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People who consume sugar and other carbohydrates in excess over a long period of time have an increased risk of developing an autoimmune disease. In affected patients, the immune system attacks the body’s own tissue and the consequences are, for example, chronic inflammatory bowel diseases such as Crohn’s disease and ulcerative colitis, type 1 diabetes and chronic inflammation of the thyroid gland.
New targets for therapy
The underlying molecular mechanisms that promote autoimmune diseases are multilayered and complex. Now, scientists at the Julius Maximilians University of Würzburg (JMU) have succeeded in deciphering new details of these processes. Their work support the notion that excessive consumption of glucose directly promotes the pathogenic functions of certain cells of the immune system and that, conversely, that a calorie-reduced diet can have a beneficial effect on immune diseases. Based on these findings, they also identified new targets for therapeutic interventions: A specific blockade of glucose-depended metabolic processes in these immune cells can suppress excessive immune reactions.
Dr. Martin Väth is responsible for the study, which has now been published in the journal Cell Metabolism. He is a junior research group leader at the Institute of Systems Immunology — a Max Planck research group under the umbrella of JMU that focusses on the interplay of the immune system with the organism. Collaborators from Amsterdam, Berlin, Freiburg and Leuven were also involved in this study.
Glucose transporter with a side job
Martin Väth explains: “Immune cells need large amounts of sugar in the form of glucose to perform their tasks. With the help of specialized transporters at their cell membrane, they can take up glucose from the environment.” Together with his team, Väth has showed that a specific glucose transporter — scientifically named GLUT3 — fulfills additional metabolic functions in T cells besides the generating energy from sugar.
In their study, the scientists focused on a group of cells of the immune system that have not been known for very long: T helper cells of type 17, also called Th17 lymphocytes, which play an important role in regulating (auto-) inflammatory processes.
“These Th17 cells express lots of GLUT3 protein on their cell surface,” Väth explains. Once taken up, glucose is readily converted to citric acid in the mitochondria before it is metabolized into acetyl-coenzyme A (acetyl-CoA) in the cytoplasm. Acetyl-CoA is involved in numerous metabolic processes, including the biosynthesis of lipids.
Influence on proinflammatory genes
However, acetyl-CoA fulfills additional functions in inflammatory Th17 cells. Väth and his team showed that this metabolic intermediate can also regulate the activity of various gene segments. Thus, glucose consumption has a direct influence on the activity of proinflammatory genes.
According to the researchers, theses new findings pave the way for the development of targeted therapy of autoimmune diseases. For example, blocking GLUT3-dependent synthesis of acetyl-CoA by the dietary supplement hydroxycitrate, which is used to treat obesity, can mitigate the pathogenic functions of Th17 cells and reduce inflammatory-pathological processes. The so-called “metabolic reprogramming” of T cells opens new possibilities to treat autoimmune diseases without curtailing protective immune cell functions.
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Materials provided by University of Würzburg. Original written by Gunnar Bartsch. Note: Content may be edited for style and length.

The findings of a new study suggest that a ketogenic diet — which is low in carbohydrates and protein, but high in fat — helps to kill pancreatic cancer cells when combined with a triple-drug therapy developed by the Translational Genomics Research Institute (TGen), an affiliate of City of Hope.
In laboratory experiments, the ketogenic diet decreased glucose (sugar) levels in the tumor, suggesting the diet helped starve the cancer. In addition, this diet elevated ketone bodies produced by the liver, which put additional stress on the cancer cells. The study published in the journal Med.
By destabilizing the cancer cells, the ketogenic diet created a microenvironment in which the triple-drug therapy designed by TGen — a combination of gemcitabine, nab-paclitaxel and cisplatin — was more effective at knocking out the tumor, according to the study.
“By limiting glucose availability, the ketogenic diet may promote chemotherapy efficacy,” said TGen Distinguished Professor Daniel D. Von Hoff, M.D., considered one of the nation’s foremost authorities on pancreatic cancer. Dr. Von Hoff is one of the study authors and designers of the therapy.
In addition, the ketogenic diet was shown to have a favorable impact on antitumor immunity by inducing pro-inflammatory tumor gene expression, which further weakened the cancer.
Clinical trials at five locations
To test these laboratory findings, researchers initiated a clinical trial of up to 40 patients at five centers nationwide: HonorHealth in Scottsdale, USC in Los Angeles, Nuvance Health in Connecticut, Atlantic Health System in New Jersey, and South Texas Accelerated Research Therapeutics in San Antonio.
The clinical trial will test whether adding a ketogenic diet to the triple-drug therapy will increase overall survival in patients with pancreatic cancer. This clinical trial began in late 2020 and is anticipated to continue to accrue patients through June 2023. Patients will be randomly assigned to either receive the triple-drug regimen while on a standard diet, while the other half will receive a ketogenic diet and the triple-drug therapy. The dietary aspects of the study are being carefully monitored.
“Our laboratory experiments show that a ketogenic diet changes pancreatic cancer metabolism and its response to chemotherapy,” said Haiyong Han, Ph.D., a Professor in TGen’s Molecular Medicine Division, and one of the study authors and a designer of the study’s experiments.
Also contributing to this study were: Princeton University, Salk Institute for Biological Studies, Rutgers Cancer Institute and Rutgers Robert Wood Johnson Medical School, the Chinese Academy of Sciences, and the Ludwig Institute for Cancer Research.
The preclinical study was funded by: Stand Up to Cancer (SU2C), the National Institutes of Health, Ludwig Cancer Research, the New Jersey Commission on Cancer Research, New Jersey Health Foundation, a Rutgers Busch Biomedical Grant, the Lustgarten Foundation, the Don and Lorraine Freeberg Foundation, and the David C. Copley Foundation.
The clinical trial is being funded by the Purple Pansies and the John E. Sabga Foundation.
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Materials provided by The Translational Genomics Research Institute. Original written by Steve Yozwiak. Note: Content may be edited for style and length.

The appearance of ovarian lesions on ultrasound is an effective predictor of cancer risk that can help women avoid unnecessary surgery, according to a new study published in the journal Radiology.
Ovarian cancer is the deadliest of the gynecologic cancers, killing about 15,000 women every year in the United States. Characterization of adnexal lesions, or lumps near the uterus, on ultrasound examination is crucial for appropriate patient management, as some adnexal lesions can progress to cancer, while many others are benign and do not require treatment.
“Based on the characteristics that we see on ultrasound, we try to evaluate if a finding needs further workup and where the patient should go from there,” said study lead author Akshya Gupta, M.D., from the University of Rochester Medical Center in Rochester, N.Y. “There is a lot of nuance to it because the lesions can be challenging to assess.”
Current risk stratification systems perform well, but their multiple sub-categories and multifaceted approach may make them difficult for radiologists in busy clinical practices to master.
In the new study, Dr. Gupta and colleagues assessed a method that uses ultrasound images to classify adnexal lesions into one of two categories: classic or non-classic. Classic lesions are the commonly detected ones such as fluid-filled cysts that carry a very low risk of malignancy. Non-classic lesions include lesions with a solid component and blood flow detected on Doppler ultrasound. A classic versus non-classic approach to these lesions could help radiologists in a busy clinical practice more quickly assess a lesion.
The researchers looked at 970 isolated adnexal lesions in 878 women, mean age 42 years, at average risk of ovarian cancer, meaning they had no family history or genetic markers linked with the disease.
Of the 970 lesions, 53 (6%) were malignant. The classic versus non-classic ultrasound-based categorization approach achieved a sensitivity of 92.5% and a specificity of 73.1% for diagnosing malignancy in ovarian cancer.
The frequency of malignancy was less than 1% in lesions with classic ultrasound features. In contrast, lesions that had a solid component with blood flow had a malignancy frequency of 32% in the overall study group and 50% in study participants who were more than 60 years old.
“If you have something that follows the classic imaging patterns described for these lesions, then the risk of cancer is really low,” Dr. Gupta said. “If you have something that’s not classic in appearance, then the presence of solid components and particularly the presence of Doppler blood flow is really what drives the risk of malignancy.”
When a classic benign lesion is encountered, patients may be reassured a benign lesion is present, avoiding extensive further work-up. If additional research supports the study findings, then the system could end up being a useful tool for radiologists that would spare many women the costs, stress and complications of surgery.
“Ultimately, we’re hoping that by using the ultrasound features we can triage which patients need follow-up imaging with ultrasound or MRI and which patients should be referred to surgery,” Dr. Gupta said.
While these findings on diagnostic ultrasound exams offer valuable triaging information, ultrasound has not been proven beneficial specifically as a screening exam for ovarian cancer.

Inside your body on the surface of cell membranes, a metaphorical communication and traffic network is underway as hormones — or chemical messengers — bind to cell membrane receptors to fine tune how the cell behaves. Once bound together, this hormone-receptor complex works to carry out a variety of functions by ferrying chemical signals from outside the cell and translating those signals into action inside the cell. The process of moving into the cell is called trafficking.
Now, for the first time, new technology developed at the University of Houston College of Pharmacy will be able to peer inside and get a close look at the trafficking in real-time. Bradley McConnell, professor of pharmacology, has devised a way to watch the membrane protein trafficking using bioluminescence, the production and emission of light inside living organisms, replacing the need for complicated protocols, methods or highly automated equipment.
“We describe a powerful unrestricted and universal technology of drug discovery that is based on trafficking properties of plasma membrane receptors,” reports McConnell in Communications Biology, a Nature journal. The paper’s lead author is Arfaxad Reyes-Alcaraz, a postdoctoral fellow in McConnell’s laboratory. “This technology can be applied to monitoring the effectiveness of a potential new therapeutic drug that is targeted to a cell receptor and then internalized into the cell. It can also be used to monitor the SARS-CoV-2 viral entry into the cell.”
Ultimately, the researchers expect the process to be used for drug development for heart disease, metabolic disorders, cancer, infectious diseases, COVID-19 and others.
The process monitors how cell receptors are internalized into the cell as part of their normal function in response to a hormone, or a therapeutic drug, interacting with its receptor — a powerful tool to understand how the body works. Scientists have successfully studied this process for years using complex and expensive biological tools, but highly sensitive and versatile technologies have been lacking to study such processes in real-time living systems.
“Now imagine studying this process simply and inexpensively with a method that is even more informative than is currently available,” said McConnell. “The ability to selectively generate a bioluminescent signal when the membrane receptor is in the early endosome to monitor receptor internalization (i.e., membrane trafficking) is novel.”
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Materials provided by University of Houston. Original written by Laurie Fickman. Note: Content may be edited for style and length.

A new study from an international team of researchers — including two from Binghamton University — demonstrates that social media could be used to detect behaviors preceding sudden unexpected death in epilepsy (SUDEP), the leading cause of death in people with uncontrolled epileptic seizures.
The findings, recently published in the journal Epilepsy & Behavior, reveal that the activity of epilepsy patients in social media increased before their sudden deaths. These changes in digital behavior could be used as early warning signals to put preventive interventions for SUDEP into practice.
SUDEP occurs when a person with epilepsy dies suddenly and no reason for death is found. Although the physiological mechanisms underlying SUDEP are still a mystery, people with frequent seizures are known to be at higher risk. The best preventive strategy currently is to keep seizures under control through medication, but reducing stress and keeping triggers in check are also key to decreasing the risk. However, measuring stress and other mood states can be difficult.
A study developed by researchers at Binghamton University, Indiana University and the Instituto Gulbenkian de Ciência (IGC) in Portugal explored the potential of using social media to identify behavior signatures that might predict SUDEP.
“We instantly know when our best friend is not OK,” said Rion Brattig Correia, co-first author of the study, a researcher at IGC and a visiting research scientist at Binghamton University. “They are mumbling, talking too much or perhaps too little, eye contact is different, their tone is off — we just know it. Sometimes we know it over the phone, only after a few words. What if by detecting this sudden behavioral change, we could save a friend’s life?”
Building on these thoughts, the study examined the Facebook timelines of six epilepsy patients who died from SUDEP, using various tools to decipher human emotion and any stress markers hidden in their posts.

Researchers at Rutgers University, Memorial Sloan Kettering Cancer Center, Rockefeller University, and Cornell University are teaming up to examine how the processes that regulate gene expression and chromosome behaviors can lead to health issues, including cancer, birth defects, miscarriage, and infertility.
Cells undergo a remarkable transformation process to form eggs and sperm, which upon fertilization can form an entire organism. A key step of this transformation involves meiosis, a cell division that halves the genome content of cells. During early stages of egg and sperm development, cells divide by mitosis, the process used by most cells in our body. They then undergo a complete remodeling of the gene expression landscape, and switch to meiosis. Mis-regulation of the mitosis-to-meiosis switch can lead to tumor-like growth, depletion of the reproductive cell pool or failure to complete meiosis.
In the new Rutgers-led study in the journal Genes & Development, the researchers applied powerful methods for mapping genome-wide protein-RNA interactions and innovative genetic mouse mutants to define how the RNA helicase, YTHDC2, binds RNA and controls gene expression to regulate meiosis. YTHDC2 and its interacting protein partners form an essential pathway that controls the mitosis-to-meiosis switch. Prior to this study, little was known about the mechanisms regulating this switch in mammals.
“Our work sheds light on the genetic and molecular mechanisms that are required for normal meiosis, which is an essential step towards understanding how and why these processes go wrong and lead to reproductive disorders,” said Devanshi Jain, a principal investigator of the study and an Assistant Professor of Genetics at the School of Arts and Sciences (SAS) at Rutgers University-New Brunswick. “Additionally, as YTHDC2 has been implicated in multiple diseases, especially cancers, our work will have broad implications on those fields as well.”
Jain said this new study, along with ongoing research at the Rutgers-housed Jain Lab, explores the genetic and molecular mechanisms of meiosis, and the processes that regulate gene expression and chromosome behaviors. Researchers at the Jain Lab use the mouse model system to explore these fundamental aspects of cell biology.
“Understanding meiosis is of paramount importance to reproductive health as errors in meiosis can lead to reproductive cell death and infertility,” said Jain. “Going forward, we plan to delve deeper into the molecular mechanisms of the YTHDC2 pathway and its control of gene expression. We also continue to study other fundamental aspects of how meiosis is regulated.”
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Materials provided by Rutgers University. Note: Content may be edited for style and length.

Accelerated glucose uptake and metabolism, known as the Warburg effect, is a feature of a small group of non-dividing cells within a colon cancer tumor. Intestinal cancer cells rely on Warburg glycolysis to eliminate toxic reactive oxidative species, not to provide energy to rapidly dividing cells. Since cancer metabolism is a heterogeneous feature within cancer cells, new research and study tools are needed.
A new paper in Nature Communications reveals new insights into adaptations made by cancer cells to rewire their metabolism to achieve growth and survive. Among the discoveries include a challenge to a well-known feature in cancer metabolism, raising the call for tools to study cancer cell metabolism on a nearly single-cell level.
In the 1920s, Otto Warburg observed that cancer cells metabolically adapt their glucose pathway in unusual ways. Normally, glucose — the main nutrient needed for cells to function — is sent to the cell’s mitochondria to be broken down for energy, a process that requires oxygen. However, cancer cells appear to rapidly increase their glucose uptake and directly ferment it into lactate, even in the presence of oxygen and functional mitochondria. “He called it aerobic glycolysis, but we know it as the Warburg effect,” says author Raul Mostoslavsky, MD, PhD, scientific co-director of the Mass General Cancer Center and the Laurel Schwartz Professor of Oncology (Medicine) at Harvard Medical School. For nearly 15 years researchers have been trying to explain why cancer cells do this.
In this paper, Mostoslavsky’s team studied colon cancer tumors to learn more. They developed a fluorescent reporter that stained only a marker of glycolysis in cells of the tumor. Using this reporter and a mass spectrometry imaging approach developed by collaborator Nathalie Agar of Brigham and Women’s Hospital, the researchers found that not all cells within the colon cancer cell relied on Warburg glycolysis. “We found that this metabolic adaptation does not happen in the whole tumor, only in a heterogeneous group that were not dividing,” says Mostoslavsky. His team had published this heterogeneous feature in squamous cell carcinoma but this is the first time it has been shown in colon cancer, and in non-dividing cells.
“What really surprised us is that when we stained the tumor cells with a marker of cell proliferation, they were mutually exclusive,” adds Mostoslavsky. Within fully transformed colon cancers, the cells that were doing Warburg glycosis were not dividing. “This completely challenges the dogma of the Warburg effect,” he adds. For the past 10 to 15 years, most researchers working in cancer metabolism have held that cancer cells do Warburg glycolysis to send glucose for biomass production, or rapid proliferation. “Instead, we found that the main reason they were doing it was to reduce reactive oxygen species, or ROS.” Reactive oxygen species damage cells during glucose breakdown and energy production: “The cells do Warburg metabolism to protect against accumulation of ROS.”
This research showed that indeed Warburg glycolysis is real and functional in cancer cells as a needed adaptation. “But it’s not for the reason we used to think,” says Mostoslavsky. “This means we need to rethink how we are studying cancer metabolism.” Much of the advancements made in the past 10 years studying cancer metabolism come from mass spectrometry analysis of metabolomics, which require many cells. The problem is a lack of means for analyzing cellular heterogeneity. “If metabolic adaptation happens in some cancer cells or not in others, you will not be able to determine that with the current technologies that exist,” he says. “We now know Warburg glycolysis is a heterogeneous feature happening in tumors so we need to develop tools that will allow us to investigate tumors in a single-cell fashion.”
In this paper, the team relied on a novel mass spectrometry imaging tool developed to achieve data almost at a single cell resolution. Says Mostoslavsky: “It is clear that cancer metabolism is highly heterogeneous so we will need new tools like this to study and define these metabolic features in tumors.”
Other authors of the study include Carlos Sebastian, Christina Ferrer, Maria Serra, Jee-Eun Choi, Nadia Ducano, Alessia Mira, Manasvi Shah, Sylwia Stopka, Andrew Perciaccante, Claudio Isella, Daniel Moya-Rull, Marianela Vara-Messler, Silvia Giordano, Elena Maldi, Niyata Desai, Diane Capen, Enzo Medico, Murat Cetinbas, Ruslan Sadreyev, Dennis Brown, Miguel Rivera, Anna Sapino, and David Breault.
This work was supported by grants from the National Institutes of Health, FPRC 5 per mille 2011 MIUR, FPRC 5 per mille 2014 MIUR, RC 2018 Ministero della Salute, and the European Union’s Horizon 2020 Research and Innovation Program.

Each person has their own individual sleep profile which can be identified by the electrical brain activity during sleep. Researchers at the University of Bern have now demonstrated that the brain waves during periods of deep sleep in a specific area of the brain can be used to determine the extent of an individual’s propensity for risk during their everyday life.
Each day, we make countless decisions in which we take different risks — in road traffic, when buying shares or in our sexual behavior, for example. The propensity for risk varies from one individual to the next. Researchers led by Daria Knoch, Professor of Social Neuroscience at the University of Bern, have demonstrated that clues in the brain concerning an individual’s propensity for risk can be gathered as they sleep: “The fewer slow waves an individual has over their right prefrontal cortex during deep sleep, the greater their propensity for risk. Among other functions, this region of the brain is important to control one’s own impulses,” explains the neuroscientist. The results have recently been published in the journal NeuroImage.
High data density and sleep investigation at participant’s home
Slow waves occur during deep sleep and indicate good sleep quality and regeneration. The topographical distribution of slow waves in the brain is highly individual and is highly stable over time; this means each individual has their own personal neuronal sleep profile. To determine whether this profile reveals anything about an individual’s propensity for risk, the research team studied 54 “good sleepers,” who typically sleep for seven to eight hours. These were identified using actigraphs, which track the patterns of movement during sleep. Because: “The individual slow-wave profile can only be interpreted correctly during normal sleep,” explains leader of the study, Lorena Gianotti.
In the next step, sleep data was collected at participants’ home using a portable polysomnographic system with 64 electrodes placed at their scalp. “The undisturbed measurement of the brain activity during sleep in a familiar environment and the high density of data collected by the 64 electrodes are rather rare as a constellation in sleep research. This allows the participants to sleep naturally and allows us to collect a large quantity of data,” explains doctoral student and first author, Mirjam Studler.
Less deep sleep in the right prefrontal cortex
And this data is very meaningful and significant: participants who show lower slow-wave activity over their right prefrontal cortex generally demonstrate a greater propensity for risk than individuals with more slow-wave activity. The propensity to take risks was elicited in a computer game where they could win actual money: the participants had to decide how far they would drive a car in the knowledge that at some point, a wall would appear with which the car would collide. Each meter driven earned them more money, but also increased their risk of crashing. “Interestingly, the sleep duration had no impact in terms of propensity for risk, at least in our study with good sleepers. Rather, it is crucial that deep sleep takes place in the ‘right’ brain regions — in this case, in the right prefrontal cortex,” explains Lorena Gianotti.
Possible implications
Health economics research has demonstrated that risky behavior can have both considerable health-related and financial consequences. According to the researchers, gaining a better understanding of the mechanisms underlying the propensity for risky behaviour is therefore important. “Our findings can be incorporated into targeted interventions. Sleep researchers are now developing techniques to specifically modulate slow waves,” says Daria Knoch.
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Materials provided by University of Bern. Note: Content may be edited for style and length.

Published in JAMA, research from the University of Minnesota assessed if there is a link between heart health and dementia.
Using echocardiography — visual ultrasound of the heart — the research team was able to identify novel measures that are linked to a higher dementia risk.
“Atrial myopathy, a condition characterized by abnormal left atrial function and size, is an independent risk factor for dementia,” said Dr. Lin Yee Chen, director of the cardiac electrophysiology section at the U of M Medical School and M Health Fairview, and principal investigator of the NIH grant that funded this study. “In this community-based cohort study, lower left atrial function was associated with higher risk of dementia.”
The study observed a cohort of 4,096 participants with an average age of 35 years. Participants were 60% women, 22% Black and 78% white. Of the cohort, there were 531 participants who developed dementia over a six year period.
When comparing the lowest to the highest quintile of left atrial function measures (reservoir strain, conduit strain, and contractile strain), the lowest quintile was significantly associated with 1.5 to 2.0-fold higher risk of developing dementia. These associations were independent of cardiovascular disease and atrial fibrillation. The research team found that the more common measures of left atrial size were not significantly associated with dementia.
“Results of this epidemiological study improve our understanding of the link between cardiovascular disease and increased risk of dementia,” said Jacqueline D. Wright, Dr.P.H., a program officer in the division of cardiovascular sciences at the National Heart, Lung, and Blood Institute, part of the National Institutes of Health. “This study suggests that atrial myopathy increases risk of dementia, independently of atrial fibrillation. Further research may confirm this finding, help us to better define and diagnose atrial myopathy, and ultimately lead to improved treatments that reduce the chance of developing dementia later in life.”
Researchers recommend additional studies to confirm their findings and to establish a robust definition for atrial myopathy.
This research was funded by the National Institutes of Health National Heart, Lung, and Blood Institute; National Institute of Neurological Disorders and Stroke; National Institute on Aging; and National Institute on Deafness and Other Communication Disorders.
Research reported in this release was supported by the NIH under the following grant numbers: HHSN268201700001I,HHSN268201700002I, HSN268201700003I, HHSN268201700005I, and HHSN268201700004I; U01 2U01HL096812, 2U01HL096814, 2U01HL096899, 2U01HL096902, and 2U01HL096917; R01-HL70825; T32GM132063; P30AG066511; K24HL148521; R01HL126637, R01HL141288, and K24HL155813; and R01HL135008, R01HL143224, R01HL150342, R01HL148218, K24HL152008.
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Materials provided by University of Minnesota Medical School. Original written by Kat Dodge. Note: Content may be edited for style and length.

Scientists have created a pipeline for identifying, prioritising and evaluating potential tumour antigens for the fast generation of cancer vaccines, according to a report published today in eLife.
The new approach could help researchers quickly identify tumour-specific antigens recognised by cytotoxic T cells, generating a powerful, durable and highly specific response against an individual’s tumour. This could lead in turn to a quicker and easier way to generate effective, personalised cancer vaccines based on the identified antigens.
“For a cancer vaccine to be effective, we need to select target antigens that elicit a strong immune response, are exclusively present on cancer cells and are tailored to an individual’s unique tumour type,” explains first author Sara Feola, Postdoctoral Researcher at the ImmunoViroTherapy Lab (IVTLab), University of Helsinki, Finland. “However, only a few, if any, of the antigens on a tumour meet those characteristics, making it very difficult to identify and prioritise potentially effective candidates. Our pipeline comprises all the essential steps for the optimal development of a therapeutic cancer vaccine, but which could be carried out much more quickly on an individual patient basis, enabling true personalised therapy.”
“Developing personalised cancer vaccines needs several different technologies working together and working fast,” adds senior author Vincenzo Cerullo, Professor of Biological Drug Development at the University of Helsinki and group leader at IVTLab. “We need fast and reliable methods to identify and prioritise antigens, as well as rapid, inexpensive and feasible approaches to deliver these antigens to patients. During the past six years, we’ve been working on a project supported by the European Research Council (ERC) to make all the pieces of this complex puzzle work together, creating the pipeline that has been partially described in this work.
“Our research, which builds on previous work, involves developing a novel approach to identify tumour-specific antigens from very small samples, creating a novel algorithm to prioritise peptides based on their similarity to pathogen-derived peptides, and building several different plug-and-play technologies to deliver these peptides together with viruses or bacteria that kill cancer cells.”
In the current study, the team began by investigating the antigen landscape of a tumour cell — that is, all the different peptides on the cell surface. They studied a mouse model of colon cancer and used state-of-the-art technologies, such as an immunopeptidomic approach based on mass spectrometry analysis, to explore surface antigens on the cell. This generated a list of thousands of peptide candidates and presented a challenge of how to prioritise them.
The team used two parallel lines of investigation: first, they looked at the relative amounts of the peptides on cancer cells compared with normal cells. This gave them clues as to whether the antigen was truly tumour specific. Second, they used a software tool previously developed in their lab to identify tumour antigens that are similar to known pathogen antigens, exploiting their potential ability to cause a similar immune response to the pathogen antigens.
Using these methods, the team narrowed their candidate list down from thousands to 26 antigen candidates. They then studied the potential of these antigens further by testing how well they stimulated T cells, and how effectively they bind to an adenoviral vector that would form the basis of the vaccine. All the candidate antigen peptides interacted with the viral vector, but six peptides performed best and were taken forward for further tests.
The next stage was to see whether a vaccine carrying these target antigens could stimulate enough of an immune response to control or halt tumour growth. To test this, the team used mice with colon tumours on their left and right flanks. They then treated one side of the mice with the vaccine coated with each of the candidate peptide antigens. As hoped, they found that vaccines carrying the peptides improved anti-tumour growth in the treated tumour, but one of the vaccines improved anti-tumor growth in the untreated tumours — suggesting that the peptide antigen in this vaccine had mounted a powerful systemic immune response against the tumours.
“We have developed and validated a pipeline that covers for the first time all the stages of personalised cancer vaccine development, starting with isolating peptides from a primary tumour to analysing them to identify the best candidates,” Cerullo concludes. “This pipeline is currently being validated in human cancer patients under our flagship project on precision cancer medicine, iCAN.
“Together, our findings demonstrate the feasibility of applying the pipeline to generate a tailored cancer vaccine by focusing on the prioritisation and selection criteria and adopting quick plug-and-play technology, called PeptiCRAd, through decorating a clinically approved adenovirus vector with the selected peptides. This opens up the possibility of rapidly generating vaccines for clinical use, where effective personalised therapies represent a major goal of successful treatment.”
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Materials provided by eLife. Note: Content may be edited for style and length.