Cancer gene mutations are found in about one percent of the total general population, occurring more frequently than previously thought, and may be associated with various types of cancers, according to researchers at Yale School of Medicine.
Published in the December 6 Journal of the National Cancer Institute (JNCI), the study looked for the presence and rate of BRCA 1 and BRCA 2 mutations in a population of women with newly diagnosed ovarian cancer. They screened not only for the most common mutations but also for variants that may be more rare or difficult to distinguish. They then calculated the incidence of those variants in the general population and in individuals with family members who have had cancer.Previous research has shown that lifetime risks for breast, ovarian and other cancers are elevated for people carrying the BRCA1/2 mutations. The Yale team found that the lifetime risk to age 80 is not the same for all mutations and some mutations have higher and some lower risks for developing cancers.
“The exact nature of the level of risk for the particular mutations needs to be further explored,” said lead researcher Harvey Risch, M.D., professor in the Division of Chronic Disease Epidemiology in the Department of Epidemiology and Public Health at Yale School of Medicine. “This study is an important first step in that direction.”
Risch and his co-authors screened 1,171 women in Ontario, Canada with ovarian cancer and assessed their risk of cancer based on whether or not they carried a mutation. The women were then asked about cancers among their 8,680 first-degree relatives—their parents, siblings and children.
“We found that cancer risk differed for each gene according to the mutation’s position in the gene,” said Risch, who is also a member of the Yale Cancer Center. “When choosing which individuals to screen for mutations, we should consider all kinds of cancers among family members, not just breast and ovary and not just cancers in females.”
Risch and his team will follow up the study with a larger population sample in order to better understand the individual mutations and their differences.
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