LRI Conference Merges Scientific Innovation and New Technologies, Advancing Discoveries and Accelerating Pace of Lupus Research
Compelling Implications for LRI’s New Human Lupus Biology Program
There’s a whole new way of looking at human lupus, and it’s not through the standard-issue microscope. It’s through the lens of exciting new technologies that enable scientists to probe vast sets of data and generate comprehensive models more akin to what actually happens in the lupus immune system than was possible before.
The technologies, all of which have matured rapidly over the past few years, include powerful and dynamic imaging tools and data from the sequencing of the human genome. The biology of whole systems—not just small bits of them—are now at scientists’ fingertips.
Looking at the whole human system—not just splintered pieces
“Systems biology recognizes that individual humans and experimental animals are comprised of a complex set of interacting elements,” said William E. Paul, MD, NIAID-NIH’s chief of the Laboratory of Immunology and LRI Scientific Advisory Board chair, “and that to truly understand the biology of a whole organism in health and disease, we need to understand how these individual elements interact in a quantitative way.”
By appreciating the body’s dynamic and massive interacting web of connections, systems biology not only produces far more realistic pictures of what happens in human lupus—it opens up a whole new spectrum of possibilities for ending the damage. And it basically does this with a flick of a switch.
Ronald N. Germain, MD, PhD, head of the Laboratory of Immunology’s Lymphocyte Biology Section and director of NIAID’s new program in Systems Immunology and Infectious Disease Modeling, explained how the recent explosion in the power of imaging technology could be harnessed to show “real time” moving pictures of the immune system in its normal state as well as in models of lupus.
He also showed how scientists can combine this new experimental insight with advances in computer simulation to eventually develop an ability to predict immune behavior.
Until recently, the best that scientists had to describe interactions in the immune system were static images (snapshots in time) or cartoons—those diagrams of action and reaction that many of us remember from biology textbooks.
“The older technologies gave us knowledge, but not understanding,” he said. “They didn’t provide us the power to predict what would happen in a dynamic immune system that includes time and space and quantity.”
The latest imaging and computational technologies put scientists in the driver’s seat, with an early stage capacity to simulate the behavior of biological systems of substantial complexity and actually make predictions about what happens in the immune system—from what goes wrong to response to therapies.
David Botstein, MD, director of the Leis-Sigler Institute for Integrative Genomics at Princeton University, sees a day coming soon when the information from the sequencing of the entire human genome produces answers about which genes are actually involved in diseases such as lupus.
Think of our genetic map as a railroad system, said the pioneer of the Human Genome Project. For years we have been looking at it on such a basic level—at how a locomotive moves along the track and how it starts and how it stops. But now “we can get into the control room down underneath…where you can see the connections about which trains go where.”
Forest M. White, PhD, associate professor at the Massachusetts Institute of Technology and a biological engineer, is busy using new technologies to nudge the static model we currently have of the human cell and its circuitry to a more realistic one with dynamic, fluid wiring. By figuring out how information flows through human cells, his laboratory aims to discover “what cells really care about.” The answers to this question will have implications for all kinds of illnesses, including lupus, in which cells end up making “bad choices.”
Virginia Pascual, MD, a pediatric rheumatologist and associate investigator at the Baylor Institute for Immunology Research, graphically described the application of one of these systems approaches to human lupus and showed the great insights that could be achieved. One example: a description of the so-called “interferon signature” with, in some cases, as little as 1 milliliter of blood.
LRI Conference Industry Panel: Cutting-Edge Technologies in Systems Biology Promise to Fast-Forward Discovery in Human Lupus
Suggestions on how to harness the new technologies to move LRI discoveries from the laboratory to patient care—and quickly
Paul Brunetta, MD, Genentech; Matthew D. Linnik, PhD, Biogen Idec;
Gregory Dennis, MD, Human Genome Sciences; Marcus Clark, MD, University of Chicago
- First, explore! Before an actual clinical trial, use the new technologies to do exploratory work to see if the proposed treatment agent is truly likely to work in patients—and which patients. Those with early disease? Late disease? Certain organ manifestations?
- Economize Design clinical trials that are smaller, faster, and more nimble with the help of new technologies that can reveal so much, so quickly, about what actually works. A good place to start: short proof-of-concept trials, some as brief as a week or two, in which an idea for a new agent can be tested in narrow, well-defi ned patient groups.
- Strategize Glean more precious data from completed clinical trials. Standardize and centralize collected samples that others might be able to use.
- Reconsider! Revamp what it means for a lupus drug to “work,” given the heterogeneity of the disease.
Moderator Mark Shlomchik, MD, PhD, Yale University
“Using systems modeling to predict immunological responses is fascinating. It suggests that one day it might be possible to perform more informative proof-of-concept studies to assess immune targets prior to initiating clinical trials.”
– Gregory Dennis, MD, Human Genome Sciences
“It’s an incredibly exciting time.”
– Paul Brunetta, MD, Genentech
Benjamin D. Schwartz, MD, PhD, Washington University School of Medicine