Jefferson Harnessing “Big Data” to Broaden Cancer Research

27
Apr

With the help of internal and external collaborations, researchers in our Computational Medicine Center (CMC) at the Sidney Kimmel Medical College here at TJU are characterizing and analyzing the molecular drivers of several cancers, which may lead to more powerful diagnostics and personalized treatments that better target cancer’s root causes.
The use of precision medicine is changing the landscape of medical treatment, and researchers at Jefferson are optimistic that their “big data” findings could alter diagnosis and treatment for thousands of cancer patients and help them benefit from this type of medical approach.
“The Computational Medicine Center (CMC) has been focusing on the human transcriptome, the molecules a person makes from their DNA,” said Isidore Rigoutsos, PhD, CMC Director. “Specifically, we study a category of molecules whose job is to regulate the production of proteins. Much to our surprise, we were able to discover that people of different sexes, geographic origin or race produce different regulatory molecules from the same piece of DNA.”
CMC’s team of Phillipe Loher, a computational biologist/software engineer, Eric Londin, PhD, Assistant Professor at TJU, and Dr. Rigoutsos has built a strong infrastructure for storing and analyzing big data. The CMC engages in data-driven research, a new scientific paradigm, which has been enabled by technological achievements. Data-driven approaches represent an important advancement in precision or personalized medicine, in which diagnoses and cancer treatments can be customized according to the makeup of a patient’s tumors.
Several CMC researchers are part of the core working group analyzing the pancreatic cancer datasets that have been collected as part of an initiative by the National Institutes of Health (NIH) known as The Cancer Genome Atlas (TCGA). TCGA’s goal is the comprehensive characterization of thousands of samples from more than thirty cancers through large-scale genome and transcriptome analyses conducted by a worldwide network of researchers.
In addition to its collaboration with the TCGA pancreatic cancer team, the CMC has been engaging with the broader research community. From pancreatic experts at Johns Hopkins University, the University of North Carolina and The Broad Institute of MIT and Harvard, to regulatory-molecule researchers in Japan, to numerous colleagues across the Jefferson Campus and the Wills Eye Hospital, the team’s partnerships are not only validating CMC’s approach, but are also enabling scientists around the world to conduct even better-informed research.
These partnerships are an integral part of our research infrastructure and shared knowledge missions — key components of the “High-Impact Science” vector of our Blueprint for Strategic Action.
“Had it not been for these collaborations, we would not have been able to advance our research work as quickly,” said Phillipe.
So what does their work mean for cancer research?
“I think it is really cool that even though we started out on the pancreatic cancer side several years ago, we have since been able to demonstrate the power of data-driven research in many other cancer settings,” said Phillipe. “I expect this will have beneficial implications for personalized medicine before too long.”
In parallel to their work on pancreatic cancer, CMC researchers recently published several articles describing intriguing findings on breast cancer. And a few months ago, they received an NIH R21 grant to extend their work to four additional cancers — prostate cancer, uveal melanoma, skin melanoma and bladder cancer. Their collaborators on this grant include a multidisciplinary team of investigators from across campus (Leonard Gomella, MD, Chairman, Department of Urology; Takami Sato, MD, PhD, Director, Metastatic Uveal Melanoma Program; Andrew E. Alpin, PhD, Program Leader, Cancer Cell Biology & Signaling) and beyond Jefferson (William Y. Kim, MD, Associate Professor of Medicine, University of North Carolina at Chapel Hill).
To learn more about research at the Computational Medicine Center, please visit the CMC website.