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

Leif E. Peterson, Jaya Paranilam, Susan Xu, Federico Monzon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publication2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
DOIs
StatePublished - Dec 1 2010
Event2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010 - Barcelona, Spain
Duration: Jul 18 2010Jul 23 2010

Other

Other2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
CountrySpain
CityBarcelona
Period7/18/107/23/10

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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