Evidence map›Paper›PMID 38751753›Full record

ArticleOncology letters2024

Construction of an immune-related gene prognostic model with experimental validation and analysis of immune cell infiltration in lung adenocarcinoma.

Jialei Yang, Chao Tang, Chengxia Li, Xuesen Li, Wenli Yang

Abstract read
In one paragraph

Article in Oncology letters, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Jialei YangInstitute for Cancer Medicine, School of Basic Medicine Sciences, Southwest Medical University, Luzhou, Sichuan 646000, P.R. China.
Chao TangInstitute for Cancer Medicine, School of Basic Medicine Sciences, Southwest Medical University, Luzhou, Sichuan 646000, P.R. China.
Chengxia LiInstitute for Cancer Medicine, School of Basic Medicine Sciences, Southwest Medical University, Luzhou, Sichuan 646000, P.R. China.
Xuesen LiInstitute for Cancer Medicine, School of Basic Medicine Sciences, Southwest Medical University, Luzhou, Sichuan 646000, P.R. China.
Wenli YangInstitute for Cancer Medicine, School of Basic Medicine Sciences, Southwest Medical University, Luzhou, Sichuan 646000, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is a correlation between tumors and immunity with the degree of immune cell infiltration in tumors being closely related to tumor growth and progression. Therefore, the present study identified immune-related prognostic genes and evaluated the immune infiltration level in lung adenocarcinoma (LUAD). This study performed Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and Gene Set Enrichment Analysis (GSEA) enrichment analyses on differential immune-associated genes. A risk model was created and validated using six immune-related prognostic genes. Reverse transcription-quantitative PCR was used to assess the prognostic gene expression in non-small cell lung cancer cells. Immune cell infiltration in LUAD was analyzed using the CIBERSORT method. Single sample GSEA was used to compare Tumor Immune Dysfunction and Exclusion (TIDE) scores between high and low-risk groups and to assess the activation of thirteen immune-related pathways. Multifactor Cox proportional hazards model analysis identified six prognostic risk genes (

Indexed as

bioinformaticsimmune cell infiltrationimmune-related geneslung adenocarcinomaprognosis

Identifiers

PMID38751753
PMCPMC11094586

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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.