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A Novel Gene List Identifies Tumors with a Stromal-Mesenchymal Phenotype and Worse Prognosis in Gastric Cancer

SIMPLE SUMMARY: Gastric cancer is a leading cause of cancer-related death worldwide. Despite developments in the clinical management of this disease, currently, only 31% of patients with gastric cancer are expected to survive 5-years. However, not all patients follow the same course of the disease,...

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Autores principales: Demirkol Canli, Secil, Uner, Meral, Kucukkaraduman, Baris, Karaoglu, Diren Arda, Isik, Aynur, Turhan, Nesrin, Akyol, Aytekin, Gomceli, Ismail, Gure, Ali Osmay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10252086/
https://www.ncbi.nlm.nih.gov/pubmed/37296997
http://dx.doi.org/10.3390/cancers15113035
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author Demirkol Canli, Secil
Uner, Meral
Kucukkaraduman, Baris
Karaoglu, Diren Arda
Isik, Aynur
Turhan, Nesrin
Akyol, Aytekin
Gomceli, Ismail
Gure, Ali Osmay
author_facet Demirkol Canli, Secil
Uner, Meral
Kucukkaraduman, Baris
Karaoglu, Diren Arda
Isik, Aynur
Turhan, Nesrin
Akyol, Aytekin
Gomceli, Ismail
Gure, Ali Osmay
author_sort Demirkol Canli, Secil
collection PubMed
description SIMPLE SUMMARY: Gastric cancer is a leading cause of cancer-related death worldwide. Despite developments in the clinical management of this disease, currently, only 31% of patients with gastric cancer are expected to survive 5-years. However, not all patients follow the same course of the disease, and it is important to identify those individuals with potentially favorable or unfavorable outcomes to better define treatment options. For this purpose, we analyzed transcriptomic data from gastric tumors and identified 20 genes by which disease outcomes could be predicted. Unsupervised clustering of tumors based on the expression of these genes generated two major subgroups in a large number of cohorts. We show that patients with a poor prognosis have tumors with a more mesenchymal profile and a higher stromal content in both in silico and ex vivo experiments. We believe these findings will help shape the clinical management of gastric cancer. ABSTRACT: Background: Molecular biomarkers that predict disease progression can help identify tumor subtypes and shape treatment plans. In this study, we aimed to identify robust biomarkers of prognosis in gastric cancer based on transcriptomic data obtained from primary gastric tumors. Methods: Microarray, RNA sequencing, and single-cell RNA sequencing-based gene expression data from gastric tumors were obtained from public databases. Freshly frozen gastric tumors (n = 42) and matched FFPE (formalin-fixed, paraffin-embedded) (n = 40) tissues from a Turkish gastric cancer cohort were used for quantitative real-time PCR and immunohistochemistry-based assessments of gene expression, respectively. Results: A novel list of 20 prognostic genes was identified and used for the classification of gastric tumors into two major tumor subgroups with differential stromal gene expression (“Stromal-UP” (SU) and “Stromal-DOWN” (SD)). The SU group had a more mesenchymal profile with an enrichment of extracellular matrix-related gene sets and a poor prognosis compared to the SD group. Expression of the genes within the signature correlated with the expression of mesenchymal markers ex vivo. A higher stromal content in FFPE tissues was associated with shorter overall survival. Conclusions: A stroma-rich, mesenchymal subgroup among gastric tumors identifies an unfavorable clinical outcome in all cohorts tested.
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spelling pubmed-102520862023-06-10 A Novel Gene List Identifies Tumors with a Stromal-Mesenchymal Phenotype and Worse Prognosis in Gastric Cancer Demirkol Canli, Secil Uner, Meral Kucukkaraduman, Baris Karaoglu, Diren Arda Isik, Aynur Turhan, Nesrin Akyol, Aytekin Gomceli, Ismail Gure, Ali Osmay Cancers (Basel) Article SIMPLE SUMMARY: Gastric cancer is a leading cause of cancer-related death worldwide. Despite developments in the clinical management of this disease, currently, only 31% of patients with gastric cancer are expected to survive 5-years. However, not all patients follow the same course of the disease, and it is important to identify those individuals with potentially favorable or unfavorable outcomes to better define treatment options. For this purpose, we analyzed transcriptomic data from gastric tumors and identified 20 genes by which disease outcomes could be predicted. Unsupervised clustering of tumors based on the expression of these genes generated two major subgroups in a large number of cohorts. We show that patients with a poor prognosis have tumors with a more mesenchymal profile and a higher stromal content in both in silico and ex vivo experiments. We believe these findings will help shape the clinical management of gastric cancer. ABSTRACT: Background: Molecular biomarkers that predict disease progression can help identify tumor subtypes and shape treatment plans. In this study, we aimed to identify robust biomarkers of prognosis in gastric cancer based on transcriptomic data obtained from primary gastric tumors. Methods: Microarray, RNA sequencing, and single-cell RNA sequencing-based gene expression data from gastric tumors were obtained from public databases. Freshly frozen gastric tumors (n = 42) and matched FFPE (formalin-fixed, paraffin-embedded) (n = 40) tissues from a Turkish gastric cancer cohort were used for quantitative real-time PCR and immunohistochemistry-based assessments of gene expression, respectively. Results: A novel list of 20 prognostic genes was identified and used for the classification of gastric tumors into two major tumor subgroups with differential stromal gene expression (“Stromal-UP” (SU) and “Stromal-DOWN” (SD)). The SU group had a more mesenchymal profile with an enrichment of extracellular matrix-related gene sets and a poor prognosis compared to the SD group. Expression of the genes within the signature correlated with the expression of mesenchymal markers ex vivo. A higher stromal content in FFPE tissues was associated with shorter overall survival. Conclusions: A stroma-rich, mesenchymal subgroup among gastric tumors identifies an unfavorable clinical outcome in all cohorts tested. MDPI 2023-06-02 /pmc/articles/PMC10252086/ /pubmed/37296997 http://dx.doi.org/10.3390/cancers15113035 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Demirkol Canli, Secil
Uner, Meral
Kucukkaraduman, Baris
Karaoglu, Diren Arda
Isik, Aynur
Turhan, Nesrin
Akyol, Aytekin
Gomceli, Ismail
Gure, Ali Osmay
A Novel Gene List Identifies Tumors with a Stromal-Mesenchymal Phenotype and Worse Prognosis in Gastric Cancer
title A Novel Gene List Identifies Tumors with a Stromal-Mesenchymal Phenotype and Worse Prognosis in Gastric Cancer
title_full A Novel Gene List Identifies Tumors with a Stromal-Mesenchymal Phenotype and Worse Prognosis in Gastric Cancer
title_fullStr A Novel Gene List Identifies Tumors with a Stromal-Mesenchymal Phenotype and Worse Prognosis in Gastric Cancer
title_full_unstemmed A Novel Gene List Identifies Tumors with a Stromal-Mesenchymal Phenotype and Worse Prognosis in Gastric Cancer
title_short A Novel Gene List Identifies Tumors with a Stromal-Mesenchymal Phenotype and Worse Prognosis in Gastric Cancer
title_sort novel gene list identifies tumors with a stromal-mesenchymal phenotype and worse prognosis in gastric cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10252086/
https://www.ncbi.nlm.nih.gov/pubmed/37296997
http://dx.doi.org/10.3390/cancers15113035
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