Evidence map›Paper›PMID 26064314›Full record

ArticleInternational journal of clinical and experimental medicine2015

MEK1 expression and its relationship with clinical pathological features in hepatocellular carcinoma.

Renhua Gong, Dengqun Sun, Xingguo Zhong, Yanjun Sun, Li Li

Open access · greenAbstract read
In one paragraph

Article in International journal of clinical and experimental medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 33% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

5 authors at 2 institutions in 2 countries.

Renhua GongDepaetment of Surgery, Armed Police Hospital of Anhui Hefei 230000, China.
Dengqun SunDepaetment of Surgery, Armed Police Hospital of Anhui Hefei 230000, China.
Xingguo ZhongDepaetment of Surgery, Armed Police Hospital of Anhui Hefei 230000, China.
Yanjun SunDepaetment of Surgery, Armed Police Hospital of Anhui Hefei 230000, China.
Li LiDepartment of Radiation Oncology, Armed Police Hospital of Shanghai Shanghai 201103, China.
Police General Hospital · THShanghai Police College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMEK1 is overexpressed in various human carcinomas, but the role of MEK1 is not well unknown in hepatocellular carcinoma (HCC). In the present study, we aimed to explore MEK1 expression of in HCC tissues, and to evaluate its relationship with clinical pathological features.

methodsExpressions of MEK1 were detected by western blot assay, real-time quantitative PCR and immunohistochemical (IHC) staining in 30 HCC tissues and their adjacent normal tissues. Pearson Chi-square test was used to analyze the relationship between MEK1 expression and clinical pathological features. The survival curve was drawn by Kaplan-Meier method, and survival was analyzed by Lon-rank test.

resultsThe expression of MEK1 mRNA in HCC tissues was significantly higher than that in adjacent normal tissues and so was the expression of MEK1 protein. In the 30 specimens, 70% was with Tumor/Normal ratio > 2, 10% with Tumor/Normal ratio < 1 and 20% with 1 < Tumor/Normal ratio < 2. The mean survival time in high MEK1 expression group was significantly lower than that in low MEK1 expression group (Log-rank value = 11.946, P < 0.01).

conclusionMEK1 expressions in HCC tissues were significantly higher than that in adjacent normal tissues, which indicated that MEK1 was involved in the genesis and development of HCC. Moreover, it was closely related to the postoperative survival time of patients with HCC.

Indexed as

HCCMEK1mRNAsurvival analysis

Identifiers

PMID26064314
PMCPMC4443148
OpenAlexW2395229169

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.