| RESEARCH HIGHLIGHTS |
site,” says Wai Leong Tam, a researcher at the A*STAR Genome Institute of Singapore who led the study. “This can prompt oncologists to perform more thorough examinations or imple- ment new treatment regimens for patients.” Lung tumors contain a variety of different
cell types, including a rare subset known as tumor-initiating cells (TICs), or cancer stem cells considered to be key drivers of disease relapse and spread throughout the body. Tam and his A*STAR colleagues teamed up with physicians from two nearby cancer centers in Singapore to identify regulatory microRNAs that are essential for TIC function. The researchers obtained biopsies from
patients diagnosed with non-small cell lung cancer, isolated TICs from the tumors, and then compared the expression pattern of microRNAs
in these cells with those from non-TIC tissue taken from the same patient samples. Tam’s team found a slew of microRNAs
that were either expressed at much higher or lower levels in the TICs. However, they focused in depth on just two, miR-1246 and miR-1290. These microRNAs were the most up-regulated and had never been characterized before. Observations and experiments showed that both play a critical role in helping seed new tumors at distant sites outside the lungs. The researchers tracked the levels of miR-
1246 and miR-1290 in patients undergoing therapy. “As expected, the higher expression levels of those two microRNAs in malignant tissues consistently predicted poorer survival outcomes in a large cohort of lung cancer patients,” says Wencai Zhang, who worked on
the study as a research scientist at A*STAR, prior to moving to his current position as a research fellow at Harvard Medical School in the United States. The microRNAs could serve as a useful pre-
dictive biomarker of expected patient outcomes. They might also provide promising drug targets. The researchers wiped out the microRNAs with a special kind of drug known as a locked nucleic acid in mouse models and saw reduced tumor growth. The same kinds of drugs are now being used in humans for other diseases, and could prove helpful in treating lung cancer.
1. Zhang, W. C., Chin, T. M., Yang, H., Nga, M. E., Lunny, D. P. et al. Tumour-initiating cell-specific miR-1246 and miR-1290 expression converge to promote non-small cell lung cancer progression. Nature Communications 7, 11702 (2016).
Materials TESTING THE WATER
THEORETICAL MODEL REVEALS HOW DROPLETS GROW AROUND TINY PARTICLES ON A SURFACE
A mathematical model that predicts how water condenses around tiny particles could help to improve chemical industrial processes, including the production of drug tablets, fertilizers and catalysts1. Previous condensation models differ in their rate predictions, depending on
0s 20s
factors such as the shape and composition of the surface that the droplet grows on. Fong Yew Leong of the A*STAR Institute of High Performance Computing wanted to develop a more realistic theoretical model to help his collaborators understand their experimental condensation results. “This
50s 2µm Water droplets grew around clusters of silica particles, rather than forming standalone droplets on the surface.
www.astar-research.com
is where modeling and computation gets really useful, in providing physical insights that can’t be obtained from experiments,” says Leong. He and his colleagues modeled a water
droplet growing in the crevice between a micrometer-sized particle and a flat surface. Their model considers factors such as particle size, the surface tension of the droplet, and how much the underlying surface attracts or repels water. The model shows, for example, that a
growing droplet covers a water-attracting (hydrophilic) surface more quickly than a water-repelling (hydrophobic) surface. The volume of a droplet initially increases more slowly on a hydrophobic surface, but then speeds up as the droplet becomes more convex. "The droplet doesn't shrink during condensation; it instead wets the particle completely," says Leong. The team carried out experiments to test
their model, filming how water condensed around micron-sized silicon dioxide particles on a glass slide (see image). They saw that water always condensed in the crevice between a particle and the slide, rather than forming standalone droplets on the surface, and found that the droplets’ growth was almost the same as that predicted by their model. The researchers also adapted the model
A*STAR RESEARCH 39
Adapted from Ref. 1 via CC-BY-4.0 (
https://creativecommons.org/licenses/by/4.0/) © T. S. B. Quang et al.
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