Evidence map›Paper›PMID 31730575›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2019

Bioinformatics Analysis Identifies Protein Tyrosine Kinase 7 (PTK7) as a Potential Prognostic and Therapeutic Biomarker in Stages I to IV Hepatocellular Carcinoma.

Ren-Chao Zou, Yun Liang, Ling-Lin Li, Jian-Zhong Tang, Yan-Ping Yang, Yan-Chun Geng, Jie He, Li-Yun Luo, Wen-Xing Li, Zhi-Wei Sun and 1 more

Abstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
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  10. Identification of Hub Genes in Hepatocellular Carcinoma Related to Progression and Prognosis by Weighted Gene Co-Expression Network Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2020
    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

11 authors.

Ren-Chao ZouDepartment of Nephrology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China (mainland).
Yun LiangDepartment of Hepatobiliary Surgery, The Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China (mainland).
Ling-Lin LiDepartment of Nephrology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China (mainland).
Jian-Zhong TangDepartment of Hepatobiliary Surgery, The First People's Hospital of Yunnan Province, Kunming, Yunnan, China (mainland).
Yan-Ping YangDepartment of Nephrology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China (mainland).
Yan-Chun GengDepartment of Nephrology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China (mainland).
Jie HeDepartment of Nephrology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China (mainland).
Li-Yun LuoDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China (mainland).
Wen-Xing LiKey Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China (mainland).
Zhi-Wei SunDepartment of Hepatobiliary Surgery, The First People's Hospital of Yunnan Province, Kunming, Yunnan, China (mainland).
Hong-Ling YuanDepartment of Nephrology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China (mainland).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND Worldwide, hepatocellular carcinoma (HCC) accounts for 80-90% of all cases of primary liver cancer, and is one of the ten most common malignancies. This study used bioinformatics analysis to identify genes associated with patient outcome in stages I-IV HCC and the gene pathways that distinguished between normal liver and liver cells and HCC and human HCC cell lines. MATERIAL AND METHODS Target genes were defined as those that had marketed drugs or drugs under development targeting a specific gene and acquired from the Clarivate Analytics Integrity Database. Differential expression gene analysis, co-expression network analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, survival analysis and receiver operating characteristic (ROC) curve analysis were used to explore the similarities and differences in gene expression profiles, functional associations, and survival in stage I-IV HCC. Normal liver cells (HL-7702) and HCC cell lines (HepaRG, HepG2, SK-Hep1, and Huh7) were studied using Western blot and quantitative reverse transcription PCR (RT-qPCR). RESULTS Hierarchical gene clustering identified target genes that distinguished between HCC and normal liver tissue. For stages I-IV HCC, there were seven commonly upregulated target genes EPHB1, LTK, NTRK2, PTK7, TBK1, TIE1, and TLR3, which were mainly involved in immune and signaling transduction pathways. PTK7 was highly expressed in stage I-IV HCC and was an independent prognostic marker for reduced overall survival (OS). CONCLUSIONS Bioinformatics analysis, combined with patient survival analysis, identified PTK7 gene expression as a potential therapeutic target and prognostic biomarker for all stages of HCC.

Indexed as

Biomarkers, TumorCarcinoma, HepatocellularCell Adhesion MoleculesCell Line, TumorChinaCluster AnalysisComputational BiologyDatabases, GeneticGene Expression ProfilingGene Expression Regulation, NeoplasticHumansLiver NeoplasmsNeoplasm StagingPrognosisProtein Interaction MapsReceptor Protein-Tyrosine KinasesBiomarkers, TumorCell Adhesion MoleculesPTK7 protein, humanReceptor Protein-Tyrosine Kinases

Identifiers

PMID31730575
PMCPMC6873638

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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.