Scientists Used Fruit Flies to Quickly Develop a Personalized Cancer Treatment for a Dying Man
Imagine a man with colorectal cancer that has spread throughout his body. His tumor is not responding to traditional chemotherapy. He needs a radically effective treatment as soon as possible and there's no time to wait for a new drug or a new clinical trial.
A plethora of novel combinations of treatments can be screened quickly on as many as 400,000 flies at once.
This was the very real, and terrifying, situation of a recent patient at Mount Sinai Medical Center in New York City. So his doctors turned to a new tactic to speed up the search for a treatment that would save him: Fruit flies.
Yes, fruit flies. Those annoying little buggers that descend on opened food containers are actually leading scientists to fully personalized cancer treatments. Oncology advances often are more about about utilizing old drugs in new combinations than about adding new drugs. But classically, the development of each new chemotherapy drug combination has required studies involving numerous patients spread over many years or decades.
With the fruit fly method, however, a novel treatment -- in the sense that a particular combination of drugs and the timing of their administration has never been used before -- is developed for each patient, almost like on Star Trek, when, faced suddenly with an unknown disease, a futuristic physician researches it and develops a cure quickly enough to save the patient's life.
How It Works
Using genetic engineering techniques, researchers produce a population of fruit fly embryos, each of which is programmed to develop a replica of the patient's cancer.
Since a lot of genetically identical fly embryos can be created, and since they hatch from eggs within 30 hours and then mature within days, a plethora of novel combinations of treatments can be screened quickly on as many as 400,000 flies at once. Then, only the regimens that are effective are administered to the patient.
Biotech entrepreneur Laura Towart, CEO of the UK- and Ireland-based company, My Personal Therapeutics, is partnering with Mount Sinai to develop and test the fruit fly tactic. The researchers recently published a paper demonstrating that the tumor of the man with metastatic colorectal cancer had shrunk considerably following the treatment, and remained stable for 11 months, although he eventually succumbed to his illness.
Open Questions
Cancer is in fact many different diseases, even if it strikes two people in the same place, and both cancers look the same under a microscope. At the level of DNA, RNA, proteins, and other molecular factors, each cancer is unique – and may require a unique treatment approach.
Determining the true impact on cancer mortality will require clinical trials involving many more patients.
"Anatomy of a cancer still plays a major role, if you're a surgeon or radiation oncologist, but the medical approach to cancer therapy is moving toward treatments that are personalized based on other factors," notes Dr. Howard McLeod, an internationally recognized expert on cancer genetics at the Moffitt Cancer Center, in Tampa, Florida. "We are also headed into an era when even the methods for monitoring patients are individualized."
One big unresolved question about the fruit fly screening approach is how effective it will be in terms of actually extending life. Determining the true impact on cancer mortality will require clinical trials involving many more patients.
Next Up
Using machine learning and artificial intelligence, Towart is now working to build a service called TuMatch that will offer rapid and affordable personalized treatment recommendations for all genetically driven cancers. "We hope to have TuMatch available to patients with colorectal/GI cancers by January 2020," she says. "We are also offering [the fruit fly approach] for patients with rare genetic diseases and for patients who are diabetic."
Are Towart's fruit flies the answer to why the man's tumor shrunk? To be sure, the definitive answer will come from further research that is expected soon, but it's also clear that, prior to the treatment, there was nothing left to do for that particular patient. Thus, although it's early in the game, there's a pretty good rationale for optimism.
A new type of cancer therapy is shrinking deadly brain tumors with just one treatment
Few cancers are deadlier than glioblastomas—aggressive and lethal tumors that originate in the brain or spinal cord. Five years after diagnosis, less than five percent of glioblastoma patients are still alive—and more often, glioblastoma patients live just 14 months on average after receiving a diagnosis.
But an ongoing clinical trial at Mass General Cancer Center is giving new hope to glioblastoma patients and their families. The trial, called INCIPIENT, is meant to evaluate the effects of a special type of immune cell, called CAR-T cells, on patients with recurrent glioblastoma.
How CAR-T cell therapy works
CAR-T cell therapy is a type of cancer treatment called immunotherapy, where doctors modify a patient’s own immune system specifically to find and destroy cancer cells. In CAR-T cell therapy, doctors extract the patient’s T-cells, which are immune system cells that help fight off disease—particularly cancer. These T-cells are harvested from the patient and then genetically modified in a lab to produce proteins on their surface called chimeric antigen receptors (thus becoming CAR-T cells), which makes them able to bind to a specific protein on the patient’s cancer cells. Once modified, these CAR-T cells are grown in the lab for several weeks so that they can multiply into an army of millions. When enough cells have been grown, these super-charged T-cells are infused back into the patient where they can then seek out cancer cells, bind to them, and destroy them. CAR-T cell therapies have been approved by the US Food and Drug Administration (FDA) to treat certain types of lymphomas and leukemias, as well as multiple myeloma, but haven’t been approved to treat glioblastomas—yet.
CAR-T cell therapies don’t always work against solid tumors, such as glioblastomas. Because solid tumors contain different kinds of cancer cells, some cells can evade the immune system’s detection even after CAR-T cell therapy, according to a press release from Massachusetts General Hospital. For the INCIPIENT trial, researchers modified the CAR-T cells even further in hopes of making them more effective against solid tumors. These second-generation CAR-T cells (called CARv3-TEAM-E T cells) contain special antibodies that attack EFGR, a protein expressed in the majority of glioblastoma tumors. Unlike other CAR-T cell therapies, these particular CAR-T cells were designed to be directly injected into the patient’s brain.
The INCIPIENT trial results
The INCIPIENT trial involved three patients who were enrolled in the study between March and July 2023. All three patients—a 72-year-old man, a 74-year-old man, and a 57-year-old woman—were treated with chemo and radiation and enrolled in the trial with CAR-T cells after their glioblastoma tumors came back.
The results, which were published earlier this year in the New England Journal of Medicine (NEJM), were called “rapid” and “dramatic” by doctors involved in the trial. After just a single infusion of the CAR-T cells, each patient experienced a significant reduction in their tumor sizes. Just two days after receiving the infusion, the glioblastoma tumor of the 72-year-old man decreased by nearly twenty percent. Just two months later the tumor had shrunk by an astonishing 60 percent, and the change was maintained for more than six months. The most dramatic result was in the 57-year-old female patient, whose tumor shrank nearly completely after just one infusion of the CAR-T cells.
The results of the INCIPIENT trial were unexpected and astonishing—but unfortunately, they were also temporary. For all three patients, the tumors eventually began to grow back regardless of the CAR-T cell infusions. According to the press release from MGH, the medical team is now considering treating each patient with multiple infusions or prefacing each treatment with chemotherapy to prolong the response.
While there is still “more to do,” says co-author of the study neuro-oncologist Dr. Elizabeth Gerstner, the results are still promising. If nothing else, these second-generation CAR-T cell infusions may someday be able to give patients more time than traditional treatments would allow.
“These results are exciting but they are also just the beginning,” says Dr. Marcela Maus, a doctor and professor of medicine at Mass General who was involved in the clinical trial. “They tell us that we are on the right track in pursuing a therapy that has the potential to change the outlook for this intractable disease.”
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.