The effectiveness of CAR T cell therapy against a variety of cancers, including solid tumors, could be boosted greatly by using CRISPR-Cas9 technology to knock out the gene for CD5, a protein found on the surface of T cells, according to a preclinical study from investigators at the University of Pennsylvania’s Perelman School of Medicine and Abramson Cancer Center.
CAR T cells are T cells that have been engineered to attack specific targets found on cancer cells. They have had remarkable results in some patients with blood cancers. But they have not performed well against other cancers including solid-tumor cancers, such as pancreatic cancer, prostate cancer, and melanoma. Researchers have been searching for techniques to boost the effectiveness of CAR T cell therapy.
The study, published today in Science Immunology, suggests that knocking out CD5 could be a prime technique. Illuminating the protein’s previously murky role, the researchers found that it works as a powerful immune checkpoint, reining in T cell effectiveness. Removing it, they showed, dramatically enhanced CAR T cell anticancer activity in a variety of preclinical cancer models.
“We’ve discovered in preclinical models that CD5 deletion greatly enhances the function of CAR T cells against multiple cancers,” said senior author Marco Ruella, MD, an assistant professor of Hematology-Oncology, researcher with the Center for Cellular Immunotherapies and the scientific director of Penn Medicine’s Lymphoma Program. “The striking effects we observed across preclinical models suggest that CD5 knockout could be a general strategy for enhancing CAR T cell function.”
The study’s first author is Ruchi Patel, PhD, a recent graduate student from the Ruella Laboratory.
Sherry (Xue) Gao, Presidental Penn Compact Associate Professor in Chemical and Biomolecular Engineering and in Bioengineering
Sherry (Xue) Gao, Presidential Penn Compact Associate Professor in Chemical and Biomolecular Engineering (CBE), always knew she had a future in the lab. “I grew up in China, and when I was little, maybe six or seven,” she recalls, “my teacher asked me, ‘What do you want to be when you grow up?’ I said, ‘I want to be a scientist!’”
Neither of her parents had studied beyond high school; when Gao finished her training as a chemical engineer, she became the first person in her family to graduate from college. “One of my greatest motivations is to help first-generation college students,” Gao says.
Now, as the newest faculty member in CBE, Gao is prepared to do just that: support the next generation of chemical engineers, while also conducting groundbreaking research in the development of small molecules to edit genes, pushing the boundaries of precision medicine.
The Presidential Penn Compact Professorships were created by former Penn President Amy Gutmann specifically to recruit and support faculty like Gao: transformative leaders working at the intersection of multiple fields with “a yen for collaboration,” as Gutmann told the Penn Gazette in 2021.
Gao joins Penn Engineering from Rice University, where she collected numerous accolades, including the 2024 BMES-CMBE Rising Star Award, a 2022 NSF CAREER Award, the 2022 Outstanding Young Faculty at Rice School of Engineering Award and the 2020 NIH MIRA R35 Award.
As a member of the Center for Precision Engineering for Health (CPE4H), Gao will partner with colleagues from across the School to develop technologies that bridge disciplines, all in the interest of advancing health care. “We are very excited to have Sherry as a new member of the Center,” says Daniel Hammer, Alfred G. and Meta A. Ennis Professor and inaugural Director of CPE4H. “Gene editing is an important new tool that can precisely alter cell behavior by deleting or redirecting cell pathways, as well as enhancing and suppressing gene expression. She will have significant interactions with other members of the Center, such as Mike Mitchell and myself, as well as the broader Penn community, especially with the CAR therapists.”
Younger scientists often ask him about exploring multiple fields, Balasubramanian says. The advice he offers is to “have a central line where you have credibility, where you’ve established that you’re really, really good at what you do, and you can be trusted.” (Image: Eric Sucar)
Academia is a long journey of specialization and behind any professor’s CV are long hours of research and study. While the path can be direct for some, for others there’s a pivot, a moment or experience that changes the course of that journey.
Penn Today spoke with four professors whose academic paths diverged, to learn about the trajectory of their interdisciplinary work. Vijay Balasubramanian traverses the boundaries of physics and neuroscience. Tukufu Zuberi is a demographer-turned-curator. Brittany Watson integrates education, research, and veterinary medicine. Amy Hillier began her career studying historical mortgage redlining and moved into supporting trans youth.
Vijay Balasubramanian The Cathy and Marc Lasry Professor of Physics in the School of Arts & Sciences
Wandering through Kolkata’s markets in India stimulates the mind. Hawkers’ cries pass through the inner ear as electrical signals; the pungent, earthy smell of turmeric enters the brain through olfactory sensory neurons. In 1976, a 7-year-old Vijay Balasubramanian had his own market revelation through a bookseller’s portico, where the cover of a slim volume showed a man peering through a microscope lens and a smattering of white paint scattered like stars across the firmament of man and machine.
“What is a scientist?” the book asked, running through a series of exciting adventure shots: archeologic discovery, venom extraction, missile control. In that moment, Balasubramanian knew he would be a scientist. It looked, he says, “amazingly cool.”
When he arrived at the Massachusetts Institute of Technology, Balasubramanian wanted to study the fundamental laws of nature. “So that’s physics,” he says. While earning his doctoral degree at Princeton University, a mentor suggested Balasubramanian read papers in the burgeoning field of neuroscience. It immediately resonated. “Oh my god, this stuff is so cool,” Balasubramanian thought. “But the final year of a Ph.D. is not the time to switch.”
He earned his degree and took a position as a junior fellow of the Harvard Society of Fellows. During the day, he worked on string theory and the information loss paradox for black holes. But in the evening, he would moonlight in a neuroscience lab.
As a young theoretical physicist at Penn, Balasubramanian met Peter Sterling. A former Freedom Rider and professor of neuroscience at the Perelman School of Medicine, Sterling was “a true intellectual,” Balasubramanian says. He knew everything, was interested in everything, and would talk with anybody.
The pair wrote a series of papers together regarding information processing and transmission. “He’s so quick and so much fun and so lively,” Sterling says of Balasubramanian. “He’s fearless; there’s nothing he won’t try.”
While in Cairo with wife Heather J. Sharkey, professor of modern Middle Eastern and North African history at Penn, Balasubramanian prepared a neuroscience grant and submitted it to the National Science Foundation, “sort of on a whim,” he says. “I put it in from an internet café on an island in the middle of the Nile.” He got the grant and started a research group.
After that, Balasubramanian says, “I was off and running.”
“I was certainly told,” Balasubramanian says of his work in neuroscience, “do not do this before tenure.” But, if he waited, “then I’d be too set my ways,” he says. “I just wouldn’t know enough; it would be too hard to learn; I wouldn’t have the time.”
Younger scientists often ask him about exploring multiple fields, Balasubramanian says. The advice he offers is to “have a central line where you have credibility, where you’ve established that you’re really, really good at what you do, and you can be trusted.” That gives you more latitude, he says.
After that, it’s just sheer discipline. “You’re going to have to wake up earlier than everybody else. You’re going to have to work longer days,” he says. “Otherwise, you know, everybody else is working hard too, and you’ll never be able to achieve the level of expertise and knowledge to be able to do things at that world-class level.”
Balasubramanian wants to see more interdisciplinary collaboration. “Each field trains its students with a certain body of techniques that has been found historically useful in that field,’ he says. “Very often, those techniques also have uses elsewhere, but they don’t know to apply it.”
Traversing borders can be helpful in producing new insights, Balasubramanian says. You can ask questions that people in the field won’t. You might experiment with new ideas or put two disjointed ideas together, he says. “If you’re coming from outside, you have the leeway to do all kinds of silly things. Sometimes, they’re not silly.”
Why not ask new questions and propose new answers? In the end, the data will tell you what’s true. “It gives me comfort to know how things tick.”
This post is adapted from a longer story in Penn Today. Read the full story here.
Balasubramanian is Cathy and Marc Lasry Professor in the Department of Physics and Astronomy in the Penn School of Arts and Sciences and is a member of the Penn Bioengineering Graduate Group. Read more stories featuring his research here.
Neurological disorders such as epilepsy, Alzheimers, Parkinson’s and certain forms of dementia are the leading cause of disability and second-leading cause of disease worldwide. These disorders disproportionately affect low-resourced communities due to lack of access to specialized healthcare, and many of these complex diseases lack curative solutions. The need to address neurological disorders is high, yet current diagnostics and treatments are not effective for preventative or personalized care and are not accessible or affordable enough to meet the needs of more than 3 billion people living with neurological disorders.
Flavia Vitale, Associate Professor in Bioengineering in Penn Engineering and in Neurology in Penn Medicine, works to meet this need, developing accessible and affordable solutions for the diagnosis, treatment and rehabilitation of people with neurological disorders.
“I started my research career in biomedical engineering hoping to one day help humanity,” says Vitale, who is also a 2024 recipient of a National Science Foundation (NSF) CAREER Award for her work. “But it wasn’t until I gained a more diverse skill set during my doctoral and postdoctoral research across chemical engineering and materials science that I was able to do that in a real way.”
Vitale’s multidisciplinary skills are what allow her to develop devices that help people living with brain disorders. The CAREER Award is now helping her further apply those skills and actualize some of her first long-term research projects at Penn.
“This CAREER Award will support my lab’s current research in leveraging innovation in materials and fabrication approaches to develop devices that are able to interface with and control different chemical and electrical signals inside the brain,” she says.
Focused primarily on understanding the brain activity involved in epilepsy-induced seizures, Vitale aims to design and develop brain-interface devices to pinpoint and suppress uncontrolled brain activity to prevent seizures from happening. Her work will lead to revolutionary health care for the 30% of epilepsy patients whose conditions are drug resistant. Currently those patients either wait out the uncontrolled brain activity and oftentimes life-threatening convulsions, or hope to be eligible for invasive surgeries to remove the part of the brain where seizures originate or to implant the seizure-controlling devices that are currently available.
How do we measure chaos and why would we want to? Together, Penn engineers Dani S. Bassett, J. Peter Skirkanich Professor in Bioengineering and in Electrical and Systems Engineering, and postdoctoral researcher Kieran Murphy leverage the power of machine learning to better understand chaotic systems, opening doors for new information analyses in both theoretical modeling and real-world scenarios.
Humans have been trying to understand and predict chaotic systems such as weather patterns, the movement of planets and population ecology for thousands of years. While our models have continued to improve over time, there will always remain a barrier to perfect prediction. That’s because these systems are inherently chaotic. Not in the sense that blue skies and sunshine can turn into thunderstorms and torrential downpours in a second, although that does happen, but in the sense that mathematically, weather patterns and other chaotic systems are governed by physics with nonlinear characteristics.
“This nonlinearity is fundamental to chaotic systems,” says Murphy. “Unlike linear systems, where the information you start with to predict what will happen at timepoints in the future stays consistent over time, information in nonlinear systems can be both lost and generated through time.”
Like a game of telephone where information from the original source gets lost as it travels from person to person while new words and phrases are added to fill in the blanks, outcomes in chaotic systems become harder to predict as time passes. This information decay thwarts our best efforts to accurately forecast the weather more than a few days out.
“You could put millions of probes in the atmosphere to measure wind speed, temperature and precipitation, but you cannot measure every single atom in the system,” says Murphy. “You must have some amount of uncertainty, which will then grow, and grow quickly. So while a prediction for the weather in a few hours might be fairly accurate, that growth in uncertainty over time makes it impossible to predict the weather a month from now.”
In their recent paper published in Physical Review Letters, Murphy and Bassett applied machine learning to classic models of chaos, physicists’ reproductions of chaotic systems that do not contain any external noise or modeling imperfections, to design a near-perfect measurement of chaotic systems to one day improve our understanding of systems including weather patterns.
“These controlled systems are testbeds for our experiments,” says Murphy. “They allow us to compare with theoretical predictions and carefully evaluate our method before moving to real-world systems where things are messy and much less is known. Eventually, our goal is to make ‘information maps’ of real-world systems, indicating where information is created and identifying what pieces of information in a sea of seemingly random data are important.”
Bicontinuous materials, like this representation of a cube of gelatin and hyaluronic acid, have greater internal surface area, allowing cells to travel faster between two points. (Credit: Karen Xu)
One of the most important but least understood aspects of healing is cell migration, or the process of cells moving from one part of the body to another. “If you are an ambulance out in the woods,” says Karen Xu, an M.D/Ph.D. student in Medicine and Bioengineering, “and there are no paths for you to move forward, it will be a lot harder for you to get to a site that needs you.”
Earlier this year, Xu co-authored a paper in Nature Communications describing a new cue to help cells get to where they need to go: a material made chiefly of hyaluronic acid and gelatin, two gooey substances commonly found outside cells in joints and connective tissue.
“Hundreds of thousands of people tear their meniscus every year,” says Robert Mauck, Mary Black Ralston Professor in Orthopaedic Surgery in Penn Medicine and Professor in Bioengineering at Penn Engineering and one of Xu’s advisors, as well as a senior author on the paper. “This material could potentially speed up their recovery.”
What makes the material — known as a hydrogel due to its blend of gelatinous matter and water — unique is that the combination of hyaluronic acid and gelatin forms a complex network of paths, providing cells many different ways to travel between two points.
This property is known as bicontinuity, and is exemplified by two discrete continuous phases that are each connected throughout the entire volume of the material (for example with a sponge, with phases of cellulose and air; in the hydrogel, this is comprised of gelatin and hyaluronic acid) resulting in a dizzying array of patterns that dramatically increase the surface area inside the material.
To test the hydrogel’s efficacy, Xu and her collaborators — including co-advisor Jason Burdick, formerly the Robert D. Bent Professor in Bioengineering at Penn Engineering and now the Bowman Endowed Professor at the University of Colorado Boulder, and the paper’s other senior author — first created several different versions of the hydrogel to find the sweet spot at which the constituents formed the bicontinuous structure and had the highest internal surface area. “We found that a precise combination of the various hydrogel components and control over their mixing was needed to form the bicontinuous structure,” says Burdick.
Enamored by the chemical processes of life, Yihui Shen, J. Peter and Geri Skirkanich Assistant Professor of Innovation in Bioengineering, started her research career as a chemist studying the way that proteins fold and the intricate dynamics underlying life processes.
“As an undergraduate, I studied physical chemistry, thinking that one day I’d be addressing challenges in hardcore STEM fields,” she says. “It wasn’t until I observed the dynamics of a single protein molecule that I fell in love with microscopy. I realized that this imaging tool could not only help us observe biological processes on a small scale, but it could also provide new insight at the interface of engineering, chemistry and physics and solve problems on a large scale.”
When Shen turned her attention to microscopy, the field itself was advancing quickly, with improvements being made and new techniques being released every month. Without missing a beat, Shen dove deeper into the most current tools available when she joined Dr. Wei Min’s lab at Columbia University as a doctoral student.
“Professor Wei Min is a pioneer in a new imaging technique called coherent Raman imaging,” says Shen. “In this type of microscopy, we focus light on a very specific point in the cell and measure the amount of scattered light that comes back after exchanging energy with the molecular vibration. This approach allows us to visualize the spatial distribution of different molecules, the very chemistry of life I had studied as an undergraduate, at a high enough resolution to gain insights into biological processes, such as tissue organization, drug distribution and cellular metabolism.”
With this new tool under her belt, Shen was able to ask the kinds of questions that could connect the use of this observation tool to practical applications for real-world challenges.
“I started thinking outside the box,” says Shen. “What if we could observe the chemical exchanges involved in metabolism as they are happening on the scale of a single cell, and then use that insight to pinpoint the exact metabolic pathways and molecules that facilitate tumor growth and disease?”
Lipid nanoparticles present one of the most advanced drug delivery platforms to shuttle promising therapeutics such as mRNA but are limited by the time it takes to synthesize cationic lipids, a key component. Now, Michael Mitchell and his team at the School of Engineering and Applied Science have developed a faster way to make cationic lipids that are also more versatile, able to carry different kinds of treatments to target specific organs. (Image: iStock / Dr_Microbe)
Imagine a scenario where a skilled hacker must upload critical software to update a central server and thwart a potentially lethal virus from wreaking havoc across a vast computer network. The programmer, armed with the lifesaving code, must navigate through treacherous territory teeming with adversaries, and success hinges on promptly getting a safe, stealthy delivery vehicle that can place the hacker exactly where they need to be.
In the context of modern medicine, messenger RNA (mRNA) serves as the hacker, carrying genetic instructions to produce specific proteins within cells that can induce desired immune responses or sequester maladaptive cellular elements. Lipid nanoparticles (LNPs) are the stealthy delivery vehicles that transport these fragile mRNA molecules through the bloodstream to their target cells, overcoming the body’s defenses to deliver their payload safely and efficiently.
However, much like building an advanced stealth vehicle, the synthesis of cationic lipids—a type of lipid molecule that’s positively charged and a key component of LNPs—is often a time-consuming process, involving multiple steps of chemical synthesis and purification.
Now, Michael Mitchell and a team at the University of Pennsylvania have addressed this challenge with a novel approach that leverages a compound library fabrication technique known as “click-like chemistry” to create LNPs in a single, simple step. Their findings, published in the journal Nature Chemistry, show that this method not only speeds up the synthesis process but also presents a way to equip these delivery vehicles with a “GPS” to better target specific organs such as the liver, lungs, and spleen, potentially opening new avenues for treating a range of diseases that arise in these organs.
“We’ve developed what we call an amidine-incorporated degradable (AID) lipid, a uniquely structured biodegradable molecule,” Mitchell says. “Think of it as an easy-to-build custom mRNA vehicle with a body kit that informs its navigation system. By adjusting its shape and degradability, we can enhance mRNA delivery into cells in a safe manner. By adjusting the amount of the AID lipid that we incorporate into the LNP, we can also guide it to different organs in the body, much like programming different destinations into a GPS.”
First author Xuexiang Han, a former postdoctoral researcher in the Mitchell Lab, explains that their new approach allows the rapid creation of diverse lipid structures in just an hour, compared to the weekslong process traditionally required.
Congratulations to the fifteen Bioengineering students to receive 2024 National Science Foundation Graduate Research Fellowship Program (NSF GRFP) fellowships. The prestigious NSF GRFP program recognizes and supports outstanding graduate students in NSF-supported fields. The recipients were selected from a highly-competitive, nationwide pool. Further information about the program can be found on the NSF website.
The following Ph.D. students in Bioengineering received awards:
Congratulations to Alison Pouch, Assistant Professor in Bioengineering in the School of Engineering and Applied Science, and in Radiology in the Perelman School of Medicine, on winning a 2024 Cardiac Center Innovation Award for scientific research from the Children’s Hospital of Philadelphia (CHOP)’s Philly Spin-In. Pouch’s study, titled “Systemic Semilunar Valve Mechanics and Simulated Repair in Congenital Heart Disease,” is a collaboration with Matthew Jolley, Assistant Professor of Anesthesiology and Critical Care at CHOP:
“Through biomechanical assessment, Drs. Matthew Jolley and Alison Pouch are leading an interdisciplinary CHOP-Penn team that plans to determine why current approaches to systemic semilunar valve (SSV) repair fail. They will also investigate methods to design improved repairs before going to the operating room by using computational simulation to iteratively optimize repair.
‘We believe that understanding biomechanics of abnormal SSVs and explorations of simulated repair will markedly improve our ability to characterize, risk stratify, and surgically treat SSV dysfunction, thereby improving long-term outcomes and quality of life in patients with SSV dysfunction,’ Dr. Jolley said.”
Pouch’s lab focuses on 3D/4D segmentation and modeling of heart valves in echocardiographic images with applications to surgical treatment of valvular regurgitation as part of the Penn Image Computing and Science Laboratory.
