Dissecting the genetic complexity of human 6p deletion syndromes by using a region-specific, phenotype-driven mouse screen.

Monosomy of the human chromosome 6p terminal region results in a variety of congenital malformations that include brain, craniofacial, and organogenesis abnormalities. To examine the genetic basis of these phenotypes, we have carried out an unbiased functional analysis of the syntenic region of the mouse genome (proximal Mmu13). A genetic screen for recessive mutations in this region recovered thirteen lines with phenotypes relevant to a variety of clinical conditions.

Genetic analysis of three-dimensional shape of mouse lung tumors reveals eight lung tumor shape-determining (Ltsd) loci that are associated with tumor heterogeneity and symmetry.

Most lung tumor linkage studies focus on identifying loci that confer susceptibility or resistance irrespective of the tumor types developed. However, different mouse strains develop different types of lung tumors. A major obstacle for genetic studies of these differences is the lack of reproducible, quantitative, and uniform assessment of tumor type.

Ptprj is a candidate for the mouse colon-cancer susceptibility locus Scc1 and is frequently deleted in human cancers.

Only a small proportion of cancers result from familial cancer syndromes with Mendelian inheritance. Nonfamilial, 'sporadic' cancers, which represent most cancer cases, also have a significant hereditary component, but the genes involved have low penetrance and are extremely difficult to detect. Therefore, mapping and cloning of quantitative trait loci (QTLs) for cancer susceptibility in animals could help identify homologous genes in humans.

Complexity of lung cancer modifiers: mapping of thirty genes and twenty-five interactions in half of the mouse genome.

Background: Numerous low-penetrance genes control susceptibility to cancer in experimental animals, but the overall genetic information on this group of genes (i.e., number of loci and their mutual interactions) is missing.

Three-dimensional patterns of lung tumor growth: association with tumor heterogeneity.

Most histological Classifications of lung tumors assess information derived from 2-dimensional surfaces. However, tumors grow in 3 dimensions in a variety of architectural patterns that possibly reflect the histological type or progresssion status of the tumor. A new mathematically derived variable (Rratio) is presented, that assesses the overall 3-dimensional shape of a tumor and classifies tumors based on their sphericality.