Evidence map›Paper›PMID 34346164›Full record

ArticleThoracic cancer2021

PIWI-interacting RNAs are aberrantly expressed and may serve as novel biomarkers for diagnosis of lung adenocarcinoma.

Juan Li, Nan Wang, Fang Zhang, Shan Jin, Yaqi Dong, Xiangjun Dong, Yuqing Chen, Xue Kong, Yao Tong, Qi Mi and 2 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Thoracic cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 10% 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

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 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

12 authors at 4 institutions in 1 country.

Juan LiDepartment of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Nan WangSchool of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China.
Fang ZhangDepartment of Pharmacy, Central Hospitlal Affiliated to Shandong First Medical University, Jinan, China.
Shan JinDepartment of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Yaqi DongDepartment of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Xiangjun DongDepartment of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Yuqing ChenDepartment of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Xue KongDepartment of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Yao TongDepartment of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Qi MiDepartment of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Yinghui ZhaoDepartment of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Yi ZhangDepartment of Respiratory and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan, China.ORCID 0000-0003-2843-7645
Second Hospital of Shandong University · CNJinan Central Hospital · CNQilu Hospital of Shandong University · CNShandong First Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung adenocarcinoma (LUAD) is the main subtype of primary lung cancer and is a leading cause of cancer-related death worldwide. PIWI-interacting RNAs (piRNAs) are a type of small non-coding RNAs that may play crucial roles in cancer progression and serve as biomarkers for tumor detection. This study aimed to explore the expression profiles and diagnostic values of piRNAs in LUAD.

methodsSmall RNA sequencing was performed to investigate tissue piRNA profiles of LUAD. The expression of selected upregulated piRNAs were detected in tissues and serum exosome samples by quantitative real-time polymerase chain reaction (qRT-PCR). Serum exosomes were identified by transmission electron microscope, nanoparticle tracking analysis, and western blot analysis. Receiver operating characteristic (ROC) curve was adopted to quantify the diagnostic potentials of piRNAs in LUAD. Finally, a piRNA panel was developed by multivariate logistic regression model.

resultsWe identified that 76 piRNAs were overexpressed and 9 piRNAs were underexpressed in LUAD tissues compared with adjacent non-tumor tissues. Among the top 10 overexpressed piRNAs, 4 piRNAs (piR-hsa-26925, piR-hsa-5444, piR-hsa-30636, and piR-hsa-8757) were verified by qRT-PCR to be significantly upregulated in LUAD tissues. Moreover, piR-hsa-26925 and piR-hsa-5444 had a significantly higher level in serum exosome samples of LUAD patients than those of healthy controls. We finally established a 2-piRNA panel composed of piR-hsa-26925 and piR-hsa-5444, which showed higher diagnostic performance for LUAD with an AUC of 0.833.

conclusionsOur finding revealed the abnormally expressed piRNAs in LUAD, and serum exosomal piR-hsa-26925 and piR-hsa-5444 could serve as potential biomarkers for LUAD diagnosis.

Indexed as

Adenocarcinoma of LungBiomarkers, TumorExosomesGene Expression Regulation, NeoplasticHumansLung NeoplasmsRNA, Small InterferingBiomarkers, TumorRNA, Small Interferingbiomarkerdiagnosislung adenocarcinomaPIWI-interacting RNAsserum exosome

Identifiers

PMID34346164
PMCPMC8447905
OpenAlexW3188958746

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.