◥A new ecologically inspired paradigm in cancer treatment known as "adaptive therapy" capitalizes on competitive interactions between drug-sensitive and drug-resistant subclones. The goal of adaptive therapy is to maintain a controllable stable tumor burden by allowing a significant population of treatment-sensitive cells to survive. These, in turn, suppress proliferation of the less-fit resistant populations. However, there remain several open challenges in designing adaptive therapies, particularly in extending these therapeutic concepts to multiple treatments. We present a cancer treatment case study (metastatic castrate-resistant prostate cancer) as a point of departure to illustrate three novel concepts to aid the design of multidrug adaptive therapies. First, frequency-dependent "cycles" of tumor evolution can trap tumor evolution in a periodic, controllable loop. Second, the availability and selection of treatments may limit the evolutionary "absorbing region" reachable by the tumor. Third, the velocity of evolution significantly influences the optimal timing of drug sequences. These three conceptual advances provide a path forward for multidrug adaptive therapy.Significance: Driving tumor evolution into periodic, repeatable treatment cycles provides a path forward for multidrug adaptive therapy.

The major excitatory and inhibitory neurotransmitters, glutamate (Glu) and gamma-aminobutyric acid (GABA), respectively, are implicated in the pathophysiology of schizophrenia. N-acetyl-aspartyl-glutamate (NAAG), a neuropeptide that modulates the Glu system, may also be altered in schizophrenia. This study investigated GABA, Glu + glutamine (Glx), and NAAG levels in younger and older subjects with schizophrenia. Forty-one subjects, 21 with chronic schizophrenia and 20 healthy controls, participated in this study. Proton magnetic resonance spectroscopy ((1)H-MRS) was used to measure GABA, Glx, and NAAG levels in the anterior cingulate (AC) and centrum semiovale (CSO) regions. NAAG in the CSO was higher in younger schizophrenia subjects compared with younger control subjects. The opposite pattern was observed in the older groups. Glx was reduced in the schizophrenia group irrespective of age group and brain region. There was a trend for reduced AC GABA in older schizophrenia subjects compared with older control subjects. Poor attention performance was correlated to lower AC GABA levels in both groups. Higher levels of CSO NAAG were associated with greater negative symptom severity in schizophrenia. These results provide support for altered glutamatergic and GABAergic function associated with illness course and cognitive and negative symptoms in schizophrenia. The study also highlights the importance of studies that combine MRS measurements of NAAG, GABA, and Glu for a more comprehensive neurochemical characterization of schizophrenia.

CD4 T cell clones have been shown to be functionally heterogeneous in the mouse. However, it is not known if normal CD4 T cells are also functionally heterogeneous, or whether functional specialization is a result of cloning and long-term culture. To approach this question, a monoclonal antibody reacting with a subset of CD4 T cells has been prepared by immunization of rats with different cloned T cell lines all sharing the same functional activity. This monoclonal antibody reacts with a subset of CD45 (T200) molecules by binding to a determinant requiring the expression of the second variable exon of the CD45 molecule. Some CD4 T cells bear high levels of this marker, while others react only weakly. This antibody was used to separate CD4 T cells into two subpopulations. The brightly staining population was found to produce interleukin (IL) 2 and not IL 4, while the weakly staining population produced IL 4 and not IL 2. These data demonstrate that CD4 T cells in normal mice are already functionally committed, and that they differentially express forms of CD45 that contain the second variable exon.

Control and conquer" -this is the philosophy behind adaptive therapy, which seeks to exploit intra-tumoural competition to avoid, or at least, delay the emergence of therapy resistance in cancer. Motivated by promising results from theoretical, experimental and, most recently, a clinical study in prostate cancer, there is an increasing interest in extending this approach to other cancers. As such, it is urgent to understand the characteristics of a cancer which determine whether it will respond well to adaptive therapy, or not. A plausible candidate for such a selection criterion is the fitness cost of resistance. In this 1 .

Purpose: Integration of evolutionary dynamics into systemic therapy for metastatic cancers can prolong tumor control compared with standard maximum tolerated dose (MTD) strategies. Prior investigations have focused on monotherapy, but many clinical cancer treatments combine two or more drugs. Optimizing the evolutionary dynamics in multidrug therapy is challenging because of the complex cellular interactions and the large parameter space of potential variations in drugs, doses, and treatment schedules. However, multidrug therapy also represents an opportunity to further improve outcomes using evolution-based strategies. Experimental Design: We examine evolution-based strategies for two-drug therapy and identify an approach that divides the treatment drugs into primary and secondary roles. The primary drug has the greatest efficacy and/or lowest toxicity. The secondary drug is applied solely to reduce the resistant population to the primary drug. Results: Simulations from the mathematical model demonstrate that the primary-secondary approach increases time to progression (TTP) compared with conventional strategies in which drugs are administered without regard to evolutionary dynamics. We apply our model to an ongoing adaptive therapy clinical trial of evolution-based administration of abiraterone to treat metastatic castrate-resistant prostate cancer. Model simulations, parameterized with data from individual patients who progressed, demonstrate that strategic application of docetaxel during abiraterone therapy would have significantly increased their TTP. Conclusions: Mathematical models can integrate evolutionary dynamics into multidrug cancer clinical trials. This has the potential to improve outcomes and to develop clinical trials in which these mathematical models are also used to estimate the mechanism(s) of treatment failure and explore alternative strategies to improve outcomes in future trials.