Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors
Abstract Novel therapies are undergoing clinical trials, for example, the Hsp90 inhibitor, XL888, in combination with BRAF inhibitors for the treatment of therapy‐resistant melanomas. Unfortunately, our data show that this combination elicits a heterogeneous response in a panel of melanoma cell line...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Azimi, Alireza [verfasserIn] Caramuta, Stefano [verfasserIn] Seashore‐Ludlow, Brinton [verfasserIn] Boström, Johan [verfasserIn] Robinson, Jonathan L [verfasserIn] Edfors, Fredrik [verfasserIn] Tuominen, Rainer [verfasserIn] Kemper, Kristel [verfasserIn] Krijgsman, Oscar [verfasserIn] Peeper, Daniel S [verfasserIn] Nielsen, Jens [verfasserIn] Hansson, Johan [verfasserIn] Egyhazi Brage, Suzanne [verfasserIn] Altun, Mikael [verfasserIn] Uhlen, Mathias [verfasserIn] Maddalo, Gianluca [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2018 |
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| Übergeordnetes Werk: |
Enthalten in: Molecular Systems Biology - Nature Publishing Group UK, 2023, 14(2018), 3 vom: 05. März |
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| Übergeordnetes Werk: |
volume:14 ; year:2018 ; number:3 ; day:05 ; month:03 |
| Links: |
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| DOI / URN: |
10.15252/msb.20177858 |
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| Katalog-ID: |
SPR058092811 |
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| 520 | |a Abstract Novel therapies are undergoing clinical trials, for example, the Hsp90 inhibitor, XL888, in combination with BRAF inhibitors for the treatment of therapy‐resistant melanomas. Unfortunately, our data show that this combination elicits a heterogeneous response in a panel of melanoma cell lines including PDX‐derived models. We sought to understand the mechanisms underlying the differential responses and suggest a patient stratification strategy. Thermal proteome profiling (TPP) identified the protein targets of XL888 in a pair of sensitive and unresponsive cell lines. Unbiased proteomics and phosphoproteomics analyses identified CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors and its expression is regulated by the transcription factor MITF upon XL888 treatment. The CDK2 inhibitor, dinaciclib, attenuated resistance to both classes of inhibitors and combinations thereof. Notably, we found that MITF expression correlates with CDK2 upregulation in patients; thus, dinaciclib would warrant consideration for treatment of patients unresponsive to BRAF‐MEK and/or Hsp90 inhibitors and/or harboring MITF amplification/overexpression. | ||
| 520 | |a Synopsis Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. Proteome and phosphoproteome profiles of resistant versus sensitive melanoma cell lines were compared upon BRAFi, Hsp90i and combination thereof.Hsp90i resistance is driven by CDK2 upregulation, mediated by MITF, in melanoma cells.CDK2i, i.e. dinaciclib, overcomes BRAFi and Hsp90i resistance in melanoma cells. | ||
| 520 | |a Graphical Abstract Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. | ||
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| 700 | 1 | |a Seashore‐Ludlow, Brinton |e verfasserin |4 aut | |
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10.15252/msb.20177858 doi (DE-627)SPR058092811 (SPR)msb.20177858-e DE-627 ger DE-627 rakwb eng Azimi, Alireza verfasserin aut Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2018 Abstract Novel therapies are undergoing clinical trials, for example, the Hsp90 inhibitor, XL888, in combination with BRAF inhibitors for the treatment of therapy‐resistant melanomas. Unfortunately, our data show that this combination elicits a heterogeneous response in a panel of melanoma cell lines including PDX‐derived models. We sought to understand the mechanisms underlying the differential responses and suggest a patient stratification strategy. Thermal proteome profiling (TPP) identified the protein targets of XL888 in a pair of sensitive and unresponsive cell lines. Unbiased proteomics and phosphoproteomics analyses identified CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors and its expression is regulated by the transcription factor MITF upon XL888 treatment. The CDK2 inhibitor, dinaciclib, attenuated resistance to both classes of inhibitors and combinations thereof. Notably, we found that MITF expression correlates with CDK2 upregulation in patients; thus, dinaciclib would warrant consideration for treatment of patients unresponsive to BRAF‐MEK and/or Hsp90 inhibitors and/or harboring MITF amplification/overexpression. Synopsis Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. Proteome and phosphoproteome profiles of resistant versus sensitive melanoma cell lines were compared upon BRAFi, Hsp90i and combination thereof.Hsp90i resistance is driven by CDK2 upregulation, mediated by MITF, in melanoma cells.CDK2i, i.e. dinaciclib, overcomes BRAFi and Hsp90i resistance in melanoma cells. Graphical Abstract Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. CDK2 (dpeaa)DE-He213 Hsp90 and BRAF inhibitors (dpeaa)DE-He213 melanoma (dpeaa)DE-He213 MITF (dpeaa)DE-He213 proteomics (dpeaa)DE-He213 Caramuta, Stefano verfasserin aut Seashore‐Ludlow, Brinton verfasserin aut Boström, Johan verfasserin (orcid)0000-0001-5252-4023 aut Robinson, Jonathan L verfasserin aut Edfors, Fredrik verfasserin aut Tuominen, Rainer verfasserin aut Kemper, Kristel verfasserin aut Krijgsman, Oscar verfasserin (orcid)0000-0003-0825-3291 aut Peeper, Daniel S verfasserin (orcid)0000-0003-1293-3177 aut Nielsen, Jens verfasserin (orcid)0000-0002-9955-6003 aut Hansson, Johan verfasserin aut Egyhazi Brage, Suzanne verfasserin aut Altun, Mikael verfasserin (orcid)0000-0002-6937-6124 aut Uhlen, Mathias verfasserin (orcid)0000-0002-4858-8056 aut Maddalo, Gianluca verfasserin (orcid)0000-0003-2297-6488 aut Enthalten in Molecular Systems Biology Nature Publishing Group UK, 2023 14(2018), 3 vom: 05. März (DE-627)490536905 (DE-600)2193510-5 1744-4292 nnns volume:14 year:2018 number:3 day:05 month:03 https://dx.doi.org/10.15252/msb.20177858 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 14 2018 3 05 03 |
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10.15252/msb.20177858 doi (DE-627)SPR058092811 (SPR)msb.20177858-e DE-627 ger DE-627 rakwb eng Azimi, Alireza verfasserin aut Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2018 Abstract Novel therapies are undergoing clinical trials, for example, the Hsp90 inhibitor, XL888, in combination with BRAF inhibitors for the treatment of therapy‐resistant melanomas. Unfortunately, our data show that this combination elicits a heterogeneous response in a panel of melanoma cell lines including PDX‐derived models. We sought to understand the mechanisms underlying the differential responses and suggest a patient stratification strategy. Thermal proteome profiling (TPP) identified the protein targets of XL888 in a pair of sensitive and unresponsive cell lines. Unbiased proteomics and phosphoproteomics analyses identified CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors and its expression is regulated by the transcription factor MITF upon XL888 treatment. The CDK2 inhibitor, dinaciclib, attenuated resistance to both classes of inhibitors and combinations thereof. Notably, we found that MITF expression correlates with CDK2 upregulation in patients; thus, dinaciclib would warrant consideration for treatment of patients unresponsive to BRAF‐MEK and/or Hsp90 inhibitors and/or harboring MITF amplification/overexpression. Synopsis Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. Proteome and phosphoproteome profiles of resistant versus sensitive melanoma cell lines were compared upon BRAFi, Hsp90i and combination thereof.Hsp90i resistance is driven by CDK2 upregulation, mediated by MITF, in melanoma cells.CDK2i, i.e. dinaciclib, overcomes BRAFi and Hsp90i resistance in melanoma cells. Graphical Abstract Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. CDK2 (dpeaa)DE-He213 Hsp90 and BRAF inhibitors (dpeaa)DE-He213 melanoma (dpeaa)DE-He213 MITF (dpeaa)DE-He213 proteomics (dpeaa)DE-He213 Caramuta, Stefano verfasserin aut Seashore‐Ludlow, Brinton verfasserin aut Boström, Johan verfasserin (orcid)0000-0001-5252-4023 aut Robinson, Jonathan L verfasserin aut Edfors, Fredrik verfasserin aut Tuominen, Rainer verfasserin aut Kemper, Kristel verfasserin aut Krijgsman, Oscar verfasserin (orcid)0000-0003-0825-3291 aut Peeper, Daniel S verfasserin (orcid)0000-0003-1293-3177 aut Nielsen, Jens verfasserin (orcid)0000-0002-9955-6003 aut Hansson, Johan verfasserin aut Egyhazi Brage, Suzanne verfasserin aut Altun, Mikael verfasserin (orcid)0000-0002-6937-6124 aut Uhlen, Mathias verfasserin (orcid)0000-0002-4858-8056 aut Maddalo, Gianluca verfasserin (orcid)0000-0003-2297-6488 aut Enthalten in Molecular Systems Biology Nature Publishing Group UK, 2023 14(2018), 3 vom: 05. März (DE-627)490536905 (DE-600)2193510-5 1744-4292 nnns volume:14 year:2018 number:3 day:05 month:03 https://dx.doi.org/10.15252/msb.20177858 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 14 2018 3 05 03 |
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10.15252/msb.20177858 doi (DE-627)SPR058092811 (SPR)msb.20177858-e DE-627 ger DE-627 rakwb eng Azimi, Alireza verfasserin aut Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2018 Abstract Novel therapies are undergoing clinical trials, for example, the Hsp90 inhibitor, XL888, in combination with BRAF inhibitors for the treatment of therapy‐resistant melanomas. Unfortunately, our data show that this combination elicits a heterogeneous response in a panel of melanoma cell lines including PDX‐derived models. We sought to understand the mechanisms underlying the differential responses and suggest a patient stratification strategy. Thermal proteome profiling (TPP) identified the protein targets of XL888 in a pair of sensitive and unresponsive cell lines. Unbiased proteomics and phosphoproteomics analyses identified CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors and its expression is regulated by the transcription factor MITF upon XL888 treatment. The CDK2 inhibitor, dinaciclib, attenuated resistance to both classes of inhibitors and combinations thereof. Notably, we found that MITF expression correlates with CDK2 upregulation in patients; thus, dinaciclib would warrant consideration for treatment of patients unresponsive to BRAF‐MEK and/or Hsp90 inhibitors and/or harboring MITF amplification/overexpression. Synopsis Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. Proteome and phosphoproteome profiles of resistant versus sensitive melanoma cell lines were compared upon BRAFi, Hsp90i and combination thereof.Hsp90i resistance is driven by CDK2 upregulation, mediated by MITF, in melanoma cells.CDK2i, i.e. dinaciclib, overcomes BRAFi and Hsp90i resistance in melanoma cells. Graphical Abstract Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. CDK2 (dpeaa)DE-He213 Hsp90 and BRAF inhibitors (dpeaa)DE-He213 melanoma (dpeaa)DE-He213 MITF (dpeaa)DE-He213 proteomics (dpeaa)DE-He213 Caramuta, Stefano verfasserin aut Seashore‐Ludlow, Brinton verfasserin aut Boström, Johan verfasserin (orcid)0000-0001-5252-4023 aut Robinson, Jonathan L verfasserin aut Edfors, Fredrik verfasserin aut Tuominen, Rainer verfasserin aut Kemper, Kristel verfasserin aut Krijgsman, Oscar verfasserin (orcid)0000-0003-0825-3291 aut Peeper, Daniel S verfasserin (orcid)0000-0003-1293-3177 aut Nielsen, Jens verfasserin (orcid)0000-0002-9955-6003 aut Hansson, Johan verfasserin aut Egyhazi Brage, Suzanne verfasserin aut Altun, Mikael verfasserin (orcid)0000-0002-6937-6124 aut Uhlen, Mathias verfasserin (orcid)0000-0002-4858-8056 aut Maddalo, Gianluca verfasserin (orcid)0000-0003-2297-6488 aut Enthalten in Molecular Systems Biology Nature Publishing Group UK, 2023 14(2018), 3 vom: 05. März (DE-627)490536905 (DE-600)2193510-5 1744-4292 nnns volume:14 year:2018 number:3 day:05 month:03 https://dx.doi.org/10.15252/msb.20177858 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 14 2018 3 05 03 |
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10.15252/msb.20177858 doi (DE-627)SPR058092811 (SPR)msb.20177858-e DE-627 ger DE-627 rakwb eng Azimi, Alireza verfasserin aut Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2018 Abstract Novel therapies are undergoing clinical trials, for example, the Hsp90 inhibitor, XL888, in combination with BRAF inhibitors for the treatment of therapy‐resistant melanomas. Unfortunately, our data show that this combination elicits a heterogeneous response in a panel of melanoma cell lines including PDX‐derived models. We sought to understand the mechanisms underlying the differential responses and suggest a patient stratification strategy. Thermal proteome profiling (TPP) identified the protein targets of XL888 in a pair of sensitive and unresponsive cell lines. Unbiased proteomics and phosphoproteomics analyses identified CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors and its expression is regulated by the transcription factor MITF upon XL888 treatment. The CDK2 inhibitor, dinaciclib, attenuated resistance to both classes of inhibitors and combinations thereof. Notably, we found that MITF expression correlates with CDK2 upregulation in patients; thus, dinaciclib would warrant consideration for treatment of patients unresponsive to BRAF‐MEK and/or Hsp90 inhibitors and/or harboring MITF amplification/overexpression. Synopsis Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. Proteome and phosphoproteome profiles of resistant versus sensitive melanoma cell lines were compared upon BRAFi, Hsp90i and combination thereof.Hsp90i resistance is driven by CDK2 upregulation, mediated by MITF, in melanoma cells.CDK2i, i.e. dinaciclib, overcomes BRAFi and Hsp90i resistance in melanoma cells. Graphical Abstract Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. CDK2 (dpeaa)DE-He213 Hsp90 and BRAF inhibitors (dpeaa)DE-He213 melanoma (dpeaa)DE-He213 MITF (dpeaa)DE-He213 proteomics (dpeaa)DE-He213 Caramuta, Stefano verfasserin aut Seashore‐Ludlow, Brinton verfasserin aut Boström, Johan verfasserin (orcid)0000-0001-5252-4023 aut Robinson, Jonathan L verfasserin aut Edfors, Fredrik verfasserin aut Tuominen, Rainer verfasserin aut Kemper, Kristel verfasserin aut Krijgsman, Oscar verfasserin (orcid)0000-0003-0825-3291 aut Peeper, Daniel S verfasserin (orcid)0000-0003-1293-3177 aut Nielsen, Jens verfasserin (orcid)0000-0002-9955-6003 aut Hansson, Johan verfasserin aut Egyhazi Brage, Suzanne verfasserin aut Altun, Mikael verfasserin (orcid)0000-0002-6937-6124 aut Uhlen, Mathias verfasserin (orcid)0000-0002-4858-8056 aut Maddalo, Gianluca verfasserin (orcid)0000-0003-2297-6488 aut Enthalten in Molecular Systems Biology Nature Publishing Group UK, 2023 14(2018), 3 vom: 05. März (DE-627)490536905 (DE-600)2193510-5 1744-4292 nnns volume:14 year:2018 number:3 day:05 month:03 https://dx.doi.org/10.15252/msb.20177858 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 14 2018 3 05 03 |
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10.15252/msb.20177858 doi (DE-627)SPR058092811 (SPR)msb.20177858-e DE-627 ger DE-627 rakwb eng Azimi, Alireza verfasserin aut Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2018 Abstract Novel therapies are undergoing clinical trials, for example, the Hsp90 inhibitor, XL888, in combination with BRAF inhibitors for the treatment of therapy‐resistant melanomas. Unfortunately, our data show that this combination elicits a heterogeneous response in a panel of melanoma cell lines including PDX‐derived models. We sought to understand the mechanisms underlying the differential responses and suggest a patient stratification strategy. Thermal proteome profiling (TPP) identified the protein targets of XL888 in a pair of sensitive and unresponsive cell lines. Unbiased proteomics and phosphoproteomics analyses identified CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors and its expression is regulated by the transcription factor MITF upon XL888 treatment. The CDK2 inhibitor, dinaciclib, attenuated resistance to both classes of inhibitors and combinations thereof. Notably, we found that MITF expression correlates with CDK2 upregulation in patients; thus, dinaciclib would warrant consideration for treatment of patients unresponsive to BRAF‐MEK and/or Hsp90 inhibitors and/or harboring MITF amplification/overexpression. Synopsis Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. Proteome and phosphoproteome profiles of resistant versus sensitive melanoma cell lines were compared upon BRAFi, Hsp90i and combination thereof.Hsp90i resistance is driven by CDK2 upregulation, mediated by MITF, in melanoma cells.CDK2i, i.e. dinaciclib, overcomes BRAFi and Hsp90i resistance in melanoma cells. Graphical Abstract Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. CDK2 (dpeaa)DE-He213 Hsp90 and BRAF inhibitors (dpeaa)DE-He213 melanoma (dpeaa)DE-He213 MITF (dpeaa)DE-He213 proteomics (dpeaa)DE-He213 Caramuta, Stefano verfasserin aut Seashore‐Ludlow, Brinton verfasserin aut Boström, Johan verfasserin (orcid)0000-0001-5252-4023 aut Robinson, Jonathan L verfasserin aut Edfors, Fredrik verfasserin aut Tuominen, Rainer verfasserin aut Kemper, Kristel verfasserin aut Krijgsman, Oscar verfasserin (orcid)0000-0003-0825-3291 aut Peeper, Daniel S verfasserin (orcid)0000-0003-1293-3177 aut Nielsen, Jens verfasserin (orcid)0000-0002-9955-6003 aut Hansson, Johan verfasserin aut Egyhazi Brage, Suzanne verfasserin aut Altun, Mikael verfasserin (orcid)0000-0002-6937-6124 aut Uhlen, Mathias verfasserin (orcid)0000-0002-4858-8056 aut Maddalo, Gianluca verfasserin (orcid)0000-0003-2297-6488 aut Enthalten in Molecular Systems Biology Nature Publishing Group UK, 2023 14(2018), 3 vom: 05. März (DE-627)490536905 (DE-600)2193510-5 1744-4292 nnns volume:14 year:2018 number:3 day:05 month:03 https://dx.doi.org/10.15252/msb.20177858 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 14 2018 3 05 03 |
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Enthalten in Molecular Systems Biology 14(2018), 3 vom: 05. März volume:14 year:2018 number:3 day:05 month:03 |
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Enthalten in Molecular Systems Biology 14(2018), 3 vom: 05. März volume:14 year:2018 number:3 day:05 month:03 |
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CDK2 Hsp90 and BRAF inhibitors melanoma MITF proteomics |
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Azimi, Alireza @@aut@@ Caramuta, Stefano @@aut@@ Seashore‐Ludlow, Brinton @@aut@@ Boström, Johan @@aut@@ Robinson, Jonathan L @@aut@@ Edfors, Fredrik @@aut@@ Tuominen, Rainer @@aut@@ Kemper, Kristel @@aut@@ Krijgsman, Oscar @@aut@@ Peeper, Daniel S @@aut@@ Nielsen, Jens @@aut@@ Hansson, Johan @@aut@@ Egyhazi Brage, Suzanne @@aut@@ Altun, Mikael @@aut@@ Uhlen, Mathias @@aut@@ Maddalo, Gianluca @@aut@@ |
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Unfortunately, our data show that this combination elicits a heterogeneous response in a panel of melanoma cell lines including PDX‐derived models. We sought to understand the mechanisms underlying the differential responses and suggest a patient stratification strategy. Thermal proteome profiling (TPP) identified the protein targets of XL888 in a pair of sensitive and unresponsive cell lines. Unbiased proteomics and phosphoproteomics analyses identified CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors and its expression is regulated by the transcription factor MITF upon XL888 treatment. The CDK2 inhibitor, dinaciclib, attenuated resistance to both classes of inhibitors and combinations thereof. Notably, we found that MITF expression correlates with CDK2 upregulation in patients; thus, dinaciclib would warrant consideration for treatment of patients unresponsive to BRAF‐MEK and/or Hsp90 inhibitors and/or harboring MITF amplification/overexpression.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Synopsis Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. Proteome and phosphoproteome profiles of resistant versus sensitive melanoma cell lines were compared upon BRAFi, Hsp90i and combination thereof.Hsp90i resistance is driven by CDK2 upregulation, mediated by MITF, in melanoma cells.CDK2i, i.e. dinaciclib, overcomes BRAFi and Hsp90i resistance in melanoma cells.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Graphical Abstract Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. 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Azimi, Alireza |
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Azimi, Alireza misc CDK2 misc Hsp90 and BRAF inhibitors misc melanoma misc MITF misc proteomics Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors |
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Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors CDK2 (dpeaa)DE-He213 Hsp90 and BRAF inhibitors (dpeaa)DE-He213 melanoma (dpeaa)DE-He213 MITF (dpeaa)DE-He213 proteomics (dpeaa)DE-He213 |
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Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors |
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Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors |
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Azimi, Alireza Caramuta, Stefano Seashore‐Ludlow, Brinton Boström, Johan Robinson, Jonathan L Edfors, Fredrik Tuominen, Rainer Kemper, Kristel Krijgsman, Oscar Peeper, Daniel S Nielsen, Jens Hansson, Johan Egyhazi Brage, Suzanne Altun, Mikael Uhlen, Mathias Maddalo, Gianluca |
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Azimi, Alireza |
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10.15252/msb.20177858 |
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targeting cdk2 overcomes melanoma resistance against braf and hsp90 inhibitors |
| title_auth |
Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors |
| abstract |
Abstract Novel therapies are undergoing clinical trials, for example, the Hsp90 inhibitor, XL888, in combination with BRAF inhibitors for the treatment of therapy‐resistant melanomas. Unfortunately, our data show that this combination elicits a heterogeneous response in a panel of melanoma cell lines including PDX‐derived models. We sought to understand the mechanisms underlying the differential responses and suggest a patient stratification strategy. Thermal proteome profiling (TPP) identified the protein targets of XL888 in a pair of sensitive and unresponsive cell lines. Unbiased proteomics and phosphoproteomics analyses identified CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors and its expression is regulated by the transcription factor MITF upon XL888 treatment. The CDK2 inhibitor, dinaciclib, attenuated resistance to both classes of inhibitors and combinations thereof. Notably, we found that MITF expression correlates with CDK2 upregulation in patients; thus, dinaciclib would warrant consideration for treatment of patients unresponsive to BRAF‐MEK and/or Hsp90 inhibitors and/or harboring MITF amplification/overexpression. Synopsis Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. Proteome and phosphoproteome profiles of resistant versus sensitive melanoma cell lines were compared upon BRAFi, Hsp90i and combination thereof.Hsp90i resistance is driven by CDK2 upregulation, mediated by MITF, in melanoma cells.CDK2i, i.e. dinaciclib, overcomes BRAFi and Hsp90i resistance in melanoma cells. Graphical Abstract Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. © The Author(s) 2018 |
| abstractGer |
Abstract Novel therapies are undergoing clinical trials, for example, the Hsp90 inhibitor, XL888, in combination with BRAF inhibitors for the treatment of therapy‐resistant melanomas. Unfortunately, our data show that this combination elicits a heterogeneous response in a panel of melanoma cell lines including PDX‐derived models. We sought to understand the mechanisms underlying the differential responses and suggest a patient stratification strategy. Thermal proteome profiling (TPP) identified the protein targets of XL888 in a pair of sensitive and unresponsive cell lines. Unbiased proteomics and phosphoproteomics analyses identified CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors and its expression is regulated by the transcription factor MITF upon XL888 treatment. The CDK2 inhibitor, dinaciclib, attenuated resistance to both classes of inhibitors and combinations thereof. Notably, we found that MITF expression correlates with CDK2 upregulation in patients; thus, dinaciclib would warrant consideration for treatment of patients unresponsive to BRAF‐MEK and/or Hsp90 inhibitors and/or harboring MITF amplification/overexpression. Synopsis Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. Proteome and phosphoproteome profiles of resistant versus sensitive melanoma cell lines were compared upon BRAFi, Hsp90i and combination thereof.Hsp90i resistance is driven by CDK2 upregulation, mediated by MITF, in melanoma cells.CDK2i, i.e. dinaciclib, overcomes BRAFi and Hsp90i resistance in melanoma cells. Graphical Abstract Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. © The Author(s) 2018 |
| abstract_unstemmed |
Abstract Novel therapies are undergoing clinical trials, for example, the Hsp90 inhibitor, XL888, in combination with BRAF inhibitors for the treatment of therapy‐resistant melanomas. Unfortunately, our data show that this combination elicits a heterogeneous response in a panel of melanoma cell lines including PDX‐derived models. We sought to understand the mechanisms underlying the differential responses and suggest a patient stratification strategy. Thermal proteome profiling (TPP) identified the protein targets of XL888 in a pair of sensitive and unresponsive cell lines. Unbiased proteomics and phosphoproteomics analyses identified CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors and its expression is regulated by the transcription factor MITF upon XL888 treatment. The CDK2 inhibitor, dinaciclib, attenuated resistance to both classes of inhibitors and combinations thereof. Notably, we found that MITF expression correlates with CDK2 upregulation in patients; thus, dinaciclib would warrant consideration for treatment of patients unresponsive to BRAF‐MEK and/or Hsp90 inhibitors and/or harboring MITF amplification/overexpression. Synopsis Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. Proteome and phosphoproteome profiles of resistant versus sensitive melanoma cell lines were compared upon BRAFi, Hsp90i and combination thereof.Hsp90i resistance is driven by CDK2 upregulation, mediated by MITF, in melanoma cells.CDK2i, i.e. dinaciclib, overcomes BRAFi and Hsp90i resistance in melanoma cells. Graphical Abstract Proteomics and phosphoproteomics analyses in melanoma cells identify CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors. Its expression is regulated by the transcription factor MITF and dinaciclib, a CDK2 inhibitor, overcomes the resistance to both classes of inhibitors. © The Author(s) 2018 |
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Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors |
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Caramuta, Stefano Seashore‐Ludlow, Brinton Boström, Johan Robinson, Jonathan L Edfors, Fredrik Tuominen, Rainer Kemper, Kristel Krijgsman, Oscar Peeper, Daniel S Nielsen, Jens Hansson, Johan Egyhazi Brage, Suzanne Altun, Mikael Uhlen, Mathias Maddalo, Gianluca |
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Caramuta, Stefano Seashore‐Ludlow, Brinton Boström, Johan Robinson, Jonathan L Edfors, Fredrik Tuominen, Rainer Kemper, Kristel Krijgsman, Oscar Peeper, Daniel S Nielsen, Jens Hansson, Johan Egyhazi Brage, Suzanne Altun, Mikael Uhlen, Mathias Maddalo, Gianluca |
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| score |
7.4004602 |