Evidence map›Paper›PMID 23554630›Full record

ArticleJournal of biomedical research2010

Elevated expression of mature miR-21 and miR-155 in cancerous gastric tissues from Chinese patients with gastric cancer.

Li Liu, Qi Chen, Rensheng Lai, Xiaobin Wu, Xiaoyu Wu, Fukun Liu, Guohua Xu, Yong Ji

Open access · bronzeAbstract read
In one paragraph

Article in Journal of biomedical research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
0.1field-weighted citation impact, top 39% 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

14 citing papers in PubMed, 28 citations in OpenAlex.

  1. Review
  2. Review
  3. Prediction of Blood miRNA-mRNA Regulatory Network in Gastric Cancer.Reports of biochemistry & molecular biology · 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

8 authors at 4 institutions in 1 country.

Li LiuAtherosclerosis Research Center, Nanjing Medical University, Nanjing 210029, Jiangsu Province, China ; Laboratory of Cytology & Molecules/Department of Pathology, the Affiliated Hospital of Nanjing University of Traditional Chinese Medicine, Nanjing 210029, Jiangsu Province, China.
Qi Chen
Rensheng Lai
Xiaobin Wu
Xiaoyu Wu
Fukun Liu
Guohua Xu
Yong Ji
Nanjing University of Chinese Medicine · CNNanjing Medical University · CNNanjing University · CNJiangsu Second Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveMicroRNA (miRNA) expression is deregulated in many types of human cancers. We sought to investigate the expression patterns of the miRNAs, miR-21, miR-145 and miR-155 in sporadic gastric cancer in a Chinese population.

methodsTotal RNA was extracted from archived gastric cancer tissues and adjacent non-cancerous tissues from 20 pairs of paraffin-embedded specimens. Expression levels of miR-21, miR-145 and miR-155 were detected by quantitative reverse transcriptase PCR using a specific stem-loop primer, with U6 as the internal reference gene.

resultsThe expression of miR-21 and miR-155 in gastric cancer samples was significantly higher than in paired non-cancerous samples (P < 0.05). There was no statistically significant difference in expression levels of miR-145 between cancerous and non-cancerous tissues (P > 0.05).

conclusionIn Chinese sporadic gastric cancer tissues, the expressions of the oncogenic miR-21 and miR-155 were significantly up-regulated, while the expression of the tumor suppressor miR-145 was decreased, although this decrease was not statistically significant. Thus there is specificity in the miRNA expression pattern in gastric cancers in the Chinese population.

Indexed as

expressiongastric cancerMicroRNA

Identifiers

PMID23554630
PMCPMC3596554
OpenAlexW2093209963

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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.