Cargando…
CRISPR-Cas9 identifies growth-related subtypes of glioblastoma with therapeutical significance through cell line knockdown
BACKGROUND: Glioblastoma (GBM) is a type of highly malignant brain tumor that is known for its significant intratumoral heterogeneity, meaning that there can be a high degree of variability within the tumor tissue. Despite the identification of several subtypes of GBM in recent years, there remains...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10424363/ https://www.ncbi.nlm.nih.gov/pubmed/37580710 http://dx.doi.org/10.1186/s12885-023-11131-7 |
_version_ | 1785089655819993088 |
---|---|
author | Zhao, Nannan Weng, Siyuan Liu, Zaoqu Xu, Hui Ren, Yuqin Guo, Chunguang Liu, Long Zhang, Zhenyu Ji, Yuchen Han, Xinwei |
author_facet | Zhao, Nannan Weng, Siyuan Liu, Zaoqu Xu, Hui Ren, Yuqin Guo, Chunguang Liu, Long Zhang, Zhenyu Ji, Yuchen Han, Xinwei |
author_sort | Zhao, Nannan |
collection | PubMed |
description | BACKGROUND: Glioblastoma (GBM) is a type of highly malignant brain tumor that is known for its significant intratumoral heterogeneity, meaning that there can be a high degree of variability within the tumor tissue. Despite the identification of several subtypes of GBM in recent years, there remains to explore a classification based on genes related to proliferation and growth. METHODS: The growth-related genes of GBM were identified by CRISPR-Cas9 and univariate Cox regression analysis. The expression of these genes in the Cancer Genome Atlas cohort (TCGA) was used to construct growth-related genes subtypes (GGSs) via consensus clustering. Validation of this subtyping was performed using the nearest template prediction (NTP) algorithm in two independent Gene Expression Omnibus (GEO) cohorts and the ZZ cohort. Additionally, copy number variations, biological functions, and potential drugs were analyzed for each of the different subtypes separately. RESULTS: Our research established multicenter-validated GGSs. GGS1 exhibits the poorest prognosis, with the highest frequency of chr 7 gain & chr 10 loss, and the lowest frequency of chr 19 & 20 co-gain. Additionally, GGS1 displays the highest expression of EGFR. Furthermore, it is significantly enriched in metabolic, stemness, proliferation, and signaling pathways. Besides we showed that Foretinib may be a potential therapeutic agent for GGS1, the worst prognostic subtype, through data screening and in vitro experiments. GGS2 has a moderate prognosis, with a slightly higher proportion of chr 7 gain & chr 10 loss, and the highest proportion of chr 19 & 20 co-gain. The prognosis of GGS3 is the best, with the least chr 7 gain & 10 loss and EGFR expression. CONCLUSIONS: These results enhance our understanding of the heterogeneity of GBM and offer insights for stratified management and precise treatment of GBM patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11131-7. |
format | Online Article Text |
id | pubmed-10424363 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-104243632023-08-15 CRISPR-Cas9 identifies growth-related subtypes of glioblastoma with therapeutical significance through cell line knockdown Zhao, Nannan Weng, Siyuan Liu, Zaoqu Xu, Hui Ren, Yuqin Guo, Chunguang Liu, Long Zhang, Zhenyu Ji, Yuchen Han, Xinwei BMC Cancer Research BACKGROUND: Glioblastoma (GBM) is a type of highly malignant brain tumor that is known for its significant intratumoral heterogeneity, meaning that there can be a high degree of variability within the tumor tissue. Despite the identification of several subtypes of GBM in recent years, there remains to explore a classification based on genes related to proliferation and growth. METHODS: The growth-related genes of GBM were identified by CRISPR-Cas9 and univariate Cox regression analysis. The expression of these genes in the Cancer Genome Atlas cohort (TCGA) was used to construct growth-related genes subtypes (GGSs) via consensus clustering. Validation of this subtyping was performed using the nearest template prediction (NTP) algorithm in two independent Gene Expression Omnibus (GEO) cohorts and the ZZ cohort. Additionally, copy number variations, biological functions, and potential drugs were analyzed for each of the different subtypes separately. RESULTS: Our research established multicenter-validated GGSs. GGS1 exhibits the poorest prognosis, with the highest frequency of chr 7 gain & chr 10 loss, and the lowest frequency of chr 19 & 20 co-gain. Additionally, GGS1 displays the highest expression of EGFR. Furthermore, it is significantly enriched in metabolic, stemness, proliferation, and signaling pathways. Besides we showed that Foretinib may be a potential therapeutic agent for GGS1, the worst prognostic subtype, through data screening and in vitro experiments. GGS2 has a moderate prognosis, with a slightly higher proportion of chr 7 gain & chr 10 loss, and the highest proportion of chr 19 & 20 co-gain. The prognosis of GGS3 is the best, with the least chr 7 gain & 10 loss and EGFR expression. CONCLUSIONS: These results enhance our understanding of the heterogeneity of GBM and offer insights for stratified management and precise treatment of GBM patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11131-7. BioMed Central 2023-08-14 /pmc/articles/PMC10424363/ /pubmed/37580710 http://dx.doi.org/10.1186/s12885-023-11131-7 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/) . 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 Zhao, Nannan Weng, Siyuan Liu, Zaoqu Xu, Hui Ren, Yuqin Guo, Chunguang Liu, Long Zhang, Zhenyu Ji, Yuchen Han, Xinwei CRISPR-Cas9 identifies growth-related subtypes of glioblastoma with therapeutical significance through cell line knockdown |
title | CRISPR-Cas9 identifies growth-related subtypes of glioblastoma with therapeutical significance through cell line knockdown |
title_full | CRISPR-Cas9 identifies growth-related subtypes of glioblastoma with therapeutical significance through cell line knockdown |
title_fullStr | CRISPR-Cas9 identifies growth-related subtypes of glioblastoma with therapeutical significance through cell line knockdown |
title_full_unstemmed | CRISPR-Cas9 identifies growth-related subtypes of glioblastoma with therapeutical significance through cell line knockdown |
title_short | CRISPR-Cas9 identifies growth-related subtypes of glioblastoma with therapeutical significance through cell line knockdown |
title_sort | crispr-cas9 identifies growth-related subtypes of glioblastoma with therapeutical significance through cell line knockdown |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10424363/ https://www.ncbi.nlm.nih.gov/pubmed/37580710 http://dx.doi.org/10.1186/s12885-023-11131-7 |
work_keys_str_mv | AT zhaonannan crisprcas9identifiesgrowthrelatedsubtypesofglioblastomawiththerapeuticalsignificancethroughcelllineknockdown AT wengsiyuan crisprcas9identifiesgrowthrelatedsubtypesofglioblastomawiththerapeuticalsignificancethroughcelllineknockdown AT liuzaoqu crisprcas9identifiesgrowthrelatedsubtypesofglioblastomawiththerapeuticalsignificancethroughcelllineknockdown AT xuhui crisprcas9identifiesgrowthrelatedsubtypesofglioblastomawiththerapeuticalsignificancethroughcelllineknockdown AT renyuqin crisprcas9identifiesgrowthrelatedsubtypesofglioblastomawiththerapeuticalsignificancethroughcelllineknockdown AT guochunguang crisprcas9identifiesgrowthrelatedsubtypesofglioblastomawiththerapeuticalsignificancethroughcelllineknockdown AT liulong crisprcas9identifiesgrowthrelatedsubtypesofglioblastomawiththerapeuticalsignificancethroughcelllineknockdown AT zhangzhenyu crisprcas9identifiesgrowthrelatedsubtypesofglioblastomawiththerapeuticalsignificancethroughcelllineknockdown AT jiyuchen crisprcas9identifiesgrowthrelatedsubtypesofglioblastomawiththerapeuticalsignificancethroughcelllineknockdown AT hanxinwei crisprcas9identifiesgrowthrelatedsubtypesofglioblastomawiththerapeuticalsignificancethroughcelllineknockdown |