New Paradigm of Breast Cancer Causation and Prevention

Institution: University of California, San Francisco
Investigator(s): Robert Hiatt, M.D., Ph.D. - Robert Hiatt, M.D., Ph.D. - Robert Hiatt, M.D., Ph.D. - Robert Hiatt, M.D., Ph.D. - Robert Hiatt, M.D., Ph.D. - Robert Hiatt, M.D., Ph.D. -
Award Cycle: 2009 (Cycle 15) Grant #: 15QB-8301 Award: $181,995
Award Type: SRI Request for Qualifications-RFQ
Research Priorities
Etiology and Prevention>Prevention and Risk Reduction: ending the danger of breast cancer

This is a collaboration with: 15QB-8301A -

Initial Award Abstract (2009)
Breast cancer involves many complex, dynamic properties that are best understood as an ecological disorder. This means that within the individual there are likely to be multiple determinants of breast cancer risk, and within populations the causes of breast cancer are heterogeneous. Women with different genetic inheritance and gene expression may develop the same disease through a different initial contributing nexus of factors. Conversely, women with similar exposures may experience different disease outcomes. The search for a single causal framework to explain the changing incidence of breast cancer may be futile.

This team will conduct research and create a conceptual framework that extends complexity theory to the study of breast cancer. We are including the perspectives of multiple disciplines to examine the web of relationships among the many variables operating on susceptibility, induction, and development of breast cancer.

Specific questions to be answered include:
1. What risk and protective factors should be included in a new, complex conceptual framework (e.g. gene expression, multiple contaminant exposures across the life course, fetal programming, the timing and pace of sexual maturation, personal experience of racism, neighborhood cohesion, etc.)
2. How can dynamics of these factors be accounted for, including interactions, timing, dose, and other properties?

An multi-disciplinary expert panel will assist the team in exploring alternative modeling approaches and generating a graphic display of the model that contains the necessary complexity and is transparent and understandable to the lay public. These will be tested to ensure effectiveness and disseminated for further use and potential development and to inform research and prevention efforts..

Final Report (2015)

This project created a model of the important elements that are considered causes of breast cancer to enlighten current thinking on the origins of breast cancer. Because the causes of breast cancer are complex and incompletely understood, the model we have created takes into account some of this complexity at multiple levels from the genetic and cellular to the social level. The novelty of our approach is that it includes the “causes of the causes” not just the proximate factors. In this way we hope that the model will illustrate to users that even elements as diverse as where women have lived as young girls, their physical activity, environmental exposures and genetic susceptibility may play a role in breast cancer’s appearance in adult life. This project stands back and uses the collective wisdom of multiple disciplinary perspectives to create a conceptual model that recognizes the causation of breast cancer from a complex systems approach. The model we have produced not only provides common ground for understanding, but point up gaps in our knowledge that require further investigation. We want the transdisciplinary approach we have used to lead to discoveries at the intersections of disciplines that may not otherwise have been obvious.

In the period covered by this Progress Report, we completed the final review and details on the conceptual model and spent most of our time completing and refining the mathematical model. The final steps for the mathematical model proved very challenging due to the exacting requirements of the data as well as conceptual and computational reasons. During this final extension we completed the mathematical model and the final manuscript. The manuscript was approved by all co-authors after two rounds of review and also reviewed by outside advisors. The manuscript contains both the conceptual and mathematical models as well as an extensive reference list linked to the conceptual model, making a standard journal presentation also a challenge. The manuscript is now under review in a widely read, high impact general medical journal. As a final step we are in discussions with the CBCRP as to how to best display the model and its dynamic qualities on their website.