Evidence map›Paper›PMID 36361541›Full record

ArticleInternational journal of molecular sciences2022

Classification of Subgroups with Immune Characteristics Based on DNA Methylation in Luminal Breast Cancer.

Mengyan Zhang, Te Ma, Cong Wang, Jiyun Zhao, Jie Xing, Honghao Liu, Mu Su, Ruiyang Zhai, Ting Liu, Baoqing Sun and 1 more

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Mengyan ZhangSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.ORCID 0000-0002-4774-9997
Te MaSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Cong WangSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Jiyun ZhaoSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Jie XingSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Honghao LiuSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Mu SuSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Ruiyang ZhaiSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Ting LiuCollege of Pathology, Qiqihar Medical University, Qiqihar 161042, China.
Baoqing SunState Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou 510089, China.
Yan ZhangSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.

Funding

Applied Technology Research and Development Project of Heilongjiang GA20C018Heilongjiang Postdoctoral Fund LBH-Z20158Heilongjiang Provincial Department of Education General Project 2016-KYYWF-0888National Natural Science Foundation of China 61972116National Natural Science Foundation of China 62102120National Natural Science Foundation of China U20A20376Qiqihar Medical College Doctoral Fund QY2016B-24
6 · The paper itself

Abstract

Luminal breast cancer (BC) accounts for a large proportion of patients in BC, with high heterogeneity. Determining the precise subtype and optimal selection of treatment options for luminal BC is a challenge. In this study, we proposed an MSBR framework that integrate DNA methylation profiles and transcriptomes to identify immune subgroups of luminal BC. MSBR was implemented both on a key module scoring algorithm and "Boruta" feature selection method by DNA methylation. Luminal A was divided into two subgroups and luminal B was divided into three subgroups using the MSBR. Furthermore, these subgroups were defined as different immune subgroups in luminal A and B respectively. The subgroups showed significant differences in DNA methylation levels, immune microenvironment (immune cell infiltration, immune checkpoint PD1/PD-L1 expression, immune cell cracking activity (CYT)) and pathology features (texture, eccentricity, intensity and tumor-infiltrating lymphocytes (TILs)). The results also showed that there is a subgroup in both luminal A and B that has the benefit from immunotherapy. This study proposed a classification of luminal BC from the perspective of epigenetics and immune characteristics, which provided individualized treatment decisions.

Indexed as

Breast NeoplasmsDNA MethylationFemaleHumansImmunotherapyLymphocytes, Tumor-InfiltratingTranscriptomeTumor MicroenvironmentDNA methylationimmune microenvironmentluminal breast cancerpathology featuresscRNA-seqsubgroup

Identifiers

PMID36361541
PMCPMC9658742

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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.