Evidence map›Paper›PMID 38317924›Full record

ArticleHeliyon2024

Novel prognostic signature for lung adenocarcinoma based on immune-related mRNA pairs.

Jiawei Yue, Hui Guo, Jinhong Ma, Weifeng Shi, Yumin Wu

Abstract read
In one paragraph

Article in Heliyon, 2024. 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
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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

5 authors.

Jiawei YueDepartment of Orthopaedics, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China.
Hui GuoDepartment of Laboratory Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China.
Jinhong MaDepartment of Laboratory Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China.
Weifeng ShiDepartment of Laboratory Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China.
Yumin WuDepartment of Laboratory Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213003, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung adenocarcinoma (LUAD) is a highly lethal malignant tumor. While the involvement of multiple mRNAs in the progression of LUAD is well established, the potential diagnostic value of immune-related mRNAs (irmRNAs) in LUAD remains largely unexplored. In this study, we utilized RNA-seq, clinical data, and immune-related gene information from LUAD patients to identify differentially expressed immune-related mRNAs (DEirmRNAs) and developed a predictive risk model based on specific DEirmRNA pairs closely linked with patient prognosis. We classified patients into high-risk and low-risk groups and analyzed factors such as survival rate, clinical characteristics, gene enrichment, immune cell infiltration, tumor mutation load, and drug susceptibility. We confirmed the expression levels of these DEirmRNAs in tumor tissues using qRT-PCR assay. Our results showed that the low-risk group had a longer survival time and lower tumor mutation burden (TMB) and microsatellite instability (MSI) compared to the high-risk group. The high-risk group also had a significant reduction in the number of certain immune cells and a lower half-maximum inhibitor concentration (IC50). We identified specific DEirmRNA pairs that were up-regulated or down-regulated in tumor tissues compared to adjacent tissues. Our prognostic risk model based on DEirmRNA pairs could be used to predict the prognosis of LUAD patients and provide reference for better treatment.

Indexed as

Immune-related mRNALung adenocarcinomaRisk modelSurvival prognosis

Identifiers

PMID38317924
PMCPMC10839877

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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.