Taking statistical pictures of metastasis using zebrafish

Metastasis, the spread of cancer from its primary site to other parts of the body, is when cancer gets really bad. But this process is poorly understood, in large part because it is stochastic. Like the dispersal of plant seeds across a fertile field, metastatic cells could end up in many different places so knowing where metastases will form exactly may seem impossible.
What we need to study physical phenomena that are stochastic is lots of samples and statistics. Studying metastasis across large samples can be very difficult however. Investigating patterns of metastasis in the human body would require compiling dozens of cases while controlling for factors that could influence metastasis in unknown ways like patient age, body-mass-index, exposure to carcinogens, etc. We could use animal models and control for these factors, but common models in cancer research like mice and rats are still quite expensive to run experiments with dozens of samples.

“The zebrafish” (2015) by Silja Heilmann

Enter the glorious zebrafish. The zebrafish is already a powerful model for genetics and development and it is gaining increasing importance in cancer biology. Our lab collaborates with the lab of Richard White in the program for Cancer Biology and Genetics to investigate metastatic spread across dozens of zebrafish. For the past three years Silja Heilmann has been working closely with Rich, Kajan and other members of the While lab to develop protocols and methods for the quantitative analysis of metastasis. The model is a transparent zebrafish called Casper that is great for imaging. In Rich’s lab, they developed a zebrafish melanoma cell line called Zmel1 that expresses GFP. Once injected into adult casper zebrafish, Zmel1 forms primary tumors that later on produce metastasis and we can visualize the process using microscopy.
Silja developed image analysis algorithms that resize and align many pictures of fish together. This procedure allows building a statistical picture of metastatic growth across the whole animal. The detailed picture reveals indeed the strong stochastic nature of metastatic spread, but some patterns start to emerge. Advancements such as these may one day enable a better understanding of metastasis and help in the development of anti-metastasis treatments.

Read the paper:

A quantitative system for studying metastasis using transparent zebrafish
Silja Heilmann, Kajan Ratnakumar, Erin Langdon, Emily Kansler, Isabella Kim, Nathaniel R Campbell, Elizabeth Perry, Amy McMahon, Charles Kaufman, Ellen van Rooijen, William Lee, Christine Iacobuzio-Donahue, Richard Hynes, Leonard Zon, Joao Xavier, and Richard M White. Cancer Research

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