Evidence map›Paper›PMID 33447052›Full record

ReviewOncoTargets and therapy2020

Mechanisms and Functions of MiR-200 Family in Hepatocellular Carcinoma.

Yinqi Mao, Wei Chen, Han Wu, Chenbin Liu, Jingjun Zhang, Shuying Chen

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in OncoTargets and therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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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.

Yinqi MaoSchool of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China.
Wei ChenSchool of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China.
Han WuSchool of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China.
Chenbin LiuSchool of Medicine, Shanghai Jiao Tong University, Shanghai, People's Republic of China.
Jingjun ZhangDepartment of Rehabilitation, Huashan Hospital Affiliated to Fudan University, Shanghai, People's Republic of China.
Shuying ChenDepartment of Laboratory Medicine, Huashan Hospital, Fudan University, Shanghai, People's Republic of China.ORCID 0000-0002-9215-9777

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is one of the most common clinically malignant tumors of the digestive system. It ranks the sixth most common malignant tumor in the world and ranks fourth among cancer-related death worldwide. At present, early diagnosis and prognosis monitoring of hepatocellular carcinoma mainly use alpha-fetoprotein combined with ultrasonography, which leads to clinical frequently missed diagnosis or even misdiagnosis. Therefore, seeking specific diagnostic and monitoring molecules of hepatocellular carcinoma are still hot topics in contemporary medical practice. MicroRNA is an endogenous non-coding small RNA that regulates the expression of the target molecule and participates in various biological processes in vivo. The miR-200 family, the most common celebrity family of microRNAs, is commonly lower expression in a variety of cancers and is closely associated with tumorigenesis and outcome, especially hepatocellular carcinoma. This review mainly discusses the expression changes, specific molecular mechanisms, biological functions and clinical values of miR-200 family in hepatocellular carcinoma. Moreover, we highlighted utilization of miR-200 family as molecular biomarkers for early diagnosis, prognostic monitoring and appropriate therapy in hepatocellular carcinoma.

Indexed as

biological functiondiagnosishepatocellular carcinomamechanismmiR-200 familyprognosis

Identifiers

PMID33447052
PMCPMC7801920

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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.