Evidence map›Paper›PMID 32372138›Full record

ArticleCancer immunology, immunotherapy : CII2020

A gene expression-based immune signature for lung adenocarcinoma prognosis.

Lijuan Wang, Xizhi Luo, Chao Cheng, Christopher I Amos, Guoshuai Cai, Feifei Xiao

Open access · greenAbstract read
In one paragraph

Article in Cancer immunology, immunotherapy : CII, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.3field-weighted citation impact, top 17% 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

16 citing papers in PubMed, 20 citations in OpenAlex.

  1. The Current Roadmap of Lung Cancer Biology, Genomics and Racial Disparity.International journal of molecular sciences · 2025
    Review
  2. A review on trends in development and translation of omics signatures in cancer.Computational and structural biotechnology journal · 2024
    Review
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  9. An advanced non-small cell lung cancer patient withAnnals of translational medicine · 2022
    Article
  10. Prognostic Value of Genomic Instability of mFrontiers in cell and developmental biology · 2022
    Article
  11. Article
  12. Article
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  16. Review
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

6 authors at 2 institutions in 2 countries.

Lijuan WangDepartment of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, 29208, USA.
Xizhi LuoDepartment of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, 29208, USA.
Chao ChengDepartment of Medicine, Baylor College of Medicine, Houston, TX, 77030, USA.
Christopher I AmosDepartment of Medicine, Baylor College of Medicine, Houston, TX, 77030, USA.
Guoshuai CaiDepartment of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, Columbia, SC, 29208, USA.
Feifei XiaoDepartment of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, 29208, USA. xiaof@mailbox.sc.edu.ORCID http://orcid.org/0000-0002-1597-4719
University of South Carolina · USBaylor College of Medicine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung adenocarcinoma (LUAD) has become the most frequent histologic type of lung cancer in the past several decades. Recent successes with immune checkpoint blockade therapy have demonstrated that the manipulation of the immune system is a very potent treatment for LUAD. This study aims to explore the role of immune-related genes in the development of LUAD and establish a signature that can predict overall survival for LUAD patients.

methodsTo identify the differential expression genes (DEGs) between normal and tumor tissues, we developed an analysis strategy to combine an independent-sample design and a paired-sample design using RNA-seq transcriptomic profiling data of The Cancer Genome Atlas LUAD samples. Further, we selected prognostic markers from DEGs and evaluated their prognostic value in a prediction model.

resultsWe identified and validated PD1, PDL1 and CTLA4 genes as prognostic markers, which are well-known immune checkpoints, and revealed two new potential prognostic immune checkpoints for LUAD, HHLA2 (logFC = 2.55, FDR = 1.89 × 10

conclusionsThe identified DEG features may serve as potential biomarkers for prognosis prediction of LUAD patients and immunotherapy. Based on that assumption, we identified a gene expression-based immune signature for lung adenocarcinoma prognosis.

Indexed as

Adenocarcinoma of LungAgedBiomarkers, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansLung NeoplasmsMalePrognosisTranscriptomeBiomarkers, TumorDifferential expressionImmunotherapyLung adenocarcinomaPathway enrichmentPrognosis

Identifiers

PMID32372138
PMCPMC11027606
OpenAlexW3020896933

What OpenQuestion holds

Textmetadata
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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.