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Highlights • Duration of metastatic latency was very small compared to the growth period. • Seeding of the first lung metastasis occurred before primary tumor reached detectable size, which implies that early cancer detection would not have prevented metastasis. • Primary tumor in situ may have slowed down metastatic growth; and. • Primary tumor contained a relatively fast growing subpopulation of metastasis-producing cells, which is consistent with the aggressive course of the disease in these patients. Abstract The goal of this study is to uncover some unobservable aspects of the individual-patient natural history of metastatic renal cell carcinoma (RCC) through mathematical modeling. We analyzed four clear cell RCC patients who at the time of primary tumor resection already had pulmonary metastases. Our description of the natural history of cancer in these patients was based on a parameterized version of a previously proposed very general mathematical model adjusted to these clinical cases. For each patient, identifiable model parameters were estimated by the method of maximum likelihood from the volumes of lung metastases computed from CT scans taken at or around the time of surgery. The model-based distribution of the volumes of lung metastases with likelihood maximizing parameters provided an excellent fit to the data for all patients analyzed. We found that, according to the model, the most likely scenario in all four patients had the following clinically important features: (1) duration of metastatic latency was very small compared to the growth period; (2) seeding of the first lung metastasis occurred before primary tumor reached detectable size, which implies that early cancer detection would not have prevented metastasis; (3) primary tumor contained a relatively fast growing subpopulation of metastasis-producing cells, which is consistent with the observed aggressive course of the disease; and (4) the volume of the primary tumor at the time of metastasis survey does not seem to be correlated with such characteristics of the metastatic burden as the number of detected lung metastases, their total volume, and the volume of the largest detected lung metastasis. [ABSTRACT FROM AUTHOR]

Abstract: A comprehensive mechanistic model of cancer natural history was utilized to obtain an explicit formula for the distribution of volumes of detectable metastases in a given secondary site at any time post-diagnosis. This model provided an excellent fit to the volumes of n =31, 20 and 15 bone metastases observed in three breast cancer patients 8 years, 5.5 years and 9 months after primary diagnosis, respectively. The model with optimal parameters allowed us to reconstruct the individual natural history of cancer for the first patient. This gave definitive answers, for the patient in question, to the following three questions of major importance in clinical oncology: (1) How early an event is metastatic dissemination of breast cancer? (2) How long is the metastasis latency time? and (3) Does extirpation of the primary breast tumor accelerate the growth of metastases? Specifically, according to the model applied to the first patient, (1) inception of the first metastasis occurred 29.5 years prior to the primary diagnosis; (2) the expected metastasis latency time was about 79.5 years; and (3) resection of the primary tumor was followed by a 32-fold increase in the rate of metastasis growth. The model and our conclusions were validated by the results for the two other patients. [Copyright &y& Elsevier]