Evidence map›Paper›PMID 33680217›Full record

ArticleDisease markers2021

Identification and Construction of a Long Noncoding RNA Prognostic Risk Model for Stomach Adenocarcinoma Patients.

Zhiqiang Zha, Peiling Zhang, Dailing Li, Guolong Liu, Lin Lu

Abstract read
In one paragraph

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 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

Who cites it

16 citing papers in PubMed.

  1. Functional, Pharmacogenomic, and Immune Landscapes of Long Non-Coding RNAs in Cancer.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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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.

Zhiqiang ZhaDepartment of Medical Oncology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou Guangdong, China.ORCID https://orcid.org/0000-0003-3292-0947
Peiling ZhangDepartment of Medical Oncology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou Guangdong, China.ORCID https://orcid.org/0000-0002-5316-6712
Dailing LiDepartment of Medical Oncology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou Guangdong, China.ORCID https://orcid.org/0000-0002-6300-1874
Guolong LiuDepartment of Medical Oncology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou Guangdong, China.ORCID https://orcid.org/0000-0002-8336-1703
Lin LuDepartment of Medical Oncology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou Guangdong, China.ORCID https://orcid.org/0000-0001-6000-0895

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLong noncoding RNA-based prognostic biomarkers have demonstrated great potential in the diagnosis and prognosis of cancer patients. However, systematic assessment of a multiple lncRNA-composed prognostic risk model is lacking in stomach adenocarcinoma (STAD). This study is aimed at constructing a lncRNA-based prognostic risk model for STAD patients.

methodsRNA sequencing data and clinical information of STAD patients were retrieved from The Cancer Genome Atlas (TCGA) database. Differentially expressed lncRNAs (DElncRNAs) were identified using the R software. Univariate and multivariate Cox regression analyses were performed to construct a prognostic risk model. The survival analysis, C-index, and receiver operating characteristic (ROC) curve were employed to assess the sensitivity and specificity of the model. The results were verified using the GEPIA online tool and our clinical samples. Pearson correlation coefficient analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed to indicate the potential biological functions of the selected lncRNA.

resultsA total of 1917 DElncRNAs were identified from 343 cases of STAD tissues and 30 cases of noncancerous tissues. According to univariate and multivariable Cox regression analyses, four DElncRNAs (AC129507.1, LINC02407, AL022316.1, and AP000695.2) were selected to establish a prognostic risk model. There was a significant difference in the overall survival between high-risk patients and low-risk patients based on this risk model. The C-index of the model was 0.652. The area under the curve (AUC) for the ROC curve was 0.769. GEPIA results confirmed the expression and prognostic significance of AP000695.2 in STAD. Our clinical data confirmed that upregulated expression of AP000695.2 was correlated with the T stage, distant metastasis, and TNM stage in STAD. GO and KEGG analyses demonstrated that AP000695.2 was closely related to the tumorigenesis process.

conclusionsIn this study, we constructed a lncRNA-based prognostic risk model for STAD patients. Our study will provide novel insight into the diagnosis and prognosis of STAD patients.

Indexed as

AdenocarcinomaAdultAgedBiomarkers, TumorFemaleHumansMaleMiddle AgedRNA, Long NoncodingStomach NeoplasmsSurvival AnalysisBiomarkers, TumorRNA, Long Noncoding

Identifiers

PMID33680217
PMCPMC7929674

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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.