Evidence map›Paper›PMID 36728032›Full record

ArticleIET systems biology2023

Development and validation of an immune-related gene signature for prognosis in Lung adenocarcinoma.

Zehuai Guo, Xiangjun Qi, Zeyun Li, Jianying Yang, Zhe Sun, Peiqin Li, Ming Chen, Yang Cao

Abstract read
In one paragraph

Article in IET systems biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Zehuai GuoThe First Clinical School of Guangzhou University of Chinese Medicine, Guangzhou, China.ORCID 0000-0002-7085-9502
Xiangjun QiThe First Clinical School of Guangzhou University of Chinese Medicine, Guangzhou, China.
Zeyun LiThe First Clinical School of Guangzhou University of Chinese Medicine, Guangzhou, China.
Jianying YangThe First Clinical School of Guangzhou University of Chinese Medicine, Guangzhou, China.
Zhe SunThe First Clinical School of Guangzhou University of Chinese Medicine, Guangzhou, China.
Peiqin LiThe First Clinical School of Guangzhou University of Chinese Medicine, Guangzhou, China.
Ming ChenThe First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Yang CaoThe First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The most common type of lung cancer tissue is lung adenocarcinoma. The TCGA-LUAD cohort retrieved from the TCGA dataset was considered the internal training cohort, while GSE68465 and GSE13213 datasets from the GEO database were used as the external test cohort. The TCGA-LUAD cohort was classified into two immune subtypes using single-sample gene set enrichment analysis of the immune gene set and unsupervised clustering analysis. The ESTIMATE algorithm, the CIBERSORT algorithm, and HLA family expression levels again validated the reliability of this typing. We performed Venn analysis using immune-related genes from the immport dataset and differentially expressed genes from the subtypes to retrieve differentially expressed immune genes (DEIGs). In addition, DEIGs were used to construct a prognostic model with the least absolute shrinkage and selection operator regression analysis. A reliable risk model consisting of 11 DEIGs, including S100P, INHA, SEMA7A, INSL4, CD40LG, AGER, SERPIND1, CD1D, CX3CR1, SFTPD, and CD79A, was then built, and its reliability was further confirmed by ROC curve and calibration plot analysis. The high-risk score subgroup had a poor prognosis and a lower tumour immune dysfunction and exclusion score, indicating a greater likelihood of anti-PD-1/cytotoxic T lymphocyte antigen 4 benefit.

Indexed as

Adenocarcinoma of LungLung NeoplasmsAlgorithmsCalibrationHumansReproducibility of Resultsbioinformaticsimmune-related geneimmunotherapylung adenocarcinomaprognosisssGSEA

Identifiers

PMID36728032
PMCPMC9931057

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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.