Evidence map›Paper›PMID 23205106›Full record

ArticleOncology letters2012

Identification of pathogenesis-related microRNAs in hepatocellular carcinoma by expression profiling.

Yuki Katayama, Moegi Maeda, Ken Miyaguchi, Shota Nemoto, Mahmut Yasen, Shinji Tanaka, Hiroshi Mizushima, Yutaka Fukuoka, Shigeki Arii, Hiroshi Tanaka

Abstract read
In one paragraph

Article in Oncology letters, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 citing papers in PubMed.

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  18. Differential MicroRibonucleic Acid Expression in Cardioembolic Stroke.Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association · 2019
    Article
  19. miR-557 inhibits the proliferation and invasion of pancreatic cancer cells by targeting EGFR.International journal of clinical and experimental pathology · 2019
    Article
  20. 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

10 authors.

Yuki KatayamaDepartments of Bioinformatics and.
Moegi Maeda
Ken Miyaguchi
Shota Nemoto
Mahmut Yasen
Shinji Tanaka
Hiroshi Mizushima
Yutaka Fukuoka
Shigeki Arii
Hiroshi Tanaka

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors of the liver. Since postoperative recurrence and intrahepatic metastases occur frequently, the postoperative 5-year survival rate is low. To investigate the molecular mechanisms of HCC progression, mRNA as well as microRNA (miRNA) expression levels have been profiled in various studies. However, no previous study has comprehensively compared the expression of miRNAs in HCC patients with various clinical features using the tumor and surrounding non-tumor tissues and normal liver samples. In this study, we profiled the expression of miRNAs in tumor and non-tumor tissues from 40 HCC patients with heterogeneous pathogenesis and 6 surrounding non-tumor tissues from patients with metastatic liver cancer. To identify miRNAs specific to each disease state, we comprehensively compared the expression of miRNAs in various combinations. The results indicate that the expression of many known as well as novel miRNAs was altered in patients with the hepatitis C virus infection compared with those with the hepatitis B virus and without any virus infection. The following miRNAs were downregulated in the tumor and non-tumor tissues, and thus could serve as novel biomarkers for chronic liver diseases: miR-18b*, miR-296-5p, miR-557, miR-581, miR-625*, miR-1228, miR-1249 and miR-2116*. Similarly, miR-129*, miR-146b-3p and miR-448 are novel candidates for HCC biomarkers regardless of virus infection.

Identifiers

PMID23205106
PMCPMC3506695

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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.