Sniffing out ovarian cancer early with a simple blood test

Interview and Blog by Amanda Hazeltine

Your support funds real breakthroughs. One of the beneficiaries of your support is Dr. Daniel Heller, Head of the Cancer Nanomedicine Laboratory at Memorial Sloan Kettering Cancer center. We recently had the honor of speaking with Dr. Heller about his research and how AI and nanotechnology may lead to a breakthrough in the early detection of ovarian cancer—and serve as a stepping stone toward a cure.

Watch the full interview by clicking play.

What started as a seed of an idea during a discussion between a biomedical engineer and gynecologic oncologist in a lobby, is now a promising new technology changing the ovarian cancer landscape a decade later. With a background in physical chemistry and engineering, Dr. Heller leads a lab at Memorial Sloan Kettering Cancer Center making new nanotechnologies to prevent, detect, treat and cure cancer. 

Challenges in early detection

Ovarian cancer is hard to detect early on, and is often diagnosed at later stages when it’s harder to treat. Dr. Heller and his collaborators realized that while there are some biomarkers that are useful for prognosis in ovarian cancer and monitoring care, there’s nothing that can move the bar for early detection. 

“Right now, the standard of care for ovarian cancer is that there’s no screening paradigm that’s clinically useful. If something’s suspected, there are certainly known biomarkers like CA-125 to test in the blood, and ultrasound and other techniques. But there’s no screening marker where someone could come into a doctor’s office and just get bloodwork done once a year, along with all their normal tests, to look for ovarian cancer,” said Dr. Heller. “That’s what we’re trying to make — something that can be measured easily, where a test can be done once a year. The hope is to not just make a test for current cancer, but even a preventive test.”

Using AI to train sensors to sniff out cancer

Given the limitations of known ovarian cancer biomarkers, Dr. Heller and his team realized that they shouldn’t focus on detecting existing ones, but rather work to identify cancer without needing to know specific biomarkers. The researchers set out to create sensors that can detect a whole disease state, rather than just one molecule. 

“It’s kind of analogous to how your nose works. If you smell cookies, there’s no one cookie molecule that binds to a cookie sensor in your nose, even though there are many sensors or receptors in your nose. There’s a whole mix of molecules that come from cookies when you smell them. And it’s a combination of cookie molecules and a combination of sensors in your nose. And so basically it’s making a fingerprint that gets interpreted by your brain that says cookie,” explained Dr. Heller.

Similar to how our sense of smell works, Dr. Heller’s team created sensors that can “sniff” out ovarian cancer. The sensors are made of carbon nanotubes, which are very tiny and give off different colors of fluorescent light depending on what molecules they bind to. The patterns of light are different in blood from people with ovarian cancer than from those without cancer. These patterns are then fed into a computer program that uses an artificial intelligence-type algorithm, to learn the difference between blood samples from people with ovarian cancer and those without cancer. With more data samples, the algorithm becomes more accurate at detecting cancer as it “learns.”

Preventing, detecting and treating ovarian cancer early—a paradigm shift

Dr. Heller and his team found that their technology detects ovarian cancer better than CA-125, the standard marker for ovarian cancer. Not only that, but it can also detect Stage I and II ovarian cancer. With more screening accuracy and earlier detection, ovarian cancer can be caught and treated earlier, increasing the chance for a cure.  

With additional research and refinement of the technology, there may be opportunities to also identify those who have a pre-cancerous state, before ovarian cancer develops. This technology may potentially serve as a liquid biopsy to identify those who may be at high risk of ovarian cancer.

“We don’t know 100%, but there’s a very good predictive mechanism here, and there’s preventive surgery that can really be used to prevent the onset of ovarian cancer,” said Dr. Heller.

The Teal Run theme: A new dawn in ovarian cancer research

Dr. Heller’s research offers many promises in the field of ovarian cancer—from prevention, early detection, better measurement and prediction of treatment responses, to also advancing the knowledge of ovarian cancer as a disease, and possibly a cure.

“This can also be applied to other cancers and even non-cancer diseases, because there’s nothing specific in our sensors that are specific to any markers in cancer or cancer itself,” said Dr. Heller.

The team is in the process of collecting more samples and working to validate their test, and are hoping it can become an FDA-approved test in the next couple of years, and start to be available to patients as a simple blood test.