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Application of single-cell RNA sequencing analysis of novel breast cancer phenotypes based on the activation of ferroptosis-related genes
Ferroptosis is distinct from classic apoptotic cell death characterized by the accumulation of reactive oxygen species (ROS) and lipid peroxides on the cell membrane. Increasing findings have demonstrated that ferroptosis plays an important role in cancer development, but the exploration of ferropto...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10203036/ https://www.ncbi.nlm.nih.gov/pubmed/37212877 http://dx.doi.org/10.1007/s10142-023-01086-0 |
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author | Liu, Shuochuan Zhao, Yajie Zhang, Jiao Liu, Zhenzhen |
author_facet | Liu, Shuochuan Zhao, Yajie Zhang, Jiao Liu, Zhenzhen |
author_sort | Liu, Shuochuan |
collection | PubMed |
description | Ferroptosis is distinct from classic apoptotic cell death characterized by the accumulation of reactive oxygen species (ROS) and lipid peroxides on the cell membrane. Increasing findings have demonstrated that ferroptosis plays an important role in cancer development, but the exploration of ferroptosis in breast cancer is limited. In our study, we aimed to establish a ferroptosis activation-related model based on the differentially expressed genes between a group exhibiting high ferroptosis activation and a group exhibiting low ferroptosis activation. By using machine learning to establish the model, we verified the accuracy and efficiency of our model in The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) set and gene expression omnibus (GEO) dataset. Additionally, our research innovatively utilized single-cell RNA sequencing data to systematically reveal the microenvironment in the high and low FeAS groups, which demonstrated differences between the two groups from comprehensive aspects, including the activation condition of transcription factors, cell pseudotime features, cell communication, immune infiltration, chemotherapy efficiency, and potential drug resistance. In conclusion, different ferroptosis activation levels play a vital role in influencing the outcome of breast cancer patients and altering the tumor microenvironment in different molecular aspects. By analyzing differences in ferroptosis activation levels, our risk model is characterized by a good prognostic capacity in assessing the outcome of breast cancer patients, and the risk score can be used to prompt clinical treatment to prevent potential drug resistance. By identifying the different tumor microenvironment landscapes between the high- and low-risk groups, our risk model provides molecular insight into ferroptosis in breast cancer patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10142-023-01086-0. |
format | Online Article Text |
id | pubmed-10203036 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-102030362023-05-24 Application of single-cell RNA sequencing analysis of novel breast cancer phenotypes based on the activation of ferroptosis-related genes Liu, Shuochuan Zhao, Yajie Zhang, Jiao Liu, Zhenzhen Funct Integr Genomics Original Article Ferroptosis is distinct from classic apoptotic cell death characterized by the accumulation of reactive oxygen species (ROS) and lipid peroxides on the cell membrane. Increasing findings have demonstrated that ferroptosis plays an important role in cancer development, but the exploration of ferroptosis in breast cancer is limited. In our study, we aimed to establish a ferroptosis activation-related model based on the differentially expressed genes between a group exhibiting high ferroptosis activation and a group exhibiting low ferroptosis activation. By using machine learning to establish the model, we verified the accuracy and efficiency of our model in The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) set and gene expression omnibus (GEO) dataset. Additionally, our research innovatively utilized single-cell RNA sequencing data to systematically reveal the microenvironment in the high and low FeAS groups, which demonstrated differences between the two groups from comprehensive aspects, including the activation condition of transcription factors, cell pseudotime features, cell communication, immune infiltration, chemotherapy efficiency, and potential drug resistance. In conclusion, different ferroptosis activation levels play a vital role in influencing the outcome of breast cancer patients and altering the tumor microenvironment in different molecular aspects. By analyzing differences in ferroptosis activation levels, our risk model is characterized by a good prognostic capacity in assessing the outcome of breast cancer patients, and the risk score can be used to prompt clinical treatment to prevent potential drug resistance. By identifying the different tumor microenvironment landscapes between the high- and low-risk groups, our risk model provides molecular insight into ferroptosis in breast cancer patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10142-023-01086-0. Springer Berlin Heidelberg 2023-05-22 2023 /pmc/articles/PMC10203036/ /pubmed/37212877 http://dx.doi.org/10.1007/s10142-023-01086-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Liu, Shuochuan Zhao, Yajie Zhang, Jiao Liu, Zhenzhen Application of single-cell RNA sequencing analysis of novel breast cancer phenotypes based on the activation of ferroptosis-related genes |
title | Application of single-cell RNA sequencing analysis of novel breast cancer phenotypes based on the activation of ferroptosis-related genes |
title_full | Application of single-cell RNA sequencing analysis of novel breast cancer phenotypes based on the activation of ferroptosis-related genes |
title_fullStr | Application of single-cell RNA sequencing analysis of novel breast cancer phenotypes based on the activation of ferroptosis-related genes |
title_full_unstemmed | Application of single-cell RNA sequencing analysis of novel breast cancer phenotypes based on the activation of ferroptosis-related genes |
title_short | Application of single-cell RNA sequencing analysis of novel breast cancer phenotypes based on the activation of ferroptosis-related genes |
title_sort | application of single-cell rna sequencing analysis of novel breast cancer phenotypes based on the activation of ferroptosis-related genes |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10203036/ https://www.ncbi.nlm.nih.gov/pubmed/37212877 http://dx.doi.org/10.1007/s10142-023-01086-0 |
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