Publications by authors named "Adam Bogdan"

Somatic mosaicism for DNA copy-number alterations (SMC-CNAs) is defined as gain or loss of chromosomal segments in somatic cells within a single organism. As cells harboring SMC-CNAs can undergo clonal expansion, it has been proposed that SMC-CNAs may contribute to the predisposition of these cells to genetic disease including cancer. Herein, the gross genomic alterations (>500 kbp) were characterized in uninvolved mammary glandular tissue from 59 breast cancer patients and matched samples of primary tumors and lymph node metastases.

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Glioblastomas (GBs) are malignant CNS tumors often associated with devastating symptoms. Patients with GB have a very poor prognosis, and despite treatment, most of them die within 12 months from diagnosis. Several pathways, such as the RAS, tumor protein 53 (TP53), and phosphoinositide kinase 3 (PIK3) pathways, as well as the cell cycle control pathway, have been identified to be disrupted in this tumor.

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Two major types of genetic variation are known: single nucleotide polymorphisms (SNPs), and a more recently discovered structural variation, involving changes in copy number (CNVs) of kilobase- to megabase-sized chromosomal segments. It is unknown whether CNVs arise in somatic cells, but it is, however, generally assumed that normal cells are genetically identical. We tested 34 tissue samples from three subjects and, having analyzed for each tissue < or =10(-6) of all cells expected in an adult human, we observed at least six CNVs, affecting a single organ or one or more tissues of the same subject.

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To further explore the extent of structural large-scale variation in the human genome, we assessed copy number variations (CNVs) in a series of 71 healthy subjects from three ethnic groups. CNVs were analyzed using comparative genomic hybridization (CGH) to a BAC array covering the human genome, using DNA extracted from peripheral blood, thus avoiding any culture-induced rearrangements. By applying a newly developed computational algorithm based on Hidden Markov modeling, we identified 1,078 autosomal CNVs, including at least two neighboring/overlapping BACs, which represent 315 distinct regions.

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