Evidence map›Paper›PMID 28943905›Full record

ArticleOncology letters2017

Screening the key genes of hepatocellular adenoma via microarray analysis of DNA expression and methylation profiles.

Dan Liu, Pengfei Liu, Liye Cao, Quan Zhang, Yaqing Chen

Abstract read
In one paragraph

Article in Oncology letters, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Expression of microRNA-99a-3p in Prostate Cancer Based on Bioinformatics Data and Meta-Analysis of a Literature Review of 965 Cases.Medical science monitor : international medical journal of experimental and clinical research · 2018
    Pooled it
  2. Article
  3. Article
  4. Current Approaches in the Management of Hepatic Adenomas.Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2019
    Review
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.

Dan LiuDepartment of Ultrasonic Imaging, Zhuhai People's Hospital, Zhuhai, Guangdong 519000, P.R. China.
Pengfei LiuDepartment of Lymphoma, Sino-US Center of Lymphoma and Leukemia, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, P.R. China.
Liye CaoDepartment of Ultrasonic Medicine, Affiliated Hospital of Hebei University, Baoding, Hebei 071000, P.R. China.
Quan ZhangDepartment of Hepatobiliary Surgery, Affiliated Hospital of Hebei University, Baoding, Hebei 071000, P.R. China.
Yaqing ChenDepartment of VIP Ward, Affiliated Hospital of Hebei University, Baoding, Hebei 071000, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of the present study was to identify the biomarkers involved in the development of hepatocellular adenoma (HCA) through integrated analysis of gene expression and methylation microarray. The microarray dataset GSE7473, containing HNF1α-mutated HCA and their corresponding non-tumor livers, 5 HNF1α-mutated HCA and 4 non-related non-tumor livers, was downloaded from the Gene Expression Omnibus (GEO) database. The DNA methylation profile GSE43091, consisting of 50 HCA and 4 normal liver tissues, was also downloaded from the GEO database. Differentially expressed genes (DEGs) were identified by the limma package of

Indexed as

DAVIDdifferentially expressed genesdifferentially methylated siteshepatocellular adenoma

Identifiers

PMID28943905
PMCPMC5605960

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.