Mechanisms of mutagenisis in 'hot spots'causing cancer

University Of Montana, Missoula MT

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Abstract

DESCRIPTION (provided by applicant): In humans, characteristic DNA sequence motifs and 'hot spots' are frequently associated with mutational events leading to genetic diseases such as dwarfism (achondroplasia) and Apert's syndrome. Short sequences of DNA repeats, called microsatellites, generate instability in colon cancer, and T-G repeats and an ATGGTC hexamer are involved in breaks of hybrid genes in liposarcoma and leukemia. Some skin cancer cell lines harbor frameshift mutations in the hRAD30 gene, and over 35% of the transition mutations in haemophilias or retinoblastoma cancers occur at C-G sites at which C-to-T transitions occur. In both humans and microbes these mutations originate preferentially on the single-stranded non-transcribed strand, which is 100-times more vulnerable to mutation than dsDNA. Thus, transcription is implicated as a cause of these mutations. DNA secondary structures are also implicated, since hot spots in microbes and certain cancers are known to be associated with these structures. They are mutagenic precursors because they can contain repeat sequences susceptible to strand slippage (frameshifts) or inverted repeats that tend to form stem-loop structures containing vulnerable mispaired or unpaired bases. Exposure to stresses such as reactive oxygen species, pollutants and heavy metals could cause mutations resulting in cancer via direct effects on supercoiling and secondary structures. We will use a microbial model system to determine the mechanisms by which gene transcription and supercoiling triggered by various forms of stress increase mutation rates specifically in the activated genes. We will determine the effects of activators and supercoiling on transcription initiation and pausing, examine predicted stem-loop structures in both transcribed and non-transcribed strands, determine whether antisense DNA to the coding strand will protect genes from mutations, and modify sequences in stem-loop structures to examine predicted effects on mutation rates.