Melanoma proteomics suggests functional differences related to mutational status
Melanoma is the most lethal cutaneous cancer. New drugs have recently appeared; however, not all patients obtain a benefit of these new drugs. For this reason, it is still necessary to characterize melanoma at molecular level. The aim of this study was to explore the molecular differences between me...
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| Veröffentlicht in: | Scientific reports 2019-05, Vol.9 (1), p.7217-7217, Article 7217 |
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| creator | Trilla-Fuertes, Lucía Gámez-Pozo, Angelo Prado-Vázquez, Guillermo Zapater-Moros, Andrea Díaz-Almirón, Mariana Fortes, Claudia Ferrer-Gómez, María López-Vacas, Rocío Parra Blanco, Verónica Márquez-Rodas, Iván Soria, Ainara Fresno Vara, Juan Ángel Espinosa, Enrique |
| description | Melanoma is the most lethal cutaneous cancer. New drugs have recently appeared; however, not all patients obtain a benefit of these new drugs. For this reason, it is still necessary to characterize melanoma at molecular level. The aim of this study was to explore the molecular differences between melanoma tumor subtypes, based on BRAF and NRAS mutational status. Fourteen formalin-fixed, paraffin-embedded melanoma samples were analyzed using a high-throughput proteomics approach, combined with probabilistic graphical models and Flux Balance Analysis, to characterize these differences. Proteomics analyses showed differences in expression of proteins related with fatty acid metabolism, melanogenesis and extracellular space between BRAF mutated and BRAF non-mutated melanoma tumors. Additionally, probabilistic graphical models showed differences between melanoma subgroups at biological processes such as melanogenesis or metabolism. On the other hand, Flux Balance Analysis predicts a higher tumor growth rate in BRAF mutated melanoma samples. In conclusion, differential biological processes between melanomas showing a specific mutational status can be detected using combined proteomics and computational approaches. |
| doi_str_mv | 10.1038/s41598-019-43512-z |
| format | Article |
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New drugs have recently appeared; however, not all patients obtain a benefit of these new drugs. For this reason, it is still necessary to characterize melanoma at molecular level. The aim of this study was to explore the molecular differences between melanoma tumor subtypes, based on BRAF and NRAS mutational status. Fourteen formalin-fixed, paraffin-embedded melanoma samples were analyzed using a high-throughput proteomics approach, combined with probabilistic graphical models and Flux Balance Analysis, to characterize these differences. Proteomics analyses showed differences in expression of proteins related with fatty acid metabolism, melanogenesis and extracellular space between BRAF mutated and BRAF non-mutated melanoma tumors. Additionally, probabilistic graphical models showed differences between melanoma subgroups at biological processes such as melanogenesis or metabolism. On the other hand, Flux Balance Analysis predicts a higher tumor growth rate in BRAF mutated melanoma samples. In conclusion, differential biological processes between melanomas showing a specific mutational status can be detected using combined proteomics and computational approaches.</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/s41598-019-43512-z</identifier><identifier>PMID: 31076580</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/114/2397 ; 631/67 ; 692/4017 ; 82/58 ; Chromatography, High Pressure Liquid ; Computer applications ; Growth rate ; GTP Phosphohydrolases - genetics ; Humanities and Social Sciences ; Humans ; Mass Spectrometry ; Melanoma ; Melanoma - genetics ; Melanoma - metabolism ; Melanoma - pathology ; Membrane Proteins - genetics ; Metabolic Flux Analysis ; Metabolism ; multidisciplinary ; Mutation ; Paraffin ; Proteomics ; Proteomics - methods ; Proto-Oncogene Proteins B-raf - genetics ; Science ; Science (multidisciplinary) ; Skin Neoplasms - genetics ; Skin Neoplasms - metabolism ; Skin Neoplasms - pathology ; Tumors</subject><ispartof>Scientific reports, 2019-05, Vol.9 (1), p.7217-7217, Article 7217</ispartof><rights>The Author(s) 2019</rights><rights>The Author(s) 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-3faa3235e6e368dbd5102b23bb691a9e80c948469a546795f2e4d404c062bdb63</citedby><cites>FETCH-LOGICAL-c474t-3faa3235e6e368dbd5102b23bb691a9e80c948469a546795f2e4d404c062bdb63</cites><orcidid>0000-0002-9675-0783 ; 0000-0003-1527-1252</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/PMC6510784/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510784/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,27901,27902,41096,42165,51551,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31076580$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Trilla-Fuertes, Lucía</creatorcontrib><creatorcontrib>Gámez-Pozo, Angelo</creatorcontrib><creatorcontrib>Prado-Vázquez, Guillermo</creatorcontrib><creatorcontrib>Zapater-Moros, Andrea</creatorcontrib><creatorcontrib>Díaz-Almirón, Mariana</creatorcontrib><creatorcontrib>Fortes, Claudia</creatorcontrib><creatorcontrib>Ferrer-Gómez, María</creatorcontrib><creatorcontrib>López-Vacas, Rocío</creatorcontrib><creatorcontrib>Parra Blanco, Verónica</creatorcontrib><creatorcontrib>Márquez-Rodas, Iván</creatorcontrib><creatorcontrib>Soria, Ainara</creatorcontrib><creatorcontrib>Fresno Vara, Juan Ángel</creatorcontrib><creatorcontrib>Espinosa, Enrique</creatorcontrib><title>Melanoma proteomics suggests functional differences related to mutational status</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><addtitle>Sci Rep</addtitle><description>Melanoma is the most lethal cutaneous cancer. New drugs have recently appeared; however, not all patients obtain a benefit of these new drugs. For this reason, it is still necessary to characterize melanoma at molecular level. The aim of this study was to explore the molecular differences between melanoma tumor subtypes, based on BRAF and NRAS mutational status. Fourteen formalin-fixed, paraffin-embedded melanoma samples were analyzed using a high-throughput proteomics approach, combined with probabilistic graphical models and Flux Balance Analysis, to characterize these differences. Proteomics analyses showed differences in expression of proteins related with fatty acid metabolism, melanogenesis and extracellular space between BRAF mutated and BRAF non-mutated melanoma tumors. Additionally, probabilistic graphical models showed differences between melanoma subgroups at biological processes such as melanogenesis or metabolism. On the other hand, Flux Balance Analysis predicts a higher tumor growth rate in BRAF mutated melanoma samples. In conclusion, differential biological processes between melanomas showing a specific mutational status can be detected using combined proteomics and computational approaches.</description><subject>631/114/2397</subject><subject>631/67</subject><subject>692/4017</subject><subject>82/58</subject><subject>Chromatography, High Pressure Liquid</subject><subject>Computer applications</subject><subject>Growth rate</subject><subject>GTP Phosphohydrolases - genetics</subject><subject>Humanities and Social Sciences</subject><subject>Humans</subject><subject>Mass Spectrometry</subject><subject>Melanoma</subject><subject>Melanoma - genetics</subject><subject>Melanoma - metabolism</subject><subject>Melanoma - pathology</subject><subject>Membrane Proteins - genetics</subject><subject>Metabolic Flux Analysis</subject><subject>Metabolism</subject><subject>multidisciplinary</subject><subject>Mutation</subject><subject>Paraffin</subject><subject>Proteomics</subject><subject>Proteomics - methods</subject><subject>Proto-Oncogene Proteins B-raf - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Trilla-Fuertes, Lucía</au><au>Gámez-Pozo, Angelo</au><au>Prado-Vázquez, Guillermo</au><au>Zapater-Moros, Andrea</au><au>Díaz-Almirón, Mariana</au><au>Fortes, Claudia</au><au>Ferrer-Gómez, María</au><au>López-Vacas, Rocío</au><au>Parra Blanco, Verónica</au><au>Márquez-Rodas, Iván</au><au>Soria, Ainara</au><au>Fresno Vara, Juan Ángel</au><au>Espinosa, Enrique</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Melanoma proteomics suggests functional differences related to mutational status</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2019-05-10</date><risdate>2019</risdate><volume>9</volume><issue>1</issue><spage>7217</spage><epage>7217</epage><pages>7217-7217</pages><artnum>7217</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><abstract>Melanoma is the most lethal cutaneous cancer. New drugs have recently appeared; however, not all patients obtain a benefit of these new drugs. For this reason, it is still necessary to characterize melanoma at molecular level. The aim of this study was to explore the molecular differences between melanoma tumor subtypes, based on BRAF and NRAS mutational status. Fourteen formalin-fixed, paraffin-embedded melanoma samples were analyzed using a high-throughput proteomics approach, combined with probabilistic graphical models and Flux Balance Analysis, to characterize these differences. Proteomics analyses showed differences in expression of proteins related with fatty acid metabolism, melanogenesis and extracellular space between BRAF mutated and BRAF non-mutated melanoma tumors. Additionally, probabilistic graphical models showed differences between melanoma subgroups at biological processes such as melanogenesis or metabolism. On the other hand, Flux Balance Analysis predicts a higher tumor growth rate in BRAF mutated melanoma samples. In conclusion, differential biological processes between melanomas showing a specific mutational status can be detected using combined proteomics and computational approaches.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>31076580</pmid><doi>10.1038/s41598-019-43512-z</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-9675-0783</orcidid><orcidid>https://orcid.org/0000-0003-1527-1252</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | 631/114/2397 631/67 692/4017 82/58 Chromatography, High Pressure Liquid Computer applications Growth rate GTP Phosphohydrolases - genetics Humanities and Social Sciences Humans Mass Spectrometry Melanoma Melanoma - genetics Melanoma - metabolism Melanoma - pathology Membrane Proteins - genetics Metabolic Flux Analysis Metabolism multidisciplinary Mutation Paraffin Proteomics Proteomics - methods Proto-Oncogene Proteins B-raf - genetics Science Science (multidisciplinary) Skin Neoplasms - genetics Skin Neoplasms - metabolism Skin Neoplasms - pathology Tumors |
| title | Melanoma proteomics suggests functional differences related to mutational status |
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