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Using nanoparticles to deliver cancer drugs allows for high drug concentrations to be delivered to tumours while avoiding the harmful side effects associated with chemotherapy. However, only a few nanoparticle-based cancer drugs have received FDA approval.
A new study from MIT and the Broad Institute of MIT and Harvard researchers may aid in the development of nanoparticle-based drugs. The researchers discovered thousands of biological traits that influence whether cancer cells take up different types of nanoparticles after studying interactions between 35 different types of nanoparticles and nearly 500 different types of cancer cells. The findings could help researchers better tailor drug-delivery particles to specific types of cancer, or design new particles that capitalise on the biological characteristics of specific types of cancer cells. "We are excited by our findings because they are only the beginning -- we can use this approach to map out what types of nanoparticles are best for targeting specific cell types, from cancer to immune cells and other types of healthy and diseased organ cells." "We're discovering how surface chemistry and other material properties influence targeting," says Paula Hammond, an MIT Institute Professor, head of the Department of Chemical Engineering, and member of MIT's Koch Institute for Integrative Cancer Research. The new study, which appears in Science, is led by Hammond. Natalie Boehnke, an MIT postdoctoral fellow who will soon join the faculty at the University of Minnesota, and Joelle Straehla, the Charles W. and Jennifer C. Johnson Clinical Investigator at the Koch Institute, an instructor at Harvard Medical School, and a paediatric oncologist at Dana-Farber Cancer Institute, are the paper's lead authors. Previously, Hammond's lab created a variety of nanoparticles that can be used to deliver drugs to cells. Several studies conducted in her lab and others have revealed that different types of cancer cells frequently respond differently to the same nanoparticles. This phenomenon was observed in the studies of Boehnke, who was studying ovarian cancer when she joined Hammond's lab, and Straehla, who was studying brain cancer. The researchers hypothesised that biological differences between cells were causing the differences in their responses. To find out what those differences were, they decided to conduct a large-scale study in which they could examine a large number of different cells interacting with various types of nanoparticles. Straehla had recently learned about the Broad Institute's PRISM platform, which allows researchers to rapidly screen thousands of drugs on hundreds of different cancer types at the same time. The team decided to try to adapt that platform to screen cell-nanoparticle interactions rather than cell-drug interactions with the help of Angela Koehler, an MIT associate professor of biological engineering. "We can start thinking about whether there is something about a cell's genotypic signature that predicts how many nanoparticles it will take up using this approach," Boehnke says. The researchers used 488 cancer cell lines from 22 different tissues for their screening. Each cell type has a unique DNA sequence that allows researchers to identify the cells later on. Extensive datasets on gene expression profiles and other biological characteristics are also available for each cell type. The researchers created 35 nanoparticles, each with a core made of liposomes (particles made from many fatty molecules called lipids), a polymer called PLGA, or another polymer called polystyrene. The particles were also coated with various types of protective or targeting molecules, such as polymers like polyethylene glycol, antibodies, and polysaccharides. This enabled them to investigate the impact of the particles' core composition as well as their surface chemistry. The researchers exposed pools of hundreds of different cells to one of 35 different nanoparticles while working with Broad Institute scientists, including Jennifer Roth, director of the PRISM lab. Because each nanoparticle had a fluorescent tag, the researchers were able to separate the cells using a cell-sorting technique based on how much fluorescence they gave off after four or 24 hours of exposure. Each cell line was assigned a score based on these measurements that represented its affinity for each nanoparticle. The researchers then analysed those scores along with all of the other biological data available for each cell line using machine learning algorithms. This investigation yielded thousands of features, or biomarkers, linked to the affinity for various types of nanoparticles. Many of these markers were genes that encoded the cellular machinery required to bind particles, transport them into cells, and process them. Some of these genes were previously identified as being involved in nanoparticle trafficking, but many others were discovered. "We found some markers that we expected, but we also discovered a lot more that was previously unknown." "We hope that other people will be able to use this dataset to help broaden their understanding of how nanoparticles and cells interact," Straehla says. The researchers chose one of the biomarkers they discovered, a protein called SLC46A3, for further investigation. According to the PRISM screen, high levels of this protein were associated with very low uptake of lipid-based nanoparticles. When the researchers tested these particles in melanoma mouse models, they discovered the same correlation. According to the findings, this biomarker could be used to assist doctors in identifying patients whose tumours are more likely to respond to nanoparticle-based therapies. The researchers are now trying to figure out how SLC46A3 regulates nanoparticle uptake. If they can find new ways to reduce cellular levels of this protein, tumours may be more susceptible to drugs delivered by lipid nanoparticles. The researchers are also investigating some of the other biomarkers they discovered. This screening method could be applied to many other types of nanoparticles that the researchers did not investigate in this study. "There is no telling what other undiscovered biomarkers are out there that we haven't captured because we haven't screened them," Boehnke says. "I hope it serves as an inspiration for others to begin looking at their nanoparticle systems in a similar way." (ANI)
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