Evidence map›Paper›PMID 34112138›Full record

ArticleBMC cancer2021

A stable gene set for prediction of prognosis and efficacy of chemotherapy in gastric cancer.

Rui Wu, Sixuan Guo, Shuhui Lai, Guixing Pan, Linyi Zhang, Huanbing Liu

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PubMed Full text at PMC Publisher
In one paragraph

Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Rui Wu *The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Sixuan Guo *The Second Clinical College, Medical College of Nanchang University, Nanchang, Jiangxi, China.
Shuhui LaiThe First Clinical College, Medical College of Nanchang University, Nanchang, Jiangxi, China.
Guixing PanShangrao Maternity and Child Care Hospital, Shangrao, Jiangxi, China.
Linyi ZhangSchool of Ophthalmology & Optometry, Nanchang University, Nanchang, Jiangxi, China.
Huanbing LiuThe First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China. liuhuanbing6911@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGastric cancer (GC) is a primary reason for cancer death in the world. At present, GC has become a public health issue urgently to be solved to. Prediction of prognosis is critical to the development of clinical treatment regimens. This work aimed to construct the stable gene set for guiding GC diagnosis and treatment in clinic.

methodsA public microarray dataset of TCGA providing clinical information was obtained. Dimensionality reduction was carried out by selection operator regression on the stable prognostic genes discovered through the bootstrap approach as well as survival analysis.

findingsA total of 2 prognostic models were built, respectively designated as stable gene risk scores of OS (SGRS-OS) and stable gene risk scores of PFI (SGRS-PFI) consisting of 18 and 21 genes. The SGRS set potently predicted the overall survival (OS) along with progression-free interval (PFI) by means of univariate as well as multivariate analysis, using the specific risk scores formula. Relative to the TNM classification system, the SGRS set exhibited apparently higher predicting ability. Moreover, it was suggested that, patients who had increased SGRS were associated with poor chemotherapeutic outcomes.

interpretationThe SGRS set constructed in this study potentially serves as the efficient approach for predicting GC patient survival and guiding their treatment.

Indexed as

Antineoplastic AgentsBiomarkers, TumorDatasets as TopicDrug Resistance, NeoplasmGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateOligonucleotide Array Sequence AnalysisPrognosisProgression-Free SurvivalROC CurveStomach NeoplasmsSurvival AnalysisSurvival RateAntineoplastic AgentsBiomarkers, TumorGastric cancerImmune infiltrationMolecular typingPrediction of efficacy of chemotherapyPrognosis

Identifiers

PMID34112138
PMCPMC8194165

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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.