Fifth in a series about collaborations between Lunenfeld scientists and Mount Sinai Hospital clinicians.
In 2009, Lunenfeld scientist Dr. Jeff Wrana and his student at the time, Ian Taylor, developed a software technology that analyzes breast cancer tumours to determine a woman’s best treatment options. The tool, called ‘DyNeMo,’ can predict with more than 80 per cent accuracy a patient’s chance of recovering from breast cancer.
Now Dr. Wrana is working with Mount Sinai surgeon Dr. Alex Zlotta, who leads the Bladder Cancer Research Program at the Hospital, as well as Dr. Ian Taylor (thanks to his newly minted PhD degree), to apply the DyNeMo technology to uro-oncologic cancers such as those of the bladder.
“The course of treatment for bladder cancer is often selected based upon presumed prognosis of the disease type; however these are presumed
,” says Dr. Zlotta. “Because bladder cancer has a variable course with tumours behaving in very different ways, quite often we treat either too aggressively, or not aggressively enough. Ultimately, by studying the tumour biology and identifying patients with good versus bad prognosis, we’re better able to tailor treatment to a patient’s particular case.”
Dr. Zlotta uses a “cat and lion” analogy to explain bladder cancer further, in which each patient’s disease has a unique biologic behaviour, although they may appear similar after standard pathology tests. “In essence, some tumours may look like lions but behave more like a ‘cat’—a slower-growing, non life-threatening tumour, therefore not requiring aggressive therapy, and, on the contrary, some cats may behave like lions,” he says.
Distinguishing between the two is where new technologies such as DyNeMo and Next Generation DNA sequencing come into play.
DyNeMo—for Dynamic Network Modularity—works by examining protein networks inside tumour cells and identifying signature variations. The technology analyzes how proteins and other components within cancer cells interact to form networks. Differences in how the networks in cells are organized can predict how the tumour behaves.
“What we find is that many proteins interact and form a network, so they’re not just isolated hubs doing their own thing,” says Dr. Wrana. “They are interlinked, in the same way humans are interlinked in a social network.” He explains that, in his earlier work using DyNeMo in breast cancer, patients who survive have a different organization of their protein network within tumour cells than those who succumb to the disease. “With these technologies, we can look at how different proteins are expressed, and identify changes in the global structure of the network that could predict outcomes from disease. We’re at a very exciting stage in applying this technology to bladder cancer.”
To do this, RNA samples from the tumours of patients with bladder cancer are subjected to Next Generation sequencing, which allows scientists to analyze the activity of an individual patient’s genes. This vast trove of data is then analyzed with the DyNeMo software to identify protein networks that are altered by the cancer. “We believe this is the future of cancer diagnostics and prognostics,” says Dr. Wrana. “Especially because very little is known about bladder cancer, with these technologies we can probe the functions of genes and their protein products. We can also assess how genes might be rearranged in cancer.”
And while the early phases of this project will focus on bladder cancer, the ultimate aim is to apply DyNeMo to other cancers such as those of the prostate.
“Next generation sequencing and bioinformatics allow us to dig deeper into the biology of tumours and grasp the true nature of a patient’s cancer,” agrees Dr. Zlotta. He notes that, whereas other cancers are more uniform in tumour biology, bladder cancer presents an ideal situation to achieve truly personalized medicine, in which therapy is customized to a patient’s specific type of tumour. “With Next Generation DNA sequencing applied to bladder cancer, the more we know about the biology of the tumour, the more readily we can target therapy to a patient’s unique type of tumour.”
The technology is still several years away from clinical use, but will hopefully serve to benefit patients and clinicians in making better choices about how to deal with the disease, says Dr. Zlotta, noting that bladder cancer is the fifth leading cause of cancer and the most expensive type to treat per patient (on average, $200,000 per patient!).
“With this collaboration, we’re progressing exponentially toward better outcomes for bladder cancer patients,” says Dr. Zlotta. “We have a unique opportunity at Mount Sinai with world-class clinicians, scientists and pathologists. With this combination, we’re well positioned to become one of the top centres globally for the management of bladder cancer.”
Drs. Wrana and Zlotta credit a team effort and say their work has depended upon the talent and expertise of dedicated students, technicians and scientific and clinical collaborators, including Drs. Yu Liu, Sergey Mokin, Ian Taylor, Kin Chan, Azar Azad, Sue Richter, Theo van der Kwast and Girish Kulkarni, as well as study coordinator Cynthia Kuk.
Mount Sinai scientist Jeff Wrana and colleague Dr. Alex Zlotta, who leads the Hospital’s Bladder Cancer Research Program, are harnessing novel Next Generation DNA sequencing technologies to evaluate new means for discriminating between indolent and aggressive tumours in patients with bladder cancer. The collaboration is aimed at more personalized treatments for this common type of cancer.