Modulating Thyroid Hormone Levels in Adult Mice: Impact on Behavior and Compensatory Brain Changes.

Thyroid hormone (TH) perturbation is a common medical problem. Because of substantial public health impact, prior researchers have studied hyper- and hypothyroidism in animal models. Although most prior research focused on in utero and/or developmental effects, changes in circulating TH levels are commonly seen in elderly individuals: approximately 20% of persons older than 80 years have clinically impactful hypothyroidism and up to 5% have clinical hyperthyroidism, with women being more often affected than men. TH disease model methodology in mice have varied but usually focus on a single sex, and the impact(s) of TH perturbation on the adult brain are not well understood. We administered thyroxine to middle-aged (13 to 14 months) male and female mice to model hyperthyroidism and TH-lowering drugs propylthiouracil (PTU) and methimazole, to induce hypothyroidism. These pharmacological agents are used commonly in adult humans. Circulating TH-level changes were observed when thyroxine was dosed at 20 µg/mL in drinking water for two weeks. By contrast, PTU and methimazole did not elicit a consistent reproducible effect until two months of treatment. No substantial changes in TH levels were detected in brain tissues of treated animals; however, pronounced changes in gene expression, specifically for TH-processing transcripts, were observed following the treatment with thyroxine. Our study indicated a robust compensatory mechanism by which the brain tissue/cells minimize the TH fluctuation in CNS by altering gene expression. Neurobehavioral changes were related to the TH perturbation and suggested potential associations between cognitive status and hyper- and hypothyroidism.

Tumor regression and growth rates determined in five intramural NCI prostate cancer trials: the growth rate constant as an indicator of therapeutic efficacy.

PURPOSE: In solid tumors such as prostate cancer, novel paradigms are needed to assess therapeutic efficacy. We utilized a method estimating tumor growth and regression rate constants from serial PSA measurements, and assessed its potential in patients with metastatic castration resistant prostate carcinoma (mCRPC). EXPERIMENTAL DESIGN: Patients were enrolled in five phase II studies, including an experimental vaccine trial, representing the evolution of therapy in mCRPC. PSA measurements obtained before, and during, therapy were used. Data analysis using a two-phase mathematical equation yielded concomitant PSA growth and regression rate constants. RESULTS: Growth rate constants (g) can be estimated while patients receive therapy and in such patients g is superior to PSA-DT in predicting OS. Incremental reductions in growth rate constants were recorded in successive trials with a 10-fold slower g in the most recent combination therapy trial (log g = 10(-3.17)) relative to single-agent thalidomide (log g = 10(-2.08)) more than a decade earlier. Growth rate constants correlated with survival, except in patients receiving vaccine-based therapy where the evidence demonstrates prolonged survival presumably due to immunity developing subsequent to vaccine administration. CONCLUSION: Incremental reductions in tumor growth rate constants suggest increased efficacy in successive chemotherapy trials. The derived growth rate constant correlates with survival, and may be used to assess efficacy. The PSA-TRICOM vaccine appears to have provided marked benefit not apparent during vaccination, but consistent with subsequent development of a beneficial immune response. If validated as a surrogate for survival, growth rate constants would offer an important new efficacy endpoint for clinical trials.

Tumor growth rates derived from data for patients in a clinical trial correlate strongly with patient survival: a novel strategy for evaluation of clinical trial data.

PURPOSE: The slow progress in developing new cancer therapies can be attributed in part to the long time spent in clinical development. To hasten development, new paradigms especially applicable to patients with metastatic disease are needed. PATIENTS AND METHODS: We present a new method to predict survival using tumor measurement data gathered while a patient with cancer is receiving therapy in a clinical trial. We developed a two-phase equation to estimate the concomitant rates of tumor regression (regression rate constant d) and tumor growth (growth rate constant g). RESULTS: We evaluated the model against serial levels of prostate-specific antigen (PSA) in 112 patients undergoing treatment for prostate cancer. Survival was strongly correlated with the log of the growth rate constant, log(g) (Pearson r = -0.72) but not with the log of the regression rate constants, log(d) (r = -0.218). Values of log(g) exhibited a bimodal distribution. Patients with log(g) values above the median had a mortality hazard of 5.14 (95% confidence interval, 3.10-8.52) when compared with those with log(g) values below the median. Mathematically, the minimum PSA value (nadir) and the time to this minimum are determined by the kinetic parameters d and g, and can be viewed as surrogates. CONCLUSIONS: This mathematical model has applications to many tumor types and may aid in evaluating patient outcomes. Modeling tumor progression using data gathered while patients are on study, may help evaluate the ability of therapies to prolong survival and assist in drug development.