Scientists Envision a Universal Coronavirus Vaccine
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
With several companies progressing through Phase III clinical trials, the much-awaited coronavirus vaccines may finally become reality within a few months.
But some scientists question whether these vaccines will produce a strong and long-lasting immunity, especially if they aren't efficient at mobilizing T-cells, the body's defense soldiers.
"When I look at those vaccines there are pitfalls in every one of them," says Deborah Fuller, professor of microbiology at the Washington University School of Medicine. "Some may induce only transient antibodies, some may not be very good at inducing T-cell responses, and others may not immunize the elderly very well."
Generally, vaccines work by introducing an antigen into the body—either a dead or attenuated pathogen that can't replicate, or parts of the pathogen or its proteins, which the body will recognize as foreign. The pathogens or its parts are usually discovered by cells that chew up the intruders and present them to the immune system fighters, B- and T-cells—like a trespasser's mug shot to the police. In response, B-cells make antibodies to neutralize the virus, and a specialized "crew" called memory B-cells will remember the antigen. Meanwhile, an army of various T-cells attacks the pathogens as well as the cells these pathogens already infected. Special helper T-cells help stimulate B-cells to secrete antibodies and activate cytotoxic T-cells that release chemicals called inflammatory cytokines that kill pathogens and cells they infected.
"Each of these components of the immune system are important and orchestrated to talk to each other," says professor Larry Corey, who studies vaccines and infectious disease at Fred Hutch, a non-profit scientific research organization. "They optimize the assault of the human immune system on the complexity of the viral, bacterial, fungal and parasitic infections that live on our planet, to which we get exposed."
Despite their variety, coronaviruses share certain common proteins and other structural elements, Fuller explains, which the immune system can be trained to identify.
The current frontrunner vaccines aim to train our body to generate a sufficient amount of antibodies to neutralize the virus by shutting off its spike proteins before it enters our cells and begins to replicate. But a truly robust vaccine should also engender a strong response from T-cells, Fuller believes.
"Everyone focuses on the antibodies which block the virus, but it's not always 100 percent effective," she explains. "For example, if there are not enough titers or the antibody starts to wane, and the virus does get into the cells, the cells will become infected. At that point, the body needs to mount a robust T-cytotoxic response. The T-cells should find and recognize cells infected with the virus and eliminate these cells, and the virus with them."
Some of the frontrunner vaccine makers including Moderna, AstraZeneca and CanSino reported that they observed T-cell responses in their trials. Another company, BioNTech, based in Germany, also reported that their vaccine produced T-cell responses.
Fuller and her team are working on their own version of a coronavirus vaccine. In their recent study, the team managed to trigger a strong antibody and T-cell response in mice and primates. Moreover, the aging animals also produced a robust response, which would be important for the human elderly population.
But Fuller's team wants to engage T-cells further. She wants to try training T-cells to recognize not only SARV-CoV-2, but a range of different coronaviruses. Wild hosts, such as bats, carry many different types of coronaviruses, which may spill over onto humans, just like SARS, MERS and SARV-CoV-2 have. There are also four coronaviruses already endemic to humans. Cryptically named 229E, NL63, OC43, and HKU1, they were identified in the 1960s. And while they cause common colds and aren't considered particularly dangerous, the next coronavirus that jumps species may prove deadlier than the previous ones.
Despite their variety, coronaviruses share certain common proteins and other structural elements, Fuller explains, which the immune system can be trained to identify. "T-cells can recognize these shared sequences across multiple different types of coronaviruses," she explains, "so we have this vision for a universal coronavirus vaccine."
Paul Offit at Children's Hospitals in Philadelphia, who specializes in infectious diseases and vaccines, thinks it's a far shot at the moment. "I don't see that as something that is likely to happen, certainly not very soon," he says, adding that a universal flu vaccine has been tried for decades but is not available yet. We still don't know how the current frontrunner vaccines will perform. And until we know how efficient they are, wearing masks and keeping social distance are still important, he notes.
Corey says that while the universal coronavirus vaccine is not impossible, it is certainly not an easy feat. "It is a reasonably scientific hypothesis," he says, but one big challenge is that there are still many unknown coronaviruses so anticipating their structural elements is difficult. The structure of new viruses, particularly the recombinant ones that leap from wild hosts and carry bits and pieces of animal and human genetic material, can be hard to predict. "So whether you can make a vaccine that has universal T-cells to every coronavirus is also difficult to predict," Corey says. But, he adds, "I'm not being negative. I'm just saying that it's a formidable task."
Fuller is certainly up to the task and thinks it's worth the effort. "T-cells can cross-recognize different viruses within the same family," she says, so increasing their abilities to home in on a broader range of coronaviruses would help prevent future pandemics. "If that works, you're just going to take one [vaccine] and you'll have lifetime immunity," she says. "Not just against this coronavirus, but any future pandemic by a coronavirus."
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
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.