Evidence map›Paper›PMID 33511215›Full record

ArticleBioMed research international2021

Potential Prognostic Biomarkers of Lung Adenocarcinoma Based on Bioinformatic Analysis.

Jili Hou, Cheng Yao

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
2.6field-weighted citation impact, top 9% of its field
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

21 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
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  3. Tumor-promoting UBR4 coordinates impaired mitophagy-associated senescence and lung adenocarcinoma pathogenesis.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  18. The Prognostic Value and Immune Landscapes of a mFrontiers in cell and developmental biology · 2021
    Article
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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

2 authors at 2 institutions in 1 country.

Jili HouDepartment of Medical Oncology, Zhuji People's Hospital of Zhejiang Province, The Zhuji Affiliated Hospital of Shaoxing University, No. 9 Jianmin Road, Tao Zhu Street, Zhuji, Zhejiang 311800, China.ORCID https://orcid.org/0000-0002-9313-9540
Cheng YaoDepartment of Medical Oncology, The Second Affiliated Hospital of Zhejiang Chinese Medical University, 318 Chaowang Road, Hangzhou, Zhejiang 310005, China.ORCID https://orcid.org/0000-0003-3405-515X
Shaoxing University · CNZhejiang Chinese Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung adenocarcinoma (LUAD), which accounts for 60% of non-small-cell lung cancers, is poorly diagnosed and has a low average 5-year survival rate (approximately 20%). It remains the leading cause of cancer-related deaths worldwide. Studies on long noncoding RNAs (lncRNAs) in LUAD-related competing endogenous RNA (ceRNA) networks are limited. We aimed to identify novel prognostic biomarkers for LUAD using bioinformatic tools and data analysis. We systemically integrated differentially expressed genes and clinically significant modules using weighted correlation network analysis. We performed a functional analysis of the collected candidate genes and explored three LUAD-related genes (

Indexed as

Adenocarcinoma of LungBiomarkers, TumorComputational BiologyGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansLung NeoplasmsMicroRNAsPrognosisProtein Interaction MapsReproducibility of ResultsRNA, Long NoncodingRNA, MessengerROC CurveSurvival AnalysisBiomarkers, TumorMicroRNAsRNA, Long NoncodingRNA, Messenger

Identifiers

PMID33511215
PMCPMC7822677
OpenAlexW3118979076

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.