cell-communication signature analyses. Finally, we performed cellular experiments to validate the role of the MTDM-associated prognostic gene Results: In this study, MTDM-associated prognostic models divided BC patients into high/low MTDM groups in TCGA/GEO datasets. The difference in survival time between the two groups was statistically significant (P<0.001). We found that high MTDM status was positively correlated with tumor cell proliferation. We analyzed the immune microenvironment and found that low-MTDM group had higher immune checkpoint gene expression/immune cell infiltration, which could lead to potential benefits from immunotherapy. In contrast, the high MTDM group had higher proliferation rates and levels of CD8+T cell exhaustion, which may be related to the secretion of GDF15 by malignant breast epithelial cells with a high MTDM status. Cellular experiments validated the role of the MTDM-associated prognostic gene NCAPD3 (the gene most positively correlated with epithelial malignant cell proliferation in the model) in BC. Knockdown of NCAPD3 significantly reduced the activity and proliferation of MDA-MB-231 and BCAP-37 cells, and significantly reduced their migration ability of BCAP-37 cell line. Conclusion: This study presented a holistic evaluation of the multifaceted roles of MTDM in BC. The analysis of MTDM levels not only enables the prediction of response to immunotherapy but also serves as an accurate prognostic indicator for patients with BC. These insightful discoveries provide novel perspectives on tumor immunity and have the potentially to revolutionize the diagnosis and treatment of BC.

Indexed as

Breast NeoplasmsDNA, MitochondrialDNA MethylationFemaleHumansImmunotherapyPrognosisSingle-Cell Gene Expression AnalysisTumor MicroenvironmentDNA, Mitochondrialbreast cancerimmunotherapymitochondrial DNA methylation (MTDM)NCAPD3prognostic model

Identifiers

PMID37457713
PMCPMC10339346
OpenAlexW4382723098

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.