Evidence map›Paper›PMID 26934001›Full record

ArticleOncotarget2016

MicroRNA-92b represses invasion-metastasis cascade of esophageal squamous cell carcinoma.

Gang Ma, Chao Jing, Lin Li, Furong Huang, Fang Ding, Baona Wang, Dongmei Lin, Aiping Luo, Zhihua Liu

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 9% 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

36 citing papers in PubMed, 1 synthesis or guideline pooled it, 53 citations in OpenAlex.

  1. Prognostic Value of MicroRNAs in Esophageal Carcinoma: A Meta-Analysis.Clinical and translational gastroenterology · 2018
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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

9 authors at 1 institution in 1 country.

Gang MaThe State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Collaborative Innovation Center for Cancer Medicine, Beijing, People's Republic of China.
Chao JingThe State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Collaborative Innovation Center for Cancer Medicine, Beijing, People's Republic of China.
Lin LiThe State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Collaborative Innovation Center for Cancer Medicine, Beijing, People's Republic of China.
Furong HuangThe State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Collaborative Innovation Center for Cancer Medicine, Beijing, People's Republic of China.
Fang DingThe State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Collaborative Innovation Center for Cancer Medicine, Beijing, People's Republic of China.
Baona WangDepartment of Anesthesiology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.
Dongmei LinDepartment of Pathology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.
Aiping LuoThe State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Collaborative Innovation Center for Cancer Medicine, Beijing, People's Republic of China.
Zhihua LiuThe State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Collaborative Innovation Center for Cancer Medicine, Beijing, People's Republic of China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Invasion and metastasis are major contributors to cancer-caused death in patients suffered from esophageal squamous cell carcinoma (ESCC). To explore the microRNAs involved in regulating invasion-metastasis cascade of ESCC, we established two pairs of sublines (30-U/D and 180-U/D) with distinct motility capacity from two ESCC cell lines (KYSE30 and KYSE180). Screening of the differentially expressed microRNAs identified that microRNA-92b-3p (miR-92b) could dramatically inhibit invasion and metastasis of ESCC cells in vitro and in vivo. Subsequent studies showed that miR-92b exerted its inhibitory function through suppressing the expression of integrin αV (ITGAV), which further reduced phosphrylated FAK and impaired Rac1 activation. Moreover, higher expression of miR-92b in ESCC tissues correlated inversely with lymph node metastasis and indicated better prognosis. Together, these results for the first time describe how miR-92b suppresses the motility of ESCC cells and provide a promise for diagnosis or therapy of ESCC invasion and metastasis.

Indexed as

Gene Expression Regulation, NeoplasticAnimalsApoptosisBiomarkers, TumorCarcinoma, Squamous CellCell ProliferationEsophageal NeoplasmsFocal Adhesion Kinase 1HumansIntegrin alphaVLymphatic MetastasisMiceMicroRNAsNeoplasm Invasivenessrac1 GTP-Binding ProteinTumor Cells, CulturedBiomarkers, TumorFocal Adhesion Kinase 1Integrin alphaVMicroRNAsMIRN92 microRNA, humanPTK2 protein, humanrac1 GTP-Binding ProteinRAC1 protein, humanesophageal cancerintegrin αVinvasionmetastasismicroRNA-92b

Identifiers

PMID26934001
PMCPMC4991448
OpenAlexW2291430342

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.