Gene Expression Changes in a Prefinal Health Stage of Lethally Irradiated Male and Female Rhesus Macaques.

Radiation-induced gene expression (GE) changes can be used for early and high-throughput biodosimetry within the first three days postirradiation. However, is the method applicable in situations such as the Alexander Litvinenko case or the Goiania accident, where diagnosis occurred in a prefinal health stage? We aimed to characterize gene expression changes in a prefinal health stage of lethally irradiated male and female rhesus macaques. Peripheral blood was drawn pre-exposure and at the prefinal stage of male and female animals, which did not survive whole-body exposure with 700 cGy (LD66/60). RNA samples originated from a blinded randomized Good Laboratory Practice study comprising altogether 142 irradiated rhesus macaques of whom 60 animals and blood samples (15 samples for both time points and sexes) were used for this analysis. We evaluated GE on 34 genes widely used in biodosimetry and prediction of the hematological acute radiation syndrome severity (H-ARS) employing quantitative real-time polymerase chain reaction (qRT-PCR). These genes were run in duplicate and triplicate and altogether 96 measurements per time point and sex could be performed. In addition, 18S ribosomal RNA (rRNA) was measured to depict the ribosome/transcriptome status as well as for normalization purposes and 16S rRNA was evaluated as a surrogate for bacteremia. Mean differential gene expression (DGE) was calculated for each gene and sex including all replicate measurements and using pre-exposure samples as the reference. From 34 genes, altogether 27 genes appeared expressed. Pre-exposure samples revealed no signs of bacteremia and 18S rRNA GE was in the normal range in all 30 samples. Regarding prefinal samples, 46.7% and 40% of animals appeared infected in females and males, respectively, and for almost all males this was associated with out of normal range 18S rRNA values. The total number of detectable GE measurements was sixfold (females) and 15-fold (males) reduced in prefinal relative to pre-exposure samples and about tenfold lower in 80% of prefinal compared to pre-exposure samples (P < 0.0001). An overall 11-fold (median) downregulation in prefinal compared to pre-exposure samples was identified for most of the 27 genes and even FDXR appeared 4-14-fold downregulated in contrast to a pronounced up-regulation according to cited work. This pattern of overall downregulation of almost all genes and the rapid reduction of detectable genes at a prefinal stage was found in uninfected animals with normal range 18S rRNA as well. In conclusion, in a prefinal stage after lethal radiation exposure, the ribosome/transcriptome status remains present (based on normal range 18S rRNA values) in 60-67% of animals, but the whole transcriptome activity in general appears silenced and cannot be used for biodosimetry purposes, but probably as an indicator for an emerging prefinal health stage.

Predicting the Radiation Sensitivity of Male and Female Rhesus Macaques Using Gene Expression.

Radiosensitivity differs in humans and likely among closely-related primates. Reasons for variation in radiosensitivity are not well known. We examined preirradiation gene expression in peripheral blood among male and female rhesus macaques which did or did not survive (up to 60 days) after whole-body irradiation with 700 cGy (LD66/60). RNA samples originated from a blinded randomized Good Laboratory Practice study in 142 irradiated rhesus macaques. Animals were untreated (placebo), or treated using recombinant human IL-12, G-CSF or combination of the two. We evaluated gene expression in a two-phase study design where phase I was a whole genome screen [next generation sequencing (NGS)] for mRNAs (RNA-seq) using five RNA samples from untreated male and female animals per group of survivor and non-survivor (total n = 20). Differential gene expression (DGE) was defined as a statistically significant and ≥2-fold up- or downregulation of mRNA species and was calculated between groups of survivors and non-survivors (reference) and by gender. Altogether 659 genes were identified, but the overlapping number of differentially expressed genes (DGE) observed in both genders was small (n = 36). Fifty-eight candidate mRNAs were chosen for independent validation in phase II using the remaining samples (n = 122) evaluated with qRT-PCR. Among the 58 candidates, 16 were of significance or borderline significance (t test) by DGE. Univariate and multivariate logistic regression analysis and receiver operating characteristic (ROC) curve analysis further refined and identified the most outstanding validated genes and gene combinations. For untreated male macaques, we identified EPX (P = 0.005, ROC=1.0), IGF2BP1 (P = 0.05, ROC=0.74) and the combination of EPX with SLC22A4 (P = 0.03, ROC=0.85) which appeared most predictive for the clinical outcome for treated and combined (untreated and treated) male macaque groups, respectively. For untreated, treated and both combined female macaque groups the same gene (MBOAT4, P = 0.0004, ROC = 0.81) was most predictive. Based on the probability function of the ROC curves, up to 74% of preirradiation RNA measurements predicted survival with a positive and negative predictive value ranging between 85-100% and associated odds ratios reflecting a 2-3-fold elevated risk for surviving per unit change (cycle threshold value) in gene expression. In conclusion, we identified gender-dependent genes and gene combinations in preirradiation blood samples for survival prediction after irradiation in rhesus macaques.

Mathematical model of radiation effects on thrombopoiesis in rhesus macaques and humans.

A mathematical model that describes the effects of acute radiation exposure on thrombopoiesis in primates and humans is presented. Thrombopoiesis is a complex multistage dynamic process with potential differences between species. Due to known differences in cellular radiosensitivities, nadir times, and cytopenia durations, direct extrapolation from rhesus to human platelet dynamics is unrealistic. Developing mathematical models of thrombopoiesis for both humans and primates allows for the comparison of the system's response across species. Thus, data obtained in primate experiments can be extrapolated to predictions in humans. Parameter values for rhesus macaques and humans were obtained either from direct experimental measurements or through optimization procedures using dynamic data on platelet counts following radiation exposure. Model simulations accurately predict trends observed in platelet dynamics: at low radiation doses platelet counts decline after a time lag, and nadir depth is dose dependent. The models were validated using data that was not used during the parameterization process. In particular, additional experimental data was used for rhesus, and accident and platelet donor data was used for humans. The model aims to simulate the average response in rhesus and humans following irradiation. Variation in platelet dynamics due to individual variability can be modeled using Monte Carlo simulations in which parameter values are sampled from distributions. This model provides insight into the time course of the physiological effects of radiation exposure, information which could be valuable for disaster planning and survivability analysis and help in drug development of radiation medical countermeasures.

Personalising docetaxel and G-CSF schedules in cancer patients by a clinically validated computational model.

BACKGROUND: This study was aimed to develop a new method for personalising chemotherapeutic and granulocyte colony-stimulating factor (G-CSF) combined schedules, and use it for suggesting efficacious chemotherapy with reduced neutropenia. METHODS: Clinical data from 38 docetaxel (Doc)-treated metastatic breast cancer patients were employed for validating a new pharmacokinetic/pharmacodynamics model for Doc, combined with a mathematical model for granulopoiesis. An optimisation procedure was constructed and used for selecting improved treatment schedules. RESULTS: The combined model accurately predicted observed nadir timing (r=0.99), grade 3 or 4 neutropenia (86% success) and neutrophil counts over time in individual patients (r=0.63), and showed robustness to CYP3A-induced variability in Doc clearance. For average patients, the predicted optimal support for the standard chemotherapy regimen, Doc 100 µg m(-2) tri-weekly, is G-CSF, 300 µg, Q1D × 3, starting day 7 post-Doc. This regimen largely moderates chemotherapy-induced neutrophil nadir and neutropenia duration. The more intensive Doc dose, 150 mg m(-2), is optimally supported by the slightly less cost-effective G-CSF 300 µg, Q1D × 4, 5 days post-Doc. The latter regimen is optimal for borderline patients (2000 neutrophils per µl) under Doc, 100-150 mg m(-2) tri-weekly. CONCLUSIONS: The new computational method can serve for tailoring efficacious cytotoxic and supportive treatments, minimising side effects to individual patients. Prospective clinical validation is warranted.

The complex effect of granulocyte colony-stimulating factor on human granulopoiesis analyzed by a new physiologically-based mathematical model.

Neutropenia, frequently a side effect of chemo- and radiotherapy, increases susceptibility to microbial infections and is a life-threatening condition. For realistically predicting drug treatment effects on granulopoiesis, we have constructed a new mathematical model of granulopoiesis in the bone marrow and in the peripheral blood, featuring cell cycle phase transition and detailed granulocyte-colony stimulating factor (G-CSF) pharmacokinetics (PK) and pharmacodynamics (PD), including intracellular second messenger. Using this model, in conjunction with clinical results, we evaluated the system parameters, implemented those in the model and successfully retrieved the results of several independent clinical experiments under a wide range of G-CSF regimens. Our results show that the introduction of G-CSF-controlled intracellular second messenger is indispensable for precise retrieval of the clinical results, and suggest that the half-life of this messenger varies between a single and multiple G-CSF administration schedules. In addition, our model provided reliable steady-state, as well as dynamic, estimations of human granulopoiesis parameters. These included an estimation of apoptosis index in the post-mitotic compartment, which corroborates previous results. At present the model is used for suggesting improved drug regimens.

A computer algorithm describing the process of vessel formation and maturation, and its use for predicting the effects of anti-angiogenic and anti-maturation therapy on vascular tumor growth.

We put forward an algorithm describing the three principal interconnected sub-processes that influence tumor and vasculature dynamics: (i) tumor cell proliferation (ii) angiogenesis, that is, the formation and regression of immature vessels (IV), and (iii) maturation, i.e., the formation and destabilization of mature vessels (MV). This algorithm takes account of the crucial quantitative interactions of these sub-processes, occurring across the molecular, cellular and organ levels. Implementing this complex algorithm in a computer model, one can evaluate the correlations between various factors influencing angiogenesis and their influence on tumor progression at any given moment. Moreover, the computer simulations enable analysis of the versatile effects of drugs on the growth and decay of both the tumor and the immature and mature blood vessels, as well as on the induction of an array of relevant growth factors such as angiopoietin-1 (Ang1), angiopoietin-2 (Ang2), vascular endothelial growth factor (VEGF) and platelet-derived growth factor (PDGF). Simulation results suggest that vessel maturation and destabilization of MV drive the otherwise non-linearly growing system into a very dynamic region, having irregular, scale-invariant, fluctuations, around certain asymptotic values of all the involved quantities. Destabilization itself adequately explains the experimentally observed eventual decrease of tumor growth, with no need to implicate additional assumptions, such as a new tumor growth inhibitory, or anti-angiogenic, factors. Our results further suggest that mono-therapy alone can slow tumor growth, but is not capable of eliminating it altogether. In contrast, the combined treatment of anti-angiogenic and anti-maturation drugs causes prolonged suppression of tumor growth and a significant linear decrease in average tumor size. Laboratory experiments are warranted for validating our predictions and for providing in vivo evaluated parameters.