Evidence map›Paper›PMID 38777866›Full record

ArticleJournal of cancer research and clinical oncology2024

A novel subtype based on driver methylation-transcription in lung adenocarcinoma.

Xin Wang, Zhenyi Xu, Shuang Zhao, Jiali Song, Yipei Yu, Han Yang, Yan Hou

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Article in Journal of cancer research and clinical oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Xin Wang *Clinical Trial Research Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, China.
Zhenyi Xu *Huadong Hospital Affiliated to Fudan University, Shanghai, 200040, China.
Shuang ZhaoClinical Trial Research Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, China.
Jiali SongDepartment of Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Yipei YuDepartment of Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Han YangClinical Trial Research Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, China.
Yan HouDepartment of Biostatistics, School of Public Health, Peking University, Beijing, 100191, China. houyan@bjmu.edu.cn.

Funding

National Key Research and Development Program of China 2021YFF0901401National Natural Science Foundation of China 82173615
6 · The paper itself

Abstract

aimsTo identify driver methylation genes and a novel subtype of lung adenocarcinoma (LUAD) by multi-omics and elucidate its molecular features and clinical significance.

methodsWe collected LUAD patients from public databases, and identified driver methylation genes (DMGs) by MethSig and MethylMix algrothms. And novel driver methylation multi-omics subtypes were identified by similarity network fusion (SNF). Furthermore, the prognosis, tumor microenvironment (TME), molecular features and therapy efficiency among subtypes were comprehensively evaluated.

results147 overlapped driver methylation were identified and validated. By integrating the mRNA expression and methylation of DMGs using SNF, four distinct patterns, termed as S1-S4, were characterized by differences in prognosis, biological features, and TME. The S2 subtype showed unfavorable prognosis. By comparing the characteristics of the DMGs subtypes with the traditional subtypes, S3 was concentrated in proximal-inflammatory (PI) subtype, and S4 was consisted of terminal respiratory unit (TRU) subtype and PI subtype. By analyzing TME and epithelial mesenchymal transition (EMT) features, increased immune infiltration and higher expression of immune checkpoint genes were found in S3 and S4. While S4 showed higher EMT score and expression of EMT associated genes, indicating S4 may not be as immunosensitive as the S3. Additionally, S3 had lower TIDE and higher IPS score, indicating its increased sensitivity to immunotherapy.

conclusionThe driver methylation-related subtypes of LUAD demonstrate prognostic predictive ability that could help inform treatment response and provide complementary information to the existing subtypes.

Indexed as

Adenocarcinoma of LungDNA MethylationLung NeoplasmsBiomarkers, TumorEpithelial-Mesenchymal TransitionFemaleGene Expression Regulation, NeoplasticHumansMalePrognosisTumor MicroenvironmentBiomarkers, TumorDriver methylation geneHeterogeneityLung adenocarcinomaPersonalized therapyPrognosisTumor microenvironment

Identifiers

PMID38777866
PMCPMC11111506

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