Don't Panic Over Waning Antibodies. Here's Why.
Since the Delta variant became predominant in the United States on July 7, both scientists and the media alike have been full of mixed messages ("breakthrough infections rare"; "breakthrough infections common"; "vaccines still work"; "vaccines losing their effectiveness") but – if we remember our infectious diseases history- one thing remains clear: immunity is the only way to get through a pandemic.
What Happened in the Past
The 1918 influenza pandemic was far the deadliest respiratory virus pandemic recorded in recent human history with over 50 million deaths (maybe even 100 million deaths, or 3% of the world's population) worldwide. Although they used some of the same measures we are using now (masks, distancing, event closures, as neither testing nor a vaccine existed back then), the deaths slowed only after enough of the population had either acquired immunity through natural infection or died. Indeed, the first influenza vaccine was not developed until 1942, more than 20 years later. As judged by the amount of suffering and death from 1918 influenza (and the deadly Delta surge in India in spring 2021), natural immunity is obviously a terrible way to get through a pandemic.
Similarly, measles was a highly transmissible respiratory virus that led to high levels of immunity among adults who were invariably exposed as children. However, measles led to deaths each year among the nonimmune until a vaccine was developed in 1963, largely restricting current measles outbreaks in the U.S. now to populations who decline to vaccinate. Smallpox also led to high levels of immunity through natural infection, which was often fatal. That's why unleashing smallpox on a largely nonimmune population in the New World was so deadly. Only an effective vaccine – and its administration worldwide, including among populations who declined smallpox vaccine at first via mandates – could control and then eventually eradicate smallpox from Earth.
Fully vaccinated people are already now able to generate some antibodies against all the variants we know of to date, thanks to their bank of memory B cells.
The Delta variant is extremely transmissible, making it unlikely we will ever eliminate or eradicate SARS-CoV-2. Even Australia, which had tried to maintain a COVID-zero nation with masks, distancing, lockdowns, testing and contact tracing before and during the vaccines, ended a strategy aimed at eliminating COVID-19 this week. But, luckily, since highly effective and safe vaccines were developed for COVID-19 less than a year after its advent on a nonimmune population and since vaccines are retaining their effectiveness against severe disease, we have a safe way out of the misery of this pandemic: more and more immunity. "Defanging" SARS-CoV-2 and stripping it of its ability to cause severe disease through immunity will relegate it to the fate of the other four circulating cold-causing coronaviruses, an inconvenience but not a world-stopper.
Immunity Is More Than Antibodies
When we say immunity, we have to be clear that we are talking about cellular immunity and immune memory, not only antibodies. This is a key point. Neutralizing antibodies, which prevent the virus from entering our cells, are generated by the vaccines. But those antibodies will necessarily wane over time since we cannot keep antibodies from every infection and vaccine we have ever seen in the bloodstream (or our blood would be thick as paste!). Vaccines with shorter intervals between doses (like Pfizer vaccines given 3 weeks apart) are likely to have their antibodies wane sooner than vaccines with longer intervals between doses (like Moderna), making mild symptomatic breakthroughs less likely with the Moderna vaccine than the Pfizer during our Delta surge, as a recent Mayo Clinic study showed.
Luckily, the vaccines generate B cells that get relegated to our memory banks and these memory B cells are able to produce high levels of antibodies to fight the virus if they see it again. Amazingly, these memory B cells will actually produce antibodies adapted against the COVID variants if they see a variant in the future, rather than the original antibodies directed against the ancestral strain. This is because memory B cells serve as a blueprint to make antibodies, like the blueprint of a house. If a house needs an extra column (or antibodies need to evolve to work against variants), the blueprint will oblige just as memory B cells will!
One problem with giving a 3rd dose of our current vaccines is that those antibodies won't be adapted towards the variants. Fully vaccinated people are already now able to generate some antibodies against all the variants we know of to date, thanks to their bank of memory B cells. In other words, no variant has evolved to date that completely evades our vaccines. Memory B cells, once generated by either natural infection or vaccination, should be long-lasting.
If memory B cells are formed by a vaccine, they should be as long-lasting as those from natural infection per various human studies. A 2008 Nature study found that survivors of the 1918 influenza pandemic were able to produce antibodies from memory B cells when exposed to the same influenza strain nine decades later. Of note, mild infections (such as the common cold from the cold-causing coronaviruses called 229E, NL63, OC43, and HKU1) may not reliably produce memory B cell immunity like more severe infections caused by SARS-CoV-2.
Right about now, you may be worrying about a super-variant that might yet emerge to evade all our hard-won immune responses. But most immunologists do not think this is very realistic because of T cells. How are T cells different from B Cells? While B cells are like the memory banks to produce antibodies when needed (helped by T cells), T cells will specifically amplify in response to a piece of the virus and help recruit cells to attack the pathogen directly. We likely have T cells to thank for the vaccine's incredible durability in protecting us against severe disease. Data from La Jolla Immunology Institute and UCSF show that the T cell response from the Pfizer vaccine is strong across all the variants.
Think of your spike protein as being comprised of 100 houses with a T cell there to cover each house (to protect you against severe disease). The variants have around 13 mutations along the spike protein so 13 of those T cells won't work, but there are over 80 T cells remaining to protect your "houses" or your body against severe disease.
Although these are theoretical numbers and we don't know exactly the number of T cell antigens (or "epitopes") across the spike protein, one review showed 1400 across the whole virus, with many of those in the spike protein. Another study showed that there were 87 epitopes across the spike protein to which T cells respond, and mutations in one of the variants (beta) took those down to 75. The virus cannot mutate indefinitely in its spike protein and still retain function. This is why it is unlikely we will get a variant that will evade the in-breadth, robust response of our T cells.
Where We Go From Here
So, what does this mean for getting through this pandemic? Immunity and more immunity. For those of us who are vaccinated, if we get exposed to the Delta variant, it will boost our immune response although the memory B cells might take 3-5 days to make new antibodies, which can leave us susceptible to a mild breakthrough infection. That's part of the reason the CDC put back masks for the vaccinated in late July. For those who are unvaccinated, immunity will be gained from Delta but often through terrible ways like severe disease.
The way for the U.S. to determine the need for 3rd shots among those who are not obviously immunocompromised, given the amazing immune memory generated by the vaccines among immunocompetent individuals, is to analyze the cases of the ~6000 individuals who have had severe breakthrough infections among the 171 million Americans fully vaccinated. Define their co-morbidities and age ranges, and boost those susceptible to severe infections (examples could include older people, those with co-morbidities, health care workers, and residents of long-term care facilities). This is an approach likely to be taken by the CDC's Advisory Committee on Immunization Practices.
If immunity is the only way to get through the pandemic and if variants are caused mostly by large populations being unvaccinated, there is not only a moral and ethical imperative but a practical imperative to vaccinate the world in order to keep us all safe. Immunocompetent Americans can boost their antibodies, which may enhance their ability to avoid mild breakthrough infections, but the initial shots still work well against the most important outcomes: hospitalizations and deaths.
There has been no randomized, controlled trial to assess whether three shots vs. two shots meaningfully improve those outcomes. While we ought to trust immune memory to get the immunocompetent in the United States through, we can hasten the end of this pandemic by providing surplus vaccines to poor countries to combat severe disease. Doing so would not only revitalize the role of the U.S. as a global health leader – it would save countless lives.
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.