Constarium
← Search

Data · dataset · 2026

<p>Comparison experiment table.</p>

Listed in NCL Data

<div><p>Colorectal cancer (CRC) is one of the most lethal malignancies worldwide, and the precise identification of biomarkers from colonic adenoma to cancer is of great significance for preventing the development of adenocarcinoma.

Description

Given that existing methods inadequately capture the topological network relationships among genes, this study proposes a graph neural network model based on multifeature learning, named ChebTs, to investigate the correlation between key genes involved in the colorectal “adenoma-cancer” transition.

The GSE41657 and GSE31905 datasets from the GEO database were stratified into normal, adenoma, and colorectal cancer groups. Feature encoding was introduced to enhance node features, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of differentially expressed genes (DEGs). A protein-protein interaction (PPI) network was constructed using Cytoscape software, and the aggregated information was embedded into the model for training to generate a list of key genes with corresponding importance scores.

Read the rest (3 more)

An attention pooling mechanism aggregated node-level representations into graph level representations for sample classification, and a two layer fully connected network, following activation and regularization, produced predicted probabilities. Furthermore, we provided interpretable analyses at the gene level using GNNExplainer. The results were validated through virtual knockout techniques.

The eight screened genes, Fibronectin 1 (<i>FN1</i>), Claudin 2 (<i>CLDN2</i>), Interleukin-33 (<i>IL-33</i>), Matrix Metallopeptidase 1 (<i>MMP1</i>), Stanniocalcin 2 (<i>STC2</i>), Insulin-Like Growth Factor-Binding Protein 7 (<i>IGFBP7</i>), NADPH Oxidase 4 (<i>NOX4</i>), and Secreted Frizzled Related Protein 1 (<i>SFRP1</i>), were all found to be associated with overall survival (OS) in CRC. In this study, eight molecules closely related to the development of colorectal adenocarcinoma were screened out, and they may be diagnostic biomarkers of colorectal cancer.

These genes affect the prognosis of patients by participating in biological processes such as remodeling of extracellular mechanisms, and are of great significance for preventing the carcinogenesis of adenoma.</p></div>

Links

Where it is published

Catalogue records · 1

Topics

Inferred from text
Tabular 65%
Provenance · 1 source records, 14 field assertions
SourceKeyLast seenRaw
NCL Dataoai:figshare.com:article/3407361817 h agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · data ncl ac ukconnector:data_ncl_ac_uk@1.0.0
concepts[disease].local:disease:cancermapping · data ncl ac ukvocabulary-mapper@1.0.0keywords['Cancer']
concepts[field].anzsrc:group:3101mapping · data ncl ac ukvocabulary-mapper@1.0.0keywords['Cell Biology']
concepts[field].anzsrc:group:3105mapping · data ncl ac ukvocabulary-mapper@1.0.0keywords['Genetics']
concepts[field].local:field:chemistrymapping · data ncl ac ukconnector:data_ncl_ac_uk@1.0.0
concepts[field].local:field:earth-environmentalmapping · data ncl ac ukconnector:data_ncl_ac_uk@1.0.0
concepts[field].local:field:life-sciencesmapping · data ncl ac ukconnector:data_ncl_ac_uk@1.0.0
concepts[field].local:field:mathematics-statisticsmapping · data ncl ac ukconnector:data_ncl_ac_uk@1.0.0
concepts[field].local:field:medicine-healthmapping · data ncl ac ukconnector:data_ncl_ac_uk@1.0.0
concepts[modality].local:modality:tabularenrichment · data ncl ac ukkeyword-concept-rules@1.0.0title+description (65%)
descriptionsource · data ncl ac ukconnector:data_ncl_ac_uk@1.0.0/metadata/dc/description
licensesource · data ncl ac ukconnector:data_ncl_ac_uk@1.0.0/metadata/dc/rights
publication_datesource · data ncl ac ukconnector:data_ncl_ac_uk@1.0.0
titlesource · data ncl ac ukconnector:data_ncl_ac_uk@1.0.0/metadata/dc/title