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The Cancer Paradox

Approximately 1 in 3 people will develop cancer in their lifetime. Elephants, on the other hand, have a 1 in 32 chance. Why do they have a lower risk of cancer than humans, you ask? Protein p53 may hold the answer.  



Visually represent the relationship between structure and function involved in a dynamic molecular process

Hypothetically, every living cell should have an equal chance of becoming cancerous. With this in mind, larger animals should have a higher risk of getting cancer than smaller animals. In the 1970’s, epidemiologist Richard Peto observed that there does not seem to be a correlation between body mass and cancer risk across animal species. This discrepancy became known as Peto’s Paradox. In our DNA there is a gene called TP53 that encodes a protein called tumour suppressor p53, commonly referred to as the “Guardian of the Genome.” As its name suggests, p53 has an important anticancer role. Mutation of p53, causing a loss of its function, is observed in over 50% of human cancers. It turns out humans only have 2 copies of the p53 gene, whereas elephants have 40! This suggests a correlation between p53 and cancer risk; therefore, understanding the role of p53 and how it is affected by mutation is important to cancer prevention and therapies.

Client: Prof. Derek Ng, University of Toronto

Format: 3D Modelling, Illustration

Software: Chimera, Cinema 4D, Photoshop, Illustrator


After deciding on my topic, I identified the characters and interactions in my story and figured out what information I needed. Unfortunately, the the Protein Data Bank (PDB), which offers structural data of thousands of proteins, doesn't have a complete model of p53. Its flexible linker regions make it difficult to obtain 3D structural data and the missing parts must be modelled manually. Luckily, scientists are generous people; I reached out to Özlem Demir who published a paper about Full-length p53 Tetramer Bound to DNA and Its Quaternary Dynamics. She was happy to supply me with the full-length 3D structural model of p53!



What is the best way to tell a molecular story?


During the ideation stage I explored different ways I could explain the relationship between structure and function of p53. This is the story I settled on:

How do common mutations of p53 affect the structure of p53 and how does this structural change promote cancer in living cells?

P53 normally binds DNA at sites of genetic damage. If this function is compromised, mutations in DNA will go unfixed and can therefore promote cancer. P53 has six 'hotspot' mutations that have been organized into two groups: contact mutants and structural mutants. Contact mutants have the highest mutation frequency and involve the substitution of amino acids that directly contact DNA; if p53 can't bind DNA, the risk of cancer increases.


Several initial iterations were made using Chimera and Illustrator. I isolated the protein domains and amino acids of interest in Chimera and exported them as STL files that could be imported into C4D. Once the layout was solidified, I moved into Cinema 4D. The PDB file of p53 and the DNA was imported using ePMV in C4D.