Catching colds may help protect kids from Covid
A common cold virus causes the immune system to produce T cells that also provide protection against SARS-CoV-2, according to new research. The study, published last month in PNAS, shows that this effect is most pronounced in young children. The finding may help explain why most young people who have been exposed to the cold-causing coronavirus have not developed serious cases of COVID-19.
One curiosity stood out in the early days of the COVID-19 pandemic – why were so few kids getting sick. Generally young children and the elderly are the most vulnerable to disease outbreaks, particularly viral infections, either because their immune systems are not fully developed or they are starting to fail.
But solid information on the new infection was so scarce that many public health officials acted on the precautionary principle, assumed a worst-case scenario, and applied the broadest, most restrictive policies to all people to try to contain the coronavirus SARS-CoV-2.
One early thought was that lockdowns worked and kids (ages 6 months to 17 years) simply were not being exposed to the virus. So it was a shock when data started to come in showing that well over half of them carried antibodies to the virus, indicating exposure without getting sick. That trend grew over time and the latest tracking data from the CDC shows that 96.3 percent of kids in the U.S. now carry those antibodies.
Antibodies are relatively quick and easy to measure, but some scientists are exploring whether the reactions of T cells could serve as a more useful measure of immune protection.
But that couldn't be the whole story because antibody protection fades, sometimes as early as a month after exposure and usually within a year. Additionally, SARS-CoV-2 has been spewing out waves of different variants that were more resistant to antibodies generated by their predecessors. The resistance was so significant that over time the FDA withdrew its emergency use authorization for a handful of monoclonal antibodies with earlier approval to treat the infection because they no longer worked.
Antibodies got most of the attention early on because they are part of the first line response of the immune system. Antibodies can bind to viruses and neutralize them, preventing infection. They are relatively quick and easy to measure and even manufacture, but as SARS-CoV-2 showed us, often viruses can quickly evolve to become more resistant to them. Some scientists are exploring whether the reactions of T cells could serve as a more useful measure of immune protection.
Kids, colds and T cells
T cells are part of the immune system that deals with cells once they have become infected. But working with T cells is much more difficult, takes longer, and is more expensive than working with antibodies. So studies often lags behind on this part of the immune system.
A group of researchers led by Annika Karlsson at the Karolinska Institute in Sweden focuses on T cells targeting virus-infected cells and, unsurprisingly, saw that they can play a role in SARS-CoV-2 infection. Other labs have shown that vaccination and natural exposure to the virus generates different patterns of T cell responses.
The Swedes also looked at another member of the coronavirus family, OC43, which circulates widely and is one of several causes of the common cold. The molecular structure of OC43 is similar to its more deadly cousin SARS-CoV-2. Sometimes a T cell response to one virus can produce a cross-reactive response to a similar protein structure in another virus, meaning that T cells will identify and respond to the two viruses in much the same way. Karlsson looked to see if T cells for OC43 from a wide age range of patients were cross-reactive to SARS-CoV-2.
And that is what they found, as reported in the PNAS study last month; there was cross-reactive activity, but it depended on a person’s age. A subset of a certain type of T cells, called mCD4+,, that recognized various protein parts of the cold-causing virus, OC43, expressed on the surface of an infected cell – also recognized those same protein parts from SARS-CoV-2. The T cell response was lower than that generated by natural exposure to SARS-CoV-2, but it was functional and thus could help limit the severity of COVID-19.
“One of the most politicized aspects of our pandemic response was not accepting that children are so much less at risk for severe disease with COVID-19,” because usually young children are among the most vulnerable to pathogens, says Monica Gandhi, professor of medicine at the University of California San Francisco.
“The cross-reactivity peaked at age six when more than half the people tested have a cross-reactive immune response,” says Karlsson, though their sample is too small to say if this finding applies more broadly across the population. The vast majority of children as young as two years had OC43-specific mCD4+ T cell responses. In adulthood, the functionality of both the OC43-specific and the cross-reactive T cells wane significantly, especially with advanced age.
“Considering that the mortality rate in children is the lowest from ages five to nine, and higher in younger children, our results imply that cross-reactive mCD4+ T cells may have a role in the control of SARS-CoV-2 infection in children,” the authors wrote in their paper.
“One of the most politicized aspects of our pandemic response was not accepting that children are so much less at risk for severe disease with COVID-19,” because usually young children are among the most vulnerable to pathogens, says Monica Gandhi, professor of medicine at the University of California San Francisco and author of the book, Endemic: A Post-Pandemic Playbook, to be released by the Mayo Clinic Press this summer. The immune response of kids to SARS-CoV-2 stood our expectations on their head. “We just haven't seen this before, so knowing the mechanism of protection is really important.”
Why the T cell immune response can fade with age is largely unknown. With some viruses such as measles, a single vaccination or infection generates life-long protection. But respiratory tract infections, like SARS-CoV-2, cause a localized infection - specific to certain organs - and that response tends to be shorter lived than systemic infections that affect the entire body. Karlsson suspects the elderly might be exposed to these localized types of viruses less often. Also, frequent continued exposure to a virus that results in reactivation of the memory T cell pool might eventually result in “a kind of immunosenescence or immune exhaustion that is associated with aging,” Karlsson says. https://leaps.org/scientists-just-started-testing-a-new-class-of-drugs-to-slow-and-even-reverse-aging/particle-3 This fading protection is why older people need to be repeatedly vaccinated against SARS-CoV-2.
Policy implications
Following the numbers on COVID-19 infections and severity over the last three years have shown us that healthy young people without risk factors are not likely to develop serious disease. This latest study points to a mechanism that helps explain why. But the inertia of existing policies remains. How should we adjust policy recommendations based on what we know today?
The World Health Organization (WHO) updated their COVID-19 vaccination guidance on March 28. It calls for a focus on vaccinating and boosting those at risk for developing serious disease. The guidance basically shrugged its shoulders when it came to healthy children and young adults receiving vaccinations and boosters against COVID-19. It said the priority should be to administer the “traditional essential vaccines for children,” such as those that protect against measles, rubella, and mumps.
“As an immunologist and a mother, I think that catching a cold or two when you are a kid and otherwise healthy is not that bad for you. Children have a much lower risk of becoming severely ill with SARS-CoV-2,” says Karlsson. She has followed public health guidance in Sweden, which means that her young children have not been vaccinated, but being older, she has received the vaccine and boosters. Gandhi and her children have been vaccinated, but they do not plan on additional boosters.
The WHO got it right in “concentrating on what matters,” which is getting traditional childhood immunizations back on track after their dramatic decline over the last three years, says Gandhi. Nor is there a need for masking in schools, according to a study from the Catalonia region of Spain. It found “no difference in masking and spread in schools,” particularly since tracking data indicate that nearly all young people have been exposed to SARS-CoV-2.
Both researchers lament that public discussion has overemphasized the quickly fading antibody part of the immune response to SARS-CoV-2 compared with the more durable T cell component. They say developing an efficient measure of T cell response for doctors to use in the clinic would help to monitor immunity in people at risk for severe cases of COVID-19 compared with the current method of toting up potential risk factors.
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.