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- Fundamentals of Evolution and Medicine
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1. Evolutionary medicine
- Prof. Randolph Nesse
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2. Evolution and medicine: from the perspective of an evolutionary biologist
- Prof. Stephen C. Stearns
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3. Developmental plasticity, evolution and the origins of disease
- Dr. Mary Jane West-Eberhard
- Evolutionary Genetics
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4. Genetic variation and human disease
- Dr. David Houle
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6. Ecogenetics, evolutionary biology and human disease
- Prof. Gilbert Omenn
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7. Race in genetics and medicine
- Prof. Jeffrey Long
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8. Health disparities in common complex diseases: a role for genetics?
- Dr. Kathleen Barnes
- Infectious Disease
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10. Evolutionary arms races
- Prof. Mark Pagel
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11. Antibiotic resistance and hospital-acquired infection
- Dr. Carl Bergstrom
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12. Evolution of drug resistance
- Dr. Pleuni Pennings
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13. Evolution of virulence: malaria, a case study
- Prof. Andrew Read
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14. Infection and chronic disease
- Prof. Paul Ewald
- Defenses
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15. Fever and related defenses
- Prof. Matthew Kluger
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16. The evolutionary ecology of immunity
- Prof. Paul Schmid-Hempel
- Novel Environmental Factors
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17. What did humans evolve to eat? evolutionary perspectives on human nutritional health
- Prof. William R. Leonard
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19. The paleolithic lifestyle and prevention of chronic disease
- Prof. S. Boyd Eaton
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22. Diseases of civilization: an evolutionary legacy
- Prof. Alan Weder
- Problems Arising From Constraints and Trade-Offs
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23. Aging and evolutionary medicine
- Prof. Linda Partridge
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24. Human aging and menopause
- Prof. Kristen Hawkes
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25. Why we cook with spices: preventative darwinian medicine
- Prof. Paul Sherman
- Sex and Reproduction
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26. Setting the second stage: the evolution of menopause & post-reproductive life
- Prof. Lynnette Sievert
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27. Evolutionary obstetrics
- Prof. Wenda Trevathan
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28. Sex differences in mortality
- Dr. Daniel Kruger
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29. The endocrinology of human life history transitions
- Prof. Peter Ellison
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30. Genetic conflicts in human pregnancy
- Prof. David Haig
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31. Environmental effects on human reproduction
- Prof. Gillian Bentley
- Cancer
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32. A darwinian eye view of cancer
- Prof. Mel Greaves
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33. Viruses and cancer
- Prof. Robin Weiss
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34. Connecting aging and cancer through the lens of evolution
- Prof. James DeGregori
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35. Evolutionary dynamics in cancer control and cure
- Dr. Bob Gatenby
- Specific Body Systems
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36. Hard tissue biology in human health and evolution: enamel biology
- Prof. Timothy Bromage
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37. Hard tissue biology in human health and evolution: bone biology
- Prof. Timothy Bromage
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38. Hard tissue biology in human health and evolution: craniofacial biology
- Prof. Timothy Bromage
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39. Hard tissue biology in human health and evolution: life history and chronobiology
- Prof. Timothy Bromage
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40. Lung biology and lung disease
- Prof. John S. Torday
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41. The evolutionary web of life
- Prof. John S. Torday
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42. Evolutionary considerations and the endothelium
- Dr. William Aird
- Mental Disorders
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43. Evolutionary psychiatry
- Prof. Randolph Nesse
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44. Evolutionary behavioural genetics and mental disorders
- Dr. Matthew Keller
- Questions and Answers
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45. Audience questions about evolution and medicine
- Prof. Randolph Nesse
- Paediatrics
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46. Evolutionary pediatrics
- Dr. Paul Turke
- Microbiome
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47. Evolution, the microbiome, and human health
- Dr. Joe Alcock
- Archived Lectures *These may not cover the latest advances in the field
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48. The hygiene hypothesis
- Prof. Graham Rook
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49. Mapping motivations: evolutionary health promotion
- Dr. Valerie Curtis
- Dr. Robert Aunger
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50. Evolutionary biology of depression
- Prof. Lewis Wolpert
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51. Evolutionary genetic epidemiology
- Prof. Nicholas Schork
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52. Mental disorders in the light of evolutionary biology
- Prof. Randolph Nesse
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53. Evolution: medicine's missing basic science
- Prof. Randolph Nesse
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54. Environmental effects on human reproduction
- Prof. Gillian Bentley
Printable Handouts
Navigable Slide Index
- Introduction
- Background
- Moffitt strategy
- Personalized oncology focuses on matching treatment to molecular targets
- General principles
- Second principle
- Combining personalized medicine and game theory models
- Adaptive therapy
- First clinical application
- Evolution-based mathematical models to design trial
- Integrating adaptive therapy mathematical model into clinical oncology practice (1)
- Integrating adaptive therapy mathematical model into clinical oncology practice (2)
- Current status
- Analyzing results using the underlying math model
- PSA dynamics pretreatment and during therapy
- Example
- Estimated patient control (1)
- Estimated patient control (2)
- Four patients in adaptive cohort remain on stably on treatment after >5 years
- Conclusions for this part
- Now, descent into pure speculation
- Has the magic bullet concept outlived its usefulness?
- Back to the drawing board
- Can cancer be cured?
- Intentional anthropogenic extinction: the Galapagos goat
- Hypothesis: first strike-second strike model for cancer cure
- First strike-second strike approaches yield highly variable dynamics
- Lessons for clinical therapy (1)
- Lessons for clinical therapy (2)
- Thank you
Topics Covered
- The molecular machinery of cancer resistance
- Adaptive therapy: exploiting the cost of resistance in cancer treatment
- Evolution-based mathematical models to design trial
- Integrating adaptive therapy mathematical model into oncology
- First strike-second strike model for cancer cure
Links
Series:
Categories:
Therapeutic Areas:
Talk Citation
Gatenby, B. (2022, October 31). Evolutionary dynamics in cancer control and cure [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved January 15, 2025, from https://doi.org/10.69645/BGZG1759.Export Citation (RIS)
Publication History
Financial Disclosures
- Dr. Bob Gatenby has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.
A selection of talks on Cancer
Transcript
Please wait while the transcript is being prepared...
0:00
Hi, my name is Bob Gatenby.
I'm a physician-scientist at
the Moffitt Cancer Center.
I'm a member of the Department
of Integrated
Mathematical Biology
and the Department of Radiology.
My topic is on the
evolutionary dynamics
in cancer control and cure.
0:19
I want to start with
some background.
The first is that cancer is
a complex dynamic system.
It's complex because
it has many components
and dynamic because
those components
interact with each other
often producing
non-linear dynamics.
To put that in perspective,
human intuition is very
good at linear dynamics.
If 1x = 2y and 2x = 4y, 3x = 6y,
we are very good at
predicting that.
However, if 1x = 2y and 2x = -5y
and 3x gives us 12y,
those are non-linear
dynamics and
human intuition is not very
good in dealing with that.
I think this is obvious
in what is the most
complex dynamic system
that's well known,
and that is the weather.
Just as an anecdote, I want
to tell a little story about
Benjamin Franklin
who was actually
a very outstanding scientist
in colonial America.
He wanted to see
a lunar eclipse.
When he was living
in Philadelphia,
he went out to see it.
But he was interrupted
by a violent storm,
in the US these are
called Nor'easters
because the wind comes
from the northeast.
Like all scientists of his day,
Franklin thought that the
wind carried the storm.
Therefore, since the wind
was coming out of the Northeast,
it would be coming from Boston.
Therefore, his brother
who lived in Boston,
would also not be able to
see the lunar eclipse.
He was shocked the next day
to learn that the storm
did not arrive in Boston until
after the eclipse was over.
Franklin was the first person
to really question this dogma,
that the wind carried the storm.
Now, this idea that wind carried
the storm is very linear.
If you ask a child,
they'll say that
because it makes sense.
But he was the
first to recognize
that this is a linear thinking,
but it's applied to a
complex dynamic system.
In fact, he very
astutely began to learn
that weather storms follow
variations in the
barometric pressure.
It's important to
recognize when we're
thinking about cancer
and cancer therapy,
that it is a non-linear system.
For that reason,
sometimes things that
are intuitively obvious
are also completely wrong.
We have to be able
to accept that.