Genome-wide germline single nucleotide polymorphisms for cancer classification in the Framingham Heart Study

Author

Peterson, Leif ; Paranilam, Jaya ; Xu, Jiaqiong ; Monzon, Federico

Author_Institution

Center for Biostat., Methodist Hosp. Res. Inst., Houston, TX, USA

fYear

2010

fDate

18-23 July 2010

Firstpage

1

Lastpage

7

Abstract

We identified 90 germline single nucleotide polymorphisms (SNPs) that were informative for discriminative analysis of 9 major cancers among genotyped Framingham Heart Study participants. Support vector machines resulted in the greatest classification performance, which was in the range of 70-100%. The germline SNPs identified are based on DNA from peripheral blood lymphocytes obtained during non-invasive blood draws, and unlike SNPs in tumor DNA, may not be functionally related to tumor characteristics. Further validation studies are required in order to understand the role of the seeding, genetic selection, and lifetime cumulative effects of these germline SNPs in cancer development.

Keywords

DNA; biology computing; blood; cancer; genomics; medical computing; support vector machines; tumours; DNA; Framingham heart study; cancer classification; discriminative analysis; genome-wide germline single nucleotide polymorphisms; noninvasive blood draws; peripheral blood lymphocytes; support vector machines; tumor characteristics; Bioinformatics; Biological cells; Cancer; DNA; Genomics; Kernel; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks (IJCNN), The 2010 International Joint Conference on

Conference_Location

Barcelona

ISSN

1098-7576

Print_ISBN

978-1-4244-6916-1

Type

conf

DOI

10.1109/IJCNN.2010.5596665

Filename

5596665