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...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-04-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-023-33785-w |
_version_ | 1797841035237261312 |
---|---|
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. |
first_indexed | 2024-04-09T16:24:24Z |
format | Article |
id | doaj.art-ca999719c7dc4881b1cc773f6593129a |
institution | Directory Open Access Journal |
issn | 2045-2322 |
language | English |
last_indexed | 2024-04-09T16:24:24Z |
publishDate | 2023-04-01 |
publisher | Nature Portfolio |
record_format | Article |
series | Scientific Reports |
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 |
work_keys_str_mv | AT christopherelhadi enhancingcancertreatmentandunderstandingthroughclusteringofgeneresponsestocategoricalstressors AT georgehilal enhancingcancertreatmentandunderstandingthroughclusteringofgeneresponsestocategoricalstressors AT ritaaoun enhancingcancertreatmentandunderstandingthroughclusteringofgeneresponsestocategoricalstressors |