Autonomous rhythmic activity in glioma networks drives brain tumour growth
Diffuse gliomas, particularly glioblastomas, are incurable brain tumours 1 . They are characterized by networks of interconnected brain tumour cells that communicate via Ca 2+ transients 2 – 6 . However, the networks’ architecture and communication strategy and how these influence tumour biology rem...
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Veröffentlicht in: | Nature (London) 2023-01, Vol.613 (7942), p.179-186 |
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creator | Hausmann, David Hoffmann, Dirk C. Venkataramani, Varun Jung, Erik Horschitz, Sandra Tetzlaff, Svenja K. Jabali, Ammar Hai, Ling Kessler, Tobias Azoŕin, Daniel D. Weil, Sophie Kourtesakis, Alexandros Sievers, Philipp Habel, Antje Breckwoldt, Michael O. Karreman, Matthia A. Ratliff, Miriam Messmer, Julia M. Yang, Yvonne Reyhan, Ekin Wendler, Susann Löb, Cathrin Mayer, Chanté Figarella, Katherine Osswald, Matthias Solecki, Gergely Sahm, Felix Garaschuk, Olga Kuner, Thomas Koch, Philipp Schlesner, Matthias Wick, Wolfgang Winkler, Frank |
description | Diffuse gliomas, particularly glioblastomas, are incurable brain tumours
1
. They are characterized by networks of interconnected brain tumour cells that communicate via Ca
2+
transients
2
–
6
. However, the networks’ architecture and communication strategy and how these influence tumour biology remain unknown. Here we describe how glioblastoma cell networks include a small, plastic population of highly active glioblastoma cells that display rhythmic Ca
2+
oscillations and are particularly connected to others. Their autonomous periodic Ca
2+
transients preceded Ca
2+
transients of other network-connected cells, activating the frequency-dependent MAPK and NF-κB pathways. Mathematical network analysis revealed that glioblastoma network topology follows scale-free and small-world properties, with periodic tumour cells frequently located in network hubs. This network design enabled resistance against random damage but was vulnerable to losing its key hubs. Targeting of autonomous rhythmic activity by selective physical ablation of periodic tumour cells or by genetic or pharmacological interference with the potassium channel KCa3.1 (also known as IK1, SK4 or KCNN4) strongly compromised global network communication. This led to a marked reduction of tumour cell viability within the entire network, reduced tumour growth in mice and extended animal survival. The dependency of glioblastoma networks on periodic Ca
2+
activity generates a vulnerability
7
that can be exploited for the development of novel therapies, such as with KCa3.1-inhibiting drugs.
A population of highly interconnected cells in glioblastoma makes these tumours resistant to general damage but vulnerable to targeted disruption of this small fraction of cells and their rhythmic Ca
2+
oscillations. |
doi_str_mv | 10.1038/s41586-022-05520-4 |
format | Article |
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1
. They are characterized by networks of interconnected brain tumour cells that communicate via Ca
2+
transients
2
–
6
. However, the networks’ architecture and communication strategy and how these influence tumour biology remain unknown. Here we describe how glioblastoma cell networks include a small, plastic population of highly active glioblastoma cells that display rhythmic Ca
2+
oscillations and are particularly connected to others. Their autonomous periodic Ca
2+
transients preceded Ca
2+
transients of other network-connected cells, activating the frequency-dependent MAPK and NF-κB pathways. Mathematical network analysis revealed that glioblastoma network topology follows scale-free and small-world properties, with periodic tumour cells frequently located in network hubs. This network design enabled resistance against random damage but was vulnerable to losing its key hubs. Targeting of autonomous rhythmic activity by selective physical ablation of periodic tumour cells or by genetic or pharmacological interference with the potassium channel KCa3.1 (also known as IK1, SK4 or KCNN4) strongly compromised global network communication. This led to a marked reduction of tumour cell viability within the entire network, reduced tumour growth in mice and extended animal survival. The dependency of glioblastoma networks on periodic Ca
2+
activity generates a vulnerability
7
that can be exploited for the development of novel therapies, such as with KCa3.1-inhibiting drugs.
A population of highly interconnected cells in glioblastoma makes these tumours resistant to general damage but vulnerable to targeted disruption of this small fraction of cells and their rhythmic Ca
2+
oscillations.</description><identifier>ISSN: 0028-0836</identifier><identifier>EISSN: 1476-4687</identifier><identifier>DOI: 10.1038/s41586-022-05520-4</identifier><identifier>PMID: 36517594</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>13/100 ; 14/1 ; 14/10 ; 14/19 ; 14/63 ; 14/69 ; 38/89 ; 42 ; 42/35 ; 42/41 ; 59/57 ; 631/67/1922 ; 64/60 ; 692/617/375/1922 ; 82/80 ; Ablation ; Animals ; Brain ; Brain - metabolism ; Brain - pathology ; Brain cancer ; Brain Neoplasms - genetics ; Brain Neoplasms - metabolism ; Brain Neoplasms - pathology ; Brain tumors ; Calcium - metabolism ; Calcium ions ; Calcium Signaling ; Calcium signalling ; Cell Death ; Cell interactions ; Cell viability ; Communication ; Drug development ; Frequency dependence ; Glioblastoma ; Glioblastoma - genetics ; Glioblastoma - metabolism ; Glioblastoma - pathology ; Glioblastoma cells ; Glioma ; Hubs ; Humanities and Social Sciences ; Lasers ; MAP kinase ; MAP Kinase Signaling System ; Mice ; multidisciplinary ; Network analysis ; Network design ; Network hubs ; Network topologies ; NF-kappa B - metabolism ; NF-κB protein ; Oscillations ; Potassium ; Potassium channels (calcium-gated) ; Rhythms ; Science ; Science (multidisciplinary) ; Survival Analysis ; Topology ; Tumors</subject><ispartof>Nature (London), 2023-01, Vol.613 (7942), p.179-186</ispartof><rights>The Author(s), under exclusive licence to Springer Nature Limited 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2022. The Author(s), under exclusive licence to Springer Nature Limited.</rights><rights>Copyright Nature Publishing Group Jan 5, 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-386d1e16f2a193c2747ae21c898d23f2a5907357d69e9d9a02c20d4630797fec3</citedby><cites>FETCH-LOGICAL-c375t-386d1e16f2a193c2747ae21c898d23f2a5907357d69e9d9a02c20d4630797fec3</cites><orcidid>0000-0003-3472-4165 ; 0000-0002-0571-4710 ; 0000-0001-8350-7074 ; 0000-0003-1370-1933 ; 0000-0002-6171-634X ; 0000-0001-5441-1962 ; 0000-0003-3237-6021 ; 0000-0002-9464-6544 ; 0000-0003-4892-6104 ; 0000-0002-2109-0186 ; 0000-0003-3305-9167 ; 0000-0003-3713-8786 ; 0000-0002-9980-2390 ; 0000-0001-7858-1501 ; 0000-0002-5896-4086 ; 0000-0002-2927-0886</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/s41586-022-05520-4$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/s41586-022-05520-4$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36517594$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hausmann, David</creatorcontrib><creatorcontrib>Hoffmann, Dirk C.</creatorcontrib><creatorcontrib>Venkataramani, Varun</creatorcontrib><creatorcontrib>Jung, Erik</creatorcontrib><creatorcontrib>Horschitz, Sandra</creatorcontrib><creatorcontrib>Tetzlaff, Svenja K.</creatorcontrib><creatorcontrib>Jabali, Ammar</creatorcontrib><creatorcontrib>Hai, Ling</creatorcontrib><creatorcontrib>Kessler, Tobias</creatorcontrib><creatorcontrib>Azoŕin, Daniel D.</creatorcontrib><creatorcontrib>Weil, Sophie</creatorcontrib><creatorcontrib>Kourtesakis, Alexandros</creatorcontrib><creatorcontrib>Sievers, Philipp</creatorcontrib><creatorcontrib>Habel, Antje</creatorcontrib><creatorcontrib>Breckwoldt, Michael O.</creatorcontrib><creatorcontrib>Karreman, Matthia A.</creatorcontrib><creatorcontrib>Ratliff, Miriam</creatorcontrib><creatorcontrib>Messmer, Julia M.</creatorcontrib><creatorcontrib>Yang, Yvonne</creatorcontrib><creatorcontrib>Reyhan, Ekin</creatorcontrib><creatorcontrib>Wendler, Susann</creatorcontrib><creatorcontrib>Löb, Cathrin</creatorcontrib><creatorcontrib>Mayer, Chanté</creatorcontrib><creatorcontrib>Figarella, Katherine</creatorcontrib><creatorcontrib>Osswald, Matthias</creatorcontrib><creatorcontrib>Solecki, Gergely</creatorcontrib><creatorcontrib>Sahm, Felix</creatorcontrib><creatorcontrib>Garaschuk, Olga</creatorcontrib><creatorcontrib>Kuner, Thomas</creatorcontrib><creatorcontrib>Koch, Philipp</creatorcontrib><creatorcontrib>Schlesner, Matthias</creatorcontrib><creatorcontrib>Wick, Wolfgang</creatorcontrib><creatorcontrib>Winkler, Frank</creatorcontrib><title>Autonomous rhythmic activity in glioma networks drives brain tumour growth</title><title>Nature (London)</title><addtitle>Nature</addtitle><addtitle>Nature</addtitle><description>Diffuse gliomas, particularly glioblastomas, are incurable brain tumours
1
. They are characterized by networks of interconnected brain tumour cells that communicate via Ca
2+
transients
2
–
6
. However, the networks’ architecture and communication strategy and how these influence tumour biology remain unknown. Here we describe how glioblastoma cell networks include a small, plastic population of highly active glioblastoma cells that display rhythmic Ca
2+
oscillations and are particularly connected to others. Their autonomous periodic Ca
2+
transients preceded Ca
2+
transients of other network-connected cells, activating the frequency-dependent MAPK and NF-κB pathways. Mathematical network analysis revealed that glioblastoma network topology follows scale-free and small-world properties, with periodic tumour cells frequently located in network hubs. This network design enabled resistance against random damage but was vulnerable to losing its key hubs. Targeting of autonomous rhythmic activity by selective physical ablation of periodic tumour cells or by genetic or pharmacological interference with the potassium channel KCa3.1 (also known as IK1, SK4 or KCNN4) strongly compromised global network communication. This led to a marked reduction of tumour cell viability within the entire network, reduced tumour growth in mice and extended animal survival. The dependency of glioblastoma networks on periodic Ca
2+
activity generates a vulnerability
7
that can be exploited for the development of novel therapies, such as with KCa3.1-inhibiting drugs.
A population of highly interconnected cells in glioblastoma makes these tumours resistant to general damage but vulnerable to targeted disruption of this small fraction of cells and their rhythmic Ca
2+
oscillations.</description><subject>13/100</subject><subject>14/1</subject><subject>14/10</subject><subject>14/19</subject><subject>14/63</subject><subject>14/69</subject><subject>38/89</subject><subject>42</subject><subject>42/35</subject><subject>42/41</subject><subject>59/57</subject><subject>631/67/1922</subject><subject>64/60</subject><subject>692/617/375/1922</subject><subject>82/80</subject><subject>Ablation</subject><subject>Animals</subject><subject>Brain</subject><subject>Brain - metabolism</subject><subject>Brain - pathology</subject><subject>Brain cancer</subject><subject>Brain Neoplasms - genetics</subject><subject>Brain Neoplasms - metabolism</subject><subject>Brain Neoplasms - pathology</subject><subject>Brain tumors</subject><subject>Calcium - metabolism</subject><subject>Calcium ions</subject><subject>Calcium Signaling</subject><subject>Calcium signalling</subject><subject>Cell Death</subject><subject>Cell interactions</subject><subject>Cell viability</subject><subject>Communication</subject><subject>Drug development</subject><subject>Frequency dependence</subject><subject>Glioblastoma</subject><subject>Glioblastoma - genetics</subject><subject>Glioblastoma - metabolism</subject><subject>Glioblastoma - pathology</subject><subject>Glioblastoma cells</subject><subject>Glioma</subject><subject>Hubs</subject><subject>Humanities and Social Sciences</subject><subject>Lasers</subject><subject>MAP kinase</subject><subject>MAP Kinase Signaling System</subject><subject>Mice</subject><subject>multidisciplinary</subject><subject>Network analysis</subject><subject>Network design</subject><subject>Network hubs</subject><subject>Network topologies</subject><subject>NF-kappa B - metabolism</subject><subject>NF-κB protein</subject><subject>Oscillations</subject><subject>Potassium</subject><subject>Potassium channels (calcium-gated)</subject><subject>Rhythms</subject><subject>Science</subject><subject>Science (multidisciplinary)</subject><subject>Survival Analysis</subject><subject>Topology</subject><subject>Tumors</subject><issn>0028-0836</issn><issn>1476-4687</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>BEC</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kLtOAzEQRS0EgvD4AQq0Eg3Nwvhtl1HEU5FooLYcr5MsZHeD7Q3K32NIAImCyiPPuXdmLkKnGC4xUHUVGeZKlEBICZwTKNkOGmAmRcmEkrtoAEBUCYqKA3QY4wsAcCzZPjqgIhdcswF6GPapa7um62MR5us0b2pXWJfqVZ3WRd0Ws0XdNbZofXrvwmssqlCvfCwmweZm6rMwFLPQvaf5Mdqb2kX0J9v3CD3fXD-N7srx4-39aDguHZU8lVSJCnsspsRiTR2RTFpPsFNaVYTmX65BUi4rob2utAXiCFRMUJBaTr2jR-hi47sM3VvvYzJNHZ1fLGzr8xmGSM4UV1KojJ7_QV_yvm3eLlOCAAWieabIhnKhizH4qVmGurFhbTCYz6TNJmmTkzZfSRuWRWdb637S-OpH8h1tBugGiLnVznz4nf2P7QcsN4h_</recordid><startdate>20230105</startdate><enddate>20230105</enddate><creator>Hausmann, 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rhythmic activity in glioma networks drives brain tumour growth</title><author>Hausmann, David ; Hoffmann, Dirk C. ; Venkataramani, Varun ; Jung, Erik ; Horschitz, Sandra ; Tetzlaff, Svenja K. ; Jabali, Ammar ; Hai, Ling ; Kessler, Tobias ; Azoŕin, Daniel D. ; Weil, Sophie ; Kourtesakis, Alexandros ; Sievers, Philipp ; Habel, Antje ; Breckwoldt, Michael O. ; Karreman, Matthia A. ; Ratliff, Miriam ; Messmer, Julia M. ; Yang, Yvonne ; Reyhan, Ekin ; Wendler, Susann ; Löb, Cathrin ; Mayer, Chanté ; Figarella, Katherine ; Osswald, Matthias ; Solecki, Gergely ; Sahm, Felix ; Garaschuk, Olga ; Kuner, Thomas ; Koch, Philipp ; Schlesner, Matthias ; Wick, Wolfgang ; Winkler, Frank</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-386d1e16f2a193c2747ae21c898d23f2a5907357d69e9d9a02c20d4630797fec3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>13/100</topic><topic>14/1</topic><topic>14/10</topic><topic>14/19</topic><topic>14/63</topic><topic>14/69</topic><topic>38/89</topic><topic>42</topic><topic>42/35</topic><topic>42/41</topic><topic>59/57</topic><topic>631/67/1922</topic><topic>64/60</topic><topic>692/617/375/1922</topic><topic>82/80</topic><topic>Ablation</topic><topic>Animals</topic><topic>Brain</topic><topic>Brain - metabolism</topic><topic>Brain - pathology</topic><topic>Brain cancer</topic><topic>Brain Neoplasms - genetics</topic><topic>Brain Neoplasms - metabolism</topic><topic>Brain Neoplasms - pathology</topic><topic>Brain tumors</topic><topic>Calcium - metabolism</topic><topic>Calcium ions</topic><topic>Calcium Signaling</topic><topic>Calcium signalling</topic><topic>Cell Death</topic><topic>Cell interactions</topic><topic>Cell viability</topic><topic>Communication</topic><topic>Drug development</topic><topic>Frequency dependence</topic><topic>Glioblastoma</topic><topic>Glioblastoma - genetics</topic><topic>Glioblastoma - metabolism</topic><topic>Glioblastoma - pathology</topic><topic>Glioblastoma cells</topic><topic>Glioma</topic><topic>Hubs</topic><topic>Humanities and Social Sciences</topic><topic>Lasers</topic><topic>MAP kinase</topic><topic>MAP Kinase Signaling System</topic><topic>Mice</topic><topic>multidisciplinary</topic><topic>Network analysis</topic><topic>Network design</topic><topic>Network hubs</topic><topic>Network topologies</topic><topic>NF-kappa B - metabolism</topic><topic>NF-κB protein</topic><topic>Oscillations</topic><topic>Potassium</topic><topic>Potassium channels (calcium-gated)</topic><topic>Rhythms</topic><topic>Science</topic><topic>Science (multidisciplinary)</topic><topic>Survival Analysis</topic><topic>Topology</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hausmann, David</creatorcontrib><creatorcontrib>Hoffmann, Dirk C.</creatorcontrib><creatorcontrib>Venkataramani, Varun</creatorcontrib><creatorcontrib>Jung, Erik</creatorcontrib><creatorcontrib>Horschitz, Sandra</creatorcontrib><creatorcontrib>Tetzlaff, Svenja K.</creatorcontrib><creatorcontrib>Jabali, Ammar</creatorcontrib><creatorcontrib>Hai, Ling</creatorcontrib><creatorcontrib>Kessler, Tobias</creatorcontrib><creatorcontrib>Azoŕin, Daniel D.</creatorcontrib><creatorcontrib>Weil, Sophie</creatorcontrib><creatorcontrib>Kourtesakis, Alexandros</creatorcontrib><creatorcontrib>Sievers, Philipp</creatorcontrib><creatorcontrib>Habel, Antje</creatorcontrib><creatorcontrib>Breckwoldt, Michael O.</creatorcontrib><creatorcontrib>Karreman, Matthia A.</creatorcontrib><creatorcontrib>Ratliff, Miriam</creatorcontrib><creatorcontrib>Messmer, Julia M.</creatorcontrib><creatorcontrib>Yang, Yvonne</creatorcontrib><creatorcontrib>Reyhan, Ekin</creatorcontrib><creatorcontrib>Wendler, Susann</creatorcontrib><creatorcontrib>Löb, Cathrin</creatorcontrib><creatorcontrib>Mayer, Chanté</creatorcontrib><creatorcontrib>Figarella, Katherine</creatorcontrib><creatorcontrib>Osswald, Matthias</creatorcontrib><creatorcontrib>Solecki, Gergely</creatorcontrib><creatorcontrib>Sahm, Felix</creatorcontrib><creatorcontrib>Garaschuk, Olga</creatorcontrib><creatorcontrib>Kuner, Thomas</creatorcontrib><creatorcontrib>Koch, Philipp</creatorcontrib><creatorcontrib>Schlesner, Matthias</creatorcontrib><creatorcontrib>Wick, Wolfgang</creatorcontrib><creatorcontrib>Winkler, Frank</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE 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Psychology</collection><collection>Engineering collection</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>University of Michigan</collection><collection>Genetics Abstracts</collection><collection>SIRS Editorial</collection><collection>Environment Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Nature (London)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hausmann, David</au><au>Hoffmann, Dirk C.</au><au>Venkataramani, Varun</au><au>Jung, Erik</au><au>Horschitz, Sandra</au><au>Tetzlaff, Svenja K.</au><au>Jabali, Ammar</au><au>Hai, Ling</au><au>Kessler, Tobias</au><au>Azoŕin, Daniel D.</au><au>Weil, Sophie</au><au>Kourtesakis, Alexandros</au><au>Sievers, Philipp</au><au>Habel, Antje</au><au>Breckwoldt, Michael O.</au><au>Karreman, Matthia A.</au><au>Ratliff, Miriam</au><au>Messmer, Julia M.</au><au>Yang, Yvonne</au><au>Reyhan, Ekin</au><au>Wendler, Susann</au><au>Löb, Cathrin</au><au>Mayer, Chanté</au><au>Figarella, Katherine</au><au>Osswald, Matthias</au><au>Solecki, Gergely</au><au>Sahm, Felix</au><au>Garaschuk, Olga</au><au>Kuner, Thomas</au><au>Koch, Philipp</au><au>Schlesner, Matthias</au><au>Wick, Wolfgang</au><au>Winkler, Frank</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Autonomous rhythmic activity in glioma networks drives brain tumour growth</atitle><jtitle>Nature (London)</jtitle><stitle>Nature</stitle><addtitle>Nature</addtitle><date>2023-01-05</date><risdate>2023</risdate><volume>613</volume><issue>7942</issue><spage>179</spage><epage>186</epage><pages>179-186</pages><issn>0028-0836</issn><eissn>1476-4687</eissn><abstract>Diffuse gliomas, particularly glioblastomas, are incurable brain tumours
1
. They are characterized by networks of interconnected brain tumour cells that communicate via Ca
2+
transients
2
–
6
. However, the networks’ architecture and communication strategy and how these influence tumour biology remain unknown. Here we describe how glioblastoma cell networks include a small, plastic population of highly active glioblastoma cells that display rhythmic Ca
2+
oscillations and are particularly connected to others. Their autonomous periodic Ca
2+
transients preceded Ca
2+
transients of other network-connected cells, activating the frequency-dependent MAPK and NF-κB pathways. Mathematical network analysis revealed that glioblastoma network topology follows scale-free and small-world properties, with periodic tumour cells frequently located in network hubs. This network design enabled resistance against random damage but was vulnerable to losing its key hubs. Targeting of autonomous rhythmic activity by selective physical ablation of periodic tumour cells or by genetic or pharmacological interference with the potassium channel KCa3.1 (also known as IK1, SK4 or KCNN4) strongly compromised global network communication. This led to a marked reduction of tumour cell viability within the entire network, reduced tumour growth in mice and extended animal survival. The dependency of glioblastoma networks on periodic Ca
2+
activity generates a vulnerability
7
that can be exploited for the development of novel therapies, such as with KCa3.1-inhibiting drugs.
A population of highly interconnected cells in glioblastoma makes these tumours resistant to general damage but vulnerable to targeted disruption of this small fraction of cells and their rhythmic Ca
2+
oscillations.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>36517594</pmid><doi>10.1038/s41586-022-05520-4</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0003-3472-4165</orcidid><orcidid>https://orcid.org/0000-0002-0571-4710</orcidid><orcidid>https://orcid.org/0000-0001-8350-7074</orcidid><orcidid>https://orcid.org/0000-0003-1370-1933</orcidid><orcidid>https://orcid.org/0000-0002-6171-634X</orcidid><orcidid>https://orcid.org/0000-0001-5441-1962</orcidid><orcidid>https://orcid.org/0000-0003-3237-6021</orcidid><orcidid>https://orcid.org/0000-0002-9464-6544</orcidid><orcidid>https://orcid.org/0000-0003-4892-6104</orcidid><orcidid>https://orcid.org/0000-0002-2109-0186</orcidid><orcidid>https://orcid.org/0000-0003-3305-9167</orcidid><orcidid>https://orcid.org/0000-0003-3713-8786</orcidid><orcidid>https://orcid.org/0000-0002-9980-2390</orcidid><orcidid>https://orcid.org/0000-0001-7858-1501</orcidid><orcidid>https://orcid.org/0000-0002-5896-4086</orcidid><orcidid>https://orcid.org/0000-0002-2927-0886</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0028-0836 |
ispartof | Nature (London), 2023-01, Vol.613 (7942), p.179-186 |
issn | 0028-0836 1476-4687 |
language | eng |
recordid | cdi_proquest_miscellaneous_2754858768 |
source | MEDLINE; Nature; Springer Online Journals - JUSTICE |
subjects | 13/100 14/1 14/10 14/19 14/63 14/69 38/89 42 42/35 42/41 59/57 631/67/1922 64/60 692/617/375/1922 82/80 Ablation Animals Brain Brain - metabolism Brain - pathology Brain cancer Brain Neoplasms - genetics Brain Neoplasms - metabolism Brain Neoplasms - pathology Brain tumors Calcium - metabolism Calcium ions Calcium Signaling Calcium signalling Cell Death Cell interactions Cell viability Communication Drug development Frequency dependence Glioblastoma Glioblastoma - genetics Glioblastoma - metabolism Glioblastoma - pathology Glioblastoma cells Glioma Hubs Humanities and Social Sciences Lasers MAP kinase MAP Kinase Signaling System Mice multidisciplinary Network analysis Network design Network hubs Network topologies NF-kappa B - metabolism NF-κB protein Oscillations Potassium Potassium channels (calcium-gated) Rhythms Science Science (multidisciplinary) Survival Analysis Topology Tumors |
title | Autonomous rhythmic activity in glioma networks drives brain tumour growth |
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