Mathematical Aspects of a New Synergy Theory Applicable to Malstressor-Dominated Mixtures which Include Damage-Ameliorating Countermeasures.

In radiobiology, and throughout translational biology, synergy theories for multi-component agent mixtures use 1-agent dose-effect relations (DERs) to calculate baseline neither synergy nor antagonism mixture DERs. The most used synergy theory, simple effect additivity, is not self-consistent when curvilinear 1-agent DERs are involved, and many alternatives have been suggested. In this paper we present the mathematical aspects of a new alternative, generalized Loewe additivity (GLA). To the best of our knowledge, generalized Loewe additivity is the only synergy theory that can systematically handle mixtures of agents that are malstressors (tend to produce disease) with countermeasures - agents that oppose malstressors and ameliorate malstressor damage. In practice countermeasures are often very important, so generalized Loewe additivity is potentially far-reaching. Our paper is a proof-of-principle preliminary study. Unfortunately, generalized Loewe additivity's scope is restricted, in various unwelcome but perhaps unavoidable ways. Our results illustrate its strengths and its weaknesses. One area where our methodology has potentially important applications is analyzing counter-measure mitigation of galactic cosmic ray damage to astronauts during interplanetary travel.

Hypo-fractionated boost in locally advanced non-small cell lung cancer: temporal distribution of boost fractions.

To propose new schemas for radiation boosting of primary tumors, in locally advanced non-small cell lung cancers (NSCLC), in conjunction with standard chemoradiotherapy. To investigate the effect of temporal distributions of the boost fractions on tumor control. NSCLC cases, previously treated with 60 Gy in 30 fractions, were retrospectively planned by adding a radiation boost (25 Gy in 5 fractions) to the primary tumor. Several integrated and sequential boosting schedules were considered. Biological doses were calculated for targets and organs at risk (OAR). Tumor control probabilities (TCP) were calculated using an empirical model and a stochastic model that accounts more systematically for tumor growth kinetics and cell kill. For heterogeneous patient populations, the TCPs for different boost schedules ranged from 82% to 84% and from 73% to 74% for integrated and sequential boosting respectively. For individual tumors with specific growth parameters, the TCP varied by up to 19% between the different schedules. The TCP for sequential boosting was expected to be up to 67% lower than front integrated boosting. The gap in TCP between schedules was higher for tumors with higher clonogenic cell numbers, lower radio-sensitivity, shorter doubling times and lower cell loss. The proposed boosting schemas are dosimetrically feasible and biologically effective. We suggest that the boosts are most effective when given during the first week of treatment and least effective when given sequentially after the end of treatment. The effect of boost scheduling and the effectiveness of front boosting are expected to be most significant for tumors with high clonogenic cell numbers, fast growing rates, low cell loss and low radio-sensitivity. Ultimately, animal studies and clinical trials, guided by biology modeling as presented in the present work, will be needed to verify the effectiveness of fine tuning temporal distributions of radiotherapy fractions.

Defining AML and MDS second cancer risk dynamics after diagnoses of first cancers treated or not with radiation.

Risks of acute myeloid leukemia (AML) and/or myelodysplastic syndromes (MDS) are known to increase after cancer treatments. Their rise-and-fall dynamics and their associations with radiation have, however, not been fully characterized. To improve risk definition we developed SEERaBomb R software for Surveillance, Epidemiology and End Results second cancer analyses. Resulting high-resolution relative risk (RR) time courses were compared, where possible, to results of A-bomb survivor analyses. We found: (1) persons with prostate cancer receiving radiation therapy have increased RR of AML and MDS that peak in 1.5-2.5 years; (2) persons with non-Hodgkin lymphoma (NHL), lung and breast first cancers have the highest RR for AML and MDS over the next 1-12 years. These increased RR are radiation specific for lung and breast cancer but not for NHL; (3) AML latencies were brief compared to those of A-bomb survivors; and (4) there was a marked excess risk of acute promyelocytic leukemia in persons receiving radiation therapy. Knowing the type of first cancer, if it was treated with radiation, the interval from first cancer diagnosis to developing AML or MDS, and the type of AML, can improve estimates of whether AML or MDS cases developing in this setting are due to background versus other processes.

Radiation-induced cancer: a modern view.

Diagnostic medical radiation has been the most rapidly increasing component of population background radiation exposure in Western countries over the past decade. This trend is set to increase as CT scanning is readily available with burgeoning use in everyday clinical practice. Consequently, the issue of cancer induction from the doses received during diagnostic medical exposures is highly relevant. In this review we explain current understanding of potential cancer induction at low doses of sparsely ionising radiation. For cancers that may be induced at low doses, a mechanistic description of radiation-induced cancer is discussed, which, in combination with extrapolation of data based on population cohort studies, provides the basis of the currently accepted linear no-threshold model. We explore the assumptions made in deriving risk estimates, the controversies surrounding the linear no-threshold model and the potential future challenges facing clinicians and policy-makers with regards to diagnostic medical radiation and cancer risk, most notably the uncertainties regarding deriving risk estimates from epidemiological data at low doses.

A new view of radiation-induced cancer.

Biologically motivated mathematical models are important for understanding the mechanisms of radiation-induced carcinogenesis. Existing models fall into two categories: (1) short-term formalisms, which focus on the processes taking place during and shortly after irradiation (effects of dose, radiation quality, dose rate and fractionation), and (2) long-term formalisms, which track background cancer risks throughout the entire lifetime (effects of age at exposure and time since exposure) but make relatively simplistic assumptions about radiation effects. Grafting long-term mechanisms on to short-term models is badly needed for modelling radiogenic cancer. A combined formalism was developed and applied to cancer risk data in atomic bomb survivors and radiotherapy patients and to background cancer incidence. The data for nine cancer types were described adequately with a set of biologically meaningful parameters for each cancer. These results suggest that the combined short-long-term approach is a potentially promising method for predicting radiogenic cancer risks and interpreting the underlying biological mechanisms.

Quantitative analysis of radiation-induced chromosome aberrations.

We review chromosome aberration modeling and its applications, especially to biodosimetry and to characterizing chromosome geometry. Standard results on aberration formation pathways, randomness, dose-response, proximity effects, transmissibility, kinetics, and relations to other radiobiological endpoints are summarized. We also outline recent work on graph-theoretical descriptions of aberrations, Monte-Carlo computer simulations of aberration spectra, software for quantifying aberration complexity, and systematic links of apparently incomplete with complete or truly incomplete aberrations.

Domestic radon risks may be dominated by bystander effects--but the risks are unlikely to be greater than we thought.

Radon risks derive from exposure of bronchio-epithelial cells to alpha particles. Alpha-particle exposure can result in bystander effects when irradiated cells emit signals resulting in damage to nearby unirradiated bystander cells. Bystander effects can cause downwardly-curving dose-response relations and inverse dose-rate effects. We have extended a quantitative mechanistic model of bystander effects to include protracted exposure, with inverse dose-rate effects attributed to replenishment, during exposure, of a subpopulation of cells which are hypersensitive to bystander signals. In this approach, bystander effects and the inverse dose-rate effect are manifestations of the same basic phenomenon. The model was fitted to dose- and dose-rate dependent radon-exposed miner data; the results suggest that one directly-hit target cell can send bystander signals to about 50 neighboring cells and that, in the case of domestic radon exposures, the risk could be dominated by bystander effects. The analysis concludes that a naive linear extrapolation of radon miner data to low doses, without accounting for dose rate/bystander effects, would result in an underestimation of domestic radon risks by about a factor of approximately 4. However, recent domestic radon risk estimates (BEIR VI) have already applied a phenomenological correction factor of approximately 4 for inverse dose-rate effects, and have thus already implicitly taken into account corrections which we here suggest are due to bystander effects. Thus current domestic radon risk estimates are unlikely to be underestimates as a result of bystander effects.

Do low dose-rate bystander effects influence domestic radon risks?

PURPOSE: Radon risks derive from exposure of bronchio-epithelial cells to high-linear energy transfer (LET) alpha-particles. alpha-particle exposure can result in bystander effects, where irradiated cells emit signals resulting in damage to nearby unirradiated bystander cells. This can result in non-linear dose-response relations, and inverse dose-rate effects. Domestic radon risk estimates are currently extrapolated from miner data, which are at both higher doses and higher dose-rates, so bystander effects on unhit cells could play a large role in the extrapolation of risks from mines to homes. Therefore, we extend an earlier quantitative mechanistic model of bystander effects to include protracted exposure, with the aim of quantifying the significance of the bystander effect for very prolonged exposures. MATERIALS AND METHODS: A model of high-LET bystander effects, originally developed to analyse oncogenic transformation in vitro, is extended to low dose-rates. The model considers radiation response as a superposition of bystander and linear direct e It attributes bystander effects to a small subpopulation of hypersensitive cells, with the bystander contribution dominating the direct contribution at very low acute doses but saturating as the dose increases. Inverse dose-rate effects are attributed to the replenishment of the hypersensitive subpopulation during prolonged irradiation. RESULTS: The model was fitted to dose- and dose-rate-dependent radon-exposed miner data, suggesting that one directly hit target bronchio-epithelial cell can send bystander signals to about 50 neighbouring target cells. The model suggests that a naïve linear extrapolation of radon miner data to low doses, without accounting for dose-rate, would result in an underestimation of domestic radon risks by about a factor of 4, a value comparable with the empirical estimate applied in the recent BEIR-VI report on radon risk estimation. CONCLUSIONS: Bystander effects represent a plausible quantitative and mechanistic explanation of inverse dose-rate effects by high-LET radiation, resulting in non-linear dose-response relations and a complex interplay between the effects of dose and exposure time. The model presented provides a potential mechanistic underpinning for the empirical exposure-time correction factors applied in the recent BEIR-VI for domestic radon risk estimation.

Computer analysis of mFISH chromosome aberration data uncovers an excess of very complicated metaphases.

PURPOSE: To analyse spectra of chromosome aberrations induced in vitro by low LET radiation, in order to characterize radiation damage mechanisms quantitatively. METHODS: Multiplex fluorescence in situ hybridization (mFISH) allows the simultaneous identification of each homologous chromosome pair by its own colour. mFISH data, specifying number distributions for colour junctions in metaphases of human peripheral blood lymphocytes 72 hours after exposure in vitro to a 3 Gy gamma-ray dose, were combined with similar, previously published results. Monte Carlo computer implementations of radiobiological models for chromosome aberration production guided quantitative analyses, which took into account distribution of cells among different metaphases and lethal effects or preferential elimination of some aberrations at cell division. RESULTS AND CONCLUSIONS: Standard models of DNA damage induction/repair/misrepair explain the main trends of the data as regards the fraction of metaphases having a particular number of colours involved in colour junctions. However, all standard models systematically under-predict the observed fraction of metaphases where a large number of different chromosomes participate in aberrations. An early appearance of chromosomal instability could explain most of the discrepancies.

Extrapolation of the dna fragment-size distribution after high-dose irradiation to predict effects at low doses.

The patterns of DSBs induced in the genome are different for sparsely and densely ionizing radiations: In the former case, the patterns are well described by a random-breakage model; in the latter, a more sophisticated tool is needed. We used a Monte Carlo algorithm with a random-walk geometry of chromatin, and a track structure defined by the radial distribution of energy deposition from an incident ion, to fit the PFGE data for fragment-size distribution after high-dose irradiation. These fits determined the unknown parameters of the model, enabling the extrapolation of data for high-dose irradiation to the low doses that are relevant for NASA space radiation research. The randomly-located-clusters formalism was used to speed the simulations. It was shown that only one adjustable parameter, Q, the track efficiency parameter, was necessary to predict DNA fragment sizes for wide ranges of doses. This parameter was determined for a variety of radiations and LETs and was used to predict the DSB patterns at the HPRT locus of the human X chromosome after low-dose irradiation. It was found that high-LET radiation would be more likely than low-LET radiation to induce additional DSBs within the HPRT gene if this gene already contained one DSB.

Prodrugs of 3-amido bearing pseudomycin analogues: novel antifungal agents.

With the aim of identifying safer pseudomycin derivatives, we synthesized and evaluated a number of N-acyloxymethyl carbamate linked prodrugs of 3-amido pseudomycin analogues. To our satisfaction, all of the prodrug-amide combinations prepared exhibited good in vivo efficacy against murine Candidiasis. When evaluated in a dose elevation study, all of the newly synthesized combinations (e.g., 4A, 6A, 8A, and 8B) demonstrated improved toxicity profiles in comparison to their corresponding 3-amides as well as the parent pseudomycin B.

Biologically based risk estimation for radiation-induced CML. Inferences from BCR and ABL geometric distributions.

Chronic myeloid leukemia (CML) invites biologically based radiation risk modeling because CML is simultaneously well-understood, homogeneous and prevalent. CML is known to be caused by a translocation involving the ABL and BCR genes, almost all CML patients have the BCR-ABL translocation, and CML is prevalent enough that its induction is unequivocally detected among Hiroshima A-bomb survivors. In a previous paper, a linear-quadratic-exponential (LQE) dose-response model was used to estimate the lifetime excess risk of CML in the limit of low doses of gamma-rays, R gamma. This estimate assumed that BCR-ABL translocation dose-response curves in stem cells for both neutrons and gamma-rays, differ only by a common proportionality constant from dicentric aberration dose-response curves in lymphocytes. In the present paper we challenge this assumption by predicting the BCR-ABL dose response. The predictions are based on the biophysical theory of dual radiation action (TDRA) as it applies to recent BCR-to-ABL distance data in G0 human lymphocytes; this data shows BCR and ABL geometric distributions that are not uniform and not independent, with close association of the two genes in some cells. The analysis speaks against the previous proportionality assumption. We compute 11 plausible LQE estimates of R gamma, 2 based on the proportionality assumption and 9 based on TDRA predictions. For each estimate of R gamma we also compute an associated estimate of the number of CML target cells, N; the biological basis of the LQE model allows us to form such estimates. Consistency between N and hematological considerations provides a plausibility check of the risk estimates. Within the group of estimates investigated, the most plausible lifetime excess risk estimates tend to lie near R gamma = 0.01 Gy-1, substantially higher than risk estimates based on the proportionality assumption.

Syntheses and antifungal activities of novel 3-amido bearing pseudomycin analogues.

As a result of our core SAR effort, we discovered a large number of 3-amido pseudomycin B (PSB) analogues (e.g., 4e LY448212 and 5b LY448731) that retain good in vitro and in vivo (IP) activities against Candida and Cryptococcus without inherent tail vein irritation. Several dimethylamino termini bearing 3-amides (e.g., 5b) also exhibited improved potency against Aspergillus in vitro. When evaluated in a two-week rat toxicology study, it was found that all animals receiving 4e (up to 75 mg/kg) were found to be normal. On the basis of these observations, we are convinced that it is possible to broaden the antifungal spectrum and improve the safety profile of pseudomycin analogues at the same time.

The bystander effect in radiation oncogenesis: II. A quantitative model.

There is strong evidence that biological response to ionizing radiation has a contribution from unirradiated "bystander" cells that respond to signals emitted by irradiated cells. We discuss here an approach incorporating a radiobiological bystander response, superimposed on a direct response due to direct energy deposition in cell nuclei. A quantitative model based on this approach is described for alpha-particle-induced in vitro oncogenic transformation. The model postulates that the oncogenic bystander response is a binary "all or nothing" phenomenon in a small sensitive subpopulation of cells, and that cells from this sensitive subpopulation are also very sensitive to direct hits from alpha particles, generally resulting in a directly hit sensitive cell being inactivated. The model is applied to recent data on in vitro oncogenic transformation produced by broad-beam or microbeam alpha-particle irradiation. Two parameters are used in analyzing the data for transformation frequency. The analysis suggests that, at least for alpha-particle-induced oncogenic transformation, bystander effects are important only at small doses-here below about 0.2 Gy. At still lower doses, bystander effects may dominate the overall response, possibly leading to an underestimation of low-dose risks extrapolated from intermediate doses, where direct effects dominate.

8-Amido-Bearing pseudomycin B (PSB) analogue: novel antifungal agents.

During the course of a structure-activity relationship (SAR) study on novel depsinonapeptide pseudomycin B, we synthesized a total of 12 8-amidopseudomycin analogues via standard two-step sequence from either ZPSB 2 or AllocPSB 3. A number of these amides exhibited good in vitro antifungal activities.

The synthesis of pseudomycin C' via a novel acid promoted side-chain deacylation of pseudomycin A.

The gamma hydroxyl present in the aliphatic side chain of the natural products pseudomycin A and C' provided a unique handle for the pH dependent side-chain deacylation. Low pH reaction conditions were used to cleave the side chain with minimal degradation of the peptide core. The pseudomycin nucleus intermediate obtained from the deacylation of pseudomycin A was pivotal in the synthesis of novel side-chain analogues. A practical synthesis of a minor fermentation factor pseudomycin C' and related analogues is reported.

Monte Carlo predictions of DNA fragment-size distributions for large sizes after HZE particle irradiation.

DSBs (double-strand breaks) produced by densely ionizing space radiation are not located randomly in the genome: recent data indicate DSB clustering along chromosomes. DSB clustering at large scales, from >100 Mbp down to approximately 2 kbp, is modeled using a Monte-Carlo algorithm. A random-walk model of chromatin is combined with a track model, that predicts the radial distribution of energy from an ion, and the RLC (randomly-located-clusters) formalism, in software called DNAbreak. This model generalizes the random-breakage model, whose broken-stick fragment-size distribution is applicable to low-LET radiation. DSB induction due to track interaction with the DNA volume depends on the radiation quality parameter Q. This dose-independent parameter depends only weakly on LET. Multi-track, high-dose effects depend on the cluster intensity parameter lambda, proportional to fluence as defined by the RLC formalism. After lambda is determined by a numerical experiment, the model reduces to one adjustable parameter Q. The best numerical fits to the experimental data, determining Q, are obtained. The knowledge of lambda and Q allows us to give biophysically based extrapolations of high-dose DNA fragment-size data to low doses or to high LETs.

On target cell numbers in radiation-induced H4-RET mediated papillary thyroid cancer.

Radiation-induced human papillary thyroid cancer (PTC) is associated with chromosomal inversions that involve the genetic loci H4 and RET on chromosome 10. Recently, experimental data has shown that these loci lie in very close spatial proximity in a high proportion of adult human thyroid cells. Applying the generalized formulation of dual radiation action to this H4-to-RET geometric distance data, we predict here the radiation dose-response of H4-RET induction. The predicted H4-RET dose-response has a linear-to-quadratic transition dose of approximately 7 Gy, suggesting the validity of linear risk extrapolations to very low doses for H4-RET mediated radiation-induced PTC. In conjunction with A-bomb survivor data, the predicted H4-RET dose-response yields estimates of the number of PTC target cells that are of the order of approximately 10(6) to approximately 10(7) cells, i.e. considerably less than the total number of follicular cells in the thyroid gland.

Radiation breakage of DNA: a model based on random-walk chromatin structure.

Monte Carlo computer software, called DNAbreak, has recently been developed to analyze observed non-random clustering of DNA double strand breaks in chromatin after exposure to densely ionizing radiation. The software models coarse-grained configurations of chromatin and radiation tracks, small-scale details being suppressed in order to obtain statistical results for larger scales, up to the size of a whole chromosome. We here give an analytic counterpart of the numerical model, useful for benchmarks, for elucidating the numerical results, for analyzing the assumptions of a more general but less mechanistic "randomly-located-clusters" formalism, and, potentially, for speeding up the calculations. The equations characterize multi-track DNA fragment-size distributions in terms of one-track action; an important step in extrapolating high-dose laboratory results to the much lower doses of main interest in environmental or occupational risk estimation. The approach can utilize the experimental information on DNA fragment-size distributions to draw inferences about large-scale chromatin geometry during cell-cycle interphase.

A polymer, random walk model for the size-distribution of large DNA fragments after high linear energy transfer radiation.

DNA double-strand breaks (DSBs) produced by densely ionizing radiation are not located randomly in the genome: recent data indicate DSB clustering along chromosomes. Stochastic DSB clustering at large scales, from > 100 Mbp down to < 0.01 Mbp, is modeled using computer simulations and analytic equations. A random-walk, coarse-grained polymer model for chromatin is combined with a simple track structure model in Monte Carlo software called DNAbreak and is applied to data on alpha-particle irradiation of V-79 cells. The chromatin model neglects molecular details but systematically incorporates an increase in average spatial separation between two DNA loci as the number of base-pairs between the loci increases. Fragment-size distributions obtained using DNAbreak match data on large fragments about as well as distributions previously obtained with a less mechanistic approach. Dose-response relations, linear at small doses of high linear energy transfer (LET) radiation, are obtained. They are found to be non-linear when the dose becomes so large that there is a significant probability of overlapping or close juxtaposition, along one chromosome, for different DSB clusters from different tracks. The non-linearity is more evident for large fragments than for small. The DNAbreak results furnish an example of the RLC (randomly located clusters) analytic formalism, which generalizes the broken-stick fragment-size distribution of the random-breakage model that is often applied to low-LET data.