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

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

doi:10.1109/IJCNN.2010.5596665

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 proceeding › Conference 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 language	English (US)
Title of host publication	2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
DOIs	https://doi.org/10.1109/IJCNN.2010.5596665
State	Published - Dec 1 2010
Event	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010 - Barcelona, Spain Duration: Jul 18 2010 → Jul 23 2010

Other

Other	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
Country/Territory	Spain
City	Barcelona
Period	7/18/10 → 7/23/10

ASJC Scopus subject areas

Software
Artificial Intelligence

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Genome-wide germline single nucleotide polymorphisms for cancer classification in the Framingham Heart Study. / Peterson, Leif E.; Paranilam, Jaya; Xu, Susan et al.

2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010. 2010. 5596665.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Peterson, LE, Paranilam, J, Xu, S & Monzon, F 2010, Genome-wide germline single nucleotide polymorphisms for cancer classification in the Framingham Heart Study. in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010., 5596665, 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010, Barcelona, Spain, 7/18/10. https://doi.org/10.1109/IJCNN.2010.5596665

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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.",

author = "Peterson, {Leif E.} and Jaya Paranilam and Susan Xu and Federico Monzon",

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N2 - 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.

AB - 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.

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

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