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The causal association between obesity and gastric cancer and shared molecular signatures: a large-scale Mendelian randomization and multi-omics analysis
PURPOSE: While observational studies have identified obesity as a potential risk factor for gastric cancer, the causality remains uncertain. This study aimed to evaluate the causal relationship between obesity and gastric cancer and identify the shared molecular signatures linking obesity to gastric...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10639150/ https://www.ncbi.nlm.nih.gov/pubmed/37954072 http://dx.doi.org/10.3389/fonc.2023.1091958 |
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author | Xing, Abao Tong, Henry H. Y. Liu, Songyan Zhai, Xiaobing Yu, Li Li, Kefeng |
author_facet | Xing, Abao Tong, Henry H. Y. Liu, Songyan Zhai, Xiaobing Yu, Li Li, Kefeng |
author_sort | Xing, Abao |
collection | PubMed |
description | PURPOSE: While observational studies have identified obesity as a potential risk factor for gastric cancer, the causality remains uncertain. This study aimed to evaluate the causal relationship between obesity and gastric cancer and identify the shared molecular signatures linking obesity to gastric cancer. METHODS: A two-sample Mendelian randomization (MR) analysis was conducted using the GWAS data of body fat percentage (exposure, n = 331,117) and gastric cancer (outcome, n = 202,308). Bioinformatics and meta-analysis of multi-omics data were performed to identify key molecules mediating the causality. The meta-analysis of the plasma/serum proteome included 1,662 obese and 3,153 gastric cancer patients. Obesity and gastric cancer-associated genes were identified using seven common gene ontology databases. The transcriptomic data were obtained from TCGA and GEO databases. The Bioinformatic findings were clinically validated in plasma from 220 obese and 400 gastric cancer patients across two hospitals. Finally, structural-based virtual screening (SBVS) was performed to explore the potential FDA-approved drugs targeting the identified mediating molecules. RESULTS: The MR analysis revealed a significant causal association between obesity and gastric cancer (IVW, OR = 1.37, 95% CI:1.12-1.69, P = 0.0028), without pleiotropy or heterogeneity. Bioinformatic and meta-analysis of multi-omics data revealed shared TNF, PI3K-AKT, and cytokine signaling dysregulation, with significant upregulation of AKT1, IL-6, and TNF. The clinical study confirmed widespread upregulation of systemic inflammatory markers in the plasma of both diseases. SBVS identified six novel potent AKT1 inhibitors, including the dietary supplement adenosine, representing a potentially preventive drug with low toxicity. CONCLUSION: Obesity causally increases gastric cancer, likely mediated by persistent AKT1/IL-6/TNF upregulation. As a potential AKT1 inhibitor, adenosine may mitigate the obesity-to-gastric cancer transition. These findings could inform preventive drug development to reduce gastric cancer risk in obesity. |
format | Online Article Text |
id | pubmed-10639150 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-106391502023-11-11 The causal association between obesity and gastric cancer and shared molecular signatures: a large-scale Mendelian randomization and multi-omics analysis Xing, Abao Tong, Henry H. Y. Liu, Songyan Zhai, Xiaobing Yu, Li Li, Kefeng Front Oncol Oncology PURPOSE: While observational studies have identified obesity as a potential risk factor for gastric cancer, the causality remains uncertain. This study aimed to evaluate the causal relationship between obesity and gastric cancer and identify the shared molecular signatures linking obesity to gastric cancer. METHODS: A two-sample Mendelian randomization (MR) analysis was conducted using the GWAS data of body fat percentage (exposure, n = 331,117) and gastric cancer (outcome, n = 202,308). Bioinformatics and meta-analysis of multi-omics data were performed to identify key molecules mediating the causality. The meta-analysis of the plasma/serum proteome included 1,662 obese and 3,153 gastric cancer patients. Obesity and gastric cancer-associated genes were identified using seven common gene ontology databases. The transcriptomic data were obtained from TCGA and GEO databases. The Bioinformatic findings were clinically validated in plasma from 220 obese and 400 gastric cancer patients across two hospitals. Finally, structural-based virtual screening (SBVS) was performed to explore the potential FDA-approved drugs targeting the identified mediating molecules. RESULTS: The MR analysis revealed a significant causal association between obesity and gastric cancer (IVW, OR = 1.37, 95% CI:1.12-1.69, P = 0.0028), without pleiotropy or heterogeneity. Bioinformatic and meta-analysis of multi-omics data revealed shared TNF, PI3K-AKT, and cytokine signaling dysregulation, with significant upregulation of AKT1, IL-6, and TNF. The clinical study confirmed widespread upregulation of systemic inflammatory markers in the plasma of both diseases. SBVS identified six novel potent AKT1 inhibitors, including the dietary supplement adenosine, representing a potentially preventive drug with low toxicity. CONCLUSION: Obesity causally increases gastric cancer, likely mediated by persistent AKT1/IL-6/TNF upregulation. As a potential AKT1 inhibitor, adenosine may mitigate the obesity-to-gastric cancer transition. These findings could inform preventive drug development to reduce gastric cancer risk in obesity. Frontiers Media S.A. 2023-10-26 /pmc/articles/PMC10639150/ /pubmed/37954072 http://dx.doi.org/10.3389/fonc.2023.1091958 Text en Copyright © 2023 Xing, Tong, Liu, Zhai, Yu and Li https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Xing, Abao Tong, Henry H. Y. Liu, Songyan Zhai, Xiaobing Yu, Li Li, Kefeng The causal association between obesity and gastric cancer and shared molecular signatures: a large-scale Mendelian randomization and multi-omics analysis |
title | The causal association between obesity and gastric cancer and shared molecular signatures: a large-scale Mendelian randomization and multi-omics analysis |
title_full | The causal association between obesity and gastric cancer and shared molecular signatures: a large-scale Mendelian randomization and multi-omics analysis |
title_fullStr | The causal association between obesity and gastric cancer and shared molecular signatures: a large-scale Mendelian randomization and multi-omics analysis |
title_full_unstemmed | The causal association between obesity and gastric cancer and shared molecular signatures: a large-scale Mendelian randomization and multi-omics analysis |
title_short | The causal association between obesity and gastric cancer and shared molecular signatures: a large-scale Mendelian randomization and multi-omics analysis |
title_sort | causal association between obesity and gastric cancer and shared molecular signatures: a large-scale mendelian randomization and multi-omics analysis |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10639150/ https://www.ncbi.nlm.nih.gov/pubmed/37954072 http://dx.doi.org/10.3389/fonc.2023.1091958 |
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