Cancer in a host induces responses that increase the ability of the microenvironment to sustain the growing mass, for example, angiogenesis, but cancer cells can have varying sensitivities to these sustainability signals. Here, we show that these sensitivities are significant determinants of ultimate tumor fate, especially in response to treatments and immune interactions. We present a mathematical model of cancer–immune interactions that modifies generalized logistic growth with both immune-predation and immune-recruitment. The role of a growing environmental carrying capacity is discussed as a possible regulatory mechanism for tumor growth, and this regulation is shown to modify cancer–immune interactions and the possibility of achieving immune-induced tumor dormancy. This mathematical model qualitatively matches experimental observations of immune-induced tumor dormancy as it predicts dormancy as a transient period of growth that necessarily ends in either tumor elimination or tumor escape. As dormant tumors may exist asymptomatically and may be easier to treat with conventional therapy, an understanding of the mechanisms behind tumor dormancy may lead to new treatments aimed at prolonging the dormant state or converting an aggressive cancer to the dormant state. Cancer Res; 73(12); 3534–44. ©2013 AACR.

Cancer dormancy, a state in which cancer cells persist in a host without significant growth, is a natural forestallment of progression to manifest disease and is thus of great clinical interest. Experimental work in mice suggests that in immune-induced dormancy, the longer a cancer remains dormant in a host, the more resistant the cancer cells become to cytotoxic T-cell-mediated killing. In this work, mathematical models are used to analyse the possible causative mechanisms of cancer escape from immune-induced dormancy. Using a data-driven approach, both decaying efficacy in immune predation and immune recruitment are analysed with results suggesting that decline in recruitment is a stronger determinant of escape than increased resistance to predation. Using a mechanistic approach, the existence of an immune-resistant cancer cell subpopulation is considered, and the effects on cancer dormancy and potential immunoediting mechanisms of cancer escape are analysed and discussed. The immunoediting mechanism assumes that the immune system selectively prunes the cancer of immune-sensitive cells, which is shown to cause an initially heterogeneous population to become a more homogeneous, and more resistant, population. The fact that this selection may result in the appearance of decreasing efficacy in T-cell cytotoxic effect with time in dormancy is also demonstrated. This work suggests that through actions that temporarily delay cancer growth through the targeted removal of immune-sensitive subpopulations, the immune response may actually progress the cancer to a more aggressive state.

Mathematical modeling has made significant contributions to drug design, development, and optimization. Virtual clinical trials that integrate mathematical models to explore patient heterogeneity and its impact on a variety of therapeutic questions have recently risen in popularity. Here, we outline best practices for creating virtual patients from mathematical models to ultimately implement and execute a virtual clinical trial. In this practical guide, we discuss and provide examples of model design, parameter estimation, parameter sensitivity, model identifiability, and virtual patient cohort creation. Our goal is to help researchers adopt these approaches to further the use of virtual population-based analysis and virtual clinical trials.

Tumor dormancy is a highly prevalent stage in cancer progression. We have previously generated and characterized in vivo experimental models of human tumor dormancy in which micro-tumors remain occult until they spontaneously shift into rapid tumor growth. We showed that the dormant micro-tumors undergo a stable microRNA (miRNA) switch during their transition from dormancy to a fast-growing phenotype and reported the identification of a consensus signature of human tumor dormancy-associated miRNAs (DmiRs). miRNA-190 (miR-190) is among the most upregulated DmiRs in all dormant tumors analyzed. Upregulation of miR-190 led to prolonged tumor dormancy in otherwise fast-growing glioblastomas and osteosarcomas. Here we investigate the transcriptional changes induced by miR-190 expression in cancer cells and show similar patterns of miR-190 mediated transcriptional reprogramming in both glioblastoma and osteosarcoma cells. The data suggests that miR-190 mediated effects rely on an extensive network of molecular changes in tumor cells and that miR-190 affects several transcriptional factors, tumor suppressor genes and interferon response pathways. The molecular mechanisms governing tumor dormancy described in this work may provide promising targets for early prevention of cancer and may lead to novel treatments to convert the malignant tumor phenotype into an asymptomatic dormant state.