Evidence map›Paper›PMID 27000824›Full record

ArticleMedical oncology (Northwood, London, England)2016

Identification of allelic expression imbalance genes in human hepatocellular carcinoma through massively parallel DNA and RNA sequencing.

Qiudao Wang, Yan An, Qing Yuan, Yao Qi, Ying Ou, Junhui Chen, Jian Huang

Abstract read
PubMed Publisher
In one paragraph

Article in Medical oncology (Northwood, London, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 26% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Weighted gene co-expression network analysis of gene modules for the prognosis of esophageal cancer.Journal of Huazhong University of Science and Technology. Medical sciences = Hua zhong ke ji da xue xue bao. Yi xue Ying De wen ban = Huazhong keji daxue xuebao. Yixue Yingdewen ban · 2017
    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

7 authors at 3 institutions in 1 country.

Qiudao WangKey Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang District, Shanghai, 200240, China.
Yan AnKey Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang District, Shanghai, 200240, China.
Qing YuanNational Engineering Center for Biochip at Shanghai, Shanghai, 201203, China.
Yao QiNational Engineering Center for Biochip at Shanghai, Shanghai, 201203, China.
Ying OuNational Engineering Center for Biochip at Shanghai, Shanghai, 201203, China.
Junhui ChenPeking University Shenzhen Hospital, Shenzhen, 518036, China.
Jian HuangKey Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang District, Shanghai, 200240, China. jianhaung@sjtu.edu.cn.
Shanghai Jiao Tong University · CNPeking University Shenzhen Hospital · CNShenzhen Third People’s Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is a common malignant tumor worldwide. The prognosis and treatment of this disease have changed little in recent decades because the mechanisms underlying most events of this disease remain obscure. Allelic variation of gene expression is associated with many important biological processes, which provide a new perspective to understand HCC pathogenesis at the molecular level. To identify allelic expression imbalance (AEI) genes in HCCs, we developed a computational method that considered accurate mapping and vigorous AEI detection using paired DNA-seq and RNA-seq data. We analyzed the DNA-seq and RNA-seq data derived from two HCC samples and two cell lines. By applying a strict criterion, a total of 203 tumor-specific AEI genes were identified with high confidence, and several genes have been reported to be associated with the migration or proliferation of cancer cells, such as the genes RELN and DHRS3. In addition, we also found some novel AEI genes in HCCs, such as HNRNPR and PTAFR. Our study provides new insight into AEI events that may contribute to understanding gene expression regulation, cell proliferation and migration, and tumorigenesis.

Indexed as

Allelic ImbalanceGene Expression Regulation, NeoplasticCarcinoma, HepatocellularHumansLiver NeoplasmsReelin ProteinReproducibility of ResultsSequence Analysis, DNASequence Analysis, RNAReelin ProteinAllelic expression imbalanceCancerDNA-seqHepatocellular carcinomaRNA-seqTumor-specific AEI gene

Identifiers

PMID27000824
OpenAlexW2309729452

What OpenQuestion holds

Textmetadata
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.