Cargando…

Constructing a cancer stem cell related prognostic model for predicting immune landscape and drug sensitivity in colorectal cancer

Background: Colorectal cancer (CRC) ranks the second malignancy with high incidence and mortality worldwide. Cancer stem cells (CSCs) function critically in cancer progression and metastasis via the interplay with immune cells in tumor microenvironment. This study aimed to identify important CSC mar...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Jianfang, Wu, Shuang, Peng, Yu, Zhao, Yang, Dong, Yan, Ran, Fengwei, Geng, Haofei, Zhang, Kang, Li, Jianjun, Huang, Shuo, Wang, Zhe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10292801/
https://www.ncbi.nlm.nih.gov/pubmed/37377935
http://dx.doi.org/10.3389/fphar.2023.1200017
_version_ 1785062888587657216
author Chen, Jianfang
Wu, Shuang
Peng, Yu
Zhao, Yang
Dong, Yan
Ran, Fengwei
Geng, Haofei
Zhang, Kang
Li, Jianjun
Huang, Shuo
Wang, Zhe
author_facet Chen, Jianfang
Wu, Shuang
Peng, Yu
Zhao, Yang
Dong, Yan
Ran, Fengwei
Geng, Haofei
Zhang, Kang
Li, Jianjun
Huang, Shuo
Wang, Zhe
author_sort Chen, Jianfang
collection PubMed
description Background: Colorectal cancer (CRC) ranks the second malignancy with high incidence and mortality worldwide. Cancer stem cells (CSCs) function critically in cancer progression and metastasis via the interplay with immune cells in tumor microenvironment. This study aimed to identify important CSC marker genes and parsed the role of these marker genes in CRC. Materials and methods: CRC samples’ single-cell RNA sequencing data and bulk transcriptome data were utilized. Seurat R package annotated CSCs and identified CSC marker genes. Consensus clustering subtyped CRC samples based on CSC marker genes. Immune microenvironment, pathway and oxidative stress analysis was performed using ESTIMATE, MCP-counter analysis and ssGSEA analysis. A prognostic model was established by Lasso and stepAIC. Sensitivity to chemotherapeutic drugs was determined by the biochemical half maximal inhibitory concentration with pRRophetic R package. Results: We identified a total of 29 CSC marker genes related to disease-specific survival (DSS). Two clusters (CSC1 and CSC2) were determined, and CSC2 showed shorter DSS, a larger proportion of late-stage samples, and higher oxidative stress response. Two clusters exhibited differential activation of biological pathways associated with immune response and oncogenic signaling. Drug sensitivity analysis showed that 44 chemotherapy drugs were more sensitive to CSC2 that those in CSC1. We constructed a seven-gene prognostic model (DRD4, DPP7, UCN, INHBA, SFTA2, SYNPO2, and NXPH4) that was effectively to distinguish high-risk and low-risk patients. 14 chemotherapy drugs were more sensitive to high-risk group and 13 chemotherapy drugs were more sensitive to low-risk group. Combination of higher oxidative stress and risk score indicated dismal prognosis. Conclusion: The CSC marker genes we identified may help to further decipher the role of CSCs in CRC development and progression. The seven-gene prognostic model could serve as an indicator for predicting the response to immunotherapy and chemotherapy as well as prognosis of CRC patients.
format Online
Article
Text
id pubmed-10292801
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-102928012023-06-27 Constructing a cancer stem cell related prognostic model for predicting immune landscape and drug sensitivity in colorectal cancer Chen, Jianfang Wu, Shuang Peng, Yu Zhao, Yang Dong, Yan Ran, Fengwei Geng, Haofei Zhang, Kang Li, Jianjun Huang, Shuo Wang, Zhe Front Pharmacol Pharmacology Background: Colorectal cancer (CRC) ranks the second malignancy with high incidence and mortality worldwide. Cancer stem cells (CSCs) function critically in cancer progression and metastasis via the interplay with immune cells in tumor microenvironment. This study aimed to identify important CSC marker genes and parsed the role of these marker genes in CRC. Materials and methods: CRC samples’ single-cell RNA sequencing data and bulk transcriptome data were utilized. Seurat R package annotated CSCs and identified CSC marker genes. Consensus clustering subtyped CRC samples based on CSC marker genes. Immune microenvironment, pathway and oxidative stress analysis was performed using ESTIMATE, MCP-counter analysis and ssGSEA analysis. A prognostic model was established by Lasso and stepAIC. Sensitivity to chemotherapeutic drugs was determined by the biochemical half maximal inhibitory concentration with pRRophetic R package. Results: We identified a total of 29 CSC marker genes related to disease-specific survival (DSS). Two clusters (CSC1 and CSC2) were determined, and CSC2 showed shorter DSS, a larger proportion of late-stage samples, and higher oxidative stress response. Two clusters exhibited differential activation of biological pathways associated with immune response and oncogenic signaling. Drug sensitivity analysis showed that 44 chemotherapy drugs were more sensitive to CSC2 that those in CSC1. We constructed a seven-gene prognostic model (DRD4, DPP7, UCN, INHBA, SFTA2, SYNPO2, and NXPH4) that was effectively to distinguish high-risk and low-risk patients. 14 chemotherapy drugs were more sensitive to high-risk group and 13 chemotherapy drugs were more sensitive to low-risk group. Combination of higher oxidative stress and risk score indicated dismal prognosis. Conclusion: The CSC marker genes we identified may help to further decipher the role of CSCs in CRC development and progression. The seven-gene prognostic model could serve as an indicator for predicting the response to immunotherapy and chemotherapy as well as prognosis of CRC patients. Frontiers Media S.A. 2023-06-12 /pmc/articles/PMC10292801/ /pubmed/37377935 http://dx.doi.org/10.3389/fphar.2023.1200017 Text en Copyright © 2023 Chen, Wu, Peng, Zhao, Dong, Ran, Geng, Zhang, Li, Huang and Wang. 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 Pharmacology
Chen, Jianfang
Wu, Shuang
Peng, Yu
Zhao, Yang
Dong, Yan
Ran, Fengwei
Geng, Haofei
Zhang, Kang
Li, Jianjun
Huang, Shuo
Wang, Zhe
Constructing a cancer stem cell related prognostic model for predicting immune landscape and drug sensitivity in colorectal cancer
title Constructing a cancer stem cell related prognostic model for predicting immune landscape and drug sensitivity in colorectal cancer
title_full Constructing a cancer stem cell related prognostic model for predicting immune landscape and drug sensitivity in colorectal cancer
title_fullStr Constructing a cancer stem cell related prognostic model for predicting immune landscape and drug sensitivity in colorectal cancer
title_full_unstemmed Constructing a cancer stem cell related prognostic model for predicting immune landscape and drug sensitivity in colorectal cancer
title_short Constructing a cancer stem cell related prognostic model for predicting immune landscape and drug sensitivity in colorectal cancer
title_sort constructing a cancer stem cell related prognostic model for predicting immune landscape and drug sensitivity in colorectal cancer
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10292801/
https://www.ncbi.nlm.nih.gov/pubmed/37377935
http://dx.doi.org/10.3389/fphar.2023.1200017
work_keys_str_mv AT chenjianfang constructingacancerstemcellrelatedprognosticmodelforpredictingimmunelandscapeanddrugsensitivityincolorectalcancer
AT wushuang constructingacancerstemcellrelatedprognosticmodelforpredictingimmunelandscapeanddrugsensitivityincolorectalcancer
AT pengyu constructingacancerstemcellrelatedprognosticmodelforpredictingimmunelandscapeanddrugsensitivityincolorectalcancer
AT zhaoyang constructingacancerstemcellrelatedprognosticmodelforpredictingimmunelandscapeanddrugsensitivityincolorectalcancer
AT dongyan constructingacancerstemcellrelatedprognosticmodelforpredictingimmunelandscapeanddrugsensitivityincolorectalcancer
AT ranfengwei constructingacancerstemcellrelatedprognosticmodelforpredictingimmunelandscapeanddrugsensitivityincolorectalcancer
AT genghaofei constructingacancerstemcellrelatedprognosticmodelforpredictingimmunelandscapeanddrugsensitivityincolorectalcancer
AT zhangkang constructingacancerstemcellrelatedprognosticmodelforpredictingimmunelandscapeanddrugsensitivityincolorectalcancer
AT lijianjun constructingacancerstemcellrelatedprognosticmodelforpredictingimmunelandscapeanddrugsensitivityincolorectalcancer
AT huangshuo constructingacancerstemcellrelatedprognosticmodelforpredictingimmunelandscapeanddrugsensitivityincolorectalcancer
AT wangzhe constructingacancerstemcellrelatedprognosticmodelforpredictingimmunelandscapeanddrugsensitivityincolorectalcancer