4.6 Article

Genome-Scale Metabolic Model Analysis of Metabolic Differences between Lauren Diffuse and Intestinal Subtypes in Gastric Cancer

期刊

CANCERS
卷 14, 期 9, 页码 -

出版社

MDPI
DOI: 10.3390/cancers14092340

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genome-scale metabolic model; transcriptome; metabolism; gastric cancer

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资金

  1. Gachon University [GCU-2019-0323]
  2. Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [NRF-2020R1F1A1069206]

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Gastric cancer is a deadly cancer with different histological subtypes. This study used transcriptome analysis to identify differential metabolic pathways between the diffuse and intestinal subtypes of gastric cancer, including cholesterol homeostasis, xenobiotic metabolism, fatty acid metabolism, the MTORC1 pathway, and glycolysis.
Simple Summary Gastric cancer (GC) is one of the most deadly cancers globally. GC is a heterogeneous cancer type and has different histological subtypes. The aim of our study is to identify the metabolic differences between the subtypes, which will lead to a better understanding of metabolism in GC heterogeneity. Gastric cancer (GC) is one of the most lethal cancers worldwide; it has a high mortality rate, particularly in East Asia. Recently, genetic events (e.g., mutations and copy number alterations) and molecular signaling associated with histologically different GC subtypes (diffuse and intestinal) have been elucidated. However, metabolic differences among the histological GC subtypes have not been studied systematically. In this study, we utilized transcriptome-based genome-scale metabolic models (GEMs) to identify differential metabolic pathways between Lauren diffuse and intestinal subtypes. We found that diverse metabolic pathways, including cholesterol homeostasis, xenobiotic metabolism, fatty acid metabolism, the MTORC1 pathway, and glycolysis, were dysregulated between the diffuse and intestinal subtypes. Our study provides an overview of the metabolic differences between the two subtypes, possibly leading to an understanding of metabolism in GC heterogeneity.

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