Evidence map›Paper›PMID 29658607›Full record

ArticleMolecular medicine reports2018

Key signaling pathways, genes and transcription factors associated with hepatocellular carcinoma.

Jingcheng Wang, Yang Tian, Hui Chen, Hui Li, Shusen Zheng

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Molecular medicine reports, 2018. 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
0.7field-weighted citation impact, top 30% 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, 20 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Jingcheng WangDivision of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Key Laboratory of Combined Multi‑Organ Transplantation, Ministry of Public Health Key Laboratory of Organ Transplantation, Collaborative Innovation Center for Diagnosis Treatment of Infectious Diseases, Hangzhou, Zhejiang 310003, P.R. China.
Yang TianDivision of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Key Laboratory of Combined Multi‑Organ Transplantation, Ministry of Public Health Key Laboratory of Organ Transplantation, Collaborative Innovation Center for Diagnosis Treatment of Infectious Diseases, Hangzhou, Zhejiang 310003, P.R. China.
Hui ChenDivision of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Key Laboratory of Combined Multi‑Organ Transplantation, Ministry of Public Health Key Laboratory of Organ Transplantation, Collaborative Innovation Center for Diagnosis Treatment of Infectious Diseases, Hangzhou, Zhejiang 310003, P.R. China.
Hui LiDivision of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Key Laboratory of Combined Multi‑Organ Transplantation, Ministry of Public Health Key Laboratory of Organ Transplantation, Collaborative Innovation Center for Diagnosis Treatment of Infectious Diseases, Hangzhou, Zhejiang 310003, P.R. China.
Shusen ZhengDivision of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Key Laboratory of Combined Multi‑Organ Transplantation, Ministry of Public Health Key Laboratory of Organ Transplantation, Collaborative Innovation Center for Diagnosis Treatment of Infectious Diseases, Hangzhou, Zhejiang 310003, P.R. China.
Zhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of the present study was to investigate the underlying molecular mechanism of hepatocellular carcinoma (HCC) using bioinformatics approaches. The microarray dataset GSE64041 was downloaded from the Gene Expression Omnibus database, which included 60 tumor liver samples and 60 matched control samples. Differentially expressed genes (DEGs) between HCC and control groups were identified. Then functional enrichment analyses, protein‑protein interaction (PPI) network, sub‑network and integrated transcription factor (TF)‑microRNA (miRNA)‑target network analyses were performed for these DEGs. A total of 378 DEGs were obtained, including 101 upregulated and 277 downregulated DEGs. In addition, functional enrichment analysis for DEGs in the sub‑network revealed 'cell division' and 'cell cycle' as key Gene Ontology (GO) terms and pathways. Topoisomerase (DNA) IIα (TOP2A) and integrin subunit α2 (ITGA2) were hub nodes in the PPI network. TOP2A, cyclin dependent kinase 1 (CDK1) and polo like kinase 1 (PLK1) were revealed to be hub nodes in the sub‑network. Finally, 4 TFs including forkhead box M1 (FOXM1), E2F transcription factor 4 (E2F4), SIN3 transcription regulator family member A (SIN3A) and transcription factor 7 like 1 (TCF7L1) were obtained through integrated network analysis. TOP2A, ITGA2, PLK1 and CDK1 may be key genes involved in HCC development. 'Cell division' and 'cell cycle' were indicated to act as key GO terms and Kyoto Encyclopedia of Genes and Genomes pathways in HCC. In addition, FOXM1, TCF7L1, E2F4 and SIN3A were revealed to be key TFs associated with HCC.

Indexed as

Gene Expression Regulation, NeoplasticSignal TransductionCarcinoma, HepatocellularComputational BiologyGene Expression ProfilingGene OntologyGene Regulatory NetworksHumansLiver NeoplasmsProtein Interaction MappingProtein Interaction MapsTranscription FactorsTranscriptomeTranscription Factors

Identifiers

PMID29658607
PMCPMC5983994
OpenAlexW2797197180

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.