A pharmacogenetic interaction analysis of bevacizumab with paclitaxel in advanced breast cancer patients
Abstract To investigate pharmacogenetic interactions among VEGF-A, VEGFR-2, IL-8, HIF-1α, EPAS-1, and TSP-1 SNPs and their role on progression-free survival (PFS) in metastatic breast cancer (MBC) patients treated with bevacizumab plus first-line paclitaxel or with paclitaxel alone. Analyses were pe...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Luigi Coltelli [verfasserIn] Giacomo Allegrini [verfasserIn] Paola Orlandi [verfasserIn] Chiara Finale [verfasserIn] Andrea Fontana [verfasserIn] Luna Chiara Masini [verfasserIn] Marco Scalese [verfasserIn] Giada Arrighi [verfasserIn] Maria Teresa Barletta [verfasserIn] Ermelinda De Maio [verfasserIn] Marta Banchi [verfasserIn] Elisabetta Fini [verfasserIn] Patrizia Guidi [verfasserIn] Giada Frenzilli [verfasserIn] Sara Donati [verfasserIn] Simona Giovannelli [verfasserIn] Lucia Tanganelli [verfasserIn] Barbara Salvadori [verfasserIn] Lorenzo Livi [verfasserIn] Icro Meattini [verfasserIn] Ilaria Pazzagli [verfasserIn] Marco Di Lieto [verfasserIn] Mirco Pistelli [verfasserIn] Virginia Casadei [verfasserIn] Antonella Ferro [verfasserIn] Samanta Cupini [verfasserIn] Francesca Orlandi [verfasserIn] Damiana Francesca [verfasserIn] Giulia Lorenzini [verfasserIn] Leonardo Barellini [verfasserIn] Alfredo Falcone [verfasserIn] Alessandro Cosimi [verfasserIn] Guido Bocci [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Übergeordnetes Werk: |
In: npj Breast Cancer - Nature Portfolio, 2016, 8(2022), 1, Seite 9 |
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| Übergeordnetes Werk: |
volume:8 ; year:2022 ; number:1 ; pages:9 |
| Links: |
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| DOI / URN: |
10.1038/s41523-022-00400-6 |
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DOAJ007896700 |
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| 520 | |a Abstract To investigate pharmacogenetic interactions among VEGF-A, VEGFR-2, IL-8, HIF-1α, EPAS-1, and TSP-1 SNPs and their role on progression-free survival (PFS) in metastatic breast cancer (MBC) patients treated with bevacizumab plus first-line paclitaxel or with paclitaxel alone. Analyses were performed on germline DNA, and SNPs were investigated by real-time PCR technique. The multifactor dimensionality reduction (MDR) methodology was applied to investigate the interaction between SNPs. The present study was an explorative, ambidirectional cohort study: 307 patients from 11 Oncology Units were evaluated retrospectively from 2009 to 2016, then followed prospectively (NCT01935102). Two hundred and fifteen patients were treated with paclitaxel and bevacizumab, whereas 92 patients with paclitaxel alone. In the bevacizumab plus paclitaxel group, the MDR software provided two pharmacogenetic interaction profiles consisting of the combination between specific VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes. Median PFS for favorable genetic profile was 16.8 vs. the 10.6 months of unfavorable genetic profile (p = 0.0011). Cox proportional hazards model showed an adjusted hazard ratio of 0.64 (95% CI, 0.5–0.9; p = 0.004). Median OS for the favorable genetic profile was 39.6 vs. 28 months of unfavorable genetic profile (p = 0.0103). Cox proportional hazards model revealed an adjusted hazard ratio of 0.71 (95% CI, 0.5–1.01; p = 0.058). In the 92 patients treated with paclitaxel alone, the results showed no effect of the favorable genetic profile, as compared to the unfavorable genetic profile, either on the PFS (p = 0.509) and on the OS (p = 0.732). The pharmacogenetic statistical interaction between VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes may identify a population of bevacizumab-treated patients with a better PFS. | ||
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10.1038/s41523-022-00400-6 doi (DE-627)DOAJ007896700 (DE-599)DOAJddb3a8574ac74c6f9118cd6ec4935bea DE-627 ger DE-627 rakwb eng RC254-282 Luigi Coltelli verfasserin aut A pharmacogenetic interaction analysis of bevacizumab with paclitaxel in advanced breast cancer patients 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract To investigate pharmacogenetic interactions among VEGF-A, VEGFR-2, IL-8, HIF-1α, EPAS-1, and TSP-1 SNPs and their role on progression-free survival (PFS) in metastatic breast cancer (MBC) patients treated with bevacizumab plus first-line paclitaxel or with paclitaxel alone. Analyses were performed on germline DNA, and SNPs were investigated by real-time PCR technique. The multifactor dimensionality reduction (MDR) methodology was applied to investigate the interaction between SNPs. The present study was an explorative, ambidirectional cohort study: 307 patients from 11 Oncology Units were evaluated retrospectively from 2009 to 2016, then followed prospectively (NCT01935102). Two hundred and fifteen patients were treated with paclitaxel and bevacizumab, whereas 92 patients with paclitaxel alone. In the bevacizumab plus paclitaxel group, the MDR software provided two pharmacogenetic interaction profiles consisting of the combination between specific VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes. Median PFS for favorable genetic profile was 16.8 vs. the 10.6 months of unfavorable genetic profile (p = 0.0011). Cox proportional hazards model showed an adjusted hazard ratio of 0.64 (95% CI, 0.5–0.9; p = 0.004). Median OS for the favorable genetic profile was 39.6 vs. 28 months of unfavorable genetic profile (p = 0.0103). Cox proportional hazards model revealed an adjusted hazard ratio of 0.71 (95% CI, 0.5–1.01; p = 0.058). In the 92 patients treated with paclitaxel alone, the results showed no effect of the favorable genetic profile, as compared to the unfavorable genetic profile, either on the PFS (p = 0.509) and on the OS (p = 0.732). The pharmacogenetic statistical interaction between VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes may identify a population of bevacizumab-treated patients with a better PFS. Neoplasms. Tumors. Oncology. Including cancer and carcinogens Giacomo Allegrini verfasserin aut Paola Orlandi verfasserin aut Chiara Finale verfasserin aut Andrea Fontana verfasserin aut Luna Chiara Masini verfasserin aut Marco Scalese verfasserin aut Giada Arrighi verfasserin aut Maria Teresa Barletta verfasserin aut Ermelinda De Maio verfasserin aut Marta Banchi verfasserin aut Elisabetta Fini verfasserin aut Patrizia Guidi verfasserin aut Giada Frenzilli verfasserin aut Sara Donati verfasserin aut Simona Giovannelli verfasserin aut Lucia Tanganelli verfasserin aut Barbara Salvadori verfasserin aut Lorenzo Livi verfasserin aut Icro Meattini verfasserin aut Ilaria Pazzagli verfasserin aut Marco Di Lieto verfasserin aut Mirco Pistelli verfasserin aut Virginia Casadei verfasserin aut Antonella Ferro verfasserin aut Samanta Cupini verfasserin aut Francesca Orlandi verfasserin aut Damiana Francesca verfasserin aut Giulia Lorenzini verfasserin aut Leonardo Barellini verfasserin aut Alfredo Falcone verfasserin aut Alessandro Cosimi verfasserin aut Guido Bocci verfasserin aut In npj Breast Cancer Nature Portfolio, 2016 8(2022), 1, Seite 9 (DE-627)844762113 (DE-600)2843288-5 23744677 nnns volume:8 year:2022 number:1 pages:9 https://doi.org/10.1038/s41523-022-00400-6 kostenfrei https://doaj.org/article/ddb3a8574ac74c6f9118cd6ec4935bea kostenfrei https://doi.org/10.1038/s41523-022-00400-6 kostenfrei https://doaj.org/toc/2374-4677 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 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_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2022 1 9 |
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10.1038/s41523-022-00400-6 doi (DE-627)DOAJ007896700 (DE-599)DOAJddb3a8574ac74c6f9118cd6ec4935bea DE-627 ger DE-627 rakwb eng RC254-282 Luigi Coltelli verfasserin aut A pharmacogenetic interaction analysis of bevacizumab with paclitaxel in advanced breast cancer patients 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract To investigate pharmacogenetic interactions among VEGF-A, VEGFR-2, IL-8, HIF-1α, EPAS-1, and TSP-1 SNPs and their role on progression-free survival (PFS) in metastatic breast cancer (MBC) patients treated with bevacizumab plus first-line paclitaxel or with paclitaxel alone. Analyses were performed on germline DNA, and SNPs were investigated by real-time PCR technique. The multifactor dimensionality reduction (MDR) methodology was applied to investigate the interaction between SNPs. The present study was an explorative, ambidirectional cohort study: 307 patients from 11 Oncology Units were evaluated retrospectively from 2009 to 2016, then followed prospectively (NCT01935102). Two hundred and fifteen patients were treated with paclitaxel and bevacizumab, whereas 92 patients with paclitaxel alone. In the bevacizumab plus paclitaxel group, the MDR software provided two pharmacogenetic interaction profiles consisting of the combination between specific VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes. Median PFS for favorable genetic profile was 16.8 vs. the 10.6 months of unfavorable genetic profile (p = 0.0011). Cox proportional hazards model showed an adjusted hazard ratio of 0.64 (95% CI, 0.5–0.9; p = 0.004). Median OS for the favorable genetic profile was 39.6 vs. 28 months of unfavorable genetic profile (p = 0.0103). Cox proportional hazards model revealed an adjusted hazard ratio of 0.71 (95% CI, 0.5–1.01; p = 0.058). In the 92 patients treated with paclitaxel alone, the results showed no effect of the favorable genetic profile, as compared to the unfavorable genetic profile, either on the PFS (p = 0.509) and on the OS (p = 0.732). The pharmacogenetic statistical interaction between VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes may identify a population of bevacizumab-treated patients with a better PFS. Neoplasms. Tumors. Oncology. Including cancer and carcinogens Giacomo Allegrini verfasserin aut Paola Orlandi verfasserin aut Chiara Finale verfasserin aut Andrea Fontana verfasserin aut Luna Chiara Masini verfasserin aut Marco Scalese verfasserin aut Giada Arrighi verfasserin aut Maria Teresa Barletta verfasserin aut Ermelinda De Maio verfasserin aut Marta Banchi verfasserin aut Elisabetta Fini verfasserin aut Patrizia Guidi verfasserin aut Giada Frenzilli verfasserin aut Sara Donati verfasserin aut Simona Giovannelli verfasserin aut Lucia Tanganelli verfasserin aut Barbara Salvadori verfasserin aut Lorenzo Livi verfasserin aut Icro Meattini verfasserin aut Ilaria Pazzagli verfasserin aut Marco Di Lieto verfasserin aut Mirco Pistelli verfasserin aut Virginia Casadei verfasserin aut Antonella Ferro verfasserin aut Samanta Cupini verfasserin aut Francesca Orlandi verfasserin aut Damiana Francesca verfasserin aut Giulia Lorenzini verfasserin aut Leonardo Barellini verfasserin aut Alfredo Falcone verfasserin aut Alessandro Cosimi verfasserin aut Guido Bocci verfasserin aut In npj Breast Cancer Nature Portfolio, 2016 8(2022), 1, Seite 9 (DE-627)844762113 (DE-600)2843288-5 23744677 nnns volume:8 year:2022 number:1 pages:9 https://doi.org/10.1038/s41523-022-00400-6 kostenfrei https://doaj.org/article/ddb3a8574ac74c6f9118cd6ec4935bea kostenfrei https://doi.org/10.1038/s41523-022-00400-6 kostenfrei https://doaj.org/toc/2374-4677 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 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_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2022 1 9 |
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10.1038/s41523-022-00400-6 doi (DE-627)DOAJ007896700 (DE-599)DOAJddb3a8574ac74c6f9118cd6ec4935bea DE-627 ger DE-627 rakwb eng RC254-282 Luigi Coltelli verfasserin aut A pharmacogenetic interaction analysis of bevacizumab with paclitaxel in advanced breast cancer patients 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract To investigate pharmacogenetic interactions among VEGF-A, VEGFR-2, IL-8, HIF-1α, EPAS-1, and TSP-1 SNPs and their role on progression-free survival (PFS) in metastatic breast cancer (MBC) patients treated with bevacizumab plus first-line paclitaxel or with paclitaxel alone. Analyses were performed on germline DNA, and SNPs were investigated by real-time PCR technique. The multifactor dimensionality reduction (MDR) methodology was applied to investigate the interaction between SNPs. The present study was an explorative, ambidirectional cohort study: 307 patients from 11 Oncology Units were evaluated retrospectively from 2009 to 2016, then followed prospectively (NCT01935102). Two hundred and fifteen patients were treated with paclitaxel and bevacizumab, whereas 92 patients with paclitaxel alone. In the bevacizumab plus paclitaxel group, the MDR software provided two pharmacogenetic interaction profiles consisting of the combination between specific VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes. Median PFS for favorable genetic profile was 16.8 vs. the 10.6 months of unfavorable genetic profile (p = 0.0011). Cox proportional hazards model showed an adjusted hazard ratio of 0.64 (95% CI, 0.5–0.9; p = 0.004). Median OS for the favorable genetic profile was 39.6 vs. 28 months of unfavorable genetic profile (p = 0.0103). Cox proportional hazards model revealed an adjusted hazard ratio of 0.71 (95% CI, 0.5–1.01; p = 0.058). In the 92 patients treated with paclitaxel alone, the results showed no effect of the favorable genetic profile, as compared to the unfavorable genetic profile, either on the PFS (p = 0.509) and on the OS (p = 0.732). The pharmacogenetic statistical interaction between VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes may identify a population of bevacizumab-treated patients with a better PFS. Neoplasms. Tumors. Oncology. Including cancer and carcinogens Giacomo Allegrini verfasserin aut Paola Orlandi verfasserin aut Chiara Finale verfasserin aut Andrea Fontana verfasserin aut Luna Chiara Masini verfasserin aut Marco Scalese verfasserin aut Giada Arrighi verfasserin aut Maria Teresa Barletta verfasserin aut Ermelinda De Maio verfasserin aut Marta Banchi verfasserin aut Elisabetta Fini verfasserin aut Patrizia Guidi verfasserin aut Giada Frenzilli verfasserin aut Sara Donati verfasserin aut Simona Giovannelli verfasserin aut Lucia Tanganelli verfasserin aut Barbara Salvadori verfasserin aut Lorenzo Livi verfasserin aut Icro Meattini verfasserin aut Ilaria Pazzagli verfasserin aut Marco Di Lieto verfasserin aut Mirco Pistelli verfasserin aut Virginia Casadei verfasserin aut Antonella Ferro verfasserin aut Samanta Cupini verfasserin aut Francesca Orlandi verfasserin aut Damiana Francesca verfasserin aut Giulia Lorenzini verfasserin aut Leonardo Barellini verfasserin aut Alfredo Falcone verfasserin aut Alessandro Cosimi verfasserin aut Guido Bocci verfasserin aut In npj Breast Cancer Nature Portfolio, 2016 8(2022), 1, Seite 9 (DE-627)844762113 (DE-600)2843288-5 23744677 nnns volume:8 year:2022 number:1 pages:9 https://doi.org/10.1038/s41523-022-00400-6 kostenfrei https://doaj.org/article/ddb3a8574ac74c6f9118cd6ec4935bea kostenfrei https://doi.org/10.1038/s41523-022-00400-6 kostenfrei https://doaj.org/toc/2374-4677 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 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_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2022 1 9 |
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Luigi Coltelli @@aut@@ Giacomo Allegrini @@aut@@ Paola Orlandi @@aut@@ Chiara Finale @@aut@@ Andrea Fontana @@aut@@ Luna Chiara Masini @@aut@@ Marco Scalese @@aut@@ Giada Arrighi @@aut@@ Maria Teresa Barletta @@aut@@ Ermelinda De Maio @@aut@@ Marta Banchi @@aut@@ Elisabetta Fini @@aut@@ Patrizia Guidi @@aut@@ Giada Frenzilli @@aut@@ Sara Donati @@aut@@ Simona Giovannelli @@aut@@ Lucia Tanganelli @@aut@@ Barbara Salvadori @@aut@@ Lorenzo Livi @@aut@@ Icro Meattini @@aut@@ Ilaria Pazzagli @@aut@@ Marco Di Lieto @@aut@@ Mirco Pistelli @@aut@@ Virginia Casadei @@aut@@ Antonella Ferro @@aut@@ Samanta Cupini @@aut@@ Francesca Orlandi @@aut@@ Damiana Francesca @@aut@@ Giulia Lorenzini @@aut@@ Leonardo Barellini @@aut@@ Alfredo Falcone @@aut@@ Alessandro Cosimi @@aut@@ Guido Bocci @@aut@@ |
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A pharmacogenetic interaction analysis of bevacizumab with paclitaxel in advanced breast cancer patients |
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Abstract To investigate pharmacogenetic interactions among VEGF-A, VEGFR-2, IL-8, HIF-1α, EPAS-1, and TSP-1 SNPs and their role on progression-free survival (PFS) in metastatic breast cancer (MBC) patients treated with bevacizumab plus first-line paclitaxel or with paclitaxel alone. Analyses were performed on germline DNA, and SNPs were investigated by real-time PCR technique. The multifactor dimensionality reduction (MDR) methodology was applied to investigate the interaction between SNPs. The present study was an explorative, ambidirectional cohort study: 307 patients from 11 Oncology Units were evaluated retrospectively from 2009 to 2016, then followed prospectively (NCT01935102). Two hundred and fifteen patients were treated with paclitaxel and bevacizumab, whereas 92 patients with paclitaxel alone. In the bevacizumab plus paclitaxel group, the MDR software provided two pharmacogenetic interaction profiles consisting of the combination between specific VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes. Median PFS for favorable genetic profile was 16.8 vs. the 10.6 months of unfavorable genetic profile (p = 0.0011). Cox proportional hazards model showed an adjusted hazard ratio of 0.64 (95% CI, 0.5–0.9; p = 0.004). Median OS for the favorable genetic profile was 39.6 vs. 28 months of unfavorable genetic profile (p = 0.0103). Cox proportional hazards model revealed an adjusted hazard ratio of 0.71 (95% CI, 0.5–1.01; p = 0.058). In the 92 patients treated with paclitaxel alone, the results showed no effect of the favorable genetic profile, as compared to the unfavorable genetic profile, either on the PFS (p = 0.509) and on the OS (p = 0.732). The pharmacogenetic statistical interaction between VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes may identify a population of bevacizumab-treated patients with a better PFS. |
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Abstract To investigate pharmacogenetic interactions among VEGF-A, VEGFR-2, IL-8, HIF-1α, EPAS-1, and TSP-1 SNPs and their role on progression-free survival (PFS) in metastatic breast cancer (MBC) patients treated with bevacizumab plus first-line paclitaxel or with paclitaxel alone. Analyses were performed on germline DNA, and SNPs were investigated by real-time PCR technique. The multifactor dimensionality reduction (MDR) methodology was applied to investigate the interaction between SNPs. The present study was an explorative, ambidirectional cohort study: 307 patients from 11 Oncology Units were evaluated retrospectively from 2009 to 2016, then followed prospectively (NCT01935102). Two hundred and fifteen patients were treated with paclitaxel and bevacizumab, whereas 92 patients with paclitaxel alone. In the bevacizumab plus paclitaxel group, the MDR software provided two pharmacogenetic interaction profiles consisting of the combination between specific VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes. Median PFS for favorable genetic profile was 16.8 vs. the 10.6 months of unfavorable genetic profile (p = 0.0011). Cox proportional hazards model showed an adjusted hazard ratio of 0.64 (95% CI, 0.5–0.9; p = 0.004). Median OS for the favorable genetic profile was 39.6 vs. 28 months of unfavorable genetic profile (p = 0.0103). Cox proportional hazards model revealed an adjusted hazard ratio of 0.71 (95% CI, 0.5–1.01; p = 0.058). In the 92 patients treated with paclitaxel alone, the results showed no effect of the favorable genetic profile, as compared to the unfavorable genetic profile, either on the PFS (p = 0.509) and on the OS (p = 0.732). The pharmacogenetic statistical interaction between VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes may identify a population of bevacizumab-treated patients with a better PFS. |
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Abstract To investigate pharmacogenetic interactions among VEGF-A, VEGFR-2, IL-8, HIF-1α, EPAS-1, and TSP-1 SNPs and their role on progression-free survival (PFS) in metastatic breast cancer (MBC) patients treated with bevacizumab plus first-line paclitaxel or with paclitaxel alone. Analyses were performed on germline DNA, and SNPs were investigated by real-time PCR technique. The multifactor dimensionality reduction (MDR) methodology was applied to investigate the interaction between SNPs. The present study was an explorative, ambidirectional cohort study: 307 patients from 11 Oncology Units were evaluated retrospectively from 2009 to 2016, then followed prospectively (NCT01935102). Two hundred and fifteen patients were treated with paclitaxel and bevacizumab, whereas 92 patients with paclitaxel alone. In the bevacizumab plus paclitaxel group, the MDR software provided two pharmacogenetic interaction profiles consisting of the combination between specific VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes. Median PFS for favorable genetic profile was 16.8 vs. the 10.6 months of unfavorable genetic profile (p = 0.0011). Cox proportional hazards model showed an adjusted hazard ratio of 0.64 (95% CI, 0.5–0.9; p = 0.004). Median OS for the favorable genetic profile was 39.6 vs. 28 months of unfavorable genetic profile (p = 0.0103). Cox proportional hazards model revealed an adjusted hazard ratio of 0.71 (95% CI, 0.5–1.01; p = 0.058). In the 92 patients treated with paclitaxel alone, the results showed no effect of the favorable genetic profile, as compared to the unfavorable genetic profile, either on the PFS (p = 0.509) and on the OS (p = 0.732). The pharmacogenetic statistical interaction between VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes may identify a population of bevacizumab-treated patients with a better PFS. |
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