How transparent mice help fight cancer

Transparent mice fight cancer - 21st August 2023

German researchers responsible for making mice transparent have discovered a method for creating 3D maps of animals' cells. The research could potentially reduce drug research times and the numbers of mice for testing.

Laboratories would use long and expensive processes to create visual representations of organs and cells using genetically modified animals. This was important for cancer researchers to study how a certain drug or treatment affected cancer cells.

In 2018, scientists at Helmholtz Munich led by Ali Ertürk discovered how to make mice organs and bodies transparent using a solvent. Now, they've combined this with their new imaging method called 'wildDISCO'.

WildDISCO involves giving dead transparent mice antibodies with fluorescent tags. These antibodies distribute throughout a mouse allowing a computer to generate 3D models of particular organs, molecules or cells of interest.

While other imaging methods such as magnetic resonance imaging (MRI) or positron emission tomography (PET) can display what is happening inside a body, wildDISCO's scans are much more detailed. Ertürk explained, "MRI and PET scans would show you only big tumours. Ours show tumours at the single cell, which they absolutely can't."

Through wildDISCO Ertürk's team has created mice body atlases including detailed structures of blood vessels, lymphatic vessels, nervous systems and immune cells. In addition, the team has mapped tumour-associated lymph node structures related to the spread of breast cancer.

All previously mapped body atlases have been made available to researchers on the team's website. One scientist on Ertürk's team said, "Other scientists have obtained critical data from our atlases, saving time, resources, and reducing animal use."

But Ertürk's team's research won't stop there. The team hopes wildDISCO will be used to train AI systems which usually require large data sets. Based on wildDISCO's atlases, AI systems could learn to predict where and how a cancer spreads.