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Tag: La Jolla Institute for Immunology

  • LJI scientists harness ‘helper’ T cells to treat tumors

    LJI scientists harness ‘helper’ T cells to treat tumors

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    Newswise — LA JOLLA, CA—Scientists are on the hunt for a unique set of mutations, called “neoantigens,” that let the immune system distinguish tumor cells from normal cells. Their goal is to help the immune system react to neoantigens and target tumor cells for destruction.

    This area of research has led to life-saving antibody therapeutics, such as immune checkpoint inhibitors, which rely on antibodies to help immune cells kill tumors. Unfortunately, antibody-based cancer immunotherapies don’t work for all patients.

    At La Jolla Institute for Immunology (LJI), Professor Stephen Schoenberger, Ph.D., and his colleagues are looking beyond antibodies. Schoenberger’s lab leads pioneering research into how the immune system’s CD4+ “helper” T cells detect neoantigens.

    Now Schoenberger and his colleagues have published a pair of studies that show how we might harness CD4+ T cells while boosting the cancer-fighting power of CD8+ “killer” T cells. In fact, the researchers demonstrate a new kind of vaccine design that recruits both types of T cells to destroy large tumors.

    “Therapeutic cancer vaccines can work,” says Schoenberger, who serves as a member of the LJI Center for Cancer Immunotherapy. “But they should leverage the natural synergy of CD4+ and CD8+ T cells.”

    Researchers help CD4+ T cells detect tumors

    As Schoenberger points out, CD4+ and CD8+ T cells already work together when fighting viruses and bacteria. “Why not learn from the immune system’s natural way of keeping us protected and turn that against cancer?” he says.

    In a paper published recently in Nature Immunology, Schoenberger worked closely with LJI Professor Bjoern Peters, Ph.D,. to demonstrate the essential role of CD4+ T cells in recognizing tumor cells. Their strategy depends on an innovative way to predict which tumor neoantigens will spark a strong CD4+ T cell response. 

    As Schoenberger explains, tumor cells arise from normal cells in the body. This means the body has a harder time recognizing tumor cells as dangerous. Other threats, such as viruses, tend to carry around very un-human looking peptide sequences. “With prompting from CD4+ T cells, immune cells called dendritic cells can capture these peptide sequences and show them to CD8+ T cells—sending the immune system into red alert. “CD8+ T cells execute the tumor,” says Schoenberger, “but they require the cooperation of CD4+ T cells to do so efficiently.”

    But tumor cells share most of their peptide sequences with normal cells, and are therefore harder for the immune system to “see.” To get around this problem, Schoenberger and Peters have devised computational tools to identify the genetic mutations and specific peptides that serve as neoantigens to distinguish tumor cells from their neighbors.

    The Nature Immunology study shows that CD4+ T cells that recognize a single target mutation can  drive a diverse CD8+ T cell response that eradicates large established tumors . The researchers tested T cells recognizing this target mutation for “avidity,” which is how strongly their antigen receptors bind to the neoantigen. Their surprising results showed that neoantigen-specific CD4+ T cells can mediate their effect across a range of affinities.

    “This is brand new because no one has ever studied the neoantigen-specific CD4+ repertoire at the level of T cell receptors,” says Schoenberger.

    The researchers also found that the most effective responses happened when the transferred CD4+ T cells were induced to develop into stem cell memory-like CD4+ T cells. This type of T cell are endowed with special properties of longevity and the ability to generate powerful effector cells. As Schoenberger’s research spans the lab to the clinic, these findings will be translated to clinical trials in the near future.

    New vaccine brings T cells together

    In a second study, published recently in the Journal of Clinical Investigation, Schoenberger and his colleagues showed how a new vaccine strategy can induce CD4+ T cells and CD8+ T cells to work together to destroy large, aggressive tumors in a mouse model.

    For the study, Schoenberger collaborated with Joseph Dolina, Ph.D., a senior scientist at Pfizer Inc., and former member of the Schoenberger Lab (Pfizer has no financial disclosures to this specific study).

    The team began with an aggressive squamous cell tumor that contained a low number of mutations, as many human cancers do. The researchers identified 270 mutations that make this tumor stand out from normal cells, and they performed in-depth studies on 39 of these mutations. They narrowed that group down to five mutations that were recognized by the natural anti-tumor T cell response—with some mutations targeted by CD4+ T cells and others by CD8+ T cells. Remarkably, only mutations targeted by both CD4+ and CD8+ T cells were capable of triggering protective or therapeutic responses against the tumor.

    “These neoantigens had to be physically linked to mediate therapy,” says Schoenberger. “We could make large tumors go away so long as the vaccine activated both CD4+ and CD8+ T cells via the same antigen-presenting cell.”

    Going forward, Schoenberger plans to work with his clinical colleagues at the UC San Diego Moores Cancer Center to study whether this type of linked vaccine is effective in human patients. He hopes a future clinical trial can give hope to patients with especially aggressive tumors.

    “The other message here is that we think we can greatly increase the number of patients who could benefit from checkpoint blockade immunotherapy if we combine it with a personalized cancer vaccine,” says Schoenberger.

    Additional authors of the Nature Immunology study, “Neoantigen-specific stem cell memory-like CD4+ T cells mediate CD8+ T cell-dependent immunotherapy of MHC class II-negative solid tumors,” include Spencer E. Brightman (first author), Angelica Becker, Rukman R. Thota, Martin S. Naradikian, Leila Chihab, Karla Soria Zavala, Ryan Q. Griswold, Joseph S. Dolina, Ezra E. W. Cohen and Aaron M. Miller.

    This study was supported by the National Institutes of Health (grant UO1 DE028227), the San Diego Center for Precision Immunotherapy, and the Sandor and Rebecca Shapery Family.

    Nature Immunology DOI: https://doi.org/10.1038/s41590-023-01543-9

    Additional authors of the Journal of Clinical Investigation study, “Linked CD4+/CD8+ T cell neoantigen vaccination overcomes immune checkpoint blockade resistance and enables tumor regression,” include Joey Lee, Spencer E. Brightman, Sara McArdle, Samantha M. Hall, Rukman R. Thota, Karla S. Zavala, Manasa Lanka, Ashmitaa Logandha Ramamoorthy Premlal, Jason A. Greenbaum, Ezra E.W. Cohen and Bjoern Peters.

    This study was supported by the National Institutes of Health (grants U01 DE028227, P30CA23100, S10 RR027366 and S10 OD016262), the San Diego Center for Precision Immunotherapy, and the Sandor and Rebecca Shapery Family.

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  • A new look inside Ebola’s “viral factories”

    A new look inside Ebola’s “viral factories”

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    Newswise — LA JOLLA, CA—New research in the journal Nature Communications gives scientists an important window into how Ebola virus replicates inside host cells. The study, led by scientists at La Jolla Institute for Immunology (LJI), reveals the inner workings of “viral factories,” clusters of viral proteins and genomes that form in host cells.

    The research team, which included experts from Scripps Research and UC San Diego School of Medicine, found that Ebola virus’s replication machinery forms fascinating microscopic structures that become viral factories. By understanding the architecture and function of these microscopic manufacturing hubs, researchers may be closer to developing new therapies that interrupt the Ebola virus life cycle and prevent severe disease.

    “We are imaging these fluid and dynamic assembly centers for the first time. Understanding how they work and what they require gives us the information needed to defeat them,” says LJI President and CEO Erica Ollmann Saphire, Ph.D., senior author of the new study.

    What is a viral factory?

    Scientists first spotted what would turn out to be “virus factories” in virus-infected animal cells back in the 1960s, but they didn’t know what they were seeing. Within a sea of normal cellular proteins, these areas looked like fuzzy splotches.

    “People had already seen that Ebola-infected cells had these ‘inclusions,’” says LJI Postdoctoral Researcher Jingru Fang, Ph.D., first author of the new study. For a long time, scientists thought of these “inclusions” as helpful visual indicators of infection, without understanding their true purpose. “But in fact, these ‘inclusion bodies’ actively gather an enormous quantity of viral proteins and viral RNAs.”

    Many viral pathogens, including rabies virus and RSV (respiratory syncytial virus) form inclusions in host cells, Fang explains. “Recent studies suggest that these cellular inclusions are the site where viruses make their RNA genomes. They are ‘viral factories’ with actual functional purpose: to offer a secured space for viral RNA synthesis,” says Fang. “The process of viral RNA synthesis involves flux of viral building blocks. This means molecules gathered inside viral factories should be able to move freely rather than being static.”

    For the new study, Saphire, Fang and their colleagues wondered: Can we observe the movement of viral building blocks directly in living cells?

    Fang began by tagging a viral protein called VP35 with a fluorescent marker that makes the protein glow in the dark. VP35 is a critical component of the viral factory and is important for viral RNA synthesis (and the making of new copies of Ebola virus). Working with imaging experts in the LJI Microscopy and Histology Core, Fang followed the glowing proteins in live cells, which express a simplified and non-infectious version of Ebola viral factories.

    Under the microscope, Fang and colleagues could indeed see and even measure how molecules move inside the viral factories formed in host cells. This finding added evidence that viral proteins are clumping together like droplets so they can churn out the proteins needed to help the virus replicate. Those mysterious inclusions really are viral factories. The researcher dubbed these “droplet-like” viral factories.

    Then the scientists saw something odd. Some of the glowing proteins didn’t gather into clumps. Instead, they joined up with a smattering of other viral proteins, creating a fluorescent swirl that evoked van Gogh’s “Starry Night.” These trails of viral proteins still had the right ingredients to replicate Ebola virus, so the scientists dubbed them “network-like” viral factories.

    “These are two different flavors of the viral factory,” says Fang. “People have mostly focused on the droplet-like form, which is the majority, and not paid too much attention to this other form.”

    Besides their shapes, there was a key difference between the two factories. It appeared the network-like factories had the right ingredients for the incoming Ebola virus to express its genes, but they didn’t actually produce virus progenies.

    A multi-tasking machine

    Next, the researchers looked at a key player in infection: a protein called virus polymerase. Polymerase is a multifunctional nanomachine that comes with the virus. This machine not only copies the Ebola virus genomic material, it also transcribes the viral genome into messenger RNAs, which instruct infected cells to produce loads of viral proteins. The researchers wanted to understand how this viral machine functions inside viral factories.

    Ebola virus polymerase is already known as a hard-working protein—all Ebola viral proteins have to be. Ebola virus is a highly efficient pathogen because it gets by with just seven genes (humans have more than 20,000 genes). Saphire has led research showing that Ebola virus survives by making proteins that can transform and take on different jobs during the course of infection.

    Just last year, Saphire, Fang, and collaborators published a related discovery that viral polymerase actually harnesses a druggable human protein to help the virus replicate its genome. The team reported that while polymerase is essential for viral replication, the polymerase doesn’t actually jump into action until infection is well underway.

    This work was important for understanding how polymerase stepped into action, but scientists also needed to know where polymerase was active. Fang knew it would be important to look at what polymerase might be up to in viral factories.

    The researchers discovered that polymerase actually builds its own special structures inside viral factories. Many copies of polymerase gather in small bundles, called foci. The researchers found that these bundles spread out when a droplet-like viral factory starts replicating viral material.

    Scientists aren’t sure exactly why polymerase needs to form bundles before it can do its job, but the spatial arrangement of the bundles must be important. As Fang points out, the idea of many small components coming together to build a structure isn’t a new concept in nature. “You can use a beehive or coral reef as the analogy to help understand why a specific spatial arrangement is important for a biological system to function,” she says.

    With this finding, scientists now know how to find different kinds of viral factories and how polymerase organizes itself down on the factory floor.

    Fighting back

    More than 30 human pathogens are known to assemble viral factories inside host cells, including respiratory syncytial virus (RSV) and even rabies virus. With this new view of Ebola’s viral factories, the scientists are curious whether other viruses construct similar forms of viral factories—and whether other viruses use their own versions of polymerase in the same way.

    “If that’s true, maybe we can target the feature of viral factory formation that has been shared by multiple different viruses,” says Fang.

    Going forward, Fang would also like to study how Ebola virus forms viral factories in different kinds of host cells. Do these viral factories look different in cells from animals (such as the virus’s natural hosts, the fruit bats) that can carry the virus around without getting sick? “Can we find some explanation for host-specific viral pathogenesis?” she asks.

    The new study also demonstrates the importance of collaboration across San Diego’s Torrey Pines Mesa. The LJI team worked closely with Scripps Research Professor Ashok Deniz, Ph.D., and UC San Diego Professor Mark H. Ellisman, Ph.D., Director of the National Center for Microscopy and Imaging Research.

    “The combination of state-of-the-art tools available on the Torrey Pines Mesa allowed us to combine the biophysical characterization with the human health insight,” says Saphire

    Additional authors of the study, “Spatial and functional arrangement of Ebola virus polymerase inside phase-separated viral factories,” include Guillaume Castillon, Sebastien Phan, Sara McArdle, Chitra Hariharan, and Aiyana Adams.

    This study was supported by the National Institute of Health (grants NIH S10OD021831, R24GM137200, and S10OD021784), an Imaging Scientist grant (2019‐198153) from the Chan Zuckerberg Initiative, LJI institutional funds, and the Donald E. and Delia B. Baxter Foundation Fellowship.

    DOI: 10.1038/s41467-023-39821-7

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    About La Jolla Institute

    The La Jolla Institute for Immunology is dedicated to understanding the intricacies and power of the immune system so that we may apply that knowledge to promote human health and prevent a wide range of diseases. Since its founding in 1988 as an independent, nonprofit research organization, the Institute has made numerous advances leading toward its goal: life without disease. Visit lji.org for more information.

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  • New algorithm may fuel vaccine development

    New algorithm may fuel vaccine development

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    Newswise — LA JOLLA, CA—Immune system researchers have designed a computational tool to boost pandemic preparedness. Scientists can use this new algorithm to compare data from vastly different experiments and better predict how individuals may respond to disease.

    “We’re trying to understand how individuals fight off different viruses, but the beauty of our method is you can apply it generally in other biological settings, such as comparisons of different drugs or different cancer cell lines,” says Tal Einav, Ph.D., Assistant Professor at La Jolla Institute for Immunology (LJI) and co-leader of the new study in Cell Reports Methods.

    This work addresses a major challenge in medical research. Laboratories that study infectious disease—even laboratories focused on the same viruses—collect wildly different kinds of data. “Each dataset becomes its own independent island,” says Einav.

    Some researchers might study animal models, others might study human patients. Some labs focus on children, others collect samples from immunocompromised senior citizens. Location matters too. Cells collected from patients in Australia might react differently to a virus compared with cells collected from a patient group in Germany, just based on past viral exposures in those regions.

    “There’s an added level of complexity in biology. Viruses are always evolving, and that changes the data too,” says Einav. “And even if two labs looked at the same patients in the same year, they might have run slightly different tests.”

    Working closely with Rong Ma, Ph.D., a postdoctoral scholar at Stanford University, Einav set out to develop an algorithm to help compare large datasets. His inspiration came from his background in physics, a discipline where—no matter how innovative an experiment is—scientists can be confident that the data will fit within the known laws of physics. E will always equal mc2.

    “What I like to do as a physicist is collect everything together and figure out the unifying principles,” says Einav.

    The new computational method doesn’t need to know precisely where or how each dataset was acquired. Instead, Einav and Ma harnessed machine learning to determine which datasets follow the same underlying patterns. 

    “You don’t have to tell me that some data came from children or adults or teenagers. We just ask the machine ‘how similar are the data to each other,’ and then we combine the similar datasets into a superset that trains even better algorithms,” says Einav. Over time, these comparisons could reveal consistent principles in immune responses—patterns that are hard to detect across the many scattered datasets that abound in immunology. 

    For example, researchers could design better vaccines by figuring out exactly how human antibodies target viral proteins. This is where biology gets really complicated again. The problem is that humans can make around one quintillion unique antibodies. Meanwhile a single viral protein can have more variations than there are atoms in the universe. 

    “That’s why people are collecting bigger and bigger data sets to try and explore biology’s nearly infinite playground,” says Einav. 

    But scientists don’t have infinite time, so they need ways to predict the vast reaches of data they can’t realistically collect. Already, Einav and Ma have shown that their new computational method can help scientists fill in these gaps. They demonstrate that their method to compare large datasets can reveal myriad new rules of immunology, and these rules can then be applied to other datasets to predict what missing data should look like.

    The new method is also thorough enough to provide scientists with confidence behind their predictions. In statistics, a “confidence interval” is a way to quantify how certain a scientist is of a prediction.

    “These predictions work a bit like the Netflix algorithm that predicts which movies you might like to watch,” says Einav. The Netflix algorithm looks for patterns in movies you’ve selected in the past. The more movies (or data) you add to these prediction tools, the more accurate those predictions will get.

    “We can never gather all the data, but we can do a lot with just a few measurements,” says Einav. “And not only do we estimate the confidence in predictions, but we can also tell you what further experiments would maximally increase this confidence. For me, true victory has always been to gain a deep understanding of a biological system, and this framework aims to do precisely that.”

    Einav recently joined the LJI faculty after completing his postdoctoral training in the laboratory of Jesse Bloom, Ph.D., at the Fred Hutch Cancer Center. As he continues his work at LJI, he plans to focus on the use of computational tools to learn more about human immune responses to many viruses, beginning with influenza. He’s looking forward to collaborating with leading immunologists and data scientists at LJI, including Professor Bjoern Peters, Ph.D., also a trained physicist.

    “You get beautiful synergy when you have people coming from these different backgrounds,” says Einav. “With the right team, solving these big, open problems finally becomes possible.”

    The study, “Using Interpretable Machine Learning to Extend Heterogeneous Antibody-Virus Datasets,” was supported by the Damon Runyon Cancer Research Foundation (grant DRQ 01-20) and by Professor David Donoho at Stanford University.

    DOI: https://doi.org/10.1016/j.crmeth.2023.100540

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  • LJI scientists confirm smallpox vaccine also teaches T cells to fight mpox

    LJI scientists confirm smallpox vaccine also teaches T cells to fight mpox

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    Newswise — LA JOLLA, CA—There’s even more reason to think a vaccine developed against smallpox can help the body fight against mpox (monkeypox virus disease) as well, according to researchers at La Jolla Institute for Immunology (LJI). Their new study, published in Cell Host & Microbe, is the first to provide evidence that the vaccinia vaccine MVA-BN (brand name JYNNEOS) should also train virus-fighting T cells to recognize mpox sequences.

    “This study gives us confidence that T cell response induced by the JYNNEOS vaccine should be able to also recognize mpox virus,” says LJI Professor Alessandro Sette, Dr.Biol.Sci., who co-led the new study with LJI Instructor Alba Grifoni, Ph.D.

    The study comes as more than 100 countries reported unprecedented mpox outbreaks. In the United States, there have been more than 28,000 reported cases and 11 deaths attributed to mpox since May 2022.

    Why we need mpox vaccine data

    Although the JYNNEOS vaccine, based on a non-live attenuated orthopox virus called modified vaccine ankara (MVA), is approved to prevent mpox infection and severe disease, researchers don’t yet have clinical efficacy data from human trials. Still, researchers know that mpox virus is similar enough to other orthopoxviruses that immunization against an orthopoxvirus called vaccinia (VACV) can also train the immune system to fight mpox.

    Mpox (termed “monkeypox” until recently) is a member of the orthopox family of viruses. The deadliest, of course, was variola virus,causing the disease known as smallpox. Smallpox was eradicated worldwide in 1980 thanks to a massive and successful vaccination campaign to administer the Dryvax vaccine, based on VACV.

    VACV and variola virus have a lot of immune system targets (called antigens), in common. This means training the body to recognize VACV also taught immune cells to recognize variola virus. But there was a downside—Dryvax (and a newer version called Acambis 2000) had harmful side effects, especially in immunocompromised people.

    JYNNEOS was designed to have a better safety profile. While the vaccine performed well in pre-clinical tests, the eradication of smallpox meant scientists couldn’t see how JYNNEOS performed in human patients in real-world infection scenarios, such as a smallpox outbreak or possible case of smallpox-based biological warfare (a concern in the early days of the Iraq War).

    How a smallpox vaccine protects against mpox

    For the new study, the LJI team set out to study if the viral proteins known to be targeted by T cells induced by VACV vaccination, would also be conserved in JYNNEOS and in mpox. As Grifoni explains, while antibodies are key for vaccine efficacy and preventing reinfections, T cells are essential for both preventing severe infections and “remembering” past infections.

    “By recognizing infected cells, T cells are able to limit how much viruses can spread inside the body modulate disease severity, and ultimately terminate the infection” says Grifoni. “T cell responses also tend to be long lasting, and resilient to viral mutations to escape immune recognition. What we have seen in the context of SARS-CoV-2 is that even if the virus mutates somewhat, T cells reactivity is still largely preserved.”

    The researchers demonstrated that the known targets of T cell responses seen in the VACV proven -efficacy vaccine, are also found in JYNNEOS and mpox, suggesting that the JYNNEOS vaccine can indeed trigger an effective T cell response against mpox infection.  The initial test of their hypothesis was based on developing viral peptide “megapools,” or reagents designed to detect T cell reactivity to mpox antigens. The experiments further showed that these megapools can be used to accurately detect specific T cells.

    “Vaccines such as JYNNEOS should be able to induce T cells that also recognize mpox and can provide protection from severe disease,” says Grifoni.

    Could the vaccine work in immunocompromised patients?

    “The majority of mpox cases have been in men who have sex with men,” Sette explains. “In that community, a significant fraction of the people that have been infected with mpox also happened to be HIV-positive. So it is important to learn how people who are HIV-positive respond to infection and vaccination compared to HIV-negative individuals. The present study enables future study to establish this key point”

    Sette emphasizes that most HIV-positive individuals are not necessarily at greater risk of mpox infection or severe disease. “We do not expect that HIV-positive individuals will respond differently to infection and vaccination, because in most cases, people who live with HIV live with a controlled HIV because of the available therapies,” he says. “Nevertheless, it’s important to provide these data to the community affected by this outbreak and to the general scientific community.”

    Whether the JYNNEOS vaccine sparks a similar immune response in people with and without HIV—and the role of T cells—will have to be determined in future studies. “We also expect to see no difference in the duration of protection between HIV positive and HIV negative individuals, but that still all needs to be proven and evaluated experimentally. We are actively engaging the community most affected by the outbreak and the scientific community at large ” says Sette.

    Next steps for the LJI team

    The researchers are now working to characterize the T cell response to mpox in more detail. They are especially interested in how T cell responses differ after vaccination versus natural infection. Sette and Grifoni would also like to compare T cell responses following JYNNEOS vaccination with the older Dryvax vaccination.

    Just as they’ve done throughout the COVID-19 pandemic, Sette and his colleagues hope to share their reagents freely to and spur more life-saving studies around the globe. “We want to make these reagents widely available to whoever asks,” says Sette.

    Additional authors of the study, “Defining antigen targets to dissect vaccinia virus (VACV) and Monkeypox virus (MPXV)-specific T cell responses in humans,” include Yun Zhang, Alison Tarke, John Sidney, Paul Rubiro, Maria Reina-Campos, Gilberto Filaci, Jennifer Dan, and Richard H. Scheuermann.

    This research was supported by the National Institutes of Health’s National Institute of Allergy and Infectious Diseases (Contract No. 75N93019C00001, 75N9301900065, and HHS75N93019C00076) and through a Ph.D. student fellowship from the Clinical and Experimental Immunology Course at the University of Genoa, Italy, and with support from other private foundations.

    DOI: 10.1016/j.chom.2022.11.003

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