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Promising development from translational or perhaps anti-translational research in breast cancer

DOI: 10.1186/2001-1326-1-17

Keywords: Breast cancer, Early relapses, NSAID, Perioperative ketorolac, Inflammatory oncotaxis, Angiogenesis, Dormancy, Transient systemic inflammation

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Abstract:

We have been diligently looking for new clinical or laboratory information that could provide a connection or correlation between the bimodal relapse pattern and some clinical factor or interventional action and perhaps lead us towards methods to prevent surgery-initiated tumor activity.A recent development occurred when a retrospective study appeared in an anesthesiology journal that suggested the perioperative NSAID analgesic ketorolac seems to reduce early relapses following mastectomy. Collaborating with these anesthesiologists to understand this effect, we independently re-examined and updated their data and, in search of a mechanism, focused in on the transient systemic inflammation that follows surgery to remove a primary tumor. We have arrived at several possible explanations ranging from mechanical to biological that suggest the relapses avoided in the early years do not show up later.We present the possibility that a nontoxic and low cost intervention could prevent early relapses. It may be that preventing systemic inflammation post surgery will prevent early relapses. This could be controlled by the surgical anesthesiologist’s choice of analgesic drugs. This development needs to be confirmed in a randomized controlled clinical trial and we have identified triple negative breast cancer as the ideal subset with which to test this. If successful, this would be relatively easy to implement in developing as well as developed countries and would be an important translational result.We are an eclectic group of scientists and physicians who have been working for almost two decades on an unusual research project dealing with breast cancer. In this project we are not conducting laboratory research nor are we treating patients with experimental therapies. We are deconstructing clinical data using powerful numerical and computational tools and trying to understand what was the actual tumor growth activity that could have produced these data. We are then extrapolating

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