Douglas E. Swartzendruber

Proposal for a new model of breast cancer metastatic development

BACKGROUND The commonly accepted theory of breast cancer metastatic development assumes continuous tumor growth from tumor seeding until documentation of clinical recurrence. In particular, Gompertzian growth kinetics is currently the theoretical cornerstone of the natural history of breast cancer, and has been widely utilized for planning treatments. MATERIALS AND METHODS To verify agreement between findings and the implications of the continuous growth model, several published papers about the natural history of breast cancer after removal of the primary tumor were reviewed. Also, findings from animal models concerning metastasis biology were considered. RESULTS The continuous growth model failed in important ways upon this critical reappraisal. As an alternative, the tumor dormancy hypothesis was considered to provide a more reasonable description of tumor recurrence. Moreover, primary tumor removal was revealed as a potentially perturbing factor for metastasis development. CONCLUSIONS A new general outline of metastatic development of breast cancer incorporating tumor dormancy in specific micrometastatic phases, stochastic transitions between them, and start signals from surgery for micrometastatic growth was designed. The proposed model suggests new views concerning scheduling of current chemotherapy, new treatment approaches aimed at keeping micrometastases in a dormant state for the patients entire life, and the careful reappraisal of the timing of surgery within the multimodal treatment of operable breast cancer.

Computer simulation of a breast cancer metastasis model

Recent analysis of relapse data from 1173 untreatedearly stage breast cancer patients with 16–20 yearfollow-up shows that the frequency of relapse hasa double peaked distribution. There is a sharppeak at 18 months, a nadir at 50months and a broad peak at 60 months.Patients with larger tumors more frequently relapse inthe first peak while those with smaller tumorsrelapse equally in both peaks.No existing theory of tumor growth predicts thiseffect. To help understand this phenomenon, a modelof metastatic growth has been proposed consisting ofthree distinct phases: a single cell, an avasculargrowth, and a vascularized lesion. Computer simulation ofthis model shows that the second relapse peakcan be explained by a steady stochastic progressionfrom one phase to the next phase. However,to account for the first relapse peak, asudden perturbation of that development at the timeof surgery is necessary.Model simulations predict that patients who relapse inthe second peak would have micrometastases in statesof relatively low chemosensitivity when adjuvant therapy isnormally administered. The simulation predicts that 15% ofT1, 39% of T2, and 51% of T3staged patients benefit from adjuvant chemotherapy, partially offsettingthe advantage of early detection. This suggests thatearly detection and adjuvant chemotherapy may not besymbiotic strategies. New therapies are needed to benefitpatients who would relapse in the second peak.

Is Gompertzian or exponential kinetics a valid description of individual human cancer growth

It is generally accepted that human cancers grow in an exponential or Gompertzian manner. This assumption is based on analysis of the growth of transplantable animal tumors and on averages of tumor growth in human populations. A computer model of breast cancer in individual patients has raised some doubts about this assumption. The computer model predicts an irregular pattern of tumor growth that incorporates plateaus or dormant periods separated by Gompertzian growth spurts. Since growth patterns involving plateaus are not predicted by conventionally accepted exponential or Gompertzian kinetics, sufficient documentation of their existence may be regarded as some evidence that the computer model is correct. The literature has been surveyed to identify growth patterns specifically predicted by the model. The literature contains clinical evidence from individual patients of this growth pattern in primary breast, large intestine and rectum, and pulmonary cancers and metastatic pulmonary cancer. Much data, including the only breast data, are not consistent with exponential or Gompertzian kinetics but are explainable by irregular growth kinetics. Exponential growth is valid for some tumors and for short times, but there are many papers citing significant deviations from that growth. Exponential growth may accurately describe averages of human tumor growth and growth of multipassaged experimental tumors, but it is not valid for all individual tumors.

Computer model challenges breast cancer treatment strategy.

The breast cancer treatment failure rate remains unacceptably high. The current breast cancer treatment paradigm, based primarily on Gompertzian kinetics and animal models, advocates short-course, intensive chemotherapy subsequent to tumor debulking, citing drug resistance and host toxicity as the primary reasons for treatment failure. To better understand treatment failure, we have studied breast cancer from the perspective of computer modeling. Our results demonstrate breast cancers grow in an irregular fashion; this differs from the Gompertzian mode of animal models and thus challenges the validity of the current paradigm. Clinical and laboratory data support the concept of irregular growth rather than the common claim that human tumors grow in a Gompertzian fashion. Treatment failure mechanisms for breast cancer appear to differ from those for animal models, and thus treatments optimize on animal models may not be optimal for breast cancer. A failure mechanism consistent with our results involves temporarily dormant tumor cells in anatomical or pharmacological sanctuary, which eventually result in aggressive metastatic disease.

Cell Kinetics in Clinical Oncology

While the etiology of most human cancers is still unknown and may be multifactorial, a number of epiphenomena discriminating normal from malignant cells have been discovered, including genetic (1, 2), biochemical (3, 4, 5), and cytokinetic parameters (6, 7). Focusing on the kinetics of tumor growth in this chapter, we will: (1) delineate how measurements of cell kinetics parameters can serve as quantitative descriptors of malignant disease potentially determining response to cytotoxic therapy; (2) review strategies to either differentially enhance tumor cell kill or to establish a viable symbiosis between tumor and host via tumor cell differentiation; and (3) address the feasibility of cytokinetic methods to predict drug responsiveness in vitro and in vivo.

The possible relationship between mercury from dental amalgam and diseases I: Effects within the oral cavity

Mercury is released from dental amalgams, and therefore it is necessary to consider the biological and clinical consequences of such exposure. Intraorally, it would appear as though mercury can cause hypersensitivity/toxic reactions resulting in lichen planus lesions, and may play a major role in the pathogenesis of gingivitis, periodontitis and periodontal disease.

Recent translational research: computational studies of breast cancer

The combination of mathematics – queen of sciences – and the general utility of computers has been used to make important inroads into insight-providing breast cancer research and clinical aids. These developments are in two broad areas. First, they provide useful prognostic guidelines for individual patients based on historic evidence. Second, by suggesting numeric tumor growth laws that are correlated to clinical parameters, they permit development of biologically relevant theories and comparison with patient data to help us understand complex biologic processes. These latter studies have produced many new ideas that are testable in clinical trials. In this review we discuss these developments from a clinical perspective, and ask whether and how they translate into useful tools for patient treatment.

An alternative approach for treatment of breast cancer

SummarySince adjuvant chemotherapy and hormonal therapy generally extend disease free survival in breast cancer rather than provide a cure, we have examined the current breast cancer paradigm. Heterogeneity is a fundamental characteristic of breast cancer tissue and a well recognized aspect of the disease. There are variations in natural history, histopathology, biochemistry and endocrinology, and molecular biology of cancer tissues and cells within the tissues. A variety of data indicate that growth kinetics are also variable, not only from tumor to tumor, but also during the natural history of an individuals tumor. To better understand kinetic heterogeneity, a stochastic numeric computer model of the natural history of breast cancer has been developed. To be consistent with inter- and intratumor kinetic heterogeneity and with late relapse, the model predicts that tumors grow in an irregular fashion with alternating periods of growth and periods of dormancy rather than the generally accepted modified exponential, or Gompertzian fashion. The prediction of irregular growth has been compared to data relevant to growth characteristics of human breast cancer. Much data support the concept of irregular kinetics and temporary dormancy rather than steady, Gompertzian growth of human breast cancer. Thus, in addition to drug resistance, kinetic heterogeneity may help explain the limited impact that traditional chemotherapeutic treatment has had on mortality from breast cancer. Although the mechanisms underlying irregular growth need to be better understood, non-Gompertzian growth kinetics indicates that there may be alternative approaches for breast cancer treatment.