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Pharmacogenetics driving personalized medicine: analysis of genetic polymorphisms related to breast cancer medications in Italian isolated populations

BACKGROUND: Breast cancer is the most common cancer in women characterized by a high variable clinical outcome among individuals treated with equivalent regimens and novel targeted therapies. In this study, we performed a population based approach intersecting high-throughput genotype data from Friu...

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Autores principales: Cocca, Massimiliano, Bedognetti, Davide, La Bianca, Martina, Gasparini, Paolo, Girotto, Giorgia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4722680/
https://www.ncbi.nlm.nih.gov/pubmed/26801900
http://dx.doi.org/10.1186/s12967-016-0778-z
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author Cocca, Massimiliano
Bedognetti, Davide
La Bianca, Martina
Gasparini, Paolo
Girotto, Giorgia
author_facet Cocca, Massimiliano
Bedognetti, Davide
La Bianca, Martina
Gasparini, Paolo
Girotto, Giorgia
author_sort Cocca, Massimiliano
collection PubMed
description BACKGROUND: Breast cancer is the most common cancer in women characterized by a high variable clinical outcome among individuals treated with equivalent regimens and novel targeted therapies. In this study, we performed a population based approach intersecting high-throughput genotype data from Friuli Venezia Giulia (FVG) isolated populations with publically available pharmacogenomics information to estimate the frequency of genotypes correlated with responsiveness to breast cancer treatment thus improving the clinical management of this disease in an efficient and cost effective way. METHODS: A list of 80 variants reported to be related to the efficacy or toxicity of breast cancer drugs was obtained from PharmGKB database. Fourty-one were present in FVG, 1000G European (EUR) and ExAC (Non Finnish European) databases. Their frequency was extracted using PLINK software and the differences tested by Fisher’s exact test. RESULTS: Statistical analyses revealed that 13 out of the 41 (32 %) variants were significantly different in frequency in our sample as compared to the EUR/ExAC cohorts. For nine variants the available level of evidence (LOE) included polymorphisms related to cyclophosphamide, tamoxifen, doxorubicin, fluorpyrimidine and paclitaxel. In particular, for trastuzumab two variants were detected: (1) rs1801274-G within FCGR2A and associated with decreased efficacy (LOE 2B); (2) rs1136201-G located within ERBB2 and associated with increased toxicity (LOE 3). Both these two variants were underrepresented in the FVG population compared to EUR/ExAC population thus suggesting a high therapeutic index of this drug in our population. Moreover, as regards fluoropyrimidines, the frequency of two polymorphisms within the DPYD gene associated with drug toxicity (e.g., rs2297595-C allele and rs3918290-T allele, LOE 2A and 1, respectively) was extremely low in FVG population thus suggesting that a larger number of FVG patients could benefit from full dosage of fluoropyrimidine therapy. CONCLUSIONS: All these findings increase the overall knowledge on the prevalence of specific variants related with breast cancer treatment responsiveness in FVG population and highlight the importance of assessing gene polymorphisms related with cancer medications in isolated communities. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12967-016-0778-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-47226802016-01-23 Pharmacogenetics driving personalized medicine: analysis of genetic polymorphisms related to breast cancer medications in Italian isolated populations Cocca, Massimiliano Bedognetti, Davide La Bianca, Martina Gasparini, Paolo Girotto, Giorgia J Transl Med Research BACKGROUND: Breast cancer is the most common cancer in women characterized by a high variable clinical outcome among individuals treated with equivalent regimens and novel targeted therapies. In this study, we performed a population based approach intersecting high-throughput genotype data from Friuli Venezia Giulia (FVG) isolated populations with publically available pharmacogenomics information to estimate the frequency of genotypes correlated with responsiveness to breast cancer treatment thus improving the clinical management of this disease in an efficient and cost effective way. METHODS: A list of 80 variants reported to be related to the efficacy or toxicity of breast cancer drugs was obtained from PharmGKB database. Fourty-one were present in FVG, 1000G European (EUR) and ExAC (Non Finnish European) databases. Their frequency was extracted using PLINK software and the differences tested by Fisher’s exact test. RESULTS: Statistical analyses revealed that 13 out of the 41 (32 %) variants were significantly different in frequency in our sample as compared to the EUR/ExAC cohorts. For nine variants the available level of evidence (LOE) included polymorphisms related to cyclophosphamide, tamoxifen, doxorubicin, fluorpyrimidine and paclitaxel. In particular, for trastuzumab two variants were detected: (1) rs1801274-G within FCGR2A and associated with decreased efficacy (LOE 2B); (2) rs1136201-G located within ERBB2 and associated with increased toxicity (LOE 3). Both these two variants were underrepresented in the FVG population compared to EUR/ExAC population thus suggesting a high therapeutic index of this drug in our population. Moreover, as regards fluoropyrimidines, the frequency of two polymorphisms within the DPYD gene associated with drug toxicity (e.g., rs2297595-C allele and rs3918290-T allele, LOE 2A and 1, respectively) was extremely low in FVG population thus suggesting that a larger number of FVG patients could benefit from full dosage of fluoropyrimidine therapy. CONCLUSIONS: All these findings increase the overall knowledge on the prevalence of specific variants related with breast cancer treatment responsiveness in FVG population and highlight the importance of assessing gene polymorphisms related with cancer medications in isolated communities. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12967-016-0778-z) contains supplementary material, which is available to authorized users. BioMed Central 2016-01-22 /pmc/articles/PMC4722680/ /pubmed/26801900 http://dx.doi.org/10.1186/s12967-016-0778-z Text en © Cocca et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Cocca, Massimiliano
Bedognetti, Davide
La Bianca, Martina
Gasparini, Paolo
Girotto, Giorgia
Pharmacogenetics driving personalized medicine: analysis of genetic polymorphisms related to breast cancer medications in Italian isolated populations
title Pharmacogenetics driving personalized medicine: analysis of genetic polymorphisms related to breast cancer medications in Italian isolated populations
title_full Pharmacogenetics driving personalized medicine: analysis of genetic polymorphisms related to breast cancer medications in Italian isolated populations
title_fullStr Pharmacogenetics driving personalized medicine: analysis of genetic polymorphisms related to breast cancer medications in Italian isolated populations
title_full_unstemmed Pharmacogenetics driving personalized medicine: analysis of genetic polymorphisms related to breast cancer medications in Italian isolated populations
title_short Pharmacogenetics driving personalized medicine: analysis of genetic polymorphisms related to breast cancer medications in Italian isolated populations
title_sort pharmacogenetics driving personalized medicine: analysis of genetic polymorphisms related to breast cancer medications in italian isolated populations
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4722680/
https://www.ncbi.nlm.nih.gov/pubmed/26801900
http://dx.doi.org/10.1186/s12967-016-0778-z
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