Evidence map›Paper›PMID 28372569›Full record

ArticleChinese journal of cancer2017

Cancer metastasis: issues and challenges.

Chao-Nan Qian, Yan Mei, Jian Zhang

Open access · goldAbstract readEditorial
In one paragraph

Article in Chinese journal of cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
81citing papers in PubMed, 2 pooled it
4.4field-weighted citation impact, top 4% 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

81 citing papers in PubMed, 2 syntheses or guidelines pooled it, 147 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  13. Pan-cancer drivers of metastasis.Molecular cancer · 2025
    Article
  14. Review
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21 more citing papers are in PubMed but not listed here.

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

3 authors at 2 institutions in 2 countries.

Chao-Nan QianState Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, Guangdong, P. R. China. qianchn@sysucc.org.cn.
Yan MeiState Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, Guangdong, P. R. China.
Jian ZhangCenter for Translational Medicine, Guangxi Medical University, and Key Laboratory of Longevity and Aging-related Diseases, Ministry of Education, Nanning, 530021, Guangxi, P. R. China.
State Key Laboratory of Oncology in South ChinaSouthern University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metastasis is the major cause of treatment failure in cancer patients and of cancer-related deaths. This editorial discusses how cancer metastasis may be better perceived and controlled. Based on big-data analyses, a collection of 150 important pro-metastatic genes was studied. Using The Cancer Genome Atlas datasets to re-analyze the effect of some previously reported metastatic genes-e.g., JAM2, PPARGC1A, SIK2, and TRAF6-on overall survival of patients with renal and liver cancers, we found that these genes are actually protective factors for patients with cancer. The role of epithelial-mesenchymal transition (EMT) in single-cell metastasis has been well-documented. However, in metastasis caused by cancer cell clusters, EMT may not be necessary. A novel role of epithelial marker E-cadherin, as a sensitizer for chemoresistant prostate cancer cells by inhibiting Notch signaling, has been found. This editorial also discusses the obstacles for developing anti-metastatic drugs, including the lack of high-throughput technologies for identifying metastasis inhibitors, less application of animal models in the pre-clinical evaluation of the leading compounds, and the need for adjustments in clinical trial design to better reflect the anti-metastatic efficacy of new drugs. We are confident that by developing more effective high-throughput technologies to identify metastasis inhibitors, we can better predict, prevent, and treat cancer metastasis.

Indexed as

Neoplasm MetastasisAntineoplastic AgentsEpithelial-Mesenchymal TransitionHumansNeoplasmsPrognosisAntineoplastic AgentsE-cadherinEMTJAM2MetastasisPPARGC1ASIK2TRAF6

Identifiers

PMID28372569
PMCPMC5379757
OpenAlexW2604854812

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.