Underscoring Genetic Testing’s Role in Enhancing Ovarian Cancer Care

Undergoing genetic testing for ovarian cancer could potentially be lifesaving… for more than just the patient undergoing treatment.

In a conversation with CancerNetwork®, Melissa K. Frey, MD, an associate professor of Obstetrics and Gynecology in the Division of Gynecologic Oncology and director of the Genetics and Personalized Cancer Prevention Program at Weill Cornell Medicine, underscored the role of genetic testing in enhancing ovarian care. She discussed how covering barriers to universal testing strategies laid out by the Society for Gynecological Oncology (SGO) impacts treatment selection and outcomes for patients, and how artificial intelligence (AI) may be used to transform genetic testing and counseling.

She began by highlighting a myriad of barriers associated with the adoption of universal genetic testing in gynecologic oncology, pointing out that more than half of patients may not undergo genetic testing due to time-related logistical concerns, financial toxicities, genetic discrimination, and the implications it may have for family members. Frey explained that genetic testing can be lifesaving for the relatives of a patient, in which timely genetic testing can help identify mutations that may heighten risks for certain cancers, but that communicating this information may be cumbersome for patients.

Furthermore, Frey covered the impact of genetic testing on treatment selection, with a primary focus on PARP inhibition, as well as how the integration of these services has impacted outcomes among patients with ovarian cancer. Specifically, she highlighted an increase in the number of long-term survivors of ovarian cancer, which begets increased testing for subsequent cancers, such as breast cancer, which is at an elevated risk among those with identified BRCA1 mutations.

She concluded by outlining the landscape for the integration of AI in genetic testing and counseling, which may help automate and streamline processes to reduce the burden for practitioners. Frey identified AI’s utility in increasing accessibility to these services for patients, and in scaling communication to relatives regarding mutational risks identified when a patient undergoes genetic testing.

CancerNetwork: What are the most significant barriers to achieving this universal testing in clinical practice, and what strategies have been most effective in overcoming them?

Frey: For several years, we have understood that there is a tremendously high genetic contribution to ovarian cancer; approximately 1 in 5 ovarian cancer cases can be linked directly to a germline causative mutation, and, as a result, several societies, including the SGO, have recommended universal genetic testing for [patients with] ovarian cancer.

Unfortunately, the best data we have still suggests that fewer than 50% of patients complete this genetic testing as part of their ovarian cancer management, which begs the question: “Why?”

There are several barriers, the first of which is that genetic testing often requires a separate appointment, meaning that a patient must be referred to a genetic counselor or a genetics clinic, and there is a drop off in patients who are eligible and who [receive] the care. For this, one of the best solutions has been what's called “mainstreaming”.

Mainstreaming is the process whereby non-traditionally considered genetics clinicians can provide genetic testing so that a patient does not have to see a genetic counselor or a genetics clinician to get their genetic testing. It can be done by their gynecological oncologist or their medical oncologist or a nurse practitioner/physician assistant who is working in their oncology office. That way, the genetic testing becomes part of their care for ovarian cancer, like their surgery and/or their chemotherapy. That's one of the biggest barriers and one of the best solutions.

That is not the only barrier, and another important thing to note is financial toxicity. While genetic testing is covered for most patients with ovarian cancer, there are patients who do not have insurance or cannot meet a copay or deductible for their genetic testing. I think it's important to consider this, but also to counsel providers and patients that the previous cost of genetic testing, which was several thousands of dollars, has come down dramatically. If a provider [or] a patient thinks this is going to be several thousand dollars, we can counsel them that, in general, now, insurance covers most patients, and most genetic testing companies have an out-of-pocket option for $250 or less. That may change or overcome that barrier.

There's also concern about genetic discrimination. It's important that providers can talk to patients about [the Genetic Information Nondiscrimination Act (GINA)] or the law that covers genetic discrimination, to be aware of what this law covers and what it does not. There is legal protection against genetic discrimination for health insurance and for employment status, but, unfortunately, this does not cover luxury insurances, including life insurance, long-term care, [or] disability insurance. That may be a real concern for patients, although it also encourages providers to discuss with patients [that] having an ovarian cancer diagnosis is probably a bigger barrier to getting some of those luxury insurances than genetic testing.

Finally, concerns about implications for family members [can emerge]. Genetic testing is an interesting test in that it is informative for the patient sitting in front of you, but it also has critical implications for family members. If we find a mutation like a BRCA1 or BRCA2 mutation in a person in front of us, we can then predict that their first-degree relatives––parents, siblings, children–––will have a 50/50 chance of also carrying the same mutation. While that can be lifesaving information, it can also be a tremendous stress or burden on the patient sitting in front of you to have to communicate that information. There's often guilt associated with that communication, and then to help facilitate their relatives’ testing. Providers should [be aware] that these are barriers and think about ways that they can counsel patients on this and also participate in family cascade testing.

How do genetic testing results impact treatment selection for ovarian cancer?

This is, at the current state, really about sensitivity to the class of drugs called PARP inhibitors. We now understand that patients who have mutations, either germline or somatic, in the pathway that includes BRCA1 and BRCA2, but also other genes, are exquisitely sensitive to PARP inhibitors. This is through the process of synthetic lethality, where you have loss of the BRCA1 or BRCA2 or related mutation at the same time as the blocking of PARP with a medication. Those two pieces become lethal to the cell.

That's why this information is important for ovarian cancer management. We also know that some mutations can predict responsiveness to [platinum-based] chemotherapies. As we move forward in the age of personalized precision medicine, it is going to become increasingly important to understand the unique genetic profile of a tumor and of a patient, to select the best treatments. Hopefully, PARP is just the beginning of what is going to be more individualized patient treatment.

How has the integration of genetic counseling and testing services improved outcomes or patient care for those with ovarian cancer?

Knowledge of a genetic mutation impacts treatment, so the better a clinic is able to embed genetic services into their clinic to maximize genetic testing or participate in mainstreaming, where the patient can access genetic testing, even without a genetics professional, will allow for more patients to get tested. Our goal, again, is universal testing. The goal is for 100% of [patients with] ovarian cancer to be offered genetic testing. The closer we can get to that, the better we are going to be able to offer patients the appropriate, personalized treatment.

I would also argue that we are getting better at treating ovarian cancer, and as a result, we have more long-term survivors. It's not only important to use genetic information to treat a tumor, but also to then consider a patient's health after their ovarian cancer treatment and to risk-stratify patients for other diseases, most commonly breast cancer. Patients who are at increased risk of ovarian cancer because of a BRCA1 or BRCA2 mutation are also going to have significantly elevated lifetime risk for breast cancer. These are patients who, when they complete their ovarian cancer treatment, can also consider enhanced breast cancer screening.

I think we will get better at additional screening, for example, pancreatic cancer screening and skin cancer screening, and all things that we are learning more about [when] trying to better understand the association with genetic mutations.

How do you see AI transforming genetic counseling and testing for ovarian cancer in the next 5 to 10 years?

Technology in general, and certainly, artificial intelligence, is being used to improve and streamline many aspects of medical care. I would argue that genetic testing is a great opportunity for the integration of this type of technology because if we think of one of the biggest barriers to delivering genetic medicine [and] completing genetic testing, it is access to a genetics professional to perform a risk assessment on a patient to perform pre- and post-test counseling.

We are [actively] working on it, and my group has done research in allowing some of that work to be done by interactive chatbots or digital risk assessment platforms. Ideally, instead of sending all patients from their oncology clinic to a genetics clinic, a patient could interact with a chatbot whereby [much] of the counseling can be automated. Patients can understand their risk in the setting of their ovarian cancer, but also import pertinent personal and family history to get a full cancer risk assessment.

In my clinic, we found that if we did a cancer risk assessment on all our [patients in] gynecologic oncology, approximately 1 in 5, in addition to their gynecologic cancer, also had a significantly elevated risk for breast cancer. This is not the sort of thing we are thinking about when we're actively treating a patient for a gynecologic cancer. With the understanding that appointment time is limited, we must prioritize the cancer. But if we could have technology easily take on some of this genetic risk assessment and genetic counseling, we could do more with our visits and arm patients with information that can help them and their relatives. We can lessen the barrier of access to genetic professionals by using technology––AI interactive chatbots––and it does not end with the patient sitting in front of you. We could then expand that information to relatives.

My group is also working on chatbots, or natural language processing tools, to scale communication with relatives. Instead of asking our patient to call all their relatives to explain what a BRCA1 mutation is, we have created a chat that can be sent directly from our patient to their relatives. It can explain the mutation that lives in the family. Through AI, the chat can be, not only interactive, but it can also help address what the relative or patient is understanding [or] not understanding, adjust to their specific level of education and understanding about health and health literacy, and then not only inform relatives and patients about their risk, but also loop into local resources so that they can seek out genetic testing in a way that is accessible. There is a tremendous opportunity for AI and technology in the world of genetics.

Reference

Gressel GM, Frey MK, Norquist B, Senter L, Blank SV, Urban RR. Germline and somatic testing for ovarian cancer: an SGO clinical practice statement. Gynecol Oncol. 2024;181:170-178. doi:10.1016/j.ygyno.2023.12.010