ArticleOncotarget2017
Systematic analysis of molecular mechanisms for HCC metastasis via text mining approach.
Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
The trial behind it
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Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- Vitamin D deficiency in chronic hepatitis B across the disease spectrum: association with viral activity rather than hepatocellular carcinoma.BMC gastroenterology · 2026Article
- Lymph node metastasis in patients with hepatocellular carcinoma using machine learning: a population-based study.Frontiers in oncology · 2025Article
- Dermcidin Enhances the Migration, Invasion, and Metastasis of Hepatocellular Carcinoma CellsJournal of clinical and translational hepatology · 2022Article
- Article
- Systematic analysis of ovarian cancer platinum-resistance mechanisms via text mining.Journal of ovarian research · 2020Article
- 8u, a pro-apoptosis/cell cycle arrest compound, suppresses invasion and metastasis through HSP90α downregulating and PI3K/Akt inactivation in hepatocellular carcinoma cells.Scientific reports · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo systematically explore the molecular mechanism for hepatocellular carcinoma (HCC) metastasis and identify regulatory genes with text mining methods.
resultsGenes with highest frequencies and significant pathways related to HCC metastasis were listed. A handful of proteins such as EGFR, MDM2, TP53 and APP, were identified as hub nodes in PPI (protein-protein interaction) network. Compared with unique genes for HBV-HCCs, genes particular to HCV-HCCs were less, but may participate in more extensive signaling processes. VEGFA, PI3KCA, MAPK1, MMP9 and other genes may play important roles in multiple phenotypes of metastasis. MATERIALS AND
methodsGenes in abstracts of HCC-metastasis literatures were identified. Word frequency analysis, KEGG pathway and PPI network analysis were performed. Then co-occurrence analysis between genes and metastasis-related phenotypes were carried out.
conclusionsText mining is effective for revealing potential regulators or pathways, but the purpose of it should be specific, and the combination of various methods will be more useful.
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Registered trials
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.