Evidence map›Paper›PMID 31779055›Full record

ArticleJournal of cellular and molecular medicine2020

Systematic construction and validation of an immune prognostic model for lung adenocarcinoma.

Chenghan Luo, Mengyuan Lei, Yixia Zhang, Qian Zhang, Lifeng Li, Jingyao Lian, Shasha Liu, Liping Wang, Guofu Pi, Yi Zhang

Open access · goldAbstract readValidation Study
In one paragraph

Article in Journal of cellular and molecular medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
13.3field-weighted citation impact, top 1% 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

48 citing papers in PubMed, 90 citations in OpenAlex.

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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

10 authors at 2 institutions in 1 country.

Chenghan LuoBiotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.ORCID 0000-0002-0815-8000
Mengyuan LeiPhysical Examination Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yixia ZhangNeonatal Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Qian ZhangNeonatal Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Lifeng LiBiotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Jingyao LianBiotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Shasha LiuBiotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Liping WangCancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Guofu PiOrthopedics Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yi ZhangBiotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.ORCID 0000-0001-9861-4681
First Affiliated Hospital of Zhengzhou University · CNHenan Cancer Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung adenocarcinoma (LUAD), the most common non-small-cell lung cancer, is characterized by a dense lymphocytic infiltrate, which indicates that the immune system plays an active role in the development and growth of this cancer. However, no investigations to date have proposed robust models for predicting survival outcome for patients with LUAD in terms of tumour immunology. A total of 761 LUAD patients were included in this study, in which the database of The Cancer Genome Atlas (TCGA) was utilized for discovery, and the Gene Expression Omnibus (GEO) database was utilized for validation. Bioinformatics analysis and R language tools were utilized to construct an immune prognostic model and annotate biological functions. Lung adenocarcinoma showed a weakened immune phenotype compared with adjacent normal tissues. Immune-related gene sets were profiled, an immune prognostic model based on 2 immune genes (ANLN and F2) was developed with the TCGA database to distinguish cases as having a low or high risk of unfavourable prognosis, and the model was verified with the GEO database. The model was prognostically significant in stratified cohorts, including stage I-II, stage III-IV and epidermal growth factor receptor (EGFR) mutant subsets, and was considered to be an independent prognostic factor for LUAD. Furthermore, the low- and high-risk groups showed marked differences in tumour-infiltrating leucocytes, tumour mutation burden, aneuploidy and PD-L1 expression. In conclusion, an immune prognostic model was proposed for LUAD that is capable of independently identifying patients at high risk for poor survival, suggesting a relationship between local immune status and prognosis.

Indexed as

Gene Expression Regulation, NeoplasticNomogramsTranscriptomeAdenocarcinoma of LungBiomarkers, TumorComputational BiologyHumansLung NeoplasmsMast CellsNeutrophilsPrognosisSurvival RateT-Lymphocytes, RegulatoryBiomarkers, Tumorbiomarkersimmune prognostic modelimmunologylung adenocarcinomaoverall survival

Identifiers

PMID31779055
PMCPMC6991688
OpenAlexW2990960788

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Registered trials

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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.