Evidence map›Paper›PMID 35572729›Full record

ArticleBioMed research international2022

lncRNA-mRNA Expression Patterns in Invasive Pituitary Adenomas: A Microarray Analysis.

Chao Peng, Shuaikai Wang, Jinxiu Yu, Xiaoyi Deng, Huiyu Ye, Zhishan Chen, Hongru Yao, Hanjia Cai, Yanli Li, Yong Yuan

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

6 citing papers in PubMed, 11 citations in OpenAlex.

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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

10 authors at 5 institutions in 1 country.

Chao PengDepartment of Neurosurgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China.ORCID https://orcid.org/0000-0002-8928-5000
Shuaikai WangDepartment of Neurosurgery, Shenzhen Luohu People's Hospital, Shenzhen, Guangdong 518001, China.ORCID https://orcid.org/0000-0003-1319-3107
Jinxiu YuDepartment of Radiotherapy, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510260, China.ORCID https://orcid.org/0000-0001-5316-8585
Xiaoyi DengDepartment of Endocrinology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510260, China.ORCID https://orcid.org/0000-0003-4250-0241
Huiyu YeDepartment of Endocrinology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510260, China.ORCID https://orcid.org/0000-0001-9455-5565
Zhishan ChenDepartment of Endocrinology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510260, China.ORCID https://orcid.org/0000-0003-2126-6839
Hongru YaoGuangzhou Medical University, Guangzhou, Guangdong 510000, China.ORCID https://orcid.org/0000-0002-9288-5429
Hanjia CaiGuangzhou Medical University, Guangzhou, Guangdong 510000, China.ORCID https://orcid.org/0000-0002-9243-1777
Yanli LiDepartment of Endocrinology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510260, China.ORCID https://orcid.org/0000-0002-9212-1752
Yong YuanDepartment of Neurosurgery, The Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650101, China.ORCID https://orcid.org/0000-0002-4615-2056
Second Affiliated Hospital of Guangzhou Medical University · CNGuangzhou Medical University · CNGuangdong Academy of Medical Sciences · CNKunming Medical University · CNShenzhen Luohu People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Long noncoding RNAs (lncRNAs) play important roles in the tumorigenesis and progression of various cancer types; however, their roles in the development of invasive pituitary adenomas (PAs) remain to be investigated. Methods: lncRNA microarray analysis was performed for three invasive and three noninvasive PAs. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed, and coexpression networks between lncRNA and mRNA were constructed. Furthermore, three differentially expressed lncRNAs were selected for validation in PA samples by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). The diagnostic values of these three lncRNAs were further evaluated by a receiver operating characteristic (ROC) curve analysis. Results: A total of 8872 lncRNAs were identified in invasive and paired noninvasive PAs via lncRNA microarray analysis. Among these, the differentially expressed lncRNAs included 81 that were upregulated and 165 that were downregulated. GO enrichment and KEGG pathway analysis showed that these differentially expressed lncRNAs were associated with the posttranslational modifications of proteins. Furthermore, we performed target gene prediction and coexpression analysis. The interrelationships between the significantly differentially expressed lncRNAs and mRNAs were identified. Additionally, three differentially expressed lncRNAs were selected for validation in 41 PA samples by qRT-PCR. The expression levels of FAM182B, LOC105371531, and LOC105375785 were significantly lower in the invasive PAs than in the noninvasive PAs ( Conclusion: Our findings demonstrated the expression patterns of lncRNAs in invasive PAs. FAM182B and LOC105375785 may be involved in the invasiveness of PAs and serve as new candidate biomarkers for the diagnosis of invasive PAs.

Indexed as

AdenomaPituitary NeoplasmsRNA, Long NoncodingGene Expression ProfilingGene Regulatory NetworksHumansMicroarray AnalysisRNA, MessengerRNA, Long NoncodingRNA, Messenger

Identifiers

PMID35572729
PMCPMC9098296
OpenAlexW4229022671

What OpenQuestion holds

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Registered trials

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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.