Enhancing cancer treatment and understanding through clustering of gene responses to categorical stressors

Abstract Cancer cells have a unique metabolic activity in the glycolysis pathway compared to normal cells, which allows them to maintain their growth and proliferation. Therefore, inhibition of glycolytic pathways may be a promising therapeutic approach for cancer treatment. In this novel study, we...

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Main Authors: Christopher El Hadi, George Hilal, Rita Aoun
Format: Article
Language:English
Published: Nature Portfolio 2023-04-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-33785-w
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author Christopher El Hadi
George Hilal
Rita Aoun
author_facet Christopher El Hadi
George Hilal
Rita Aoun
author_sort Christopher El Hadi
collection DOAJ
description Abstract Cancer cells have a unique metabolic activity in the glycolysis pathway compared to normal cells, which allows them to maintain their growth and proliferation. Therefore, inhibition of glycolytic pathways may be a promising therapeutic approach for cancer treatment. In this novel study, we analyzed the genetic responses of cancer cells to stressors, particularly to drugs that target the glycolysis pathway. Gene expression data for experiments on different cancer cell types were extracted from the Gene Expression Omnibus and the expression fold change was then clustered after dimensionality reduction. We identified four groups of responses: the first and third were most affected by anti-glycolytic drugs, especially those acting on multiple pathways at once, and consisted mainly of squamous and mesenchymal tissues, showing higher mitotic inhibition and apoptosis. The second and fourth groups were relatively unaffected by treatment, comprising mainly gynecologic and hormone-sensitive groups, succumbing least to glycolysis inhibitors. Hexokinase-targeted drugs mainly showed this blunted effect on cancer cells. This study highlights the importance of analyzing the molecular states of cancer cells to identify potential targets for personalized cancer therapies and to improve our understanding of the disease.
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spelling doaj.art-ca999719c7dc4881b1cc773f6593129a2023-04-23T11:17:54ZengNature PortfolioScientific Reports2045-23222023-04-0113111010.1038/s41598-023-33785-wEnhancing cancer treatment and understanding through clustering of gene responses to categorical stressorsChristopher El Hadi0George Hilal1Rita Aoun2Faculty of Medicine, Saint-Joseph UniversityCancer and Metabolism Laboratory, Faculty of Medicine, Saint-Joseph UniversityCancer and Metabolism Laboratory, Faculty of Medicine, Saint-Joseph UniversityAbstract Cancer cells have a unique metabolic activity in the glycolysis pathway compared to normal cells, which allows them to maintain their growth and proliferation. Therefore, inhibition of glycolytic pathways may be a promising therapeutic approach for cancer treatment. In this novel study, we analyzed the genetic responses of cancer cells to stressors, particularly to drugs that target the glycolysis pathway. Gene expression data for experiments on different cancer cell types were extracted from the Gene Expression Omnibus and the expression fold change was then clustered after dimensionality reduction. We identified four groups of responses: the first and third were most affected by anti-glycolytic drugs, especially those acting on multiple pathways at once, and consisted mainly of squamous and mesenchymal tissues, showing higher mitotic inhibition and apoptosis. The second and fourth groups were relatively unaffected by treatment, comprising mainly gynecologic and hormone-sensitive groups, succumbing least to glycolysis inhibitors. Hexokinase-targeted drugs mainly showed this blunted effect on cancer cells. This study highlights the importance of analyzing the molecular states of cancer cells to identify potential targets for personalized cancer therapies and to improve our understanding of the disease.https://doi.org/10.1038/s41598-023-33785-w
spellingShingle Christopher El Hadi
George Hilal
Rita Aoun
Enhancing cancer treatment and understanding through clustering of gene responses to categorical stressors
Scientific Reports
title Enhancing cancer treatment and understanding through clustering of gene responses to categorical stressors
title_full Enhancing cancer treatment and understanding through clustering of gene responses to categorical stressors
title_fullStr Enhancing cancer treatment and understanding through clustering of gene responses to categorical stressors
title_full_unstemmed Enhancing cancer treatment and understanding through clustering of gene responses to categorical stressors
title_short Enhancing cancer treatment and understanding through clustering of gene responses to categorical stressors
title_sort enhancing cancer treatment and understanding through clustering of gene responses to categorical stressors
url https://doi.org/10.1038/s41598-023-33785-w
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