Tag: Penn Medicine

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Knockout of CD5 on CAR T Cells Boosts Anti-Tumor Efficacy

by Meagan Raeke

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.

Read the full story in Penn Medicine News.

Marco Ruella is a member of the Penn Bioengineering Graduate Group. Read more stories featuring Ruella in the BE Blog.

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2024 CAREER Award Recipient: Flavia Vitale

by Melissa Pappas

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.

Read the full story in Penn Engineering Today.

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Highways to Health: Bicontinuous Structures Speed Up Cell Migration

by Ian Scheffler

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.

Read the full story in Penn Engineering Today.

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From Chance to Certainty: Solving Science’s Reproducibility Crisis

by Ian Scheffler

Jamie Moffa, host of In Plain English; Konrad Kording, Kaela Singleton and Arjun Raj

One of the pillars of science is the idea that experimental results can be replicated. If they cannot be reproduced, what if the findings of an experiment were due just to chance? Over the last two decades, a growing chorus of scientists has raised concerns about the “reproducibility crisis,” in which many published research findings can’t be independently validated, calling into question the rigor of contemporary science.

Two years ago, a group led by Konrad Kording, a Penn Integrates Knowledge Professor in Bioengineering and Neuroscience, founded the Community For Rigor (C4R) to build a grassroots movement to improve the rigor of scientific research.

Supported by a grant from the National Institutes of Health (NIH) and partners at Harvard, Duquesne, Smith College and Johns Hopkins, among other institutions, C4R creates educational materials that teach the principles of rigorous research, from data collection to pre-registration of results. “Everyone has done wrong things,” says Kording. “We’re all making these mistakes and we need to be able to talk about it.”

Last month, Kording appeared on In Plain English, a podcast devoted to making science more accessible, alongside Kaela Singleton, the co-founder and President of Black in Neuro; Arjun Raj, Professor in Bioengineering in Penn Engineering and in Genetics in Penn Medicine; and Jamie Moffa, a physician-scientist in training at Washington University in St. Louis, to discuss scientific rigor, including actionable strategies for students and faculty alike.

The conversation touched on everything from successfully managing the reams of data produced by experiments to the power of community to drive cultural change, as well as the difficulty of filtering useful feedback from the noise of social media. “I hope we can get to a point where people feel comfortable sharing what’s working and what’s not working,” says Raj.

Listen to the episode here.

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Showing Up for Penn in London

by Laura Bellet

Leaders and faculty from Penn Medicine, including Kevin Mahoney, Carl June, John Wherry, and Mike Mitchell (pictured left to right), speak on stage during the Penn London symposium.

Sharing the exciting work happening at Penn with alumni, parents, and friends throughout the world is a priority for Interim President J. Larry Jameson.

Shortly after challenging the graduating Class of 2024 to “keep reinventing, learning, and engaging” he brought that same spirit to the Penn community in London. He met with leadership volunteers from the region and welcomed approximately 200 attendees to an academic symposium titled “Frontiers of Knowledge and Discovery: Leading in a Changing World.”

Kevin Mahoney, CEO of the University of Pennsylvania Health System, moderated the first panel, on the genesis of breakthroughs. “When our faculty explain how landmark achievements like new fields of science or first-in-class cancer therapies come about, they never fail to emphasize how collaboration turns expertise into progress,” he said. “Hearing Mike Mitchell, John Wherry, and Carl June speak made plain how our brilliant, interconnected Penn faculty work together on one campus with results that are changing our world.”

Vijay Kumar, the Nemirovsky Family Dean of Penn Engineering, shared Mahoney’s perspective on collaboration—with a twist. “Non-engineers can be mystified, if not intimidated, by the complexities of the work we do,” he explained. “When a faculty member breaks down a project and talks it through, step by step, the engineering concepts become so much more understandable and relatable.” Kumar moderated a session with Dan Rader and Rene Vidal that focused on the increasing and powerful synergies among data science and AI, medical research, and clinical practice

Read the full story in the Penn Giving website.

Michael Mitchell is Associate Professor in Bioengineering. Read more stories featuring Mitchell in the BE Blog.

Carl June is Richard W. Vague Professor in Immunotherapy in the Perelman School of Medicine and is a member of the Penn Bioengineering Graduate Group. Read more stories featuring June in the BE Blog.

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Alison Pouch Wins 2024 Cardiac Center Innovation Award

Alison Pouch

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.

Read the full awards announcement in the CHOP Cornerstone Blog.

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How to Learn About a World-class Double Bass? Give it a CT

by Darcy Lewis  

The instrument imaging team, from left: Philadelphia Orchestra bassist Duane Rosengard; Peter Noël, PhD, director of CT Research at the Perelman School of Medicine; luthier Zachary S. Martin; Leening Liu, a PhD student in Noël’s Laboratory of Advanced Computed Tomography Imaging; and Mark Kindig.

When you’re an expert in medical CT imaging, two things are bound to happen, says Peter Noël, PhD, associate professor of Radiology and director of CT Research at the Perelman School of Medicine. One: You develop an insatiable curiosity about the inner workings of all kinds of objects, including those unrelated to your research. And two: Both colleagues and complete strangers will ask for your help in imaging a wide variety of unexpected items.

Over the course of his career, in between managing his own research projects, Noël has imaged diverse objects ranging from animal skulls to tree samples from a German forest, all in the name of furthering scientific knowledge. But none has intrigued him as much as his current extracurricular project: the first known attempt to perform CT imaging of some of the world’s finest string basses. 

The goal is to crack the code on what makes a world-class instrument. This knowledge could both increase the ability to better care for masterworks built between the 17th and 19th centuries, as well as providing insights into refining the building of new ones, including possibly shifting from older, scarcer European wood to the use of sustainably harvested U.S. wood.

That’s why Noël and Leening Liu, a PhD student in Noël’s Laboratory of Advanced Computed Tomography Imaging, have found themselves volunteering to run the basses through a Penn CT scanner occasionally, when they’re not developing next-generation CT technology. 

“We always learn something out of projects like this … the more appealing part is that medical research can also be applied to non-medical things,” Noël said. “We have the opportunity to take what we learn in medicine and use it for something else—in this case, moving the arts forward.”

Read the full story in Penn Medicine News.

Peter Noël is Assistant Professor of Radiology in the Perelman School of Medicine and member of the Penn Bioengineering Graduate Group.

Leening Liu is a Ph.D. student in Bioengineering. She is a member of the Laboratory for Advanced Tomography Imaging (LACTI) with research interests including clinical applications of spectral CT and spectral CT thermometry.

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Who, What, Why: Lasya Sreepada on Decoding Alzheimer’s Disease

by Nathi Magubane

Lasya Sreepada, Ph.D. student in Bioengineering

Lasya Sreepada has always been fascinated by the brain and the underlying biology that shapes how people develop and age. “My curiosity traces back to observing differences between myself and my sister,” says Sreepada, a Ph.D. candidate in Bioengineering whose research unites efforts across Penn Medicine and Penn Engineering. “We grew up in the same environment but had remarkably different personalities, which led me to question what drove these differences and which brought me to the brain.”

Her academic journey began by applying medical imaging to understand how brain injuries sustained by professional athletes or military veterans impact their brain structure and chemistry over time. She became curious about how neurotrauma impacts aging and degeneration in the long term. Now, she leverages large, multimodal datasets to investigate neurodegenerative disease, with a particular focus on Alzheimer’s.

Read the full story in Penn Today.

Lasya Sreepada is a Bioengineering Ph.D. student at the Bioinformatics in Neurodegenerative Disease (BiND) Lab at Penn, advised by Corey McMillan and Dave Wolk, both Associate Professors in Neurology and members of the Bioengineering Graduate Group.

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Looking to AI to Solve Antibiotic Resistance

by Nathi Magubane

Cesar de la Fuente (left), Fangping Wan (center), and Marcelo der Torossian Torres (right). Fangping holds a 3D model of a unique ATP synthase fragment, identified by their lab’s deep learning model, APEX, as having potent antibiotic properties.

“Make sure you finish your antibiotics course, even if you start feeling better’ is a medical mantra many hear but ignore,” says Cesar de la Fuente of the University of Pennsylvania.

He explains that this phrase is, however, crucial as noncompliance could hamper the efficacy of a key 20th century discovery, antibiotics. “And in recent decades, this has led to the rise of drug-resistant bacteria, a growing global health crisis causing approximately 4.95 million deaths per year and threatens to make even common infections deadly,” he says.

De la Fuente, a Presidential Assistant Professor, and a team of interdisciplinary researchers have been working on biomedical innovations tackling this looming threat. In a new study, published in Nature Biomedical Engineering, they developed an artificial intelligence tool to mine the vast and largely unexplored biological data—more than 10 million molecules of both modern and extinct organisms— to discover new candidates for antibiotics.

“With traditional methods, it takes around six years to develop new preclinical drug candidates to treat infections and the process is incredibly painstaking and expensive,” de la Fuente says. “Our deep learning approach can dramatically reduce that time, driving down costs as we identified thousands of candidates in just a few hours, and many of them have preclinical potential, as tested in our animal models, signaling a new era in antibiotic discovery.” César de la Fuente holds a 3D model of a unique ATP synthase fragment, identified by his lab’s deep learning model, APEX, as having potent antibiotic properties. This molecular structure, resurrected from ancient genetic data, represents a promising lead in the fight against antibiotic-resistant bacteria.

These latest findings build on methods de la Fuente has been working on since his arrival at Penn in 2019. The team asked a fundamental question: Can machines be used to accelerate antibiotic discovery by mining the world’s biological information? He explains that this idea is based on the notion that biology, at its most basic level, is an information source, which could theoretically be explored with AI to find new useful molecules.

Read the full story in Penn Today.

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Largest-Ever Antibiotic Discovery Effort Uses AI to Uncover Potential Cures in Microbial Dark Matter

by Eric Horvath

Credit: Georgina Joyce

Almost a century ago, the discovery of antibiotics like penicillin revolutionized medicine by harnessing the natural bacteria-killing abilities of microbes. Today, a new study co-led by researchers at the Perelman School of Medicine at the University of Pennsylvania suggests that natural-product antibiotic discovery is about to accelerate into a new era, powered by artificial intelligence (AI).

The study, published in Cell, the researchers used a form of AI called machine learning to search for antibiotics in a vast dataset containing the recorded genomes of tens of thousands of bacteria and other primitive organisms. This unprecedented effort yielded nearly one million potential antibiotic compounds, with dozens showing promising activity in initial tests against disease-causing bacteria.

“AI in antibiotic discovery is now a reality and has significantly accelerated our ability to discover new candidate drugs. What once took years can now be achieved in hours using computers” said study co-senior author César de la Fuente, PhD, a Presidential Assistant Professor in Psychiatry, Microbiology, Chemistry, Chemical and Biomolecular Engineering, and Bioengineering.

Nature has always been a good place to look for new medicines, especially antibiotics. Bacteria, ubiquitous on our planet, have evolved numerous antibacterial defenses, often in the form of short proteins (“peptides”) that can disrupt bacterial cell membranes and other critical structures. While the discovery of penicillin and other natural-product-derived antibiotics revolutionized medicine, the growing threat of antibiotic resistance has underscored the urgent need for new antimicrobial compounds.

In recent years, de la Fuente and colleagues have pioneered AI-powered searches for antimicrobials. They have identified preclinical candidates in the genomes of contemporary humans, extinct Neanderthals and Denisovans, woolly mammoths, and hundreds of other organisms. One of the lab’s primary goals is to mine the world’s biological information for useful molecules, including antibiotics.

Read the full story in Penn Medicine News.