Evidence map›Paper›PMID 31312366›Full record

ArticleAmerican journal of translational research2019

Anti-metastasis traditional Chinese medicine monomer screening system based on perinucleolar compartment analysis in hepatocellular carcinoma cells.

Feifei Liu, Guohua Lou, Tianbao Zhang, Senzhong Chen, Jia Xu, Lichen Xu, Chunhong Huang, Yanning Liu, Zhi Chen

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

7 citing papers in PubMed, 13 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

9 authors at 1 institution in 1 country.

Feifei LiuState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University Hangzhou 310003, China.
Guohua LouState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University Hangzhou 310003, China.
Tianbao ZhangState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University Hangzhou 310003, China.
Senzhong ChenState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University Hangzhou 310003, China.
Jia XuState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University Hangzhou 310003, China.
Lichen XuState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University Hangzhou 310003, China.
Chunhong HuangState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University Hangzhou 310003, China.
Yanning LiuState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University Hangzhou 310003, China.
Zhi ChenState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University Hangzhou 310003, China.
Zhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular Carcinoma (HCC) lacks effective anti-metastasis drugs. Traditional Chinese Medicine (TCM) monomers have shown anti-proliferation activity in HCC, but few of them are specifically anti-metastasis. Therefore, further clarifying the indicators of HCC metastasis and screening TCM monomers based on the indicators, will effectively guide the development of novel anti-HCC drugs. The perinucleolar compartment (PNC), existing in the nuclear of tumor cells, is closely correlated with metastasis of several tumors. In this study, we found positive correlation between higher PNC prevalence and metastasis in HCC tissue of patients. The PNC prevalence was also positively correlated with the malignancy of HCC cell lines. On this premise, we established a PNC-based screening system for anti-metastasis TCM monomers and obtained Camptothecin (CPT), Evodiamine and Isoglycyrrhizin, the three most effective TCM monomers from a TCM monomer library to reduce the PNC prevalence in Huh7 cells. The anti-metastasis effect of these TCM monomers was positively correlated with their PNC inhibitor effect. Our data further revealed that CPT reduced metastasis of Huh7 cells possibly by inhibiting Epithelial-Mesenchymal Transition by upregulating the expression of ZO-1, E-cadherin and Claudin-1. The PNC-based screening system is effective and it may provide an effective technical platform for the development of anti-metastasis drugs.

Indexed as

Hepatocellular carcinomametastasisperinucleolar compartmenttraditional Chinese medicine monomers

Identifiers

PMID31312366
PMCPMC6614616
OpenAlexW2989208813

What OpenQuestion holds

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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.