The identification of the molecular basis of disease remains an important step in development of new approaches for diagnosis and treatment. Although diseases that show a simple pattern of inheritance can be studied by conventional methods of genetic analysis and gene cloning, more complex diseases that are controlled by the environment and/or by multiple genetic factors require different approaches. The development of new methods for mutation detection, as well as the optimization of existing methods, is important to studying complex diseases. Thus, we have sought to optimize the single-stranded conformation polymorphism method and develop a non-radioactive system to apply this method. For many cancer types, a percentage of cases is caused by inherited cancer syndromes. Analysis of the patients with von Hippel-Lindau disease has enabled a number of mutations in the gene to be identified and correlations made between clinical characteristics and mutation type. Patients with the nevoid basal cell carcinoma syndrome (NBCCS) suffer from basal cell carcinomas as well as developmental defects. Genetic mapping as well as physical mapping techniques have been employed to define a fine structure map of the NBCCS region. A limitation of positional cloning approaches to disease gene identification is the ability to rapidly find genes in the region of analysis. Sequences surrounding Not I restriction sites have been shown to be highly enriched for transcribed sequences. A panel of Not I-containing clones on chromosome 3 has been used to identify expressed sequences in a region commonly deleted in lung tumors. One of these genes is a new member of the mitogen- activated protein kinase-activated protein (MAP) family of MAP kinase substrates.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Intramural Research (Z01)
Project #
1Z01CP005678-04
Application #
3752726
Study Section
Project Start
Project End
Budget Start
Budget End
Support Year
4
Fiscal Year
1994
Total Cost
Indirect Cost
Name
Division of Cancer Epidemiology and Genetics
Department
Type
DUNS #
City
State
Country
United States
Zip Code