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A novel stemness-hypoxia-related signature for prognostic stratification and immunotherapy response in hepatocellular carcinoma
BACKGROUND: The specific differentiation potential, unlimited proliferation, and self-renewal capacity of cancer stem cells (CSCs) are closely related to the occurrence, recurrence, and drug resistance of hepatocellular carcinoma (HCC), as well as hypoxia. Therefore, an in-depth analysis of the rela...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617384/ https://www.ncbi.nlm.nih.gov/pubmed/36307751 http://dx.doi.org/10.1186/s12885-022-10195-1 |
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author | Zhang, Genhao Zhang, Kai Zhao, Yanteng Yang, Qiankun Lv, Xianping |
author_facet | Zhang, Genhao Zhang, Kai Zhao, Yanteng Yang, Qiankun Lv, Xianping |
author_sort | Zhang, Genhao |
collection | PubMed |
description | BACKGROUND: The specific differentiation potential, unlimited proliferation, and self-renewal capacity of cancer stem cells (CSCs) are closely related to the occurrence, recurrence, and drug resistance of hepatocellular carcinoma (HCC), as well as hypoxia. Therefore, an in-depth analysis of the relationship between HCC stemness, oxygenation status, and the effectiveness of immunotherapy is necessary to improve the poor prognosis of HCC patients. METHODS: The weighted gene co-expression network analysis (WGCNA) was utilized to find hypoxia-related genes, and the stemness index (mRNAsi) was evaluated using the one-class logistic regression (OCLR) technique. Based on stemness-hypoxia-related genes (SHRGs), population subgroup categorization using NMF cluster analysis was carried out. The relationship between SHRGs and survival outcomes was determined using univariate Cox regression. The LASSO-Cox regression strategy was performed to investigate the quality and establish the classifier associated with prognosis. The main effect of risk scores on the tumor microenvironment (TME) and its response to immune checkpoint drugs was also examined. Finally, qRT-PCR was performed to explore the expression and prognostic value of the signature in clinical samples. RESULTS: After identifying tumor stemness- and hypoxia-related genes through a series of bioinformatics analyses, we constructed a prognostic stratification model based on these SHRGs, which can be effectively applied to the prognostic classification of HCC patients and the prediction of immune checkpoint inhibitors (ICIs) efficacy. Independent validation of the model in the ICGC cohort yielded good results. In addition, we also constructed hypoxic cell models in Herp3B and Huh7 cells to verify the expression of genes in the prognostic model and found that C7, CLEC1B, and CXCL6 were not only related to the tumor stemness but also related to hypoxia. Finally, we found that the constructed signature had a good prognostic value in the clinical sample. CONCLUSIONS: We constructed and validated a stemness-hypoxia-related prognostic signature that can be used to predict the efficacy of ICIs therapy. We also verified that C7, CLEC1B, and CXCL6 are indeed associated with stemness and hypoxia through a hypoxic cell model, which may provide new ideas for individualized immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10195-1. |
format | Online Article Text |
id | pubmed-9617384 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-96173842022-10-30 A novel stemness-hypoxia-related signature for prognostic stratification and immunotherapy response in hepatocellular carcinoma Zhang, Genhao Zhang, Kai Zhao, Yanteng Yang, Qiankun Lv, Xianping BMC Cancer Research BACKGROUND: The specific differentiation potential, unlimited proliferation, and self-renewal capacity of cancer stem cells (CSCs) are closely related to the occurrence, recurrence, and drug resistance of hepatocellular carcinoma (HCC), as well as hypoxia. Therefore, an in-depth analysis of the relationship between HCC stemness, oxygenation status, and the effectiveness of immunotherapy is necessary to improve the poor prognosis of HCC patients. METHODS: The weighted gene co-expression network analysis (WGCNA) was utilized to find hypoxia-related genes, and the stemness index (mRNAsi) was evaluated using the one-class logistic regression (OCLR) technique. Based on stemness-hypoxia-related genes (SHRGs), population subgroup categorization using NMF cluster analysis was carried out. The relationship between SHRGs and survival outcomes was determined using univariate Cox regression. The LASSO-Cox regression strategy was performed to investigate the quality and establish the classifier associated with prognosis. The main effect of risk scores on the tumor microenvironment (TME) and its response to immune checkpoint drugs was also examined. Finally, qRT-PCR was performed to explore the expression and prognostic value of the signature in clinical samples. RESULTS: After identifying tumor stemness- and hypoxia-related genes through a series of bioinformatics analyses, we constructed a prognostic stratification model based on these SHRGs, which can be effectively applied to the prognostic classification of HCC patients and the prediction of immune checkpoint inhibitors (ICIs) efficacy. Independent validation of the model in the ICGC cohort yielded good results. In addition, we also constructed hypoxic cell models in Herp3B and Huh7 cells to verify the expression of genes in the prognostic model and found that C7, CLEC1B, and CXCL6 were not only related to the tumor stemness but also related to hypoxia. Finally, we found that the constructed signature had a good prognostic value in the clinical sample. CONCLUSIONS: We constructed and validated a stemness-hypoxia-related prognostic signature that can be used to predict the efficacy of ICIs therapy. We also verified that C7, CLEC1B, and CXCL6 are indeed associated with stemness and hypoxia through a hypoxic cell model, which may provide new ideas for individualized immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10195-1. BioMed Central 2022-10-28 /pmc/articles/PMC9617384/ /pubmed/36307751 http://dx.doi.org/10.1186/s12885-022-10195-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Zhang, Genhao Zhang, Kai Zhao, Yanteng Yang, Qiankun Lv, Xianping A novel stemness-hypoxia-related signature for prognostic stratification and immunotherapy response in hepatocellular carcinoma |
title | A novel stemness-hypoxia-related signature for prognostic stratification and immunotherapy response in hepatocellular carcinoma |
title_full | A novel stemness-hypoxia-related signature for prognostic stratification and immunotherapy response in hepatocellular carcinoma |
title_fullStr | A novel stemness-hypoxia-related signature for prognostic stratification and immunotherapy response in hepatocellular carcinoma |
title_full_unstemmed | A novel stemness-hypoxia-related signature for prognostic stratification and immunotherapy response in hepatocellular carcinoma |
title_short | A novel stemness-hypoxia-related signature for prognostic stratification and immunotherapy response in hepatocellular carcinoma |
title_sort | novel stemness-hypoxia-related signature for prognostic stratification and immunotherapy response in hepatocellular carcinoma |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617384/ https://www.ncbi.nlm.nih.gov/pubmed/36307751 http://dx.doi.org/10.1186/s12885-022-10195-1 |
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