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Representing ECM composition and EMT pathways in gastric cancer using a new metastatic gene signature. | LitMetric

AI Article Synopsis

  • - Gastric cancer (GC) is a complex and aggressive type of cancer that starts in the stomach and can spread to other organs, often becoming deadly by stage IV.
  • - The study analyzed gene expression data from 719 patients to identify a specific gene signature linked to the progression from stage I to stage IV GC, focusing on factors like ECM organization and epithelial-to-mesenchymal transition (EMT).
  • - The findings suggest that this gene signature could help identify stage I patients at higher risk of progression, potentially aiding in early treatment strategies, while also providing a new experimental model to study how gastric cancer spreads.

Article Abstract

Introduction: Gastric cancer (GC) is an aggressive and heterogeneous malignancy marked by cellular and molecular diversity. In GC, cancer cells invade locally in the stomach at stage I and can progress to metastasis in distant organs by stage IV, where it often becomes fatal.

Methods: We analyzed gene expression profiles from 719 stage I and stage IV GC patients across seven public datasets, conducting functional enrichment analysis to identify a gene signature linked to disease progression. Additionally, we developed an model of a simplified extracellular matrix (ECM) for cell-based assays.

Results: Our analysis identified a progression-associated gene signature () that characterizes stage IV GC. This signature is associated with ECM organization and epithelial-to-mesenchymal transition (EMT), both of which influence the tumor microenvironment by promoting cell invasion and triggering EMT.

Discussion: This gene signature may help identify stage I GC patients at higher risk, offering potential utility in early-stage patient management. Furthermore, our experimental ECM model may serve as a platform for investigating molecular mechanisms underlying metastatic spread in gastric cancer.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11573575PMC
http://dx.doi.org/10.3389/fcell.2024.1481818DOI Listing

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