Evidence map›Paper›PMID 42153344›Full record

ArticleDatabase : the journal of biological databases and curation2026

MetaCancerDB: a database of site-specific RNA-miRNA correlations in cancer metastasis.

Myeonghun Cho, Byungkyu Park, Kyungsook Han

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Myeonghun ChoDepartment of Computer Engineering, Inha University, Inha-ro, Incheon 22212, Republic of Korea.
Byungkyu ParkDepartment of Quantum Information, Yonsei University, Seoul 03722, Republic of Korea.
Kyungsook HanDepartment of Computer Engineering, Inha University, Inha-ro, Incheon 22212, Republic of Korea.ORCID 0000-0001-9900-6741

Funding

Ministry of Science and ICT RS-2023-00208892MOTIENational Research FoundationTechnology Innovation Program RS-2024-00410585
6 · The paper itself

Abstract

Cancer metastasis involves complex molecular mechanisms that cannot be fully explained by individual gene expression profiles. Previous studies have shown that correlations between RNA and miRNA expression can capture metastatic behaviour more effectively than expression of individual genes. However, no publicly available databases provide systematic analysis of RNA-miRNA correlations specific to cancer metastasis. We developed an efficient computational method to identify differential correlations between miRNAs and RNAs that are specific to individual tumour samples. Using data from The Cancer Genome Atlas (TCGA), we computed differential correlations for tumour samples across 9 cancer types and 21 metastatic sites, encompassing ~200 million RNA-miRNA pairs. Statistical analysis identified RNA-miRNA pairs with site-specific correlations using Mann-Whitney U-tests. MetaCancerDB contains RNA-miRNA correlation networks for 9 primary cancer types and 21 metastatic sites. Site-specific correlations showed distinct patterns, with lung metastasis displaying the most conserved correlations across cancer types. Survival analysis revealed that specific RNA-miRNA pairs are prognostic for patient outcomes in a metastatic site-dependent manner. MetaCancerDB provides a comprehensive resource for exploring RNA-miRNA correlations in cancer metastasis. The database enables researchers to identify molecular signatures specific to metastatic sites and can serve as a foundation for developing predictive biomarkers. MetaCancerDB is freely available for academic purposes.

Indexed as

Databases, GeneticDatabases, Nucleic AcidMicroRNAsNeoplasm MetastasisNeoplasmsRNA, NeoplasmBiocurationGene Expression Regulation, NeoplasticHumansMicroRNAsRNA, Neoplasm

Identifiers

PMID42153344
PMCPMC13231512

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LicenceCC BY
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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.