Borrowing strength with nonexchangeable priors over subpopulations.

We introduce a nonparametric Bayesian model for a phase II clinical trial with patients presenting different subtypes of the disease under study. The objective is to estimate the success probability of an experimental therapy for each subtype. We consider the case when small sample sizes require extensive borrowing of information across subtypes, but the subtypes are not a priori exchangeable. The lack of a priori exchangeability hinders the straightforward use of traditional hierarchical models to implement borrowing of strength across disease subtypes. We introduce instead a random partition model for the set of disease subtypes. This is a variation of the product partition model that allows us to model a nonexchangeable prior structure. Like a hierarchical model, the proposed clustering approach considers all observations, across all disease subtypes, to estimate individual success probabilities. But in contrast to standard hierarchical models, the model considers disease subtypes a priori nonexchangeable. This implies that when assessing the success probability for a particular type our model borrows more information from the outcome of the patients sharing the same prognosis than from the others. Our data arise from a phase II clinical trial of patients with sarcoma, a rare type of cancer affecting connective or supportive tissues and soft tissue (e.g., cartilage and fat). Each patient presents one subtype of the disease and subtypes are grouped by good, intermediate, and poor prognosis. The prior model should respect the varying prognosis across disease subtypes. The practical motivation for the proposed approach is that the number of accrued patients within each disease subtype is small. Thus it is not possible to carry out a clinical study of possible new therapies for rare conditions, because it would be impossible to plan for sufficiently large sample size to achieve the desired power. We carry out a simulation study to compare the proposed model with a model that assumes similar success probabilities for all subtypes with the same prognosis, i.e., a fixed partition of subtypes by prognosis. When the assumption is satisfied the two models perform comparably. But the proposed model outperforms the competing model when the assumption is incorrect.

Changes in serum concentrations of soluble vascular endothelial growth factor receptor-1 after pregnancy.

BACKGROUND: Vascular endothelial growth factor (VEGF) is the most potent stimulator of angiogenesis. It mediates its activity through two membrane-bound receptors, VEGFR-1 and VEGFR-2, both expressed in the placenta. Beginning in early pregnancy, the soluble form of the first, sVEGFR-1, binds and inhibits most of the biological actions of circulating VEGF. After delivery, it disappears from the maternal circulation. METHODS: We determined the biological elimination rate of endogenous sVEGFR-1 after term pregnancy in serial venous samples obtained during and after elective Caesarean sections (n=8), and we demonstrated the relationship between serum sVEGFR-1 and VEGF after mid-trimester legal termination of pregnancy (n = 5), by analysing their concentrations using immunoassays (ELISA). RESULTS: The disappearance of sVEGFR-1 from circulation after Caesarean delivery was biphasic with a rapid half-life of 3.4 h (2.2-7.5 h; median, range) and a slow one of 29 h (17-94 h). After mid-trimester legal termination of pregnancy the sVEGFR-1 concentrations decreased and those of free VEGF simultaneously increased with a highly significant negative correlation with each other (r = -0.90, P < 0.0001). CONCLUSIONS: The disappearance of endogenous sVEGFR-1 after pregnancy is biphasic, and it is associated with a simultaneous increase in free VEGF concentrations.

A novel cytokine receptor-ligand pair. Identification, molecular characterization, and in vivo immunomodulatory activity.

As part of a large scale effort to discover novel secreted proteins, a cDNA encoding a novel cytokine was identified. Alignments of the sequence of the new protein, designated IL-17B, suggest it to be a homolog of the recently described T cell-derived cytokine, IL-17. By Northern analysis, EST distribution and real-time quantitative polymerase chain reaction analysis, mRNA was detected in many cell types. A novel type I transmembrane protein, identified in an EST data base by homology to IL-17R, was found to bind specifically IL-17B, as determined by surface plasmon resonance analysis, flow cytometry, and co-immunoprecipitation experiments. Readily detectable transcription of IL-17BR was restricted to human kidney, pancreas, liver, brain, and intestines and only a few of the many cell lines tested. By using a rodent ortholog of IL-17BR as a probe, IL-17BR message was found to be drastically up-regulated during intestinal inflammation elicited by indomethacin treatment in rats. In addition, intraperitoneal injection of IL-17B purified from Chinese hamster ovary cells caused marked neutrophil migration in normal mice, in a specific and dose-dependent manner. Together these results suggest that IL-17B may be a novel proinflammatory cytokine acting on a restricted set of target cell types. They also demonstrate the strength of genomic approaches in the unraveling of novel biological pathways.