Throughout most of human history, a cancer diagnosis was considered a death sentence – a fatal forecast of physical deterioration as mutant cells aggressively attacked the victim’s body.
One of the most significant recent breakthroughs in the war on cancer is the rise of precision medicine, the painstaking process of identifying the tiniest molecular and genomic details within a cancer, then using those details to fine-tune treatment.
An explosion in knowledge about the genetic mutations that cause tumors allows physicians to pinpoint DNA changes that drive cancer cells and tailor treatments faster and more confidently, based on each patient’s genetic profile.
“What we have learned through the years is that cancer is not a single disease, but rather a collection of diseases, each with unique features,” says Shridar Ganesan, associate director for translational science at Rutgers Cancer Institute of New Jersey and associate professor of medicine at Rutgers Robert Wood Johnson Medical School.
“Instead of determining cancer type only by the organ in which it originates, time-saving genomic analysis opens the door for additional classification by the set of changes present in each cancer, which can guide more precise, or tailored, therapy,” notes Ganesan, a medical oncologist.
Despite these advances, cancer treatment remains a race against time – a struggle to find the best way to beat the disease.
Enter Big Data
Aided by supercomputing resources, Rutgers doctors and scientists are analyzing genomes and human tissues – and identifying cancer patterns – far faster than ever before.
This novel approach to cancer diagnosis and treatment teams physicians, scientists, pathologists, geneticists, systems biologists and others from the Cancer Institute with computer engineering experts at the Rutgers Discovery Informatics Institute (RDI2). Enhancing the relationship further is collaboration with another university entity – RUCDR Infinite Biologics, the world’s largest university-based biorepository, located within the Human Genetics Institute of New Jersey.
“We have the latest technology to come up with potential solutions very fast,” says Manish Parashar, director of RDI2 and professor in the Rutgers School of Engineering’s Department of Electrical and Computer Engineering.
The scientists at RDI2 receive patient tissue samples from the Cancer Institute that have been digitized at high-resolution and work closely with the institute’s medical imaging experts to understand the computational and data challenges and come up with a treatment plan.
“Our team provides the computational engine to review thousands of images, so our collaborators at the Cancer Institute can analyze these images, search the database, test hypotheses and answer important questions,” Parashar says. “We take the imaged samples and radiology studies from one patient and ask, ‘Have I seen a case like this before?’”
By optimizing the data mining and pattern matching algorithms developed by a research team led by David J. Foran, bioinformatics executive director at the Cancer Institute, the software can be run in a high-performance computing environment. “That way the analysis can be completed in a matter of minutes, rather than days, “ Parashar says.
Data crunching and analytics expertise provided by RDI2 and biomaterials and technical support from RUCDR Infinite Biologics – coupled with evaluation by a team of scientific, clinical and bioinformatics experts at the Cancer Institute – is shaping a revolution in how best to determine therapy – a vast improvement over the time-intensive, trial-and-error approach that clinicians have faced for years.
While other U.S. cancer centers engage precision medicine experts to target the more common breast and prostate cancers, the Cancer Institute at Rutgers is believed to be one of the few centers addressing the challenges of rare and poor prognosis cancers – such as ovarian cancers, pancreatic cancers, sarcomas and certain pediatric cancers – for which traditional therapies usually aren’t working. A clinical trial there is focused on the genomic makeup of a tumor, offering hope to poor prognosis patients.
One Patient’s Story
Rev. James L. Seawood is one of the people benefiting from the advances of precision medicine in a clinical trial at the Cancer Institute. Seawood, a retired Army chaplain and pastor from Staten Island, New York, arrived at the Cancer Institute in the spring of 2012 with Stage IV kidney cancer; he came under the care of medical oncologist Mark Stein.
During the past year and a half, Seawood has received standard treatment regimens and participated in two clinical trials, all of which have kept his disease at bay only briefly. Throughout those 18 months, treatment side effects kept him from his congregation and community meetings. But he always found a way to be with them for the Sunday service. “Even though it took extra effort, I knew I had to get up each day and engage in my normal activities, because to stop would mean to give up,” Seawood says.
Earlier this year, he received the news that the cancer had spread to his lungs and liver. “I felt like giving up,” Seawood says. When his physician suggested a genomic analysis of his tumor, he felt he had little to lose. Within days, he learned that the biopsy had revealed a mutation his health care team thought might respond to a treatment approved for a rare form of lung cancer. Within eight weeks of targeting the cancer with this off-label use, the tumors on Seawood’s kidneys, lung and liver either shrank dramatically or disappeared.
The 65-year-old clergyman, back to taking care of his family and ministering to his community, is encouraged by his response to the latest treatment. “I finally feel like I’m getting back to my old self. I can breathe and have more energy – I just feel like doing more,” Seawood says.
While not every tumor analysis will yield a specific mutation, the addition of this rapid assessment tool to the cancer care armamentarium is extremely helpful in guiding therapy decisions and providing an opportunity to tailor treatment, notes Stein.
“The ability to bring the results of this analysis from the laboratory directly to the patient would not be possible without the unique relationship that exists between the Cancer Institute and its Rutgers partners,” Stein says.
Potential to Spur New Partnerships
The partnership between the Cancer Institute and RDI2 evolved from joint projects over several years, while Cancer Institute investigators have benefited from research sequencing capabilities from RUCDR Infinite Biologics since 2012. The collaborations grew even stronger over the past several months as Rutgers prepared to integrate with the Cancer Institute and most of the other schools, centers and institutes that made up the former University of Medicine and Dentistry of New Jersey. The Cancer Institute of New Jersey, along with most of the former UMDNJ, joined Rutgers on July 1.
Such an enriched research environment is conducive to groundbreaking discoveries and new treatment options – allowing New Jerseyans to remain close to home to receive the most advanced cancer care.
“Joining forces and areas of expertise offers Rutgers the opportunity to develop customized approaches for extracting genomic information from tumors, interpret the genomic variation and offer options to patients that may not be available elsewhere,” says Jay A. Tischfield, scientific director and CEO of RUCDR Infinite Biologics. In addition, the enhanced collaboration has the potential to spur new partnerships with pharmaceutical and biotechnology companies and additional grant-funding opportunities.
This initiative also provides an opportunity to invest in the future of the precision medicine field, enabling students from Robert Wood Johnson Medical School and the School of Engineering to work together, Parashar says. “This allows them to talk to both sides: precision medicine pathology and the radiology side, as well as the computer science and computer engineering side.
“That’s one of the key goals – getting students equipped with the necessary multidisciplinary skills that combine understanding how to deal with Big Data and understanding the science you want to do with it,” Parashar says.