A new technique developed at the University of
Virginia School of Medicine will let a single cancer research lab do the work
of dozens
Associate professor of
pharmacology J. Julius Zhu led the team that created the new technique.
A new technique developed at the University of Virginia School of Medicine will let a single cancer research lab do the
work of dozens, dramatically accelerating the search for new treatments and
cures. And the technique will benefit not just cancer research but research
into every disease driven by gene mutations, from cystic fibrosis to
Alzheimer’s disease—ultimately enabling customized treatments for patients in a
way never before possible.
The new technique lets scientists analyze the effects
of gene mutations at an unprecedented scale and speed, and at a fraction of the
cost of traditional methods. For patients, this means that rather than thinking
about the right drug for a certain disease, doctors will think about the right
drug to treat the patient’s specific gene mutation.
“Every patient shouldn’t receive the same treatment.
No way. Not even if they have the same syndrome, the same disease,” said UVA
researcher J. Julius Zhu, who led the team that created the new technique.
“It’s very individual in the patient, and they have to be treated in different
ways.”
Understanding Gene Mutations
Understanding the effect of gene mutations has,
traditionally, been much like trying to figure out what an unseen elephant
looks like just by touching it. Touch enough places and you might get a rough
idea, but the process will be long and slow and frustrating. “The way we have
had to do this is so slow,” said Zhu, of UVA’s Department of Pharmacology and
the UVA Cancer Center. “You can do one gene and one mutation at a time. Now,
hopefully, we can do like 40 or 100 of them simultaneously.”
Zhu’s approach uses an HIV-like virus to replace genes
with mutant genes, so that scientists can understand the effects caused by the
mutation. He developed the approach, requiring years of effort, out of a desire
to both speed up research and also make it possible for more labs to
participate. “Even with the CRISPR [gene editing] technology we have now, it
still costs a huge amount of money and time and most labs cannot do it, so we
wanted to develop something simple every lab can do,” he said. “No other
approach is so efficient and fast right now. You’d need to spend 10 years to do
what we are doing in three months, so it’s an entirely different scale.”
To demonstrate the effectiveness of his new technique,
Zhu already has analyzed approximately 50 mutations of the BRaf gene, mutations
that have been linked to tumors and to a neurodevelopmental disorder known as
cardio-facio-cutaneous syndrome. The work sheds important light on the role of
the mutations in disease.
Rescuing Failed Treatments
Zhu’s new technique may even let researchers revisit
failed experimental treatments, determine why they failed and identify patients
in which they will be effective. It may be that a treatment didn’t work because
the patient didn’t have the right mutation, or because the treatment didn’t
affect the gene in the right way. It’s not as simple as turning a gene on or
off, Zhu noted; instead, a treatment must prompt the right amount of gene
activity, and that may require prodding a gene to do more or pulling on the
reins so that it does less.
“The problem in the cancer field is that they have
many high-profile papers of clinical trials [that] all failed in some way,” he
said. “We wondered why in these patients sometimes it doesn’t work, that with
the same drug some patients are getting better and some are getting worse. The
reason is that you don’t know which drugs are going to help with their
particular mutation. So that would be true precision medicine: You have the
same condition, the same syndrome, but a different mutation, so you have to use
different drugs.”
Findings Published
Zhu and his team have described the technique in an article published in the scientific
journal Genes & Development, making it available to scientists
around the world. The paper was written by Chae-Seok Lim, Xi Kang, Vincent
Mirabella, Huaye Zhang, Qian Bu, Yoichi Araki, Elizabeth T. Hoang, Shiqiang
Wang, Ying Shen, Sukwoo Choi, Bong-Kiun Kaang, Qiang Chang, Zhiping P. Pang,
Richard L. Huganir, and Zhu.
The work was supported by the National Natural Science
Foundation of China, the Robert Wood Johnson Foundation, the National Honor
Scientist Program of Korea, the Howard Hughes Medical Institute and the
National Institutes of Health, grants MH108321, NS065183, NS089578, HD064743,
AA023797, MH64856, NS036715, NS053570, NS091452, and NS092548.
BY UNIVERSITY OF VIRGINIA | PHOTO COURTESY OF THE UVA
HEALTH SYSTEM
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