Evidence map›Paper›PMID 34580602›Full record

ArticleDisease markers2021

An Inflammation-Related Nine-Gene Signature to Improve Prognosis Prediction of Lung Adenocarcinoma.

Ze-Jing Liu, Peng-Xiao Hou, Xi-Xing Wang

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Article in Disease markers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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.

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2 · The registry

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Ze-Jing LiuDepartment of Oncology, Shanxi Provincial Hospital of Traditional Chinese Medicine, Taiyuan City, Shanxi Province, China.
Peng-Xiao HouDepartment of Traditional Chinese Medicine, Shanxi Cancer Hospital, Taiyuan City, Shanxi Province, China.
Xi-Xing WangDepartment of Oncology, Shanxi Provincial Hospital of Traditional Chinese Medicine, Taiyuan City, Shanxi Province, China.ORCID https://orcid.org/0000-0003-2941-7291

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA novel predictive model was rarely reported based on inflammation-related genes to explore clinical outcomes of lung adenocarcinoma (LUAD) patients.

methodsUsing TCGA database, we screened nine inflammation-related genes with a prognostic value, and LASSO regression was applied for model construction. The predictive value of the prognostic signature developed from inflammation-related genes was assessed by survival assays and multivariate assays. PCA and t-SNE analysis were performed to demonstrate clustering abilities of risk scores.

resultsThirteen inflammation-related genes (BTG2, CCL20, CD69, DCBLD2, GPC3, IL7R, LAMP3, MMP14, NMUR1, PCDH7, PIK3R5, RNF144B, and TPBG) with prognostic values were finally identified. LASSO regression further screened nine candidates (BTG2, CCL20, CD69, IL7R, MMP14, NMUR1, PCDH7, RNF144B, and TPBG). Then, a prognostic prediction model using the above nine genes was constructed. A reliable clustering ability of risk score was demonstrated by PCA and t-SNE assays in 500 LUAD patients. The survival assays revealed that the overall survivals of the high-risk group were distinctly poorer than those of the low-risk group with 1-, 3-, and 5-year AUC values of 0.695, 0.666, and 0.694, respectively. Finally, multivariate assays demonstrated the scoring system as an independent prognostic factor for overall survival.

conclusionsOur study shows that the signature of nine inflammation-related genes can be used as a prognostic marker for LUAD.

Indexed as

Gene Expression Regulation, NeoplasticTranscriptomeAdenocarcinoma of LungBiomarkers, TumorGene Expression ProfilingHumansInflammationLung NeoplasmsPrognosisSurvival RateBiomarkers, Tumor

Identifiers

PMID34580602
PMCPMC8464410

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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.