Slow-Cycling Cells in Glioblastoma: A Specific Population in the Cellular Mosaic of Cancer Stem Cells
Glioblastoma (GBM) exhibits populations of cells that drive tumorigenesis, treatment resistance, and disease progression. Cells with such properties have been described to express specific surface and intracellular markers or exhibit specific functional states, including being slow-cycling or quiesc...
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Veröffentlicht in: | Cancers 2022-02, Vol.14 (5), p.1126 |
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creator | Yang, Changlin Tian, Guimei Dajac, Mariana Doty, Andria Wang, Shu Lee, Ji-Hyun Rahman, Maryam Huang, Jianping Reynolds, Brent A Sarkisian, Matthew R Mitchell, Duane Deleyrolle, Loic P |
description | Glioblastoma (GBM) exhibits populations of cells that drive tumorigenesis, treatment resistance, and disease progression. Cells with such properties have been described to express specific surface and intracellular markers or exhibit specific functional states, including being slow-cycling or quiescent with the ability to generate proliferative progenies. In GBM, each of these cellular fractions was shown to harbor cardinal features of cancer stem cells (CSCs). In this study, we focus on the comparison of these cells and present evidence of great phenotypic and functional heterogeneity in brain cancer cell populations with stemness properties, especially between slow-cycling cells (SCCs) and cells phenotypically defined based on the expression of markers commonly used to enrich for CSCs. Here, we present an integrative analysis of the heterogeneity present in GBM cancer stem cell populations using a combination of approaches including flow cytometry, bulk RNA sequencing, and single cell transcriptomics completed with functional assays. We demonstrated that SCCs exhibit a diverse range of expression levels of canonical CSC markers. Importantly, the property of being slow-cycling and the expression of these markers were not mutually inclusive. We interrogated a single-cell RNA sequencing dataset and defined a group of cells as SCCs based on the highest score of a specific metabolic signature. Multiple CSC groups were determined based on the highest expression level of CD133, SOX2, PTPRZ1, ITGB8, or CD44. Each group, composed of 22 cells, showed limited cellular overlap, with SCCs representing a unique population with none of the 22 cells being included in the other groups. We also found transcriptomic distinctions between populations, which correlated with clinicopathological features of GBM. Patients with strong SCC signature score were associated with shorter survival and clustered within the mesenchymal molecular subtype. Cellular diversity amongst these populations was also demonstrated functionally, as illustrated by the heterogenous response to the chemotherapeutic agent temozolomide. In conclusion, our study supports the cancer stem cell mosaicism model, with slow-cycling cells representing critical elements harboring key features of disseminating cells. |
doi_str_mv | 10.3390/cancers14051126 |
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Cells with such properties have been described to express specific surface and intracellular markers or exhibit specific functional states, including being slow-cycling or quiescent with the ability to generate proliferative progenies. In GBM, each of these cellular fractions was shown to harbor cardinal features of cancer stem cells (CSCs). In this study, we focus on the comparison of these cells and present evidence of great phenotypic and functional heterogeneity in brain cancer cell populations with stemness properties, especially between slow-cycling cells (SCCs) and cells phenotypically defined based on the expression of markers commonly used to enrich for CSCs. Here, we present an integrative analysis of the heterogeneity present in GBM cancer stem cell populations using a combination of approaches including flow cytometry, bulk RNA sequencing, and single cell transcriptomics completed with functional assays. We demonstrated that SCCs exhibit a diverse range of expression levels of canonical CSC markers. Importantly, the property of being slow-cycling and the expression of these markers were not mutually inclusive. We interrogated a single-cell RNA sequencing dataset and defined a group of cells as SCCs based on the highest score of a specific metabolic signature. Multiple CSC groups were determined based on the highest expression level of CD133, SOX2, PTPRZ1, ITGB8, or CD44. Each group, composed of 22 cells, showed limited cellular overlap, with SCCs representing a unique population with none of the 22 cells being included in the other groups. We also found transcriptomic distinctions between populations, which correlated with clinicopathological features of GBM. Patients with strong SCC signature score were associated with shorter survival and clustered within the mesenchymal molecular subtype. Cellular diversity amongst these populations was also demonstrated functionally, as illustrated by the heterogenous response to the chemotherapeutic agent temozolomide. In conclusion, our study supports the cancer stem cell mosaicism model, with slow-cycling cells representing critical elements harboring key features of disseminating cells.</description><identifier>ISSN: 2072-6694</identifier><identifier>EISSN: 2072-6694</identifier><identifier>DOI: 10.3390/cancers14051126</identifier><identifier>PMID: 35267434</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Bioinformatics ; Brain cancer ; Cancer ; CD44 antigen ; Cell cycle ; Disease resistance ; Flow cytometry ; Gene expression ; Glioblastoma ; Glioblastoma cells ; Glycoproteins ; Growth factors ; Lipids ; Medical prognosis ; Mesenchyme ; Metabolism ; Mosaicism ; Stem cells ; Temozolomide ; Transcription ; Transcriptomics ; Tumorigenesis</subject><ispartof>Cancers, 2022-02, Vol.14 (5), p.1126</ispartof><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 by the authors. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c421t-734cf4a24d2a62166f6ea86e99695faa9345c8cc964f4e1417d295ba3c4cc0ab3</citedby><cites>FETCH-LOGICAL-c421t-734cf4a24d2a62166f6ea86e99695faa9345c8cc964f4e1417d295ba3c4cc0ab3</cites><orcidid>0000-0002-1129-744X ; 0000-0001-5687-600X ; 0000-0001-9813-6069 ; 0000-0001-6420-5150</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8909138/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8909138/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27923,27924,53790,53792</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35267434$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yang, Changlin</creatorcontrib><creatorcontrib>Tian, Guimei</creatorcontrib><creatorcontrib>Dajac, Mariana</creatorcontrib><creatorcontrib>Doty, Andria</creatorcontrib><creatorcontrib>Wang, Shu</creatorcontrib><creatorcontrib>Lee, Ji-Hyun</creatorcontrib><creatorcontrib>Rahman, Maryam</creatorcontrib><creatorcontrib>Huang, Jianping</creatorcontrib><creatorcontrib>Reynolds, Brent A</creatorcontrib><creatorcontrib>Sarkisian, Matthew R</creatorcontrib><creatorcontrib>Mitchell, Duane</creatorcontrib><creatorcontrib>Deleyrolle, Loic P</creatorcontrib><title>Slow-Cycling Cells in Glioblastoma: A Specific Population in the Cellular Mosaic of Cancer Stem Cells</title><title>Cancers</title><addtitle>Cancers (Basel)</addtitle><description>Glioblastoma (GBM) exhibits populations of cells that drive tumorigenesis, treatment resistance, and disease progression. Cells with such properties have been described to express specific surface and intracellular markers or exhibit specific functional states, including being slow-cycling or quiescent with the ability to generate proliferative progenies. In GBM, each of these cellular fractions was shown to harbor cardinal features of cancer stem cells (CSCs). In this study, we focus on the comparison of these cells and present evidence of great phenotypic and functional heterogeneity in brain cancer cell populations with stemness properties, especially between slow-cycling cells (SCCs) and cells phenotypically defined based on the expression of markers commonly used to enrich for CSCs. Here, we present an integrative analysis of the heterogeneity present in GBM cancer stem cell populations using a combination of approaches including flow cytometry, bulk RNA sequencing, and single cell transcriptomics completed with functional assays. We demonstrated that SCCs exhibit a diverse range of expression levels of canonical CSC markers. Importantly, the property of being slow-cycling and the expression of these markers were not mutually inclusive. We interrogated a single-cell RNA sequencing dataset and defined a group of cells as SCCs based on the highest score of a specific metabolic signature. Multiple CSC groups were determined based on the highest expression level of CD133, SOX2, PTPRZ1, ITGB8, or CD44. Each group, composed of 22 cells, showed limited cellular overlap, with SCCs representing a unique population with none of the 22 cells being included in the other groups. We also found transcriptomic distinctions between populations, which correlated with clinicopathological features of GBM. Patients with strong SCC signature score were associated with shorter survival and clustered within the mesenchymal molecular subtype. Cellular diversity amongst these populations was also demonstrated functionally, as illustrated by the heterogenous response to the chemotherapeutic agent temozolomide. In conclusion, our study supports the cancer stem cell mosaicism model, with slow-cycling cells representing critical elements harboring key features of disseminating cells.</description><subject>Bioinformatics</subject><subject>Brain cancer</subject><subject>Cancer</subject><subject>CD44 antigen</subject><subject>Cell cycle</subject><subject>Disease resistance</subject><subject>Flow cytometry</subject><subject>Gene expression</subject><subject>Glioblastoma</subject><subject>Glioblastoma cells</subject><subject>Glycoproteins</subject><subject>Growth factors</subject><subject>Lipids</subject><subject>Medical prognosis</subject><subject>Mesenchyme</subject><subject>Metabolism</subject><subject>Mosaicism</subject><subject>Stem cells</subject><subject>Temozolomide</subject><subject>Transcription</subject><subject>Transcriptomics</subject><subject>Tumorigenesis</subject><issn>2072-6694</issn><issn>2072-6694</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNpdkc1LxDAQxYMoKurZmwS8eKnmq2njQZDiFygKq-cwm001kjZr0ir-92ZdFTWXCTO_eczjIbRLySHnihwZ6I2NiQpSUsrkCtpkpGKFlEqs_vpvoJ2Unkl-nNNKVutog5dMVoKLTWQnPrwVzbvxrn_EjfU-YdfjC-_C1EMaQgfH-BRP5ta41hl8F-ajh8GFfoENT_ZzJ7civgkJMhFa3HwehieD7ZaS22itBZ_szlfdQg_nZ_fNZXF9e3HVnF4XRjA6FBUXphXAxIyBZFTKVlqopVVKqrIFUFyUpjZGSdEKSwWtZkyVU-BGGENgyrfQyVJ3Pk47OzO2HyJ4PY-ug_iuAzj9d9K7J_0YXnWtiKK8zgIHXwIxvIw2DbpzyWQL0NswJs0kryvGasEyuv8PfQ5j7LO9BVVJKgQlmTpaUiaGlKJtf46hRC9S1P9SzBt7vz388N-Z8Q_NJ5l7</recordid><startdate>20220223</startdate><enddate>20220223</enddate><creator>Yang, Changlin</creator><creator>Tian, Guimei</creator><creator>Dajac, Mariana</creator><creator>Doty, Andria</creator><creator>Wang, Shu</creator><creator>Lee, Ji-Hyun</creator><creator>Rahman, Maryam</creator><creator>Huang, Jianping</creator><creator>Reynolds, Brent A</creator><creator>Sarkisian, Matthew R</creator><creator>Mitchell, Duane</creator><creator>Deleyrolle, Loic P</creator><general>MDPI AG</general><general>MDPI</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T5</scope><scope>7TO</scope><scope>7XB</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M2O</scope><scope>M7P</scope><scope>MBDVC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-1129-744X</orcidid><orcidid>https://orcid.org/0000-0001-5687-600X</orcidid><orcidid>https://orcid.org/0000-0001-9813-6069</orcidid><orcidid>https://orcid.org/0000-0001-6420-5150</orcidid></search><sort><creationdate>20220223</creationdate><title>Slow-Cycling Cells in Glioblastoma: A Specific Population in the Cellular Mosaic of Cancer Stem Cells</title><author>Yang, Changlin ; Tian, Guimei ; Dajac, Mariana ; Doty, Andria ; Wang, Shu ; Lee, Ji-Hyun ; Rahman, Maryam ; Huang, Jianping ; Reynolds, Brent A ; Sarkisian, Matthew R ; Mitchell, Duane ; Deleyrolle, Loic P</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c421t-734cf4a24d2a62166f6ea86e99695faa9345c8cc964f4e1417d295ba3c4cc0ab3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Bioinformatics</topic><topic>Brain cancer</topic><topic>Cancer</topic><topic>CD44 antigen</topic><topic>Cell cycle</topic><topic>Disease resistance</topic><topic>Flow cytometry</topic><topic>Gene expression</topic><topic>Glioblastoma</topic><topic>Glioblastoma cells</topic><topic>Glycoproteins</topic><topic>Growth factors</topic><topic>Lipids</topic><topic>Medical prognosis</topic><topic>Mesenchyme</topic><topic>Metabolism</topic><topic>Mosaicism</topic><topic>Stem cells</topic><topic>Temozolomide</topic><topic>Transcription</topic><topic>Transcriptomics</topic><topic>Tumorigenesis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yang, Changlin</creatorcontrib><creatorcontrib>Tian, Guimei</creatorcontrib><creatorcontrib>Dajac, Mariana</creatorcontrib><creatorcontrib>Doty, Andria</creatorcontrib><creatorcontrib>Wang, Shu</creatorcontrib><creatorcontrib>Lee, Ji-Hyun</creatorcontrib><creatorcontrib>Rahman, Maryam</creatorcontrib><creatorcontrib>Huang, Jianping</creatorcontrib><creatorcontrib>Reynolds, Brent A</creatorcontrib><creatorcontrib>Sarkisian, Matthew R</creatorcontrib><creatorcontrib>Mitchell, Duane</creatorcontrib><creatorcontrib>Deleyrolle, Loic P</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Immunology Abstracts</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>Biological Sciences</collection><collection>ProQuest Research Library</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Cancers</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yang, Changlin</au><au>Tian, Guimei</au><au>Dajac, Mariana</au><au>Doty, Andria</au><au>Wang, Shu</au><au>Lee, Ji-Hyun</au><au>Rahman, Maryam</au><au>Huang, Jianping</au><au>Reynolds, Brent A</au><au>Sarkisian, Matthew R</au><au>Mitchell, Duane</au><au>Deleyrolle, Loic P</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Slow-Cycling Cells in Glioblastoma: A Specific Population in the Cellular Mosaic of Cancer Stem Cells</atitle><jtitle>Cancers</jtitle><addtitle>Cancers (Basel)</addtitle><date>2022-02-23</date><risdate>2022</risdate><volume>14</volume><issue>5</issue><spage>1126</spage><pages>1126-</pages><issn>2072-6694</issn><eissn>2072-6694</eissn><abstract>Glioblastoma (GBM) exhibits populations of cells that drive tumorigenesis, treatment resistance, and disease progression. Cells with such properties have been described to express specific surface and intracellular markers or exhibit specific functional states, including being slow-cycling or quiescent with the ability to generate proliferative progenies. In GBM, each of these cellular fractions was shown to harbor cardinal features of cancer stem cells (CSCs). In this study, we focus on the comparison of these cells and present evidence of great phenotypic and functional heterogeneity in brain cancer cell populations with stemness properties, especially between slow-cycling cells (SCCs) and cells phenotypically defined based on the expression of markers commonly used to enrich for CSCs. Here, we present an integrative analysis of the heterogeneity present in GBM cancer stem cell populations using a combination of approaches including flow cytometry, bulk RNA sequencing, and single cell transcriptomics completed with functional assays. We demonstrated that SCCs exhibit a diverse range of expression levels of canonical CSC markers. Importantly, the property of being slow-cycling and the expression of these markers were not mutually inclusive. We interrogated a single-cell RNA sequencing dataset and defined a group of cells as SCCs based on the highest score of a specific metabolic signature. Multiple CSC groups were determined based on the highest expression level of CD133, SOX2, PTPRZ1, ITGB8, or CD44. Each group, composed of 22 cells, showed limited cellular overlap, with SCCs representing a unique population with none of the 22 cells being included in the other groups. We also found transcriptomic distinctions between populations, which correlated with clinicopathological features of GBM. Patients with strong SCC signature score were associated with shorter survival and clustered within the mesenchymal molecular subtype. Cellular diversity amongst these populations was also demonstrated functionally, as illustrated by the heterogenous response to the chemotherapeutic agent temozolomide. In conclusion, our study supports the cancer stem cell mosaicism model, with slow-cycling cells representing critical elements harboring key features of disseminating cells.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>35267434</pmid><doi>10.3390/cancers14051126</doi><orcidid>https://orcid.org/0000-0002-1129-744X</orcidid><orcidid>https://orcid.org/0000-0001-5687-600X</orcidid><orcidid>https://orcid.org/0000-0001-9813-6069</orcidid><orcidid>https://orcid.org/0000-0001-6420-5150</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Bioinformatics Brain cancer Cancer CD44 antigen Cell cycle Disease resistance Flow cytometry Gene expression Glioblastoma Glioblastoma cells Glycoproteins Growth factors Lipids Medical prognosis Mesenchyme Metabolism Mosaicism Stem cells Temozolomide Transcription Transcriptomics Tumorigenesis |
title | Slow-Cycling Cells in Glioblastoma: A Specific Population in the Cellular Mosaic of Cancer Stem Cells |
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