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Thompson, J. F.

Publications and source records attributed to Thompson, J. F..

2 recordsLinked to original sources

SNP Selection and Concordance in Consumer Genetics Testing

The use of Direct To Consumer (DTC) genetic testing for predicting health risks and a variety of other phenotypes has been extensively discussed. Additionally, there have been wide ranging discourses on privacy and ethical concerns. Much less attention has been paid to what most people actually use DTC testing for: ancestry determination. Furthermore, comparison of the platforms used by different companies and how they have chosen SNPs to address the questions of health and ancestry have not been broadly reported. When SNPs across three genotyping platforms are compared, only 16-18% of SNPs with reported genotypes are shared across all platforms. Only 110,051 of the more than 600,000 SNPs are called on all three panels examined (Ancestry, 23andMe and MyHeritage). SNPs genotyped on all platforms are highly concordant with only two SNPs having discordant calls. When the SNPs unique to a single panel are examined, it is apparent that each company has its own strategy for choosing SNPs. When each platform is examined, the unique SNPs have different frequencies, ethnic selectivities, and chromosomal locations. Because each company separates the world into different, overlapping geographical regions, it is impossible to do an exact comparison of ancestry results. Factoring in the ways the regions overlap, congruent results are generated for the major contributors to ancestry.

genomics

Epigenetic Profiling for the Molecular Classification of Metastatic Brain Tumors

Optimal treatment of brain metastases is often hindered by limitations in diagnostic capabilities. To meet these challenges, we generated genome-scale DNA methylomes of the three most frequent types of brain metastases: melanoma, breast, and lung cancers (n=96). Using supervised machine learning and integration of multiple DNA methylomes from normal, primary, and metastatic tumor specimens (n=1,860), we unraveled epigenetic signatures specific to each type of metastatic brain tumor and constructed a three-step DNA methylation-based classifier (BrainMETH) that categorizes brain metastases according to the tissue of origin and therapeutically-relevant subtypes. BrainMETH predictions were supported by routine histopathologic evaluation. We further characterized and validated the most predictive genomic regions in a large cohort of brain tumors (n=165) using quantitative methylation-specific PCR. Our study highlights the importance of brain tumor-defining epigenetic alterations, which can be utilized to further develop DNA methylation profiling as a critical tool in the histomolecular stratification of patients with brain metastases.

cancer biology