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Войти в исследования Cancer reports (Hoboken, N.J.) · 2026
Integrated Network Analysis Suggests an miR-21/MMP/VEGF-Associated Regulatory Axis in Gastric Cancer.
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Babajani Fatemeh, Mozafari Hadi
Аннотация
BACKGROUND, AIMS: Gastric cancer (GC) pathogenesis involves complex molecular interactions that remain incompletely understood at a biological systems level. While microRNA-21 (miR-21), matrix metalloproteinases (MMPs), and vascular endothelial growth factor (VEGF) have been individually implicated in GC, their integrated role as a coordinated regulatory network remains uncharacterized. And we aim to reveal novel biology systems level insights into the miR-21/MMP/VEGF regulatory axis.
METHODS: In this study, 27 tumor and matched adjacent noncancerous tissues in GC patients were analyzed. Expression of miR-21, MMP-2/9, and VEGF was analyzed using qRT-PCR, Western blotting, and zymography (for MMP-2/9 activity). Computational analyses integrated KEGG pathway enrichment (clusterProfiler), random forest machine learning, structural equation modeling (lavaan), and protein-protein interaction network analysis (igraph) to decipher system-level organization. All statistical analyses and computational modeling were performed using RStudio version 4.4.2.
RESULTS: Pathway analysis revealed significant enrichment in cancer-related pathways, including MicroRNAs in cancer (p = 8.66 × 10-10, FDR = 2.09 × 10-7). Random forest classification achieved a mean cross-validated accuracy of 85.0% (±14.8%) in discriminating tumor from normal tissues, identifying miR-21 as the most potent predictor. Structural equation modeling demonstrated a significant direct effect of miR-21 on tumor size (β = 0.576, p = 0.001) and an indirect effect mediated through MMP-9 (β = 0.194, p = 0.047). Network topology analysis confirmed miR-21 as the central hub (degree = 5).
CONCLUSION: Our integrated biology systems analysis suggests that the miR-21/MMP-9/VEGF axis may represent a candidate regulatory network in GC, with miR-21 appearing to play a central role in tumor progression. These findings offer preliminary insights and highlight molecules of interest for further studies for intervention in GC pathogenesis.
METHODS: In this study, 27 tumor and matched adjacent noncancerous tissues in GC patients were analyzed. Expression of miR-21, MMP-2/9, and VEGF was analyzed using qRT-PCR, Western blotting, and zymography (for MMP-2/9 activity). Computational analyses integrated KEGG pathway enrichment (clusterProfiler), random forest machine learning, structural equation modeling (lavaan), and protein-protein interaction network analysis (igraph) to decipher system-level organization. All statistical analyses and computational modeling were performed using RStudio version 4.4.2.
RESULTS: Pathway analysis revealed significant enrichment in cancer-related pathways, including MicroRNAs in cancer (p = 8.66 × 10-10, FDR = 2.09 × 10-7). Random forest classification achieved a mean cross-validated accuracy of 85.0% (±14.8%) in discriminating tumor from normal tissues, identifying miR-21 as the most potent predictor. Structural equation modeling demonstrated a significant direct effect of miR-21 on tumor size (β = 0.576, p = 0.001) and an indirect effect mediated through MMP-9 (β = 0.194, p = 0.047). Network topology analysis confirmed miR-21 as the central hub (degree = 5).
CONCLUSION: Our integrated biology systems analysis suggests that the miR-21/MMP-9/VEGF axis may represent a candidate regulatory network in GC, with miR-21 appearing to play a central role in tumor progression. These findings offer preliminary insights and highlight molecules of interest for further studies for intervention in GC pathogenesis.