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Genetically Modified Animals Will Not Fix The Prediction Problem

The fact that humans respond differently to drugs and disease should inform scientists regarding the use of animal models to predict human response to drugs and disease. Nevertheless, animal models consume billions of dollars of taxpayer money per year in addition to driving up the cost of drug development. The futility of this nonsense is exposed every time we learn more about human variation in disease.

An analysis of breast cancer genes from humans was recently published in the journal Nature.(Banerji et al. 2012) Scientists discovered that genes previously thought unrelated to breast cancer were actually important in causing the disease, including triple-negative breast cancer which is the most difficult to treat. Cooney reported:

"One of the lessons here is the real diversity of mutations in breast cancer. I think it's clear there are going to be roughly 50 or so different mutated genes in breast cancer," said Matthew Meyerson, co-senior author of the paper, Broad senior associate member, and professor of pathology at Dana-Farber Cancer Institute and Harvard Medical School. "There's a big diversity of driver genes in cancer. We don't understand what all of them are, but larger data sets will enable us to identify them" . . . "This is the first translocation event resulting in an oncogenic fusion protein that has been identified in this pathway," said Alex Toker, a professor in the department of pathology at Beth Israel Deaconess and Harvard Medical School. "That's important because this is one of the most frequently mutated pathways in human cancer, especially in women's cancers such as breast, ovarian, and endometrial cancer."

Breast cancer is an excellent example of what we should expect from a complex disease in a complex system. Breast cancer is not one disease but many. Each version of the disease affects different genomes differently and consequently treatments for the same version vary. There are probably at least 50 genes that contribute to breast cancer. Different combinations of these genes as well as differences in modifying genes would essentially eliminate the use of animal models for predicting human response to breast cancer. The related, but more important aspect of the problem, however, is the fact that animals and humans are complex systems with properties like emergence, the whole being greater than the sum of the parts, redundancy, robustness, modules, and hierarchal organization.(Greek, Menache, and Rice 2012) Even a single very small difference between complex systems can result in opposite outcomes to perturbations such as those that cause disease. Replacing one or two or even more genes in a mouse with genes from humans is not going to solve this problem. Complexity theory and the theory of evolution predict such and empirical evidence confirms it.

But note how Toker concludes:

"There are many additional studies that need to be performed using mouse models of disease that would recapitulate the expression of this protein in the mammary gland, in addition to the mechanism by which this protein promotes the effects associated with malignancy," Toker said. "These are all experiments that are under way." Once the mechanism at work in triple-negative breast cancer is understood through animal models, the next step would be to test chemical compounds to see how effective they might be at targeting cells that harbor this fusion gene's protein.

This is exactly how cancer research has been historically conducted and why anti-cancer drugs have a 95% failure rate in clinical trials.(Kummar et al. 2007) I have stated before that anyone applying for a grant from NIH should have to pass a test on complexity science and evolutionary biology. This is why. The mechanisms for cancer in animals are not the same as humans and even if they were identical there would still be substantial differences secondary to the fact that the pathways are operating in complex systems that are differently complex.

But as long as there is money to be made from animal models, academia will use animal models and humans will continue to die. (See Animal Research: Money Talks and Money in Animal-Based Research.)


Banerji, S. et al. 2012. Sequence analysis of mutations and translocations across breast cancer subtypes. Nature 486 (7403):405-9.

Greek, Ray, Andre Menache, and Mark J. Rice. 2012. Animal models in an age of personalized medicine. Personalized Medicine 9 (1):47-64.

Kummar, S. et al. 2007. Compressing drug development timelines in oncology using phase '0' trials. Nature reviews. Cancer 7 (2):131-9.


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