Scientists Just Started Testing a New Class of Drugs to Slow--and Even Reverse--Aging
Imagine reversing the processes of aging. It's an age-old quest, and now a study from the Mayo Clinic may be the first ray of light in the dawn of that new era.
The immune system can handle a certain amount of senescence, but that capacity declines with age.
The small preliminary report, just nine patients, primarily looked at the safety and tolerability of the compounds used. But it also showed that a new class of small molecules called senolytics, which has proven to reverse markers of aging in animal studies, can work in humans.
Aging is a relentless assault of chronic diseases including Alzheimer's, cardiovascular disease, diabetes, and frailty. Developing one chronic condition strongly predicts the rapid onset of another. They pile on top of each other and impede the body's ability to respond to the next challenge.
"Potentially, by targeting fundamental aging processes, it may be possible to delay or prevent or alleviate multiple age-related conditions and many diseases as a group, instead of one at a time," says James Kirkland, the Mayo Clinic physician who led the study and is a top researcher in the growing field of geroscience, the biology of aging.
Getting Rid of "Zombie" Cells
One element common to many of the diseases is senescence, a kind of limbo or zombie-like state where cells no longer divide or perform many regular functions, but they don't die. Senescence is thought to be beneficial in that it inhibits the cancerous proliferation of cells. But in aging, the senescent cells still produce molecules that create inflammation both locally and throughout the body. It is a cycle that feeds upon itself, slowly ratcheting down normal body function and health.
Disease and harmful stimuli like radiation to treat cancer can also generate senescence, which is why young cancer patients seem to experience earlier and more rapid aging. The immune system can handle a certain amount of senescence, but that capacity declines with age. There also appears to be a threshold effect, a tipping point where senescence becomes a dominant factor in aging.
Kirkland's team used an artificial intelligence approach called machine learning to look for cell signaling networks that keep senescent cells from dying. To date, researchers have identified at least eight such signaling networks, some of which seem to be unique to a particular type of cell or tissue, but others are shared or overlap.
Then a computer search identified molecules known to disrupt these signaling pathways "and allow cells that are fully senescent to kill themselves," he explains. The process is a bit like looking for the right weapons in a video game to wipe out lingering zombie cells. But instead of swords, guns, and grenades, the list of biological tools so far includes experimental molecules, approved drugs, and natural supplements.
Treatment
"We found early on that targeting single components of those networks will only kill a very small minority of senescent cells or senescent cell types," says Kirkland. "So instead of going after one drug-one target-one disease, we're going after networks with combinations of drugs or drugs that have multiple targets. And we're going after every age-related disease."
The FDA is grappling with guidance for researchers wanting to conduct clinical trials on something as broad as aging rather than a single disease.
The large number of potential senolytic (i.e. zombie-neutralizing) compounds they identified allowed Kirkland to be choosy, "purposefully selecting drugs where the side effects profile was good...and with short elimination half-lives." The hit and run approach meant they didn't have to worry about maintaining a steady state of drugs in the body for an extended period of time. Some of the compounds they selected need only a half hour exposure to trigger the dying process in senescent cells, which can then take several days.
Work in mice has already shown impressive results in reversing diabetes, weight gain, Alzheimer's, cardiovascular disease and other conditions using senolytic agents.
That led to Kirkland's pilot study in humans with diabetes-related kidney disease using a three-day regimen of dasatinib, a kinase inhibitor first approved in 2006 to treat some forms of blood cancer, and quercetin, a flavonoid found in many plants and sold as a food supplement.
The combination was safe and well tolerated; it reduced the number of senescent cells in the belly fat of patients and restored their normal function, according to results published in September in the journal EBioMedicine. This preliminary paper was based on 9 patients in an ongoing study of 30 patients.
Kirkland cautions that these are initial and incomplete findings looking primarily at safety issues, not effectiveness. There is still much to be learned about the use of senolytics, starting with proof that they actually provide clinical benefit, and against what chronic conditions. The drug combinations, doses, duration, and frequency, not to mention potential risks all must be worked out. Additional studies of other diseases are being developed.
What's Next
Ron Kohanski, a senior administrator at the NIH National Institute on Aging (NIA), says the field of senolytics is so new that there isn't even a consensus on how to identify a senescent cell, and the FDA is grappling with guidance for researchers wanting to conduct clinical trials on something as broad as aging rather than a single disease.
Intellectual property concerns may temper the pharmaceutical industry's interest in developing senolytics to treat chronic diseases of aging. It looks like many mix-and-match combinations are possible, and many of the potential molecules identified so far are found in nature or are drugs whose patents have or will soon expire. So the ability to set high prices for such future drugs, and hence the willingness to spend money on expensive clinical trials, may be limited.
Still, Kohanski believes the field can move forward quickly because it often will include products that are already widely used and have a known safety profile. And approaches like Kirkland's hit and run strategy will minimize potential exposure and risk.
He says the NIA is going to support a number of clinical trials using these new approaches. Pharmaceutical companies may feel that they can develop a unique part of a senolytic combination regimen that will justify their investment. And if they don't, countries with socialized medicine may take the lead in supporting such research with the goal of reducing the costs of treating aging patients.
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.