Stanimir Vuk-Pavlović

Immunosuppressive CD14+HLA-DRlow/− Monocytes in Prostate Cancer

To determine if the levels of circulating myeloid‐derived suppressor cells increase with progression of prostate cancer (PCa); to determine if such cells could contribute to the relative inefficiency of PCa immunotherapy.

Dexamethasone inhibits dendritic cell maturation by redirecting differentiation of a subset of cells

To investigate how corticosteroids affect differentiation of human dendritic cells (DC) in a defined inflammatory environment, we incubated immature DC with dexamethasone in the presence of tumor necrosis factor α (TNF‐α), interleukin‐1β (IL‐1β), and prostaglandin E2. Dexamethasone inhibited differentiation into mature DC, as indicated by the reduced expression of antigen‐presenting molecules, costimulatory and adhesion molecules, a marker of mature DC, and IL‐12. Dexamethasone increased expression of CD14, CD36, and CD68, molecules characteristic of monocytes/macrophages and induced CD14+CD83− cells, a subset distinct both from immature DC and mature DC. The effects were concentration‐dependent, with ID50 values between 2 and 30 nM dexamethasone. Unlike T and B cells, in DC dexamethasone induced no apoptosis, although it suppressed activated nuclear transcription factor NF‐κB. Dexamethasone reduced the ability of DC to stimulate proliferation of allogeneic T cells in proportion to the level of CD14+CD83− cells in the population. CD83+ cells, isolated from dexamethasone‐treated populations, retained the synthesis of IL‐12 and the ability to stimulate proliferation of allogeneic T cells. Our data demonstrate that the dominant effect of the drug was redirecting differentiation of a subset of cells despite the presence of inflammatory cytokines. The observed ID50 values indicate that inhibition of DC differentiation might contribute significantly to in vivo immunosuppression by chronic administration of corticosteroids. J. Leukoc. Biol. 66: 909–914; 1999.

Cyclooxygenase-independent inhibition of dendritic cell maturation by aspirin

When immature human myeloid dendritic cells were differentiated in vitro in the presence of aspirin, they were unable to stimulate T‐cell proliferation. Aspirin and its major metabolite salicylate changed the surface marker phenotype of dendritic cells. The drugs particularly suppressed the levels of CD83 and the secreted p40 unit of interleukin‐12 (IL‐12), both markers of mature dendritic cells; 50% inhibitory concentration (IC50) values were 2·5 m m, a concentration more than 100 times greater than the concentration at mid‐point inhibition (ID50) value for inhibition of prostaglandin synthesis. Concomitantly, the levels of CD14, a marker of monocytes/macrophages, increased above the levels found in immature dendritic cells. Cyclooxygenase inhibitors ketoprofen, indomethacin and NS‐398 had no effect at concentrations more than a thousand‐fold higher than their IC50 values. The effects were independent of the presence of prostaglandin E2 in the medium. Salicylates suppressed activation of the nuclear transcription factor κB, which regulates dendritic cell differentiation, but their effects on mature dendritic cells were negligible. Hence, aspirin inhibits dendritic cell function by inhibiting their terminal differentiation at concentrations achieved in the blood of patients chronically treated with high‐dose aspirin.

Tumor growth in vivo and as multicellular spheroids compared by mathematical models

In vivo volume growth of two murine tumor cell lines was compared by mathematical modeling to their volume growth as multicellular spheroids. Fourteen deterministic mathematical models were studied. For one cell line, spheroid growth could be described by a model simpler than needed for description of growthin vivo. A model that explicitly included the stimulatory role for cell-cell interactions in regulation of growth was always superior to a model that did not include such a role. The von Bertalanffy model and the logistic model could not fit the data; this result contradicted some previous literature and was found to depend on the applied least squares fitting method. By the use of a particularly designed mathematical method, qualitative differences were discriminated from quantitative differences in growth dynamics of the same cells cultivated in two different three-dimensional systems.

A novel source of viable peripheral blood mononuclear cells from leukoreduction system chambers.

BACKGROUND: Buffy coats are becoming less available as a source of research‐grade peripheral blood mononuclear cells (PBMNCs). Therefore, alternative sources of these cells were investigated.

Predicting outcomes of prostate cancer immunotherapy by personalized mathematical models.

Background Therapeutic vaccination against disseminated prostate cancer (PCa) is partially effective in some PCa patients. We hypothesized that the efficacy of treatment will be enhanced by individualized vaccination regimens tailored by simple mathematical models. Methodology/Principal Findings We developed a general mathematical model encompassing the basic interactions of a vaccine, immune system and PCa cells, and validated it by the results of a clinical trial testing an allogeneic PCa whole-cell vaccine. For model validation in the absence of any other pertinent marker, we used the clinically measured changes in prostate-specific antigen (PSA) levels as a correlate of tumor burden. Up to 26 PSA levels measured per patient were divided into each patients training set and his validation set. The training set, used for model personalization, contained the patients initial sequence of PSA levels; the validation set contained his subsequent PSA data points. Personalized models were simulated to predict changes in tumor burden and PSA levels and predictions were compared to the validation set. The model accurately predicted PSA levels over the entire measured period in 12 of the 15 vaccination-responsive patients (the coefficient of determination between the predicted and observed PSA values was R 2 = 0.972). The model could not account for the inconsistent changes in PSA levels in 3 of the 15 responsive patients at the end of treatment. Each validated personalized model was simulated under many hypothetical immunotherapy protocols to suggest alternative vaccination regimens. Personalized regimens predicted to enhance the effects of therapy differed among the patients. Conclusions/Significance Using a few initial measurements, we constructed robust patient-specific models of PCa immunotherapy, which were retrospectively validated by clinical trial results. Our results emphasize the potential value and feasibility of individualized model-suggested immunotherapy protocols.

Optimizing Preparation of Normal Dendritic Cells and bcr-abl+ Mature Dendritic Cells Derived from Immunomagnetically Purified CD14+ Cells

The goal of this work was to optimize dendritic cell (DC) preparations obtained from patients suffering from chronic myeloid leukemia (CML) and compare them with DC prepared from normal CD14+ mononuclear cells (MNC). We studied normal DC and bcr-abl+ leukemic DC (CML-DC) yields, expression of membrane molecules, differentiation status, and ability to stimulate T cells. We isolated DC precursors from PBMC by CD14-specific immunoadsorption and cultured them for 7 days in GM-CSF and IL-4, followed by a 3-day incubation to fully differentiate the cells. We evaluated cultures of CML-DC using RPMI 1640 medium supplemented with FBS and X-VIVO 15 medium containing human AB serum. In contrast to cells matured in RPMI 1640, virtually all cells incubated in X-VIVO 15 expressed CD83, a marker of mature DC. CML-DC and normal DC were indistinguishable in expression of CD83, resulting in the highest percentage reported so far. The yields of normal DC and CML-DC from CD14+ cells were indistinguishable. The percentage of bcr-abl+ cells in PBMC varied among patients between 65% and 97% and the final CML-DC preparations were >98% bcr-abl+ the highest purity of bcr-abl+ cells to date. Normal DC and CML-DC were equally effective in stimulating proliferation of allogeneic and autologous T cells. These techniques provide highly enriched, mature, functional CML-DC.

Mathematical Modeling of Tumor Growth Kinetics

The overall goal of this survey is to develop and present a coherent and integrated interpretation of mathematical models which describe tumor growth. Rigorous description and quantitative understanding of tumor growth kinetics have been a focus of mathematical modelers for more than five decades. Consequently, many models have been proposed, ranging from conceptually and mathematically simple empirical models to complex “functional” models which include kinetics of the cell cycle, cell-cell interactions, cell age distribution, microenvironmental factors, etc. However, these models have been seldom validated against experimental tumor growth curves, largely because of the relative scarcity of appropriate data. On the other hand, contemporary experimental techniques increase the prospects for obtaining high quality data. With this in mind, we summarize the pertinent deterministic models of tumor growth kinetics with special emphasis on model scrutiny against experimental data. Prominent among these models is the Gompertz model which has been remarkably successful in description of growth curves for various tumors. The biological interpretation of this model, originally developed as an actuarial curve, remains unclear and we summarize the relevant interpretations of this model. Also, we discuss two other similarly simple models, the logistic model and the von Bertalanffy model, and then present models of increasing complexity which include elements of the cell cycle and cell-cell interactions. Within the typical kinetic paradigm, these models are based on systems of ordinary differential equations. However, we also consider models defined by partial differential equations which involve age and time.

Dendritic cell microvilli: a novel membrane structure associated with the multifocal synapse and T-cell clustering

Polarizing effects of productive dendritic cell (DC)-T-cell interactions on DC cytoskeleton have been known in some detail, but the effects on DC membrane have been studied to a lesser extent. We found that T-cell incubation led to DC elongation and segregation of characteristic DC veils to the broader pole of the cell. On the opposite DC pole, we observed a novel membrane feature in the form of bundled microvilli. Each villus was approximately 100 nm in diameter and 600 to 1200 nm long. Microvilli exhibited high density of antigen-presenting molecules and costimulatory molecules and provided the physical basis for the multifocal immune synapse we observed during human DC and T-cell interactions. T cells preferentially bound to this site in clusters often contained both CD4(+) and CD8(+) T cells.

Mathematical Modeling in Immunotherapy of Cancer: Personalizing Clinical Trials

Despite the massive resources currently invested in medical research and development, the rate of entry of new drugs into the market is decreasing. The present system of clinical trials may put too many hurdles in the way of drug development—particularly those targeting cancer, for which the prevalent format of clinical trials was developed long ago mostly to test small molecules. Although the format has been adapted to some protein therapeutics, it is clearly inadequate for the recent, more complex biological treatments. Hence, for these new approaches to help patients, clinical trials must become more innovative and substantially streamlined. This concern has brought up the idea of information technology–mediated trials (“e-trials”) that could broaden the patient base.1 Another idea is that of virtual research and development, using computer simulations of the human body intended to replace the laborious efficacy testing in real humans and reduce the likelihood of drug failure.2