miR clusters target cellular functional complexes by defining their degree of regulatory freedom
Using the two paralog miR-23∼27∼24 clusters as an example and combining experimental and clinical data in a systematical approach to microRNA (miR) function and dysregulation, a complex picture of their roles in cancer is drawn. Various findings appear to be contradictory to a larger extent and cann...
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Veröffentlicht in: | Cancer and metastasis reviews 2016-06, Vol.35 (2), p.289-322 |
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description | Using the two paralog miR-23∼27∼24 clusters as an example and combining experimental and clinical data in a systematical approach to microRNA (miR) function and dysregulation, a complex picture of their roles in cancer is drawn. Various findings appear to be contradictory to a larger extent and cannot be fully explained by the classical regulatory network models and feedback loops that are mainly considered by one-to-one regulatory interactions of the involved molecules. Here, we propose an extended model of the regulatory role of miRs that, at least, supplements the usually considered single/oligo-target regulation of certain miRs. The cellular availability of the participating miR members in this model reflects an upper hierarchy level of intracellular and extracellular environmental influences, such as neighboring cells, soluble factors, hypoxia, chemotherapeutic drugs, and irradiation, among others. The novel model is based on the understanding of cellular functional complexes, such as for apoptosis, migration, and proliferation. These complexes consist of many regulatory components that can be targeted by miR cluster members to a different extent but may affect the functional complex in different ways. We propose that the final miR-related effect is a result of the possible degree of regulatory freedom provided by the miR effects on the whole functional complex structure. This degree of regulatory freedom defines to which extent the cellular functional complex can react in response to regulatory triggers, also understood as sensitization (more regulatory response options) or de-sensitization (less regulatory response options) of the system rather than single molecules. |
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Various findings appear to be contradictory to a larger extent and cannot be fully explained by the classical regulatory network models and feedback loops that are mainly considered by one-to-one regulatory interactions of the involved molecules. Here, we propose an extended model of the regulatory role of miRs that, at least, supplements the usually considered single/oligo-target regulation of certain miRs. The cellular availability of the participating miR members in this model reflects an upper hierarchy level of intracellular and extracellular environmental influences, such as neighboring cells, soluble factors, hypoxia, chemotherapeutic drugs, and irradiation, among others. The novel model is based on the understanding of cellular functional complexes, such as for apoptosis, migration, and proliferation. These complexes consist of many regulatory components that can be targeted by miR cluster members to a different extent but may affect the functional complex in different ways. We propose that the final miR-related effect is a result of the possible degree of regulatory freedom provided by the miR effects on the whole functional complex structure. This degree of regulatory freedom defines to which extent the cellular functional complex can react in response to regulatory triggers, also understood as sensitization (more regulatory response options) or de-sensitization (less regulatory response options) of the system rather than single molecules.</description><identifier>ISSN: 0167-7659</identifier><identifier>EISSN: 1573-7233</identifier><identifier>DOI: 10.1007/s10555-016-9617-1</identifier><identifier>PMID: 26970968</identifier><identifier>CODEN: CMRED4</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Animals ; Biomedical and Life Sciences ; Biomedicine ; Cancer Research ; Cell Transformation, Neoplastic - genetics ; Cell Transformation, Neoplastic - metabolism ; Clinical ; Computational Biology - methods ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Gene Regulatory Networks ; Humans ; MicroRNAs - genetics ; Models, Biological ; Multigene Family ; Neoplasms - diagnosis ; Neoplasms - genetics ; Neoplasms - metabolism ; Neoplasms - therapy ; Oncology ; Prognosis ; RNA Interference ; Transcription, Genetic ; Transcriptome ; Treatment Outcome</subject><ispartof>Cancer and metastasis reviews, 2016-06, Vol.35 (2), p.289-322</ispartof><rights>Springer Science+Business Media New York 2016</rights><rights>COPYRIGHT 2016 Springer</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c541t-6bf8228e3b5dfd388b58818f7342f17d23bd7de375979ba47b0c5775616e7d213</citedby><cites>FETCH-LOGICAL-c541t-6bf8228e3b5dfd388b58818f7342f17d23bd7de375979ba47b0c5775616e7d213</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10555-016-9617-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10555-016-9617-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51297</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26970968$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Haier, Jörg</creatorcontrib><creatorcontrib>Ströse, Anda</creatorcontrib><creatorcontrib>Matuszcak, Christiane</creatorcontrib><creatorcontrib>Hummel, Richard</creatorcontrib><title>miR clusters target cellular functional complexes by defining their degree of regulatory freedom</title><title>Cancer and metastasis reviews</title><addtitle>Cancer Metastasis Rev</addtitle><addtitle>Cancer Metastasis Rev</addtitle><description>Using the two paralog miR-23∼27∼24 clusters as an example and combining experimental and clinical data in a systematical approach to microRNA (miR) function and dysregulation, a complex picture of their roles in cancer is drawn. Various findings appear to be contradictory to a larger extent and cannot be fully explained by the classical regulatory network models and feedback loops that are mainly considered by one-to-one regulatory interactions of the involved molecules. Here, we propose an extended model of the regulatory role of miRs that, at least, supplements the usually considered single/oligo-target regulation of certain miRs. The cellular availability of the participating miR members in this model reflects an upper hierarchy level of intracellular and extracellular environmental influences, such as neighboring cells, soluble factors, hypoxia, chemotherapeutic drugs, and irradiation, among others. The novel model is based on the understanding of cellular functional complexes, such as for apoptosis, migration, and proliferation. These complexes consist of many regulatory components that can be targeted by miR cluster members to a different extent but may affect the functional complex in different ways. We propose that the final miR-related effect is a result of the possible degree of regulatory freedom provided by the miR effects on the whole functional complex structure. 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Ströse, Anda ; Matuszcak, Christiane ; Hummel, Richard</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c541t-6bf8228e3b5dfd388b58818f7342f17d23bd7de375979ba47b0c5775616e7d213</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Animals</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Cancer Research</topic><topic>Cell Transformation, Neoplastic - genetics</topic><topic>Cell Transformation, Neoplastic - metabolism</topic><topic>Clinical</topic><topic>Computational Biology - methods</topic><topic>Gene Expression Profiling</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Gene Regulatory Networks</topic><topic>Humans</topic><topic>MicroRNAs - genetics</topic><topic>Models, Biological</topic><topic>Multigene Family</topic><topic>Neoplasms - diagnosis</topic><topic>Neoplasms - genetics</topic><topic>Neoplasms - metabolism</topic><topic>Neoplasms - therapy</topic><topic>Oncology</topic><topic>Prognosis</topic><topic>RNA Interference</topic><topic>Transcription, Genetic</topic><topic>Transcriptome</topic><topic>Treatment Outcome</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Haier, Jörg</creatorcontrib><creatorcontrib>Ströse, Anda</creatorcontrib><creatorcontrib>Matuszcak, Christiane</creatorcontrib><creatorcontrib>Hummel, Richard</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Canadian Business & Current Affairs Database</collection><collection>Canadian Business & Current Affairs Database (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>CBCA Reference & Current Events</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><jtitle>Cancer and metastasis reviews</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Haier, Jörg</au><au>Ströse, Anda</au><au>Matuszcak, Christiane</au><au>Hummel, Richard</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>miR clusters target cellular functional complexes by defining their degree of regulatory freedom</atitle><jtitle>Cancer and metastasis reviews</jtitle><stitle>Cancer Metastasis Rev</stitle><addtitle>Cancer Metastasis Rev</addtitle><date>2016-06-01</date><risdate>2016</risdate><volume>35</volume><issue>2</issue><spage>289</spage><epage>322</epage><pages>289-322</pages><issn>0167-7659</issn><eissn>1573-7233</eissn><coden>CMRED4</coden><abstract>Using the two paralog miR-23∼27∼24 clusters as an example and combining experimental and clinical data in a systematical approach to microRNA (miR) function and dysregulation, a complex picture of their roles in cancer is drawn. Various findings appear to be contradictory to a larger extent and cannot be fully explained by the classical regulatory network models and feedback loops that are mainly considered by one-to-one regulatory interactions of the involved molecules. Here, we propose an extended model of the regulatory role of miRs that, at least, supplements the usually considered single/oligo-target regulation of certain miRs. The cellular availability of the participating miR members in this model reflects an upper hierarchy level of intracellular and extracellular environmental influences, such as neighboring cells, soluble factors, hypoxia, chemotherapeutic drugs, and irradiation, among others. The novel model is based on the understanding of cellular functional complexes, such as for apoptosis, migration, and proliferation. These complexes consist of many regulatory components that can be targeted by miR cluster members to a different extent but may affect the functional complex in different ways. We propose that the final miR-related effect is a result of the possible degree of regulatory freedom provided by the miR effects on the whole functional complex structure. This degree of regulatory freedom defines to which extent the cellular functional complex can react in response to regulatory triggers, also understood as sensitization (more regulatory response options) or de-sensitization (less regulatory response options) of the system rather than single molecules.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>26970968</pmid><doi>10.1007/s10555-016-9617-1</doi><tpages>34</tpages></addata></record> |
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subjects | Animals Biomedical and Life Sciences Biomedicine Cancer Research Cell Transformation, Neoplastic - genetics Cell Transformation, Neoplastic - metabolism Clinical Computational Biology - methods Gene Expression Profiling Gene Expression Regulation, Neoplastic Gene Regulatory Networks Humans MicroRNAs - genetics Models, Biological Multigene Family Neoplasms - diagnosis Neoplasms - genetics Neoplasms - metabolism Neoplasms - therapy Oncology Prognosis RNA Interference Transcription, Genetic Transcriptome Treatment Outcome |
title | miR clusters target cellular functional complexes by defining their degree of regulatory freedom |
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