The development of cancer is a somatic evolutionary process. Evolving diseases are difficult to treat because they adapt to treatment and because they continually diversify — from so simple a beginning, endless forms evolved. We integrate evolutionary theory with quantitative experimentation to better understand cancers.
My interest in scientific research began at the age of 16 in the Morse Lab studying gene regulation.
My adventure in science started with studying the structure of the neutron and eventually led me to computational biology.
I am interested in cancer genomics, high-throughput screening, and developing CRISPR-based technologies.
I am interested in the fields of translational genomics and molecular oncology.
Gianna studied biophysics at Loyola University Chicago and earned her master’s in medical science at Boston University.
I grew up in Kent, OH. While pursuing my undergrad degree at The Ohio State University, I was given the opportunity to shadow in a lab here at Case. This molecular biology lab introduced me to cancer research, and the wet lab environment.
My first experience in research was in Dr. Wenjun Zhang’s lab at UC Berkeley where I studied natural product production of anaerobic bacteria.
Technological advances in genomics and computation are revolutionizing our understanding of cancer. We believe these advances will make sense only in the light of evolution. Specifically, we believe evolutionary theory can answer many of the most enigmatic aspects of tumor biology, including:
Why do most tumors never progress to malignancy?
Why are mutations that drive growth in one tumor maladaptive in another?
Why do the other ‘passenger’ mutations appear to be unaffected by natural selection?
To answer these questions, our lab pursues an interdisciplinary and inter-laboratory approach that combines experiment and theory with tech development.
Mutations that harm cancer cells accumulate in tumors - despite selective pressures against them - because cancer cells do not genetically recombine and mutate rapidly. These mutations cause proteotoxic stress that can be clinically targeted.
To study the genomic complexity of lung cancers and model tumor growth from initiation, we developed a new technology. We’re now using this technology to mathematically-describe the heterogeneity of tumor growth and identify pharmacogenomic interactions in vivo.
Scientists of all academic levels are encouraged to apply. All members must be team players, demonstrate scientific curiosity and self-motivation, and articulate a scientific vision that aligns with the lab’s goals. Both life & physical scientists; MD & PhD students; and wet- and dry-lab specialists are encouraged to apply.
Everyone in the Cancer Evolution group is committed to fostering a better living and learning environment. We value equity and inclusion, and celebrate diversity in all forms.