Translating Mathematical Modeling of Tumor Growth Patterns into Novel Therapeutic Approaches for Breast Cancer

Abstract

In breast cancer, mortality is driven by the metastatic process, whereby some cancer cells leave their primary site of origin and travel to distant vital organs. Despite improved screening and therapies to treat breast cancers, metastasis continues to undermine these advances. The pervasive albatross of metastasis necessitates improved prevention and treatment of metastasis. To this end, clinicians routinely employ post-operative or adjuvant therapy to decrease the risk of future metastasis and improve the chance for cure. This article evaluates the limitations of breast cancer therapies within the context of growth curves, and in doing so, provides new insight into the metastatic process as well as more effective means for therapeutic delivery. Two critical developments evolve from this mathematical analysis: first, the use of dose dense chemotherapy to improve survival among breast cancer patients; and second, the theory of self-seeding, which fundamentally changes our understanding of metastasis and the trajectory of drug development.

Estimating Tumor Growth Rates In Vivo

“…Many models have been proposed, but there is still no consensus about the growth patterns that solid tumors exhibit [7]. This is an important problem because an accurate model of tumor growth is needed for evaluating screening strategies [18], optimizing radiation treatment protocols [27, 2], and making decisions about patient treatment [5, 6]. …”

Self-targeting of TNF-releasing cancer cells in preclinical models of primary and metastatic tumors

“…Recent studies showed that circulating cancer cells can traffic from primary or metastatic lesions to the peripheral blood and then back to their tumor of origin through a process termed "self-seeding" (1,2). This process is proposed to mediate cancer progression by recruiting circulating tumor cells capable of surviving under harsh conditions in the bloodstream, thereby promoting both primary tumor growth and secondary metastatic dissemination (1,3). Such homing properties may be facilitated by the presence of blood vessels with altered vascular endothelial barrier function in tumors (2,4) and by the presence of a favorable tumor microenvironment (1).…”

Current Advances in Mathematical Modeling of Anti-Cancer Drug Penetration into Tumor Tissues

“…Traina et al ( 71 ) continued to use the Norton-Simon model to optimize chemotherapeutic dosages and schedules in mouse xenograft models. Similar mathematical models have been used to study dose-dense chemotherapies ( 72 ) and to evaluate both the limitations of current schedules in breast cancer treatment and therapeutic advantages of novel dose-dense chemotherapies ( 73 ). Gatenby et al ( 74 ) examined a novel approach in which cancer therapy was adapted to the evolving temporal and spatial variability of the tumor microenvironment, cellular phenotypes, and therapy-induced perturbations instead of using a typical linear protocol of drug administration.…”