Avery Posey’s cancer research takes high risks for big rewards

by Melissa Moody

Avery Posey, PhD (Image: Penn Medicine Newsby Melissa Moody

Much of the world, including research at Penn Medicine, has focused its attention on how T cells–which play a central role in immune response—might shape the trajectory of COVID-19 infection, and how immunotherapy can shed light on treatment of the disease.

Already a leader in immunotherapy research and treatment, Penn Medicine pioneered the groundbreaking development of CAR T cell cancer therapy. Avery Posey, an assistant professor of systems pharmacology and translational therapeutics, trained as a postdoctoral fellow in the lab of Carl June, who pioneered CAR T cell immunotherapy to treat cancer. Now as a faculty member at Penn, Posey has maintained a focus on T cell therapeutics, mostly for the treatment of cancer.

“This research combines two of my biggest interests—the use of gene therapy to treat disease and the investigation of little known biology, such as the roles of glycans in cell behavior. The pursuit of new knowledge, the roads less traveled—those are my inspirations,” Posey says.

Read more at Penn Medicine News.

N.B.: Avery Posey and Carl June are members of the Department of Bioengineering Graduate Group. Learn more about BE’s Grad Group Faculty here.

Penn Bioengineering’s Tsourkas Lab and Penn Start-up AlphaThera Awarded $667,000 SBIR Phase II Grant to Improve COVID-19 Detection Assays

To combat the COVID-19 pandemic caused by the SARS-CoV2 virus, Dr. Andrew Tsourkas’s Targeted Imaging Therapeutics and Nanomedicine (Titan) Lab in Penn Bioengineering, in collaboration with the Penn-based startup, AlphaThera, was recently awarded a $667,000 SBIR Phase II Grant Extension to support its efforts in commercializing COVID-19 detection technology. The grant supports work to address the growing need for anti-viral antibody testing. Specifically, the Tsourkas Lab and AlphaThera hope to leverage their expertise with antibody conjugation technologies to reduce the steps and complexity of existing detection assays to enable greater production and higher sensitivity tests. AlphaThera was founded in 2016 by Andrew Tsourkas, PhD, Professor of Bioengineering and James Hui, MD, PhD, a graduate of the Perelman School of Medicine and Penn Bioengineering’s doctoral program.

During this pandemic it is crucial to characterize disease prevalence among populations, understand immunity, test vaccine efficacy and monitor disease resurgence. Projections have indicated that millions of daily tests will be needed to effectively control the virus spread. One important testing method is the serological assay: These tests detect the presence of SARS-CoV2 antibodies in a person’s blood produced by the body’s immune system responding to infection. Serological tests not only diagnose active infections, but also establish prior infection in an individual, which can greatly aid in forecasting disease spread and contact tracing. To perform the serological assays for antibody detection, well-established immunoassay methods are used such as ELISA.

A variety of issues have slowed the distribution of these serological assays for antibody testing. The surge in demand for testing has caused shortages in materials and reagents that are crucial for the assays. Furthermore, complexity in some of the assay formats can slow both production and affect the sensitivity of test results. Recognizing these problems, AlphaThera is leveraging its novel conjugation technology to greatly improve upon traditional assay formats.

With AlphaThera’s conjugation technology, the orientation of antibodies can be precisely controlled so that they are aligned and uniformly immobilized on assay detection plates. This is crucial as traditional serological assays often bind antibodies to plates in a non-uniform manner, which increases variability of results and reduces sensitivity. See Fig 1 below. With AlphaThera’s uniform antibody immobilization, assay specificity could increase by as much as 1000- fold for detection of a patient’s SaRS-CoV2 antibodies.

Fig 1: Uniform vs Non-Uniform Immobilized Antibodies on Surface: Top is AlphaThera improvement, showing how antibodies would be uniformly immobilized and oriented on a plate for detection. Bottom is how many traditional serological assays immobilize antibodies, resulting in variability of results and lower specificity.

Furthermore, AlphaThera is addressing the shortage of assay reagents, specifically secondary antibody reagents, by removing certain steps from traditional serological assays. Rather than relying on secondary antibodies for detection of the patient antibodies, AlphaThera’s technology can label the patient SaRS-CoV2 primary antibodies directly in serum with a detection reagent. This eliminates several processing steps, reducing the time of the assay by as much as 50%, as well as the costs.

The Tsourkas Lab and AlphaThera have initiated their COVID-19 project, expanding into the Pennovation Center and onboarding new lab staff. Other antibody labeling products have also become available and are currently being prepared for commercialization. Check out the AlphaThera website to learn more about their technology at https://www.alphathera.com.

NIH SBIR Phase II Grant Extension— 5-R44-EB023750-03 (PI: Yu)  — 10/07/2020 – 10/07/2021

Jennifer Phillips-Cremins Wins CZI Grant to Study 3D Genome’s Role in Neurodegenerative Disease

The Chan Zuckerberg Initiative’s Collaborative Pairs Pilot Project Award is part of its Neurodegeneration Challenge Network

Jennifer Phillips-Cremins, Ph.D.

Read the full story on the Penn Engineering blog.

Danielle Bassett on ‘A Radical New Model of the Brain’

In a ‘Wired’ feature, Bassett helps explain the growing field of network neuroscience and how the form and function of the brain are connected.

Danielle Bassett, Ph.D.

Early attempts to understand how the brain works included the pseudoscience of phrenology, which theorized that various mental functions could be determined through the shape of the skull. While those theories have long been debunked, modern neuroscience has shown a kernel of truth to them: those functions are highly localized to different regions of the brain.

Now, Danielle Bassett, Professor of J. Peter Skirkanich Professor of Bioengineering and Electrical and Systems Engineering, is pioneering a new subfield that goes even deeper into the connection between the brain’s form and function: network neuroscience.

In a recent feature article in Wired, Bassett explains the concepts behind this new subfield. While prior understanding has long relied on the idea that certain areas of the brain control certain functions, Bassett and other network neuroscientists are using advances in imaging and machine learning to reveal the role the connections between those areas play.

For Bassett, one of the first indicators that these connections mattered more than previously realized was the shape of the neurons themselves.

Speaking with Wired’s Grace Huckins, Bassett says:

“Neurons are not spherical — neurons have a cell body, and then they have this long tail that allows them to connect to many other cells. You can even look at the morphology of the neuron and say, ‘Oh, well, connectivity has to matter. Otherwise, it wouldn’t look like this.’”

Read more about Bassett and the field of network neuroscience in Wired.

Originally posted on the Penn Engineering blog.

César de la Fuente Wins Inaugural NEMO Prize, Will Develop Rapid COVID Virus Breath Tests

The paper-based tests could be integrated directly into facemasks and provide instant results at testing sites.

Cesar de la Fuente-Nunez, PhD

When Penn Health-Tech announced its Nemirovsky Engineering and Medicine Opportunity, or NEMO Prize, in February, the center’s researchers could only begin to imagine the impact the looming COVID-19 pandemic was about to unleash. But with the promise of $80,000 to support early-stage ideas at the intersection of engineering and medicine, the contest quickly sparked a winning innovation aimed at combating the crisis.

Judges from the University of Pennsylvania’s School of Engineering and Applied Sciences and Perelman School of Medicine awarded its first NEMO Prize to César de la Fuente, PhD, who proposed a paper-based COVID diagnostic system that could capture viral particles on a person’s breath, then give a result in a matter of seconds when taken to a testing site.

Similar tests for bacteria cost less than a dollar each to make. De la Fuente, a Presidential Assistant Professor in the departments of Psychiatry, Microbiology, and Bioengineering, is aiming to make COVID tests at a similar price point and with a smaller footprint so that they could be directly integrated into facemasks, providing further incentive for their regular use.

“Wearing a facemask is vital to containing the spread of COVID because, before you know you’re sick, they block your virus-carrying droplets so those droplets can’t infect others,” de la Fuente says. “What we’re proposing could eventually lead to a mask that can be infected by the virus and let you know that you’re infected, too.”

De la Fuente’s lab has conducted molecular dynamic simulations of the regions of the SARS-COV-2 spike protein (blue) that bind to the human ACE2 receptor (red and yellow).

De la Fuente’s expertise is in synthetic biology and molecular-scale simulations of disease-causing viruses and bacteria. Having such fine-grained computational models of these microbes’ binding sites allow de la Fuente to test them against massive libraries of proteins, seeing which bind best. Other machine learning techniques can then further narrow down the minimum molecular structures responsible for binding, resulting in functional protein fragments that are easier to synthesize and manipulate.

The spike-shaped proteins that give coronaviruses their crown-like appearance and name bind to a human receptor known as ACE2. De la Fuente and his colleagues are now aiming to characterize the molecular elements and environmental factors that would allow for the most precise, reliable detection of the virus.

Read the full story on the Penn Engineering blog.

Rooting Out Systemic Bias in Neuroscience Publishing

An interdisciplinary research team has found statistical evidence of women being under-cited in academic literature. They are now studying similar effects along racial lines.

By Izzy Lopez

Danielle Bassett, Jordan Dworkin and Perry Zurn are leading efforts to analyze systemic bias in neuroscience citations, and have suggestions for combatting it.

Scientific papers are the backbone of a research community and the citation of those papers sparks conversation in a given field. This cycle of publication and citation leads to new knowledge, but what happens when implicit discrimination in a field leads to papers by minority scholars being cited less often than their counterparts? A new team of researchers has come together to ask this question and dig into the numbers of gender and racial bias in neuroscience.

The team members include physicist and neuroscientist Danielle Bassett, J. Peter Skirkanich Professor of Bioengineering at the University of Pennsylvania, with secondary appointments in the Departments of Neurology and Psychiatry in Penn’s Perelman School of Medicine, statistician Jordan Dworkin, then a graduate student in Penn Medicine’s Department of Biostatistics, Epidemiology and Bioinformatics, and ethicist Perry Zurn, an Assistant Professor of Philosophy at American University.

Their study on gender bias, which recently appeared in Nature Neuroscience, reports on the extent and drivers of gender imbalance in neuroscience reference lists. The team has also published a perspective paper in Neuron that makes practical recommendations for improving awareness of this issue and correcting for biases.

They are now working on a second study, led by Maxwell Bertolero, a postdoctoral researcher in Bassett’s lab, that considers the extent and drivers of racial imbalances in neuroscience reference lists.

Together, Bassett, Dworkin and Zurn are using their combined research strengths to uncover the under-citation of women or otherwise minority-led papers in neuroscience and to assess its significance. This research is fundamental in highlighting a true gap in representation in research paper citations, which can have detrimental effects for women and other minorities leading science. In addition, they provide actionable steps to address the problem and build a more equitable future.

Your research team is a distinctive one. How did you come together for a study about gender discrimination in neuroscience citations?

As it turns out, there is really strong literature on issues of diversity and citation in science. Some disciplines have done field-specific investigations, such as the foundational studies in political science, international relations, and economics, but there wasn’t yet any research in neuroscience. Since biomedical sciences often have different approaches to citation, it seemed that it would be worth doing a deeper neuroscience-specific investigation to give quantitative backing to the issue of gender bias in neuroscience research.

Danielle Bassett: When Jordan and I started working together on this project, I knew it was important. To do it right, we needed to present the information in a way that made it actionable, with clear recommendations about how each of us as scientists can help address the issue. We also needed to add someone to the team with expertise in gender theory and research ethics. We especially wanted to make sure we were discussing gender bias in a way that was informed by recent advances in gender studies. That’s when we brought Perry in.

Perry Zurn: I’m a philosopher by training, with a focus on ethics and politics. Citations are both an ethical and a political issue. Citations reflect whose questions and whose contributions are recognized as important in the scholarly conversation. As such, citations can either bring in marginalized voices, voices that have been historically excluded from a conversation, or they can simply replicate that exclusion. My own field of philosophy has just as much of a problem with gender and racial diversity as STEM fields, something Dani and I have been talking about for a long time. This work seemed like a natural point of collaboration.

Describe this study and what it means for promoting gender diversity in neuroscience.

Dworkin: To understand the role of gender in citation practices, we looked at the authors and reference lists of articles published in five top neuroscience journals since 1995. We accounted for self-citations, and various potentially relevant characteristics of papers, and we found that women-led papers are under-cited relative to what would be expected if gender was not a consideration in citation behavior. Importantly, we also found that the under-citation of women-led papers is driven largely by the citation behavior of men-led teams. We also found that this trend is getting worse over time, because the field is getting more diverse while citation rates are generally staying the same.

For a very simple example, if there were 10 women and 90 men neuroscientists in 1980, then citing 10% women would be roughly proportional. But with a diversifying field, say there are now 200 women and 200 men neuroscientists and citations are still 10% women. Sure, the percentage of women cited didn’t go down, but that percentage is now vastly lower than the true percentage in the field. That’s a dramatic example, but it shows you that if we’re going to call for equality in scientific citation, the number of women-led papers on a given reference list should reflect, or even exceed, the number of available and relevant women-led papers in a field, and our work found that it does not.

Bassett: This under-citation of women scientists is a key issue because the gaps in the amount of engagement that women’s work receives could have detrimental downstream effects on conference invitations, grant and fellowship awards, tenure and promotion, inclusion in syllabi, and even student evaluations. As a result, understanding and eliminating gender bias in citation practices is vital for addressing gender imbalances in a field.

Why are citations important to gender representation in neuroscience?

Bassett: There are a lot of underrepresented scholars who have fantastic ideas and write really interesting papers but they’re not being acknowledged — and cited — in the way they deserve. And there are great role models for all the young women who are thinking about going into science, but unless the older women scientists are being cited, the younger ones will never see them. Without serious changes in the field, and a deep commitment to gender and racial diversity, many young women and minority scientists won’t stick with it, they won’t be hired, they won’t be promoted, and they won’t be put in the textbooks.

Zurn: Exactly. I think it’s important not only to think about who we’re citing as leading scientists, but also what sorts of people we’re representing as scientists at all. If you are looking at neuroscience as a field and you see predominantly white cisgender men in the research labs and the reference lists, then you begin to think that is what a neuroscientist looks like. But this homogeneity is neither representative of an increasingly diverse field like neuroscience, nor supportive of continuing efforts to diversify STEM in general. We need to expand what a scientist looks like and citations are one way to do that.

Read the full interview on the Penn Engineering blog.

Danielle Bassett also has appointments in Penn Engineering’s Department of Electrical and Systems Engineering and Penn Arts & Sciences Department of Physics and Astronomy.

Jordan Dworkin is now an Assistant Professor of Clinical Biostatistics in the Department of Psychiatry at Columbia University.

Kristin Linn, Assistant Professor of Biostatics, Russell Shinohara, Associate Professor of Biostatistics, and Erin Teich, a postdoctoral researcher in Bassett’s lab, also contributed to the study published in Nature Neuroscience. It was supported by the National Institute of Neurological Disorders and Stroke through grants R01 NS085211 and R01 NS060910, the John D. and Catherine T. MacArthur Foundation, the Alfred P. Sloan Foundation, and the National Science Foundation through CAREER Award PHY-1554488.

Lyle Ungar: ‘Philadelphia Needs More Contact Tracers’

Lyle Ungar, Ph.D. (Photo: Eric Sucar)

In May, Lyle Ungar, Professor of Computer and Information Science and Angela Duckworth, Rosa Lee and Egbert Chang Professor in Penn Arts & Sciences and the Wharton School, contributed to a New York Times op-ed on how to slow the COVID-19 pandemic through a culture of mask-wearing.

As infections continue to rise, Ungar and Duckworth are following up with another op-ed. Writing in the Philadelphia Inquirer, they outline the need to rapidly ramp-up the city and state’s contact tracing capacity:

Guidelines from health officials suggest Pennsylvania needs about 4,000 contact tracers, including 2,000 for the Philadelphia metro area. Our state has been operating with fewer than 200.

Continue reading Ungar and Duckworth’s op-ed at the Philadelphia Inquirer.

Originally posted on the Penn Engineering blog. Media contact Evan Lerner.

Lyle Ungar is a Professor of Computer and Information Science (CIS) and a member of the Penn Bioengineering Graduate Group. Read more stories about the coronavirus pandemic written by Lyle Ungar here.

What do ‘Bohemian Rhapsody,’ ‘Macbeth,’ and a list of Facebook Friends All Have in Common?

New research finds that works of literature, musical pieces, and social networks have a similar underlying structure that allows them to share large amounts of information efficiently.

Examples of statistical network analysis of characters in two of Shakespeare’s tragedies. Two characters are connected by a line, or edge, if they appear in the same scene. The size of the circles that represent these characters, called nodes, indicate how many other characters one is connected to. The network’s density relates to how complete the graph is, with 100% density meaning that it has all of the characters are connected. (Image: Martin Grandjean)

 

By Erica K. Brockmeier

To an English scholar or avid reader, the Shakespeare Canon represents some of the greatest literary works of the English language. To a network scientist, Shakespeare’s 37 plays and the 884,421 words they contain also represent a massively complex communication network. Network scientists, who employ math, physics, and computer science to study vast and interconnected systems, are tasked with using statistically rigorous approaches to understand how complex networks, like all of Shakespeare, convey information to the human brain.

New research published in Nature Physics uses tools from network science to explain how complex communication networks can efficiently convey large amounts of information to the human brain. Conducted by postdoc Christopher Lynn, graduate students Ari Kahn and Lia Papadopoulos, and professor Danielle S. Bassett, the study found that different types of networks, including those found in works of literature, musical pieces, and social connections, have a similar underlying structure that allows them to share information rapidly and efficiently.

Technically speaking, a network is simply a statistical and graphical representation of connections, known as edges, between different endpoints, called nodes. In pieces of literature, for example, a node can be a word, and an edge can connect words when they appear next to each other (“my” — “kingdom” — “for” — “a” — “horse”) or when they convey similar ideas or concepts (“yellow” — “orange” — “red”).

The advantage of using network science to study things like languages, says Lynn, is that once relationships are defined on a small scale, researchers can use those connections to make inferences about a network’s structure on a much larger scale. “Once you define the nodes and edges, you can zoom out and start to ask about what the structure of this whole object looks like and why it has that specific structure,” says Lynn.

Building on the group’s recent study that models how the brain processes complex information, the researchers developed a new analytical framework for determining how much information a network conveys and how efficient it is in conveying that information. “In order to calculate the efficiency of the communication, you need a model of how humans receive the information,” he says.

Continue reading at Penn Today.

Beth Winkelstein Appointed Deputy Provost at Penn

Provost Wendell Pritchett has announced the appointment of Beth Winkelstein as Deputy Provost.

Beth Winkelstein, Ph.D.

“Beth Winkelstein has become one of our most essential leaders of teaching, learning, and student life,” said Pritchett, “since she began her tenure as vice provost for education five years ago. Her insight and energy enhance every part of our campus. She leads both undergraduate and graduate education, collaborating with deans, faculty leaders, and the Office of the Vice Provost for University Life, as well as the Council of Undergraduate Deans, Council of Graduate Deans, Graduate Council of the Faculties, and Council of Professional Master’s Degree Deans.

“As deputy provost, she will continue this invaluable work while working closely with me to better integrate and expand our educational initiatives, especially by incorporating new technologies, new ways of teaching, and additional supports for faculty and students that advance our core priorities of innovation, impact, and inclusion,” Pritchett said. “As we enter this new and challenging phase of Penn history, Beth is the perfect person to help us chart the landscape ahead.”

Drawing on her experience as a former Penn undergraduate, Winkelstein has been a dynamic leader of initiatives to enhance undergraduate student life, especially the new Penn First Plus program, which provides targeted support for first-generation and/or low-income students, and the dedicated Second-Year Experience, which offers enhanced programs for second-year students to accompany Penn’s new second-year housing requirement. She has at the same time been a vital advocate for graduate and professional students, overseeing the Graduate Student Center and Family Center, while advancing a series of initiatives to improve every aspect of support for students’ academic progress, professional advancement, and work-life balance. Her leadership spans such key areas as College Houses and Academic Services, New Student Orientation, the Center for Undergraduate Research and Fellowships, and the Office of Student Conduct. And that leadership has been especially critical for the Online Learning Initiative and the Center for Teaching and Learning, in these recent months when that work has become central to Penn’s educational efforts.

Winkelstein’s leadership is based in her deep knowledge of and appreciation for the University, as well as her own scholarly and research distinction. She has taught in the Bioengineering Department in the School of Engineering and Applied Science since 2002, becoming in that time one of the world’s leading innovators in research on new treatments for spine and other joint injuries. Appointed two years ago as the Eduardo D. Glandt President’s Distinguished Professor, she continues to lead her pioneering Spine Pain Research Lab, mentor students and postdocs, and serve as co-editor of the Journal of Biomechanical Engineering. Among her many professional honors, she is a Fellow of the Biomedical Engineering Society and the American Society of Mechanical Engineering and was elected to the American Institute for Medical and Biological Engineering and the World Council of Biomechanics.

Winkelstein earned a Ph.D. in bioengineering from Duke University and a B.S.E. cum laude in bioengineering from Penn as a Benjamin Franklin Scholar.

Originally posted in Penn Today.

Lyle Ungar on Normalizing Face Masks

As scientists continue to battle the novel coronavirus, public health officials maintain that wearing a face mask is a powerful way to curb the spread of the virus and keep communities safe. However, America has struggled to adopt this change, as compared to other countries that have made wearing a face mask an unremarkable aspect of their culture.

Lyle Ungar, Ph.D.

In an opinion piece for the New York Times, Lyle Ungar, Professor of Computer and Information Science, Angela Duckworth, Rosa Lee and Egbert Chang Professor in Penn Arts & Sciences and the Wharton School, and Ezekiel J. Emanuel, Professor of Medical Ethics and Health Policy in Penn’s Perelman School of Medicine, propose a new approach to increase consistent face mask use among Americans: make wearing a mask “easy,” “understood,” and “expected.”

In their article, Ungar, Duckworth, and Emanuel make reference to communities that provided face masks free of charge for residents and note the decrease in infection in these areas. In addition, they point out how uncertainty about the necessity of face masks in the U.S. has led to public confusion which inhibits trust and use of masks. Finally, the three researchers push for a shift in social norms to embrace wearing a face mask as standard in America for the near future.

Some of Ungar’s recent research is also focused on the pandemic, including a “COVID Twitter map,” created with colleagues at the World Well-Being Project and Penn Medicine’s Center for Digital Health. Their map helps show, in real time, how people across the country perceive the virus and how it is affecting their mental health.

Read more about Ungar, Duckworth, and Emanuel’s strategy for normalizing face masks in their opinion piece for the New York Times.

Originally posted on the Penn Engineering blog.

Lyle Ungar is a Professor of Computer and Information Science (CIS) and a member of the Penn Bioengineering Graduate Group.