Evidence map›Paper›PMID 39831256›Full record

ArticleJournal of thoracic disease2024

Comprehensive bioinformatics analysis of prognosis and immunotherapy in lung adenocarcinoma.

Ling Peng, Luping Xia, Meiyu Yang, Yali Wen, Qinghua Zeng

Abstract read
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In one paragraph

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

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0citing papers in PubMed
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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

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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

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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.

Ling PengDepartment of Respiratory and Critical Care Medicine, Jiangxi Provincial Key Laboratory of Respiratory Diseases, Jiangxi Institute of Respiratory Diseases, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Luping XiaChina-Japan Friendship Jiangxi Hospital, National Regional Center for Respiratory Medicine, Nanchang, China.
Meiyu YangDepartment of Respiratory and Critical Care Medicine, Jiangxi Provincial Key Laboratory of Respiratory Diseases, Jiangxi Institute of Respiratory Diseases, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Yali WenDepartment of Respiratory and Critical Care Medicine, Jiangxi Provincial Key Laboratory of Respiratory Diseases, Jiangxi Institute of Respiratory Diseases, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Qinghua ZengDepartment of Respiratory and Critical Care Medicine, Jiangxi Provincial Key Laboratory of Respiratory Diseases, Jiangxi Institute of Respiratory Diseases, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Research has shown that genetic mutations play an important role in the prognosis of lung adenocarcinoma (LUAD). However, the genes that influence the prognosis and immunotherapy of lung cancer patients have not yet been thoroughly studied. In this study, data from The Cancer Genome Atlas (TCGA) Program and other databases were used to identify the survival-related genes in LUAD. Methods: First, the TCGA database was used to screen key LUAD genes. Second, the Gene Expression Profiling Interactive Analysis 2 (GEPIA2), University of ALabama at Birmingham CANcer (UALCAN), Tumor IMmune Estimation Resource (TIMER), Kaplan-Meier plotter, and cBioPortal databases, and a univariate Cox analysis combined with a random forest (RF) model were used to estimate gene expression, patient prognosis, and gene mutations, respectively. TIMER was also used to predict the immune function of the genes. Results: A total of 2,138 up-regulated and 2,559 down-regulated differentially expressed genes (DEGs) were identified from TCGA-LUAD dataset. Next, four prognostic genes (i.e., Conclusions: Of the four key genes identified,

Indexed as

immunotherapyLung adenocarcinoma (LUAD)survival analysisThe Cancer Genome Atlas (TCGA)

Identifiers

PMID39831256
PMCPMC11740037

What Socratic holds

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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 Socratic graph.