Combination of phenotype and polygenic risk score in breast cancer risk evaluation in the Spanish population: a case –control study
Abstract Background In recent years, the identification of genetic and phenotypic biomarkers of cancer for prevention, early diagnosis and patient stratification has been a main objective of research in the field. Different multivariable models that use biomarkers have been proposed for the evaluati...
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doaj-a5825554e335470dbaea0b65a5bddec72020-11-25T04:04:38ZengBMCBMC Cancer1471-24072020-11-0120111010.1186/s12885-020-07584-9Combination of phenotype and polygenic risk score in breast cancer risk evaluation in the Spanish population: a case –control studyJ. C. Triviño0A. Ceba1E. Rubio-Solsona2D. Serra3I. Sanchez-Guiu4G. Ribas5R. Rosa6M. Cabo7L. Bernad8G. Pita9A. Gonzalez-Neira10G. Legarda11J. L. Diaz12A. García-Vigara13A. Martínez-Aspas14M. Escrig15B. Bermejo16P. Eroles17J. Ibáñez18D. Salas19A. Julve20A. Cano21A. Lluch22R. Miñambres23J. Benitez24Sistemas GenómicosSistemas GenómicosSistemas GenómicosSistemas GenómicosSistemas GenómicosSistemas GenómicosSistemas GenómicosSistemas GenómicosSistemas GenómicosSpanish National Genotyping Center (CEGEN)Spanish National Genotyping Center (CEGEN)Sistemas GenómicosSistemas GenómicosObstetrics and Gynecology Service, Hospital Clínico Universitario – INCLIVAObstetrics and Gynecology Service, Hospital Clínico Universitario – INCLIVADepartment of Hematology and Medical Oncology, Hospital Clínico Universitario de Valencia, University of Valencia, INCLIVA Biomedical Research InstituteDepartment of Hematology and Medical Oncology, Hospital Clínico Universitario de Valencia, University of Valencia, INCLIVA Biomedical Research InstituteDepartment of Hematology and Medical Oncology, Hospital Clínico Universitario de Valencia, University of Valencia, INCLIVA Biomedical Research InstituteGeneral Directorate Public Health, Valencian CommunityGeneral Directorate Public Health, Valencian CommunityRadiology Service, Hospital Clínico Universitario – INCLIVAObstetrics and Gynecology Service, Hospital Clínico Universitario – INCLIVADepartment of Hematology and Medical Oncology, Hospital Clínico Universitario de Valencia, University of Valencia, INCLIVA Biomedical Research InstituteSistemas GenómicosSpanish National Genotyping Center (CEGEN)Abstract Background In recent years, the identification of genetic and phenotypic biomarkers of cancer for prevention, early diagnosis and patient stratification has been a main objective of research in the field. Different multivariable models that use biomarkers have been proposed for the evaluation of individual risk of developing breast cancer. Methods This is a case control study based on a population-based cohort. We describe and evaluate a multivariable model that incorporates 92 Single-nucleotide polymorphisms (SNPs) (Supplementary Table S1) and five different phenotypic variables and which was employed in a Spanish population of 642 healthy women and 455 breast cancer patients. Results Our model allowed us to stratify two groups: high and low risk of developing breast cancer. The 9th decile included 1% of controls vs 9% of cases, with an odds ratio (OR) of 12.9 and a p-value of 3.43E-07. The first decile presented an inverse proportion: 1% of cases and 9% of controls, with an OR of 0.097 and a p-value of 1.86E-08. Conclusions These results indicate the capacity of our multivariable model to stratify women according to their risk of developing breast cancer. The major limitation of our analysis is the small cohort size. However, despite the limitations, the results of our analysis provide proof of concept in a poorly studied population, and opens up the possibility of using this method in the routine screening of the Spanish population.http://link.springer.com/article/10.1186/s12885-020-07584-9Polygenic risk scorePredictive testIdentification of high risk womenRisk algorithms |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
J. C. Triviño A. Ceba E. Rubio-Solsona D. Serra I. Sanchez-Guiu G. Ribas R. Rosa M. Cabo L. Bernad G. Pita A. Gonzalez-Neira G. Legarda J. L. Diaz A. García-Vigara A. Martínez-Aspas M. Escrig B. Bermejo P. Eroles J. Ibáñez D. Salas A. Julve A. Cano A. Lluch R. Miñambres J. Benitez |
spellingShingle |
J. C. Triviño A. Ceba E. Rubio-Solsona D. Serra I. Sanchez-Guiu G. Ribas R. Rosa M. Cabo L. Bernad G. Pita A. Gonzalez-Neira G. Legarda J. L. Diaz A. García-Vigara A. Martínez-Aspas M. Escrig B. Bermejo P. Eroles J. Ibáñez D. Salas A. Julve A. Cano A. Lluch R. Miñambres J. Benitez Combination of phenotype and polygenic risk score in breast cancer risk evaluation in the Spanish population: a case –control study BMC Cancer Polygenic risk score Predictive test Identification of high risk women Risk algorithms |
author_facet |
J. C. Triviño A. Ceba E. Rubio-Solsona D. Serra I. Sanchez-Guiu G. Ribas R. Rosa M. Cabo L. Bernad G. Pita A. Gonzalez-Neira G. Legarda J. L. Diaz A. García-Vigara A. Martínez-Aspas M. Escrig B. Bermejo P. Eroles J. Ibáñez D. Salas A. Julve A. Cano A. Lluch R. Miñambres J. Benitez |
author_sort |
J. C. Triviño |
title |
Combination of phenotype and polygenic risk score in breast cancer risk evaluation in the Spanish population: a case –control study |
title_short |
Combination of phenotype and polygenic risk score in breast cancer risk evaluation in the Spanish population: a case –control study |
title_full |
Combination of phenotype and polygenic risk score in breast cancer risk evaluation in the Spanish population: a case –control study |
title_fullStr |
Combination of phenotype and polygenic risk score in breast cancer risk evaluation in the Spanish population: a case –control study |
title_full_unstemmed |
Combination of phenotype and polygenic risk score in breast cancer risk evaluation in the Spanish population: a case –control study |
title_sort |
combination of phenotype and polygenic risk score in breast cancer risk evaluation in the spanish population: a case –control study |
publisher |
BMC |
series |
BMC Cancer |
issn |
1471-2407 |
publishDate |
2020-11-01 |
description |
Abstract Background In recent years, the identification of genetic and phenotypic biomarkers of cancer for prevention, early diagnosis and patient stratification has been a main objective of research in the field. Different multivariable models that use biomarkers have been proposed for the evaluation of individual risk of developing breast cancer. Methods This is a case control study based on a population-based cohort. We describe and evaluate a multivariable model that incorporates 92 Single-nucleotide polymorphisms (SNPs) (Supplementary Table S1) and five different phenotypic variables and which was employed in a Spanish population of 642 healthy women and 455 breast cancer patients. Results Our model allowed us to stratify two groups: high and low risk of developing breast cancer. The 9th decile included 1% of controls vs 9% of cases, with an odds ratio (OR) of 12.9 and a p-value of 3.43E-07. The first decile presented an inverse proportion: 1% of cases and 9% of controls, with an OR of 0.097 and a p-value of 1.86E-08. Conclusions These results indicate the capacity of our multivariable model to stratify women according to their risk of developing breast cancer. The major limitation of our analysis is the small cohort size. However, despite the limitations, the results of our analysis provide proof of concept in a poorly studied population, and opens up the possibility of using this method in the routine screening of the Spanish population. |
topic |
Polygenic risk score Predictive test Identification of high risk women Risk algorithms |
url |
http://link.springer.com/article/10.1186/s12885-020-07584-9 |
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