A new computational tool based on an algorithm designed to recognize human faces plucked the four distinguishing gene patterns out of a landscape of many DNA alterations in the myeloma genome, the researchers report in the April issue of Cancer Cell.
These results "define new disease subgroups of multiple myeloma that can be correlated with different clinical outcomes," wrote the authors, led by Ronald DePinho, MD, director of Dana-Farber's Center for Applied Cancer Science.
Not only do the findings pave the way for treatments tailored to a patient's specific form of the disease, they also narrow down areas of the chromosomes in myeloma cells likely to contain undiscovered genetic flaws that drive myeloma, and which might turn out to be vulnerable to targeted designer drugs.
Kenneth Anderson, MD, medical director of the Jerome Lipper Multiple Myeloma Center at Dana-Farber and an author of the paper, said the findings "allow us to predict how patients will respond to current treatments based on a genetic analysis of their disease." In addition, the findings "identify many new genes implicated in the cause and progression of myeloma, and the product of those genes can be targeted with novel therapies."
Multiple myeloma, the second most common blood cancer after non-Hodgkin's lymphoma, is incurable, although some patients live for a number of years following diagnosis. About 50,000 people in the United States are living with the disease, and an estimated 16,000 new cases are diagnosed annually. Despite improvements in therapy, the five-year survival rate in multiple myeloma is only 32 percent and durable responses are rare.
The new report emerged from a co
Source:Dana-Farber Cancer Institute