Nanotech can help distinguish lung cancer cells from healthy cells

lung cancer

Recently, researchers from University of Colorado Boulder developed a new technique to distinguish lung cancer cells from healthy cells via nanoparticles. The finding is published in Proceedings of the National Academy of Sciences.

The new synthetic polymer can deliver a drug into lung cancer cells only, and hence leave the healthy lung cells intact. The drug is RNA-based and it can disrupt the function and inhibit the growth of cancer cells by eliminating the proteins in the cells.

Cell selection is an important advantage because previous chemical drugs can kill all rapidly dividing cells, including both cancer cells and normal cells. Although they are effective to stop the growth of cancer, they also can bring serious side-effects.

In the new technique, cancer cells are selected based on their physical and chemical features. This means the drug carriers are cell-specific, and that patient outcomes in the clinic can change significantly.

However, developing the process was not easy. Researchers tested hundreds of materials, and finally found that cells could respond to a synthetic polymer differently. Importantly, the polymer could distinguish cancer cells from heathy cells in the same patient.

Currently, it is possible to use genetic sequencing to customize drug regiments for each patient. This new nanotech finding enable doctors customize the drug carrier to improve patient responses.

Experiments in mice showed that the cancer-selective nanoparticles could stay in the cancer cells for more than 1 week, whereas in the control condition (nonselective) nanoparticles only could exist for several hours. This means that the cancer growth could be greatly inhibited.

Future research will apply to this new technique to clinical field to improve efficacy and reduce adverse side effect of cancer therapies.

Citation: Yunfeng Yan et al. Functional polyesters enable selective siRNA delivery to lung cancer over matched normal cells, Proceedings of the National Academy of Sciences (2016). doi: 10.1073/pnas.1606886113
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