Is a Successful HIV Vaccine Finally on the Horizon?
Few vaccines have been as complicated—and filled with false starts and crushed hopes—as the development of an HIV vaccine.
While antivirals help HIV-positive patients live longer and reduce viral transmission to virtually nil, these medications must be taken for life, and preventative medications like pre-exposure prophylaxis, known as PrEP, need to be taken every day to be effective. Vaccines, even if they need boosters, would make prevention much easier.
In August, Moderna began human trials for two HIV vaccine candidates based on messenger RNA.
As they have with the Covid-19 pandemic, mRNA vaccines could change the game. The technology could be applied for gene editing therapy, cancer, other infectious diseases—even a universal influenza vaccine.
In the past, three other mRNA vaccines completed phase-2 trials without success. But the easily customizable platforms mean the vaccines can be tweaked better to target HIV as researchers learn more.
Ever since HIV was discovered as the virus causing AIDS, researchers have been searching for a vaccine. But the decades-long journey has so far been fruitless; while some vaccine candidates showed promise in early trials, none of them have worked well among later-stage clinical trials.
There are two main reasons for this: HIV evolves incredibly quickly, and the structure of the virus makes it very difficult to neutralize with antibodies.
"We in HIV medicine have been desperate to find a vaccine that has effectiveness, but this goal has been elusive so far."
"You know the panic that goes on when a new coronavirus variant surfaces?" asked John Moore, professor of microbiology and immunology at Weill Cornell Medicine who has researched HIV vaccines for 25 years. "With HIV, that kind of variation [happens] pretty much every day in everybody who's infected. It's just orders of magnitude more variable a virus."
Vaccines like these usually work by imitating the outer layer of a virus to teach cells how to recognize and fight off the real thing off before it enters the cell. "If you can prevent landing, you can essentially keep the virus out of the cell," said Larry Corey, the former president and director of the Fred Hutchinson Cancer Research Center who helped run a recent trial of a Johnson & Johnson HIV vaccine candidate, which failed its first efficacy trial.
Like the coronavirus, HIV also has a spike protein with a receptor-binding domain—what Moore calls "the notorious RBD"—that could be neutralized with antibodies. But while that target sticks out like a sore thumb in a virus like SARS-CoV-2, in HIV it's buried under a dense shield. That's not the only target for neutralizing the virus, but all of the targets evolve rapidly and are difficult to reach.
"We understand these targets. We know where they are. But it's still proving incredibly difficult to raise antibodies against them by vaccination," Moore said.
In fact, mRNA vaccines for HIV have been under development for years. The Covid vaccines were built on decades of that research. But it's not as simple as building on this momentum, because of how much more complicated HIV is than SARS-CoV-2, researchers said.
"They haven't succeeded because they were not designed appropriately and haven't been able to induce what is necessary for them to induce," Moore said. "The mRNA technology will enable you to produce a lot of antibodies to the HIV envelope, but if they're the wrong antibodies that doesn't solve the problem."
Part of the problem is that the HIV vaccines have to perform better than our own immune systems. Many vaccines are created by imitating how our bodies overcome an infection, but that doesn't happen with HIV. Once you have the virus, you can't fight it off on your own.
"The human immune system actually does not know how to innately cure HIV," Corey said. "We needed to improve upon the human immune system to make it quicker… with Covid. But we have to actually be better than the human immune system" with HIV.
But in the past few years, there have been impressive leaps in understanding how an HIV vaccine might work. Scientists have known for decades that neutralizing antibodies are key for a vaccine. But in 2010 or so, they were able to mimic the HIV spike and understand how antibodies need to disable the virus. "It helps us understand the nature of the problem, but doesn't instantly solve the problem," Moore said. "Without neutralizing antibodies, you don't have a chance."
Because the vaccines need to induce broadly neutralizing antibodies, and because it's very difficult to neutralize the highly variable HIV, any vaccine will likely be a series of shots that teach the immune system to be on the lookout for a variety of potential attacks.
"Each dose is going to have to have a different purpose," Corey said. "And we hope by the end of the third or fourth dose, we will achieve the level of neutralization that we want."
That's not ideal, because each individual component has to be made and tested—and four shots make the vaccine harder to administer.
"You wouldn't even be going down that route, if there was a better alternative," Moore said. "But there isn't a better alternative."
The mRNA platform is exciting because it is easily customizable, which is especially important in fighting against a shapeshifting, complicated virus. And the mRNA platform has shown itself, in the Covid pandemic, to be safe and quick to make. Effective Covid vaccines were comparatively easy to develop, since the coronavirus is easier to battle than HIV. But companies like Moderna are capitalizing on their success to launch other mRNA therapeutics and vaccines, including the HIV trial.
"You can make the vaccine in two months, three months, in a research lab, and not a year—and the cost of that is really less," Corey said. "It gives us a chance to try many more options, if we've got a good response."
In a trial on macaque monkeys, the Moderna vaccine reduced the chances of infection by 85 percent. "The mRNA platform represents a very promising approach for the development of an HIV vaccine in the future," said Dr. Peng Zhang, who is helping lead the trial at the National Institute of Allergy and Infectious Diseases.
Moderna's trial in humans represents "a very exciting possibility for the prevention of HIV infection," Dr. Monica Gandhi, director of the UCSF-Gladstone Center for AIDS Research, said in an email. "We in HIV medicine have been desperate to find a vaccine that has effectiveness, but this goal has been elusive so far."
If a successful HIV vaccine is developed, the series of shots could include an mRNA shot that primes the immune system, followed by protein subunits that generate the necessary antibodies, Moore said.
"I think it's the only thing that's worth doing," he said. "Without something complicated like that, you have no chance of inducing broadly neutralizing antibodies."
"I can't guarantee you that's going to work," Moore added. "It may completely fail. But at least it's got some science behind it."
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.