Evidence map›Paper›PMID 30272310›Full record

ArticleMolecular medicine reports2018

Examining the key genes and pathways in hepatocellular carcinoma development from hepatitis B virus‑positive cirrhosis.

Qi-Feng Chen, Jin-Guo Xia, Wang Li, Lu-Jun Shen, Tao Huang, Peihong Wu

Open access · hybridAbstract read
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 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

23 citing papers in PubMed, 30 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Genomic Relevance ofJournal of clinical medicine · 2022
    Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Identification of Key Genes for Hepatitis Delta Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2021
    Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. 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

6 authors at 4 institutions in 1 country.

Qi-Feng Chen *Department of Medical Imaging and Interventional Radiology, Sun Yat‑sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong 510060, P.R. China.
Jin-Guo Xia *Department of Interventional Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210009, P.R. China.
Wang LiDepartment of Medical Imaging and Interventional Radiology, Sun Yat‑sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong 510060, P.R. China.
Lu-Jun ShenDepartment of Medical Imaging and Interventional Radiology, Sun Yat‑sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong 510060, P.R. China.
Tao HuangDepartment of Medical Imaging and Interventional Radiology, Sun Yat‑sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong 510060, P.R. China.
Peihong WuDepartment of Medical Imaging and Interventional Radiology, Sun Yat‑sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong 510060, P.R. China.
Sun Yat-sen University Cancer Center · CNNanjing Medical University · CNState Key Laboratory of Oncology in South ChinaSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To identify the key genes and pathways in the development of hepatocellular carcinoma (HCC) from hepatitis B virus (HBV)‑positive liver cirrhosis, differentially expressed genes (DEGs) between HCC and liver cirrhosis tissue samples from the GSE17548 gene expression profile dataset were screened. A total of 1,845 DEGs were identified, including 1,803 upregulated and 42 downregulated genes. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein‑protein interaction (PPI) network analyses were performed. It was identified that the 'cell cycle' and 'progesterone‑mediated oocyte maturation' KEGG pathways were significantly enriched in the DEGs. In addition, the high expression of the hub genes from the PPI network (including cyclin dependent kinase 1, cyclin B1, cyclin B2, mitotic arrest deficient 2 like 1, BUB1 mitotic checkpoint serine/threonine kinase and cyclin A2; P=0.00116, 0.00021, 0.04889, 0.00222, 0.00015 and 0.00647, respectively) was associated with a decrease in overall survival for patients with HCC as identified using survival and expression data from The Cancer Genome Atlas. The identified hub genes and pathways may help to elucidate the molecular mechanisms of HCC progression from HBV‑positive liver cirrhosis. Additionally, they may be useful as therapeutic targets or serve as novel biomarkers for HCC prognosis prediction.

Indexed as

Hepatitis B virusCarcinoma, HepatocellularComputational BiologyGene Expression ProfilingGene OntologyHepatitis BHumansKaplan-Meier EstimateLiver CirrhosisLiver NeoplasmsProtein Interaction MappingProtein Interaction MapsReproducibility of ResultsTranscriptomebioinformatics analysisdifferentially expressed geneshepatitis B virushepatocellular carcinomaliver cirrhosis

Identifiers

PMID30272310
PMCPMC6236263
OpenAlexW2890487827

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.