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Abiraterone treats metastatic castrate-resistant prostate cancer by inhibiting CYP17A, an enzyme for testosterone auto-production. With standard dosing, evolution of resistance with treatment failure (radiographic progression) occurs at a median of ~16.5 months. We hypothesize time to progression (TTP) could be increased by integrating evolutionary dynamics into therapy. We developed an evolutionary game theory model using Lotka–Volterra equations with three competing cancer “species”: androgen dependent, androgen producing, and androgen independent. Simulations with standard abiraterone dosing demonstrate strong selection for androgen-independent cells and rapid treatment failure. Adaptive therapy, using patient-specific tumor dynamics to inform on/off treatment cycles, suppresses proliferation of androgen-independent cells and lowers cumulative drug dose. In a pilot clinical trial, 10 of 11 patients maintained stable oscillations of tumor burdens; median TTP is at least 27 months with reduced cumulative drug use of 47% of standard dosing. The outcomes show significant improvement over published studies and a contemporaneous population. Evolution of resistance is a common cause of cancer treatment failure and tumor progression. Here, the authors present a method for integrating evolutionary principles based on adaptive therapy into abiraterone therapy for metastatic castrate-resistant prostate cancer and show the positive results of an interim analysis of a trial cohort.

Abiraterone acetate is an effective treatment for metastatic castrate-resistant prostate cancer (mCRPC), but evolution of resistance inevitably leads to progression. We present a pilot study in which abiraterone dosing is guided by evolution-informed mathematical models to delay onset of resistance. In the study cohort, abiraterone was stopped when PSA was <50% of pretreatment value and resumed when PSA returned to baseline. Results are compared to a contemporaneous cohort who had >50% PSA decline after initial abiraterone administration and met trial eligibility requirements but chose standard of care (SOC) dosing. 17 subjects were enrolled in the adaptive therapy group and 16 in the SOC group. All SOC subjects have progressed, but four patients in the study cohort remain stably cycling (range 53-70 months). The study cohort had significantly improved median time to progression (TTP; 33.5 months; p<0.001) and median overall survival (OS; 58.5 months; hazard ratio, 0.41, 95% confidence interval (CI), 0.20-0.83, p<0.001) compared to 14.3 and 31.3 months in the SOC cohort. On average, study subjects received no abiraterone during 46% of time on trial. Longitudinal trial data demonstrated the competition coefficient ratio ( ) of sensitive and resistant populations, a critical factor in intratumoral evolution, was two- to threefold higher than pre-trial estimates. Computer simulations of intratumoral evolutionary dynamics in the four long-term survivors found that, due to the larger value for cycled therapy significantly decreased the resistant population. Simulations in subjects who progressed predicted further increases in OS could be achieved with prompt abiraterone withdrawal after achieving 50% PSA reduction. Incorporation of evolution-based mathematical models into abiraterone monotherapy for mCRPC significantly increases TTP and OS. Computer simulations with updated parameters from longitudinal trial data can estimate intratumoral evolutionary dynamics in each subject and identify strategies to improve outcomes. Moffitt internal grants and NIH/NCI U54CA143970-05 (Physical Science Oncology Network).

In the absence of curative therapies, treatment of metastatic castrate-resistant prostate cancer (mCRPC) using currently available drugs can be improved by integrating evolutionary principles that govern proliferation of resistant subpopulations into current treatment protocols. Here we develop what is coined as an ‘evolutionary stable therapy’, within the context of the mathematical model that has been used to inform the first adaptive therapy clinical trial of mCRPC. The objective of this therapy is to maintain a stable polymorphic tumor heterogeneity of sensitive and resistant cells to therapy in order to prolong treatment efficacy and progression free survival. Optimal control analysis shows that an increasing dose titration protocol, a very common clinical dosing process, can achieve tumor stabilization for a wide range of potential initial tumor compositions and volumes. Furthermore, larger tumor volumes may counter intuitively be more likely to be stabilized if sensitive cells dominate the tumor composition at time of initial treatment, suggesting a delay of initial treatment could prove beneficial. While it remains uncertain if metastatic disease in humans has the properties that allow it to be truly stabilized, the benefits of a dose titration protocol warrant additional pre-clinical and clinical investigations.

Tumors are highly dynamic ecosystems in which diverse cancer cell subpopulations compete for space and resources. These complex, often non-linear interactions govern continuous spatial and temporal changes in the size and phenotypic properties of these subpopulations. Because intra-tumoral blood flow is often chaotic, competition for resources may be a critical selection factor in progression and prognosis. Here, we quantify resource competition using 3D spheroid cultures with MDA-MB-231 and MCF-7 breast cancer cells. We hypothesized that MCF-7 cells, which primarily rely on efficient aerobic glucose metabolism, would dominate the population under normal pH and low glucose conditions; and MDA-MB-231 cells, which exhibit high levels of glycolytic metabolism, would dominate under low pH and high glucose conditions. In spheroids with single populations, MCF-7 cells exhibited equal or superior intrinsic growth rates (density-independent measure of success) and carrying capacities (density-dependent measure of success) when compared to MDA-MB-231 cells under all pH and nutrient conditions. Despite these advantages, when grown together, MCF-7 cells do not always outcompete MDA-MB-231 cells. MDA-MB-231 cells outcompete MCF-7 cells in low glucose conditions and coexistence is achieved in low pH conditions. Under all conditions, MDA-MB-231 has a stronger competitive effect (frequency-dependent interaction) on MCF-7 cells than vice-versa. This, and the inability of growth rate or carrying capacity when grown individually to predict the outcome of competition, suggests a reliance on frequency-dependent interactions and the need for competition assays. We frame these results in a game-theoretic (frequency-dependent) model of cancer cell interactions and conclude that competition assays can demonstrate critical density-independent, density-dependent and frequency-dependent interactions that likely contribute to in vivo outcomes.

Intracellular thermometry has recently demonstrated temperatures in the nucleus, mitochondria, and centrosome to be significantly higher than those of the cytoplasm and cell membrane. This local thermogenesis and the resulting temperature gradient could facilitate the development of persistent, self-organizing convection currents in the cytoplasm of large eukaryotes. Using 3-dimensional computational simulations of intracellular fluid motion, we quantify the convective velocities that could result from the temperature differences observed experimentally. Based on these velocities, we identify the conditions necessary for this temperature-driven bulk flow to dominate over random thermal diffusive motion at the scale of a single eukaryotic cell. With temperature gradients of the order 1°C and diffusion coefficients comparable to those described in the literature, Péclet numbers ≥ 1 are feasible and permit comparable or greater effects of convection than diffusion in determining intracellular mass flux. In addition to the temperature gradient, the resulting flow patterns would also depend on the spatial localization of the heat source, the shape of the cell membrane, and the complex intracellular structure including the cytoskeleton. While this intracellular convection would be highly context-dependent, in certain settings, convective motion could provide a previously unrecognized mechanism for directed, bulk transport within eukaryotic cells.

Metastatic disease remains invariably fatal. Until truly curative therapies are developed, can clinical oncology benefit from lessons learned in pest management?

Cilia are evolutionarily conserved hair-like structures with a wide spectrum of key biological roles, and their dysfunction has been linked to a growing class of genetic disorders, known collectively as ciliopathies. Many strides have been made towards deciphering the molecular causes for these diseases, which have in turn expanded the understanding of cilia and their functional roles. One recently-identified ciliary gene is ARL2BP, encoding the ADP-Ribosylation Factor Like 2 Binding Protein. In this study, we have identified multiple ciliopathy phenotypes associated with mutations in ARL2BP in human patients and in a mouse knockout model. Our research demonstrates that spermiogenesis is impaired, resulting in abnormally shaped heads, shortened and mis-assembled sperm tails, as well as in loss of axonemal doublets. Additional phenotypes in the mouse included enlarged ventricles of the brain and situs inversus. Mouse embryonic fibroblasts derived from knockout animals revealed delayed depolymerization of primary cilia. Our results suggest that ARL2BP is required for the structural maintenance of cilia as well as of the sperm flagellum, and that its deficiency leads to syndromic ciliopathy.

The “war on cancer” began over 40 years ago with the signing of the National Cancer Act of 1971. Currently, complete eradication has proven possible in early stage premetastatic disease with increasingly successful early detection and surgery protocols; however, late stage metastatic disease remains invariably fatal. One of the main causes of treatment failure in metastatic disease is the ability of cancer cells to evolve resistance to currently available therapies. Evolution of resistance to control measures is a universal problem. While it may seem that the mechanisms of resistance employed by cancer cells are impossible to control, we show that many of the resistance mechanisms are mirrored in agricultural pests. In this way, we argue that measures developed in the agricultural industry to slow or prevent pesticide resistance could be adopted in clinical cancer biology to do the same. The agriculture industry recognized the problem of pesticide resistance and responded by developing and enforcing guidelines on resistance management and prevention. These guidelines, known as integrated pest management (IPM), do not encourage eradication of pests but instead strive to maintain pests, even with the presence of resistant strains, at a level that does not cause economic damage to the crops. Integrated pest management inspired management of metastatic cancer could result in the slowing or curtailing of widespread resistance to treatment, reducing overall drug usage, and increasing the survival and quality of life of patients with cancer. Using IPM principles as a foundation and shifting the goal of treatment of metastatic disease to long-term management will require close monitoring of evolving tumor populations, judicious application of currently available therapies, and development of new criteria of success.

Large animals should have higher lifetime probabilities of cancer than small animals because each cell division carries an attendant risk of mutating towards a tumour lineage. However, this is not observed—a (Peto's) paradox that suggests large and/or long-lived species have evolved effective cancer suppression mechanisms. Using the Euler–Lotka population model, we demonstrate the evolutionary value of cancer suppression as determined by the ‘cost’ (decreased fecundity) of suppression verses the ‘cost’ of cancer (reduced survivorship). Body size per se will not select for sufficient cancer suppression to explain the paradox. Rather, cancer suppression should be most extreme when the probability of non-cancer death decreases with age (e.g. alligators), maturation is delayed, fecundity rates are low and fecundity increases with age. Thus, the value of cancer suppression is predicted to be lowest in the vole (short lifespan, high fecundity) and highest in the naked mole rat (long lived with late female sexual maturity). The life history of pre-industrial humans likely selected for quite low levels of cancer suppression. In modern humans that live much longer, this level results in unusually high lifetime cancer risks. The model predicts a lifetime risk of 49% compared with the current empirical value of 43%.