Population Testing to Prevent Gynecologic Cancers

Podcast

Dr. Ranjit Manchanda speaks with Cancer Network about using population testing to predict and prevent gynecologic cancers.

Ahead of the 12th Biennial Ovarian Cancer Research Symposium, being held September 13–15 at the University of Washington in Seattle, we are speaking with Dr. Ranjit Manchanda, MD, MRCOG, PhD, a clinical senior lecturer and consultant gynecological oncologist at the Barts Cancer Institute, which is part of the University of London in the United Kingdom. Manchanda studies ways to risk stratify patients with gynecological cancers to both predict the onset of these tumors and to help prevent them. At the meeting, he will give a talk titled “Population testing for ovarian cancer gene mutations for primary prevention.”

-Interviewed by Anna Azvolinsky

 

Cancer Network: First, specifically for ovarian cancer, what are the major questions on primary prevention? What do we know, if anything, about potential ways to prevent this tumor type?

Dr. Manchanda: The most effective way to prevent ovarian cancer is through an operation or surgical procedure, which involves removal of both the tubes and the ovaries once a woman has completed her family. This is typically done for women who are at high-risk of developing ovarian cancer, and it is often done through keyhole surgery and is effective in preventing ovarian cancer.

Taking a contraceptive pill for about 5 years can also help decrease the risk of ovarian cancer. These are two important ways of preventing ovarian cancer that are currently used. A relatively new method is removal of the tubes alone, which is called a salpingectomy. In a recent study of high-risk women, we are looking at a two-step procedure which is removing the fallopian tubes as a first step and the ovaries later to prevent ovarian cancer.  The removal of ovaries in premenopausal women can have detrimental effects on long-term health, including osteoporosis and risk of cardiovascular disease, neurocognitive impact, and sexual dysfunction.

Cancer Network: What exactly is the population testing approach in cancer?

Dr. Manchanda: The way we identify people who are at increased risk of developing ovarian cancer currently in clinical practice is based on taking someone’s family history of cancer, which is usually a three-generation family history. Using the descriptions of the cancers in the family and the age of onset, we calculate the probability of the individual carrying a cancer-risk gene. If individuals with a family history of cancer fit these criteria or have cancer themselves, a number of them have access to gene testing.

The common genes that are tested are the BRCA1 and BRCA2 genes, which are associated with about a 40% and 17% risk of developing ovarian cancer over a lifetime, respectively. Additionally, some newer genes have been identified including RAD51C, RAD51D, and BRIP1, each of which has an associated ovarian cancer risk of between 6%–11%.

This gene testing based on family history is offered in clinical practice; however, a number of people may not carry a strong family history of cancer but may carry a faulty gene, and so this system is not perfect and can miss up to half of the people who are at risk. The only way to identify these people who don’t fill the family criteria is by offering testing to everyone. Hence, we propose population testing. [Which means] testing everyone to identify additional people who are at risk to more effectively prevent cancer in the future in many more individuals.

Cancer Network: Could you describe the specific population approach you and your colleagues use for your studies of primary prevention of ovarian cancer in the context of what data you will present at the conference?

Dr. Manchanda: We undertook a randomized, controlled trial in London in a Jewish population. A lot of the population studies have been done initially in the Jewish population and in London. Our trial compared a clinical criteria-based approach to population testing for the BRCA gene mutations in an unselected population. We showed that it is possible to do

population-based testing outside the hospital in a community-based setting and that this was acceptable and feasible and did not cause detrimental psychological or quality-of-life consequences.

Over 50% of people we identified as being at-risk would not have been identified by standard clinical family criteria. We also undertook a cost-effectiveness analysis and showed that this would be cost-saving in most scenarios and not just cost-effective which means it would save lives and money.

We also did an analysis for both the UK and the US healthcare systems which showed that this population-based approach would be cost-effective in both of these healthcare systems. Studies done in Israel and in Canada have also demonstrated the feasibility, acceptability, and utility of population-based testing among the Jewish female population.

We’ve also done a study in London evaluating current rates of testing across a large, 16 million population and found that only a very small proportion of BRCA carriers have been identified since this genetic testing has been going on. If we continue to identify those at risk at current rates in this clinical, family-history focused way, we will never be able to identify all of the people who are at risk. The current system has a number of limitations, and the way that the genetic testing technology has progressed and the falling costs of testing enable us, technically, to be able to do large-scale testing on a population basis. This provides the opportunity to identify far more people at risk and to offer them options of primary prevention.

We are currently undertaking a pilot study of population testing for ovarian cancer in a primary care setting in London that is ongoing and will be reported in the next year or so. We have also done a cost-effectiveness analysis and evaluated costs and consequences of doing population testing in the UK and US populations for breast and ovarian cancer gene mutations and found that this approach could save thousands more lives and prevent thousands of cancers in both healthcare systems. So, we’ve done a number of such population testing studies over the last 8–9 years.

Cancer Network: In your talk, you’re going to discuss ovarian cancer gene mutations that could confer risk of developing ovarian cancer. What do we know so far about what mutations do confer risk of developing this type of cancer, and you did mention that there are certain groups of women that are more likely to develop ovarian cancer?

Dr. Manchanda: The most common and most widely studied genes are the BRCA1 and BRCA2 genes. The BRCA1 gene confers about a 40% risk of developing ovarian cancer over a woman’s lifetime, and the BRCA2 gene confers a 17% risk. The newer genes are RAD51C, RAD51D, and BRIP1, which have, depending on the gene, a risk of about 6%–11% of developing ovarian cancer. It’s about 6% with the BRIP1 gene and closer to 11% for the RAD genes. Then there are other genes, including the Lynch Syndrome genes, which have about a 6%–14% risk of developing ovarian cancer. These are the current, well-known, moderate- and high-risk gene mutations. There are a number of other low-penetrant genetic variants, known as SNPS [single nucleotide polymorphisms], which have been identified and linked to ovarian cancer, and these are now being used in risk models with epidemiological factors that can also impact ovarian cancer risk.

The models are being built to predict ovarian cancer risk and to stratify the population. We have been involved in this with other colleagues. The aim is to ultimately have validated risk models that can use a large number of these factors to stratify people into different risk categories and identify those above a certain risk threshold that could benefit from primary prevention of ovarian cancer. Additionally, we defined the risk threshold for offering primary prevention, have published a few papers on this [topic], and feel that it is justifiable over about 5% lifetime risk of ovarian cancer.

Cancer Network: Thank you so much for joining us today Dr. Manchada.

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