Evidence map›Paper›PMID 32175651›Full record

ArticleMolecular oncology2020

Mast cell-based molecular subtypes and signature associated with clinical outcome in early-stage lung adenocarcinoma.

Xuanwen Bao, Run Shi, Tianyu Zhao, Yanfang Wang

Open access · goldAbstract read
In one paragraph

Article in Molecular oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
3.9field-weighted citation impact, top 5% 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

40 citing papers in PubMed, 68 citations in OpenAlex.

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  7. DeSide: A unified deep learning approach for cellular deconvolution of tumor microenvironment.Proceedings of the National Academy of Sciences of the United States of America · 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

4 authors at 2 institutions in 1 country.

Xuanwen BaoInstitute of Radiation Biology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany.ORCID 0000-0002-6232-3783
Run ShiDepartment of Radiation Oncology, University Hospital, Ludwig Maximilian University of Munich, Germany.ORCID 0000-0003-4667-4812
Tianyu ZhaoInstitute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, Ludwig Maximilian University of Munich, Germany.ORCID 0000-0002-2696-273X
Yanfang WangLudwig-Maximilians-Universität München (LMU), Munich, Germany.ORCID 0000-0002-7989-5323
Helmholtz Zentrum München · DELudwig-Maximilians-Universität München · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mast cells are a major component of the immune microenvironment in tumour tissues and modulate tumour progression by releasing pro-tumorigenic and antitumorigenic molecules. Regarding the impact of mast cells on the outcomes of patients with lung adenocarcinoma (LUAD) patient, several published studies have shown contradictory results. Here, we aimed at elucidating the role of mast cells in early-stage LUAD. We found that high mast cell abundance was correlated with prolonged survival in early-stage LUAD patients. The mast cell-related gene signature and gene mutation data sets were used to stratify early-stage LUAD patients into two molecular subtypes (subtype 1 and subtype 2). The neural network-based framework constructed with the mast cell-related signature showed high accuracy in predicting response to immunotherapy. Importantly, the prognostic mast cell-related signature predicted the survival probability and the potential relationship between TP53 mutation, c-MYC activation and mast cell activities. The meta-analysis confirmed the prognostic value of the mast cell-related gene signature. In summary, this study might improve our understanding of the role of mast cells in early-stage LUAD and aid in the development of immunotherapy and personalized treatments for early-stage LUAD patients.

Indexed as

ImmunotherapyAdenocarcinoma of LungAlgorithmsBiomarkers, TumorDatabases, GeneticFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGene OntologyHumansKaplan-Meier EstimateLung NeoplasmsMaleMast CellsMutationNeoplasm StagingBiomarkers, TumorMYC protein, humanProto-Oncogene Proteins c-mycTP53 protein, humanTumor Suppressor Protein p53early-stage lung adenocarcinomaimmunotherapymast cellprognosis

Identifiers

PMID32175651
PMCPMC7191192
OpenAlexW3010955233

What OpenQuestion holds

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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 OpenQuestion graph.