Evidence map›Paper›PMID 28849135›Full record

ArticleMolecular medicine reports2017

Identification of an lncRNA‑miRNA‑mRNA interaction mechanism in breast cancer based on bioinformatic analysis.

Yuhan Zhang, Yongfeng Li, Qing Wang, Xiping Zhang, Dajin Wang, Hong Chao Tang, Xuli Meng, Xianfeng Ding

Abstract read
In one paragraph

Article in Molecular medicine reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
–field-weighted citation impact
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

37 citing papers in PubMed.

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  3. Transcription Analysis of theInternational journal of genomics · 2023
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  10. Long non-coding RNA PVT1 facilitates cell migration and invasion by regulating miR-148a-3p and ROCK1 in breast cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2022
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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

8 authors.

Yuhan ZhangCollege of Life Science, Zhejiang Sci‑Tech University, Hangzhou, Zhejiang 310018, P.R. China.
Yongfeng LiDepartment of Breast Cancer Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang 310022, P.R. China.
Qing WangCollege of Life Science, Zhejiang Sci‑Tech University, Hangzhou, Zhejiang 310018, P.R. China.
Xiping ZhangDepartment of Breast Cancer Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang 310022, P.R. China.
Dajin WangCollege of Life Science, Zhejiang Sci‑Tech University, Hangzhou, Zhejiang 310018, P.R. China.
Hong Chao TangThe Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, P.R. China.
Xuli MengDepartment of Breast Cancer Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang 310022, P.R. China.
Xianfeng DingCollege of Life Science, Zhejiang Sci‑Tech University, Hangzhou, Zhejiang 310018, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non‑coding RNAs serve important roles in regulating the expression of certain genes and are involved in the principal biological processes of breast cancer. The majority of studies have focused on defining the regulatory functions of long non‑coding RNAs (lncRNAs) and microRNAs (miRNAs/miRs), and few studies have investigated how lncRNAs and miRNAs are transcriptionally regulated. In the present study, based on the breast invasive carcinoma dataset from The Cancer Genome Atlas at cBioPortal, and using a bioinformatics computational approach, an lncRNA‑miRNA‑mRNA network was constructed. The network consisted of 601 nodes and 706 edges, which represented the complex web of regulatory effects between lncRNAs, miRNAs and target genes. The results of the present study demonstrated that miR‑510 was the most potent miRNA controller and regulator of numerous target genes. In addition, it was observed that the lncRNAs PVT1, CCAT1 and linc00861 exhibited possible interactions with clinical biomarkers, including receptor tyrosine‑protein kinase erbB‑2, estrogen receptor and progesterone receptor, demonstrated using RNA‑protein interaction prediction software. The network of lncRNA‑miRNA‑mRNA interactions will facilitate further experimental studies and may be used to refine biomarker predictions for developing novel therapeutic approaches in breast cancer.

Indexed as

Computational BiologyGene Expression Regulation, NeoplasticGene Regulatory NetworksRNA InterferenceBreast NeoplasmsDatabases, GeneticFemaleGene Expression ProfilingGenetic VariationHumansMicroRNAsNucleic Acid ConformationRNA, Long NoncodingRNA, MessengerTranscriptomeMicroRNAsRNA, Long NoncodingRNA, Messenger

Identifiers

PMID28849135
PMCPMC5647044

What OpenQuestion holds

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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.