Evidence map›Paper›PMID 28789336›Full record

ArticleOncology letters2017

Potential role of miR-139-5p in cancer diagnosis, prognosis and therapy.

Ling-Li Huang, Ling-Wei Huang, Lei Wang, Ben-Ding Tong, Qing Wei, Xuan-Sheng Ding

Abstract read
In one paragraph

Article in Oncology letters, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

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  11. Impact of Oncogenic Targets by Tumor-SuppressiveInternational journal of molecular sciences · 2021
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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

6 authors.

Ling-Li HuangDepartment of Clinical Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu 210009, P.R. China.
Ling-Wei HuangKey Laboratory for Space Biosciences and Biotechnology, Institute of Special Environmental Biophysics, School of Life Sciences, Northwestern Polytechnical University, Xi'an, Shanxi 710072, P.R. China.
Lei WangDepartment of Pharmacy, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, Jiangsu 210009, P.R. China.
Ben-Ding TongDepartment of Pharmacy, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, Jiangsu 210009, P.R. China.
Qing WeiDepartment of Pharmacy, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, Jiangsu 210009, P.R. China.
Xuan-Sheng DingDepartment of Clinical Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu 210009, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) are short non-coding RNAs that regulate the expression of protein-coding genes by partially binding to specific target sites of mRNAs. miRNAs perform important functions in complicated cellular biological processes and their abnormal expression is involved in various disorders, including cancer. Among the miRNAs, differential expression of miR-139-5p serves a significant role in tumorigenesis, metastasis and recurrence, thus suggesting that it may potentially be used as a promising biomarker for cancer diagnosis, prognosis and therapy. miR-139-5p is expected to serve as a biomarker to eventually be implemented in a clinical setting. In the present review, we focus on the importance of miR-139-5p in cancer, summarize the association between miR-139-5p expression level and diagnosis and prognosis, and discuss the potential therapeutic implications for the future.

Indexed as

cancerdiagnosismicroRNAmicroRNA-139-5pprognosistherapy

Identifiers

PMID28789336
PMCPMC5529864

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.