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In the study, published in the Archives of Internal Medicine,  researchers compared tea consumption and the risk of ovarian cancer in more than  60,000 women aged 40 to 76 in Sweden.

 

The women filled out questionnaires on food and beverages they consumed  regularly; the participants were followed for about 15 years. About two-thirds  of the women said they drank tea at least once a month.

 

During the follow-up period, 301 women were diagnosed with ovarian cancer,  and researchers found tea drinking was associated with lowered ovarian cancer  risk.

 

Women who drank at least 2 cups of tea per day were half as likely to develop  ovarian cancer as nondrinkers; those who drank at least 1 cup of tea a day had a  24% lower risk.

Dr. McCollum says women can reduce their risk of ovarian cancer by having  multiple babies, breast feeding and using oral contraceptives.

 

"We've seen survival gradually extend.  The cure rate has not improved,  but the average life expectancy has become prolonged," he noted.

 

Research continues to look for early markers that a woman has ovarian cancer,  but Dr. McCollum believes finding them is still years away.

July 22, 2010 -- A newly identified genetic marker may help predict ovarian  cancer risk, Yale University researchers report online in Cancer  Research. Variations in the KRAS gene occur in one-quarter of women with  ovarian cancer, and 61% of women with ovarian cancer who have a family history  of breast and ovarian cancer.

 

"For many women out there with a  strong family history of ovarian cancer who previously have had no identified  genetic cause for their family's disease, this might be it for them," says study  researcher Joanne B. Weidhaas, MD, PhD, an associate professor of therapeutic  radiology and researcher for the Yale Cancer Center in New Haven, Conn., in a  news release. "Our findings support that the KRAS-variant is a new genetic  marker of ovarian cancer risk."

 

While BRCA1 and BRCA2 genes are known markers for breast and ovarian cancer  risk, only half of the women with a family history of these cancers tested  positive for these genes. Fully 60% of these women did test positive for the  KRAS genetic mutation, the new study shows.

 

Women with BRCA genetic mutations tend to develop ovarian cancer at younger  ages, but those with the new genetic marker tend to develop ovarian cancer after  menopause, the researchers report.

Ovarian cancer is known as a particularly lethal cancer because symptoms can  be vague and many women are not diagnosed until the cancer has already started  to spread.

 

"People are blindsided when they get ovarian cancer; they really had no  idea," Weidhaas tells WebMD. "This is a cancer where there are not a lot of  known risks so there is probably more of an inherited component and it's really  important to identify ways for us to know who is really at risk."

 

What's more, the new KRAS mutation "might predict ovarian cancer in the  general population as well," she says. "This will require a large study and  needs additional validation."

cientists at the Georgia Institute of Technology have attained very promising results on their initial investigations of a new test for ovarian cancer. Using a new technique involving mass spectrometry of a single drop of blood serum, the test correctly identified women with ovarian cancer in 100 percent of the patients tested. The results can be found online in the journal Cancer Epidemiology, Biomarkers, & Prevention Researc

Because ovarian cancer is a disease of relatively low prevalence, it’s essential that tests for it be extremely accurate. We believe we may have developed such a test,” said John McDonald, chief research scientist at the Ovarian Cancer Institute (Atlanta) and professor of biology at Georgia Tech.

The measurement step in the test, developed by the research group of Facundo Fernandez, associate professor in the School of Chemistry and Biochemistry at Tech, uses a single drop of blood serum, which is vaporized by hot helium plasma. As the molecules from the serum become electrically charged, a mass spectrometer is used to measure their relative abundance. The test looks at the small molecules involved in metabolism that are in the serum, known as metabolites. Machine learning techniques developed by Alex Gray, assistant professor in the College of Computing and the Center for the Study of Systems Biology, were then used to sort the sets of metabolites that were found in cancerous plasma from the ones found in healthy samples. Then, McDonald’s lab mapped the results between the metabolites found in both sets of tissue to discover the biological meaning of these metabolic changes.