In a “proof of concept” study, scientists at Johns Hopkins Medicine say they have successfully delivered nano-size packets of genetic code called microRNAs to treat human brain tumors implanted in mice. The contents of the super-small containers were designed to target cancer stem cells, a kind of cellular “seed” that produces countless progeny and is a relentless barrier to ridding the brain of malignant cells.
Nanoparticles releasing microRNAs (light blue) inside a human brain cancer cell
“Brain cancer is one of the most widely understood cancers in terms of its genetic makeup, but we have yet to develop a good treatment for it,” says John Laterra, MD, PhD, professor of neurology, oncology and neuroscience at the Johns Hopkins University School of Medicine and a research scientist at the Kennedy Krieger Institute. “The resilience of cancer stem cells and the blood-brain barrier are major hurdles.”
Blood that enters the brain is filtered through a series of vessels that act as a protective barrier. But this blood-brain barrier blocks molecular medicines that have the potential to revolutionize brain cancer therapy by targeting cancer stem cells, says Laterra.
“To modernize brain tumor treatments, we need tools and methods that bypass the blood-brain barrier,” says Jordan Green, PhD, professor of biomedical engineering, ophthalmology, oncology, neurosurgery, materials science and engineering and chemical and biomolecular engineering at the Johns Hopkins University School of Medicine. “We need technology to safely and effectively deliver sensitive genetic medicines directly to tumors without damaging normal tissue.”
A case in point, Green says, is glioblastoma, the form of brain cancer that Arizona Sen. John McCain is battling, which often requires repeated surgeries. Doctors remove the brain tumor tissue that they can see, but the malignancy often returns quickly, says Laterra. Most patients with glioblastoma live less than two years after diagnosis.
Results of the experiments were published online in Nano Letters.
Source: https://engineering.jhu.edu/
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