Platelets increase survival of adenocarcinoma cells challenged with anticancer drugs: mechanisms and implications for chemoresistance.

BACKGROUND AND PURPOSE: Cancer cells grow without the restraints of feedback control mechanisms, leading to increased cancer cell survival. The treatment of cancer is often complicated by the lack of response to chemotherapy leading to chemoresistance and persistent survival of tumour cells. In this work we studied the role of platelets in chemotherapy-induced cancer cell death and survival. EXPERIMENTAL APPROACH: Human adenocarcinoma cells, colonic (Caco-2) and ovarian (59 M) cells, were incubated with 5-fluorouracil (1-300 µg·mL(-1) ) or paclitaxel (1-200 µg·mL(-1) ) in the presence or absence of platelets (1.5 × 10(8) mL(-1) ) for 1, 24 or 72 h. Following incubation, cancer cells were harvested and cell survival/death was assayed using flow cytometry, Western blotting, real-time PCR, TaqMan® Gene Expression Assays and proteomics. KEY RESULTS: Human platelets increased the survival of colonic and ovarian adenocarcinoma cells treated with two standard anticancer drugs, 5-fluorouracil and paclitaxel. In the presence of platelets, cancer cells up-regulated anti-apoptotic and down-regulated pro-apoptotic genes, increased the number of cells in the synthesis of DNA and decreased the number in the quiescent phase, increased expression of cyclins, DNA repair proteins and MAPKs. The analysis of platelet-Caco-2 secretome demonstrated the release of the chemokine RANTES, thrombospondin-1, TGF-ß and clusterin. Finally, human recombinant RANTES and thrombospondin-1 improved survival of Caco-2 cells challenged with paclitaxel. CONCLUSIONS AND IMPLICATIONS: These data demonstrate that platelets increase adenocarcinoma cells survival, proliferation and chemoresistance to standard anticancer drugs. Modulating cancer cell-platelet interactions may offer a new strategy to improve the efficacy of chemotherapy.

A Markov chain Monte Carlo method for estimating population mixing using Y-chromosome markers: mixing of the Han people in China.

We present a new approach for estimating mixing between populations based on non-recombining markers, specifically Y-chromosome microsatellites. A Markov chain Monte Carlo (MCMC) Bayesian statistical approach is used to calculate the posterior probability distribution of population parameters of interest, including the effective population size and the time to most recent common ancestor (MRCA). To test whether two populations are homogeneously mixed we introduce a "mixing" statistic defined for each coalescent event that weights the contribution of that ancestor's descendants to the two subpopulations, and an associated population "purity" statistic. Using simulated data with low levels of migration between two populations, we demonstrate that our method is more sensitive than other commonly used distance-based methods such as R(ST) and D(SW). To illustrate our method, we analysed mixing between 11 pre-defined Chinese ethnic/regional populations, using 5 microsatellite markers from the non-recombining region of the Y-chromosome (NRY), demonstrating a significant clustering of a subset of subpopulations with a high mutual relative degree of mixing (homogeneous mixing with support >0.99). Our analysis suggests that there is a strong correlation between effective population size and mixing with other subpopulations. Thus, despite considerable mixing between these groups, the purity statistic still identifies significant heterogeneity, suggesting that periods of historical isolation continue to leave a recoverable signal despite modern introgression.

Bayesian phylogenetics using an RNA substitution model applied to early mammalian evolution.

We study the phylogeny of the placental mammals using molecular data from all mitochondrial tRNAs and rRNAs of 54 species. We use probabilistic substitution models specific to evolution in base paired regions of RNA. A number of these models have been implemented in a new phylogenetic inference software package for carrying out maximum likelihood and Bayesian phylogenetic inferences. We describe our Bayesian phylogenetic method which uses a Markov chain Monte Carlo algorithm to provide samples from the posterior distribution of tree topologies. Our results show support for four primary mammalian clades, in agreement with recent studies of much larger data sets mainly comprising nuclear DNA. We discuss some issues arising when using Bayesian techniques on RNA sequence data.

Biokinetics and dosimetry of titanium tritide particles in the lung.

Doses of internal radiation from inhalation of metal tritide aerosols are potentially a major radiation protection problem encountered by nuclear industry workers. Based on results of experiments with rats intratracheally instilled with titanium tritide particles and on a self-absorption factor of beta particles determined by a numerical method, a biokinetic model was developed for inhaled particles of titanium tritide. Results showed that lung burdens of the tritide are well represented by a two-component exponential equation; biological half-lives derived for the retention of 3H in lung were 0.81 d and 66 d. The tritium clearance rate via urine or feces was described by bi-phase exponential components. At 121 d after instillation, 82% of the initial lung burden of 3H had been eliminated, of which 37% was excreted in urine, 29% via feces, and 16% through exhaled air. Based on simulation results of the biokinetic model, the cumulative absorbed dose and committed effective dose were calculated as well as the annual limit of intake (ALI) and derived air concentration (DAC). The ALI and DAC values for titanium tritide were a factor of 5 lower than values for tritiated water. This information will be useful in developing new guidelines for radiation protection purposes.

Performance assessment in support of the 1996 compliance certification application for the Waste Isolation Pilot Plant.

The conceptual and computational structure of a performance assessment (PA) for the Waste Isolation Pilot Plant (WIPP) is described. Important parts of this structure are (1) maintenance of a separation between stochastic (i.e., aleatory) and subjective (i.e., epistemic) uncertainty, with stochastic uncertainty arising from the many possible disruptions that could occur over the 10,000-year regulatory period that applies to the WIPP, and subjective uncertainty arising from the imprecision with which many of the quantities required in the analysis are known, (2) use of Latin hypercube sampling to incorporate the effects of subjective uncertainty, (3) use of Monte Carlo (i.e., random) sampling to incorporate the effects of stochastic uncertainty, and (4) efficient use of the necessarily limited number of mechanistic calculations that can be performed to support the analysis. The WIPP is under development by the U.S. Department of Energy (DOE) for the geologic (i.e., deep underground) disposal of transuranic (TRU) waste, with the indicated PA supporting a Compliance Certification Application (CCA) by the DOE to the U.S. Environmental Protection Agency (EPA) in October 1996 for the necessary certifications for the WIPP to begin operation. The EPA certified the WIPP for the disposal of TRU waste in May 1998, with the result that the WIPP will be the first operational facility in the United States for the geologic disposal of radioactive waste.

Dissolution of metal tritides in a simulated lung fluid.

Metal tritides including titanium tritide (Ti 3Hx) and erbium tritide (Er 3Hx) have been used as components of neutron generators. The current understanding of metal tritides and their radiation dosimetry for internal exposure is very limited, and the ICRP Publication 30 does not provide for tritium dosimetry in metal tritide form. However, a few papers in the literature suggest that the solubility of metal tritides could be low. The current radiation protection guidelines for metal tritide particles are based on the assumption that their biological behavior is similar to tritiated water, which could be easily absorbed into body fluid. Therefore, these particles could have relatively short biological half-lives (10 d). If the solubility is low, the biological half-life of metal tritide particles and the dosimetry of an inhalation exposure to these particles could be quite different from tritiated water. This paper describes experiments on the dissolution rate of titanium tritide particles in a simulated lung fluid. Titanium tritide particles with mean sizes of 103 microm (coarse) and 0.95 microm (fine) were used. The results showed that the coarse particles dissolved much more slowly than the fine particles. The long-term dissolution half times were 361 and 33 d for the coarse and fine particles, respectively. Dissolution data of the fine particles were consistent with the diffusion theory. The dissolution half times were longer than the 10-d biological half time for tritiated water in the body. This finding has significant implications for the current health protection guidelines, including annual limits of intakes and derived air concentrations.