Evidence map›Paper›PMID 34141460›Full record

ArticleMolecular therapy. Nucleic acids2021

Systematic identification of clinically relevant miRNAs for potential miRNA-based therapy in lung adenocarcinoma.

Shu-Hsuan Liu, Kai-Wen Hsu, Yo-Liang Lai, Yu-Feng Lin, Fang-Hsin Chen, Pei-Hwa Peng, Li-Jie Lin, Heng-Hsiung Wu, Chia-Yang Li, Shu-Chi Wang and 3 more

Open access · goldAbstract read
In one paragraph

Article in Molecular therapy. Nucleic acids, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.0field-weighted citation impact, top 30% 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

10 citing papers in PubMed, 12 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

13 authors at 6 institutions in 2 countries.

Shu-Hsuan LiuResearch Center for Cancer Biology, China Medical University, Taichung 40402, Taiwan.
Kai-Wen HsuInstitute of New Drug Development, Drug Development Center, China Medical University, Taichung 40402, Taiwan.
Yo-Liang LaiDepartment of Radiation Oncology, China Medical University Hospital, Taichung 40447, Taiwan.
Yu-Feng LinDepartment of Biotechnology, College of Medical and Health Science, Asia University, Taichung 41354, Taiwan.
Fang-Hsin ChenDepartment of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan 33302, Taiwan.
Pei-Hwa PengCancer Genome Research Center, Chang Gung Memorial Hospital at Linkou, Taoyuan 33305, Taiwan.
Li-Jie LinThe Ph.D. program for Cancer Biology and Drug Discovery, China Medical University and Academia Sinica, Taichung 40402, Taiwan.
Heng-Hsiung WuThe Ph.D. program for Cancer Biology and Drug Discovery, China Medical University and Academia Sinica, Taichung 40402, Taiwan.
Chia-Yang LiGraduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.
Shu-Chi WangDepartment of Medical Laboratory Science and Biotechnology, College of Health Sciences, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.
Min-Zu WuAbbVie Biotherapeutics Inc., Redwood City, CA 94063, USA.
Yuh-Pyng SherGraduate Institute of Biomedical Science, China Medical University, Taichung 40402, Taiwan.
Wei-Chung ChengResearch Center for Cancer Biology, China Medical University, Taichung 40402, Taiwan.
China Medical University · TWKaohsiung Medical University · TWAbbVie (United States) · USAsia University · TWChang Gung Memorial Hospital · TWChang Gung University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung adenocarcinoma (LUAD), the most common histological type of non-small cell lung cancer, is one of the most malignant and deadly diseases. Current treatments for advanced LUAD patients are far from ideal and require further improvements. Here, we utilized a systematic integrative analysis of LUAD microRNA sequencing (miRNA-seq) and RNA-seq data from The Cancer Genome Atlas (TCGA) to identify clinically relevant tumor suppressor miRNAs. Three miRNA candidates (miR-195-5p, miR-101-3p, and miR-338-5p) were identified based on their differential expressions, survival significance levels, correlations with targets, and an additive effect on survival among them. We further evaluated mimics of the three miRNAs to determine their therapeutic potential in inhibiting cancer progression. The results showed not only that each of the miRNA mimics alone but also the three miRNA mimics in combination were efficient at inhibiting tumor growth and progression with equal final concentrations, meaning that the three miRNA mimics in combination were more effective than the single miRNA mimics. Moreover, the combined miRNA mimics provided significant therapeutic effects in terms of reduced tumor volume and metastasis nodules in lung tumor animal models. Hence, our findings show the potential of using the three miRNAs in combination to treat LUAD patients with poor survival outcomes.

Indexed as

additive effectlung adenocarcinomamiRNAmiRNA mimicsnucleotide drugtherapy

Identifiers

PMID34141460
PMCPMC8181588
OpenAlexW3158388393

What OpenQuestion holds

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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.