alexa Computer simulation of a breast cancer metastasis model.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Proteomics & Bioinformatics

Author(s): Retsky MW, Demicheli R, Swartzendruber DE, Bame PD, Wardwell RH,

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Abstract Recent analysis of relapse data from 1173 untreated early stage breast cancer patients with 16-20 year follow-up shows that frequency of relapse has a double peaked distribution. There is a sharp peak at 18 months, a nadir at 50 months and a broad peak at 60 months. Patients with larger tumors more frequently relapse in the first peak while those with smaller tumors relapse equally in both peaks. No existing theory of tumor growth predicts this effect. To help understand this phenomenon, a model of metastatic growth has been proposed consisting of three distinct phases: a single cell, an avascular growth, and a vascularized lesion. Computer simulation of this model shows that the second relapse peak can be explained by a steady stochastic progression from one phase to the next phase. However, to account for the first relapse peak, a sudden perturbation of the development at the time of surgery is necessary. Model simulations predict that patients who relapse in the second peak would have micrometastases in states of relatively low chemosensitivity when adjuvant therapy is normally administered. The simulation predicts that 15\% of T1, 39\% of T2, and 51\% of T3 staged patients benefit from adjuvant chemotherapy, partially offsetting the advantage of early detection. This suggests that early detection and adjuvant chemotherapy may not be symbiotic strategies. New therapies are needed to benefit patients who would relapse in the second peak.
This article was published in Breast Cancer Res Treat and referenced in Journal of Proteomics & Bioinformatics

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