A nine-gene signature predicting clinical outcome in cutaneous melanoma
Purpose Current histopathological staging of cutaneous melanoma is limited in predicting outcome, and complementary molecular markers are not available for prognostic assessment. The purpose of this study was to identify a quantitative gene expression score in primary melanoma and adjacent stroma th...
Ausführliche Beschreibung
Autor*in: |
Brunner, G. [verfasserIn] Reitz, M. [verfasserIn] Heinecke, A. [verfasserIn] Lippold, A. [verfasserIn] Berking, C. [verfasserIn] Suter, L. [verfasserIn] Atzpodien, J. [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2012 |
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Übergeordnetes Werk: |
Enthalten in: Journal of cancer research and clinical oncology - Berlin : Springer, 1904, 139(2012), 2 vom: 09. Okt., Seite 249-258 |
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Übergeordnetes Werk: |
volume:139 ; year:2012 ; number:2 ; day:09 ; month:10 ; pages:249-258 |
Links: |
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DOI / URN: |
10.1007/s00432-012-1322-z |
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Katalog-ID: |
SPR005850754 |
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100 | 1 | |a Brunner, G. |e verfasserin |4 aut | |
245 | 1 | 2 | |a A nine-gene signature predicting clinical outcome in cutaneous melanoma |
264 | 1 | |c 2012 | |
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520 | |a Purpose Current histopathological staging of cutaneous melanoma is limited in predicting outcome, and complementary molecular markers are not available for prognostic assessment. The purpose of this study was to identify a quantitative gene expression score in primary melanoma and adjacent stroma that can be used in clinical routine to define, at the time of diagnosis, patient risk and need for therapy. Methods Expression of 92 candidate genes was quantified by RT-PCR in a training subset of 38 fresh-frozen melanomas. Correlation of gene expression with overall survival (OS) was evaluated using univariate regression analysis. Expression analysis of 11 prognostically significant genes in the complete training cohort of 91 melanomas yielded nine genes predicting outcome. Results were confirmed in a validation cohort of 44 melanomas. Results We identified a nine-gene signature associated with OS and distant metastasis-free survival. The signature comprised risk and protective genes and was applicable to melanoma samples across all AJCC stages in the presence of adjacent stroma. A signature-based risk score predicted OS in both the training cohort (multivariate regression analysis: p = 0.0004, hazard ratio 3.83) and the validation cohort, independently of AJCC staging. Consequently, when combining risk score and AJCC staging, patients in the AJCC intermediate-risk stages, IIA/B or IIIA, were re-classified either to low or high risk. Conclusions Our gene score defines patient risk and need for therapy in melanoma. The score has the potential to be utilized in clinical routine, since it is quantitative, robust, simple, and independent of AJCC stage and sample purity. | ||
650 | 4 | |a Melanoma |7 (dpeaa)DE-He213 | |
650 | 4 | |a Prognosis |7 (dpeaa)DE-He213 | |
650 | 4 | |a Gene signature |7 (dpeaa)DE-He213 | |
650 | 4 | |a Gene expression profiling |7 (dpeaa)DE-He213 | |
650 | 4 | |a RT-PCR |7 (dpeaa)DE-He213 | |
700 | 1 | |a Reitz, M. |e verfasserin |4 aut | |
700 | 1 | |a Heinecke, A. |e verfasserin |4 aut | |
700 | 1 | |a Lippold, A. |e verfasserin |4 aut | |
700 | 1 | |a Berking, C. |e verfasserin |4 aut | |
700 | 1 | |a Suter, L. |e verfasserin |4 aut | |
700 | 1 | |a Atzpodien, J. |e verfasserin |4 aut | |
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10.1007/s00432-012-1322-z doi (DE-627)SPR005850754 (SPR)s00432-012-1322-z-e DE-627 ger DE-627 rakwb eng 610 ASE 44.81 bkl Brunner, G. verfasserin aut A nine-gene signature predicting clinical outcome in cutaneous melanoma 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose Current histopathological staging of cutaneous melanoma is limited in predicting outcome, and complementary molecular markers are not available for prognostic assessment. The purpose of this study was to identify a quantitative gene expression score in primary melanoma and adjacent stroma that can be used in clinical routine to define, at the time of diagnosis, patient risk and need for therapy. Methods Expression of 92 candidate genes was quantified by RT-PCR in a training subset of 38 fresh-frozen melanomas. Correlation of gene expression with overall survival (OS) was evaluated using univariate regression analysis. Expression analysis of 11 prognostically significant genes in the complete training cohort of 91 melanomas yielded nine genes predicting outcome. Results were confirmed in a validation cohort of 44 melanomas. Results We identified a nine-gene signature associated with OS and distant metastasis-free survival. The signature comprised risk and protective genes and was applicable to melanoma samples across all AJCC stages in the presence of adjacent stroma. A signature-based risk score predicted OS in both the training cohort (multivariate regression analysis: p = 0.0004, hazard ratio 3.83) and the validation cohort, independently of AJCC staging. Consequently, when combining risk score and AJCC staging, patients in the AJCC intermediate-risk stages, IIA/B or IIIA, were re-classified either to low or high risk. Conclusions Our gene score defines patient risk and need for therapy in melanoma. The score has the potential to be utilized in clinical routine, since it is quantitative, robust, simple, and independent of AJCC stage and sample purity. Melanoma (dpeaa)DE-He213 Prognosis (dpeaa)DE-He213 Gene signature (dpeaa)DE-He213 Gene expression profiling (dpeaa)DE-He213 RT-PCR (dpeaa)DE-He213 Reitz, M. verfasserin aut Heinecke, A. verfasserin aut Lippold, A. verfasserin aut Berking, C. verfasserin aut Suter, L. verfasserin aut Atzpodien, J. verfasserin aut Enthalten in Journal of cancer research and clinical oncology Berlin : Springer, 1904 139(2012), 2 vom: 09. Okt., Seite 249-258 (DE-627)253769515 (DE-600)1459285-X 1432-1335 nnns volume:139 year:2012 number:2 day:09 month:10 pages:249-258 https://dx.doi.org/10.1007/s00432-012-1322-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 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_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 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_4393 GBV_ILN_4700 44.81 ASE AR 139 2012 2 09 10 249-258 |
spelling |
10.1007/s00432-012-1322-z doi (DE-627)SPR005850754 (SPR)s00432-012-1322-z-e DE-627 ger DE-627 rakwb eng 610 ASE 44.81 bkl Brunner, G. verfasserin aut A nine-gene signature predicting clinical outcome in cutaneous melanoma 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose Current histopathological staging of cutaneous melanoma is limited in predicting outcome, and complementary molecular markers are not available for prognostic assessment. The purpose of this study was to identify a quantitative gene expression score in primary melanoma and adjacent stroma that can be used in clinical routine to define, at the time of diagnosis, patient risk and need for therapy. Methods Expression of 92 candidate genes was quantified by RT-PCR in a training subset of 38 fresh-frozen melanomas. Correlation of gene expression with overall survival (OS) was evaluated using univariate regression analysis. Expression analysis of 11 prognostically significant genes in the complete training cohort of 91 melanomas yielded nine genes predicting outcome. Results were confirmed in a validation cohort of 44 melanomas. Results We identified a nine-gene signature associated with OS and distant metastasis-free survival. The signature comprised risk and protective genes and was applicable to melanoma samples across all AJCC stages in the presence of adjacent stroma. A signature-based risk score predicted OS in both the training cohort (multivariate regression analysis: p = 0.0004, hazard ratio 3.83) and the validation cohort, independently of AJCC staging. Consequently, when combining risk score and AJCC staging, patients in the AJCC intermediate-risk stages, IIA/B or IIIA, were re-classified either to low or high risk. Conclusions Our gene score defines patient risk and need for therapy in melanoma. The score has the potential to be utilized in clinical routine, since it is quantitative, robust, simple, and independent of AJCC stage and sample purity. Melanoma (dpeaa)DE-He213 Prognosis (dpeaa)DE-He213 Gene signature (dpeaa)DE-He213 Gene expression profiling (dpeaa)DE-He213 RT-PCR (dpeaa)DE-He213 Reitz, M. verfasserin aut Heinecke, A. verfasserin aut Lippold, A. verfasserin aut Berking, C. verfasserin aut Suter, L. verfasserin aut Atzpodien, J. verfasserin aut Enthalten in Journal of cancer research and clinical oncology Berlin : Springer, 1904 139(2012), 2 vom: 09. Okt., Seite 249-258 (DE-627)253769515 (DE-600)1459285-X 1432-1335 nnns volume:139 year:2012 number:2 day:09 month:10 pages:249-258 https://dx.doi.org/10.1007/s00432-012-1322-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 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_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 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_4393 GBV_ILN_4700 44.81 ASE AR 139 2012 2 09 10 249-258 |
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10.1007/s00432-012-1322-z doi (DE-627)SPR005850754 (SPR)s00432-012-1322-z-e DE-627 ger DE-627 rakwb eng 610 ASE 44.81 bkl Brunner, G. verfasserin aut A nine-gene signature predicting clinical outcome in cutaneous melanoma 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose Current histopathological staging of cutaneous melanoma is limited in predicting outcome, and complementary molecular markers are not available for prognostic assessment. The purpose of this study was to identify a quantitative gene expression score in primary melanoma and adjacent stroma that can be used in clinical routine to define, at the time of diagnosis, patient risk and need for therapy. Methods Expression of 92 candidate genes was quantified by RT-PCR in a training subset of 38 fresh-frozen melanomas. Correlation of gene expression with overall survival (OS) was evaluated using univariate regression analysis. Expression analysis of 11 prognostically significant genes in the complete training cohort of 91 melanomas yielded nine genes predicting outcome. Results were confirmed in a validation cohort of 44 melanomas. Results We identified a nine-gene signature associated with OS and distant metastasis-free survival. The signature comprised risk and protective genes and was applicable to melanoma samples across all AJCC stages in the presence of adjacent stroma. A signature-based risk score predicted OS in both the training cohort (multivariate regression analysis: p = 0.0004, hazard ratio 3.83) and the validation cohort, independently of AJCC staging. Consequently, when combining risk score and AJCC staging, patients in the AJCC intermediate-risk stages, IIA/B or IIIA, were re-classified either to low or high risk. Conclusions Our gene score defines patient risk and need for therapy in melanoma. The score has the potential to be utilized in clinical routine, since it is quantitative, robust, simple, and independent of AJCC stage and sample purity. Melanoma (dpeaa)DE-He213 Prognosis (dpeaa)DE-He213 Gene signature (dpeaa)DE-He213 Gene expression profiling (dpeaa)DE-He213 RT-PCR (dpeaa)DE-He213 Reitz, M. verfasserin aut Heinecke, A. verfasserin aut Lippold, A. verfasserin aut Berking, C. verfasserin aut Suter, L. verfasserin aut Atzpodien, J. verfasserin aut Enthalten in Journal of cancer research and clinical oncology Berlin : Springer, 1904 139(2012), 2 vom: 09. Okt., Seite 249-258 (DE-627)253769515 (DE-600)1459285-X 1432-1335 nnns volume:139 year:2012 number:2 day:09 month:10 pages:249-258 https://dx.doi.org/10.1007/s00432-012-1322-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 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_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 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_4393 GBV_ILN_4700 44.81 ASE AR 139 2012 2 09 10 249-258 |
allfieldsGer |
10.1007/s00432-012-1322-z doi (DE-627)SPR005850754 (SPR)s00432-012-1322-z-e DE-627 ger DE-627 rakwb eng 610 ASE 44.81 bkl Brunner, G. verfasserin aut A nine-gene signature predicting clinical outcome in cutaneous melanoma 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose Current histopathological staging of cutaneous melanoma is limited in predicting outcome, and complementary molecular markers are not available for prognostic assessment. The purpose of this study was to identify a quantitative gene expression score in primary melanoma and adjacent stroma that can be used in clinical routine to define, at the time of diagnosis, patient risk and need for therapy. Methods Expression of 92 candidate genes was quantified by RT-PCR in a training subset of 38 fresh-frozen melanomas. Correlation of gene expression with overall survival (OS) was evaluated using univariate regression analysis. Expression analysis of 11 prognostically significant genes in the complete training cohort of 91 melanomas yielded nine genes predicting outcome. Results were confirmed in a validation cohort of 44 melanomas. Results We identified a nine-gene signature associated with OS and distant metastasis-free survival. The signature comprised risk and protective genes and was applicable to melanoma samples across all AJCC stages in the presence of adjacent stroma. A signature-based risk score predicted OS in both the training cohort (multivariate regression analysis: p = 0.0004, hazard ratio 3.83) and the validation cohort, independently of AJCC staging. Consequently, when combining risk score and AJCC staging, patients in the AJCC intermediate-risk stages, IIA/B or IIIA, were re-classified either to low or high risk. Conclusions Our gene score defines patient risk and need for therapy in melanoma. The score has the potential to be utilized in clinical routine, since it is quantitative, robust, simple, and independent of AJCC stage and sample purity. Melanoma (dpeaa)DE-He213 Prognosis (dpeaa)DE-He213 Gene signature (dpeaa)DE-He213 Gene expression profiling (dpeaa)DE-He213 RT-PCR (dpeaa)DE-He213 Reitz, M. verfasserin aut Heinecke, A. verfasserin aut Lippold, A. verfasserin aut Berking, C. verfasserin aut Suter, L. verfasserin aut Atzpodien, J. verfasserin aut Enthalten in Journal of cancer research and clinical oncology Berlin : Springer, 1904 139(2012), 2 vom: 09. Okt., Seite 249-258 (DE-627)253769515 (DE-600)1459285-X 1432-1335 nnns volume:139 year:2012 number:2 day:09 month:10 pages:249-258 https://dx.doi.org/10.1007/s00432-012-1322-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 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_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 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_4393 GBV_ILN_4700 44.81 ASE AR 139 2012 2 09 10 249-258 |
allfieldsSound |
10.1007/s00432-012-1322-z doi (DE-627)SPR005850754 (SPR)s00432-012-1322-z-e DE-627 ger DE-627 rakwb eng 610 ASE 44.81 bkl Brunner, G. verfasserin aut A nine-gene signature predicting clinical outcome in cutaneous melanoma 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose Current histopathological staging of cutaneous melanoma is limited in predicting outcome, and complementary molecular markers are not available for prognostic assessment. The purpose of this study was to identify a quantitative gene expression score in primary melanoma and adjacent stroma that can be used in clinical routine to define, at the time of diagnosis, patient risk and need for therapy. Methods Expression of 92 candidate genes was quantified by RT-PCR in a training subset of 38 fresh-frozen melanomas. Correlation of gene expression with overall survival (OS) was evaluated using univariate regression analysis. Expression analysis of 11 prognostically significant genes in the complete training cohort of 91 melanomas yielded nine genes predicting outcome. Results were confirmed in a validation cohort of 44 melanomas. Results We identified a nine-gene signature associated with OS and distant metastasis-free survival. The signature comprised risk and protective genes and was applicable to melanoma samples across all AJCC stages in the presence of adjacent stroma. A signature-based risk score predicted OS in both the training cohort (multivariate regression analysis: p = 0.0004, hazard ratio 3.83) and the validation cohort, independently of AJCC staging. Consequently, when combining risk score and AJCC staging, patients in the AJCC intermediate-risk stages, IIA/B or IIIA, were re-classified either to low or high risk. Conclusions Our gene score defines patient risk and need for therapy in melanoma. The score has the potential to be utilized in clinical routine, since it is quantitative, robust, simple, and independent of AJCC stage and sample purity. Melanoma (dpeaa)DE-He213 Prognosis (dpeaa)DE-He213 Gene signature (dpeaa)DE-He213 Gene expression profiling (dpeaa)DE-He213 RT-PCR (dpeaa)DE-He213 Reitz, M. verfasserin aut Heinecke, A. verfasserin aut Lippold, A. verfasserin aut Berking, C. verfasserin aut Suter, L. verfasserin aut Atzpodien, J. verfasserin aut Enthalten in Journal of cancer research and clinical oncology Berlin : Springer, 1904 139(2012), 2 vom: 09. Okt., Seite 249-258 (DE-627)253769515 (DE-600)1459285-X 1432-1335 nnns volume:139 year:2012 number:2 day:09 month:10 pages:249-258 https://dx.doi.org/10.1007/s00432-012-1322-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 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_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 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_4393 GBV_ILN_4700 44.81 ASE AR 139 2012 2 09 10 249-258 |
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Enthalten in Journal of cancer research and clinical oncology 139(2012), 2 vom: 09. Okt., Seite 249-258 volume:139 year:2012 number:2 day:09 month:10 pages:249-258 |
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Enthalten in Journal of cancer research and clinical oncology 139(2012), 2 vom: 09. Okt., Seite 249-258 volume:139 year:2012 number:2 day:09 month:10 pages:249-258 |
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Melanoma Prognosis Gene signature Gene expression profiling RT-PCR |
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Brunner, G. @@aut@@ Reitz, M. @@aut@@ Heinecke, A. @@aut@@ Lippold, A. @@aut@@ Berking, C. @@aut@@ Suter, L. @@aut@@ Atzpodien, J. @@aut@@ |
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The purpose of this study was to identify a quantitative gene expression score in primary melanoma and adjacent stroma that can be used in clinical routine to define, at the time of diagnosis, patient risk and need for therapy. Methods Expression of 92 candidate genes was quantified by RT-PCR in a training subset of 38 fresh-frozen melanomas. Correlation of gene expression with overall survival (OS) was evaluated using univariate regression analysis. Expression analysis of 11 prognostically significant genes in the complete training cohort of 91 melanomas yielded nine genes predicting outcome. Results were confirmed in a validation cohort of 44 melanomas. Results We identified a nine-gene signature associated with OS and distant metastasis-free survival. The signature comprised risk and protective genes and was applicable to melanoma samples across all AJCC stages in the presence of adjacent stroma. A signature-based risk score predicted OS in both the training cohort (multivariate regression analysis: p = 0.0004, hazard ratio 3.83) and the validation cohort, independently of AJCC staging. Consequently, when combining risk score and AJCC staging, patients in the AJCC intermediate-risk stages, IIA/B or IIIA, were re-classified either to low or high risk. Conclusions Our gene score defines patient risk and need for therapy in melanoma. 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Brunner, G. |
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Brunner, G. ddc 610 bkl 44.81 misc Melanoma misc Prognosis misc Gene signature misc Gene expression profiling misc RT-PCR A nine-gene signature predicting clinical outcome in cutaneous melanoma |
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610 ASE 44.81 bkl A nine-gene signature predicting clinical outcome in cutaneous melanoma Melanoma (dpeaa)DE-He213 Prognosis (dpeaa)DE-He213 Gene signature (dpeaa)DE-He213 Gene expression profiling (dpeaa)DE-He213 RT-PCR (dpeaa)DE-He213 |
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ddc 610 bkl 44.81 misc Melanoma misc Prognosis misc Gene signature misc Gene expression profiling misc RT-PCR |
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A nine-gene signature predicting clinical outcome in cutaneous melanoma |
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Brunner, G. |
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verfasserin |
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nine-gene signature predicting clinical outcome in cutaneous melanoma |
title_auth |
A nine-gene signature predicting clinical outcome in cutaneous melanoma |
abstract |
Purpose Current histopathological staging of cutaneous melanoma is limited in predicting outcome, and complementary molecular markers are not available for prognostic assessment. The purpose of this study was to identify a quantitative gene expression score in primary melanoma and adjacent stroma that can be used in clinical routine to define, at the time of diagnosis, patient risk and need for therapy. Methods Expression of 92 candidate genes was quantified by RT-PCR in a training subset of 38 fresh-frozen melanomas. Correlation of gene expression with overall survival (OS) was evaluated using univariate regression analysis. Expression analysis of 11 prognostically significant genes in the complete training cohort of 91 melanomas yielded nine genes predicting outcome. Results were confirmed in a validation cohort of 44 melanomas. Results We identified a nine-gene signature associated with OS and distant metastasis-free survival. The signature comprised risk and protective genes and was applicable to melanoma samples across all AJCC stages in the presence of adjacent stroma. A signature-based risk score predicted OS in both the training cohort (multivariate regression analysis: p = 0.0004, hazard ratio 3.83) and the validation cohort, independently of AJCC staging. Consequently, when combining risk score and AJCC staging, patients in the AJCC intermediate-risk stages, IIA/B or IIIA, were re-classified either to low or high risk. Conclusions Our gene score defines patient risk and need for therapy in melanoma. The score has the potential to be utilized in clinical routine, since it is quantitative, robust, simple, and independent of AJCC stage and sample purity. |
abstractGer |
Purpose Current histopathological staging of cutaneous melanoma is limited in predicting outcome, and complementary molecular markers are not available for prognostic assessment. The purpose of this study was to identify a quantitative gene expression score in primary melanoma and adjacent stroma that can be used in clinical routine to define, at the time of diagnosis, patient risk and need for therapy. Methods Expression of 92 candidate genes was quantified by RT-PCR in a training subset of 38 fresh-frozen melanomas. Correlation of gene expression with overall survival (OS) was evaluated using univariate regression analysis. Expression analysis of 11 prognostically significant genes in the complete training cohort of 91 melanomas yielded nine genes predicting outcome. Results were confirmed in a validation cohort of 44 melanomas. Results We identified a nine-gene signature associated with OS and distant metastasis-free survival. The signature comprised risk and protective genes and was applicable to melanoma samples across all AJCC stages in the presence of adjacent stroma. A signature-based risk score predicted OS in both the training cohort (multivariate regression analysis: p = 0.0004, hazard ratio 3.83) and the validation cohort, independently of AJCC staging. Consequently, when combining risk score and AJCC staging, patients in the AJCC intermediate-risk stages, IIA/B or IIIA, were re-classified either to low or high risk. Conclusions Our gene score defines patient risk and need for therapy in melanoma. The score has the potential to be utilized in clinical routine, since it is quantitative, robust, simple, and independent of AJCC stage and sample purity. |
abstract_unstemmed |
Purpose Current histopathological staging of cutaneous melanoma is limited in predicting outcome, and complementary molecular markers are not available for prognostic assessment. The purpose of this study was to identify a quantitative gene expression score in primary melanoma and adjacent stroma that can be used in clinical routine to define, at the time of diagnosis, patient risk and need for therapy. Methods Expression of 92 candidate genes was quantified by RT-PCR in a training subset of 38 fresh-frozen melanomas. Correlation of gene expression with overall survival (OS) was evaluated using univariate regression analysis. Expression analysis of 11 prognostically significant genes in the complete training cohort of 91 melanomas yielded nine genes predicting outcome. Results were confirmed in a validation cohort of 44 melanomas. Results We identified a nine-gene signature associated with OS and distant metastasis-free survival. The signature comprised risk and protective genes and was applicable to melanoma samples across all AJCC stages in the presence of adjacent stroma. A signature-based risk score predicted OS in both the training cohort (multivariate regression analysis: p = 0.0004, hazard ratio 3.83) and the validation cohort, independently of AJCC staging. Consequently, when combining risk score and AJCC staging, patients in the AJCC intermediate-risk stages, IIA/B or IIIA, were re-classified either to low or high risk. Conclusions Our gene score defines patient risk and need for therapy in melanoma. The score has the potential to be utilized in clinical routine, since it is quantitative, robust, simple, and independent of AJCC stage and sample purity. |
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container_issue |
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title_short |
A nine-gene signature predicting clinical outcome in cutaneous melanoma |
url |
https://dx.doi.org/10.1007/s00432-012-1322-z |
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Reitz, M. Heinecke, A. Lippold, A. Berking, C. Suter, L. Atzpodien, J. |
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Reitz, M. Heinecke, A. Lippold, A. Berking, C. Suter, L. Atzpodien, J. |
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up_date |
2024-07-03T19:07:49.437Z |
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|
score |
7.399932 |