Hierarchical clustering of flow cytometry data for the study of conventional central chondrosarcoma

We have investigated the use of hierarchical clustering of flow cytometry data to classify samples of conventional central chondrosarcoma, a malignant cartilage forming tumor of uncertain cellular origin, according to similarities with surface marker profiles of several known cell types. Human primary chondrosarcoma cells, articular chondrocytes, mesenchymal stem cells, fibroblasts, and a panel of tumor cell lines from chondrocytic or epithelial origin were clustered based on the expression profile of eleven surface markers. For clustering, eight hierarchical clustering algorithms, three distance metrics, as well as several approaches for data preprocessing, including multivariate outlier detection, logarithmic transformation, and z-score normalization, were systematically evaluated. By selecting clustering approaches shown to give reproducible results for cluster recovery of known cell types, primary conventional central chondrosacoma cells could be grouped in two main clusters with distinctive marker expression signatures: one group clustering together with mesenchymal stem cells (CD49b-high/CD10-low/CD221-high) and a second group clustering close to fibroblasts (CD49b-low/CD10-high/CD221-low). Hierarchical clustering also revealed substantial differences between primary conventional central chondrosarcoma cells and established chondrosarcoma cell lines, with the latter not only segregating apart from primary tumor cells and normal tissue cells, but clustering together with cell lines from epithelial lineage. Our study provides a foundation for the use of hierarchical clustering applied to flow cytometry data as a powerful tool to classify samples according to marker expression patterns, which could lead to uncover new cancer subtypes.

Detecting outlying studies in meta-regression models using a forward search algorithm.

When considering data from many trials, it is likely that some of them present a markedly different intervention effect or exert an undue influence on the summary results. We develop a forward search algorithm for identifying outlying and influential studies in meta-analysis models. The forward search algorithm starts by fitting the hypothesized model to a small subset of likely outlier-free studies and proceeds by adding studies into the set one-by-one that are determined to be closest to the fitted model of the existing set. As each study is added to the set, plots of estimated parameters and measures of fit are monitored to identify outliers by sharp changes in the forward plots. We apply the proposed outlier detection method to two real data sets; a meta-analysis of 26 studies that examines the effect of writing-to-learn interventions on academic achievement adjusting for three possible effect modifiers, and a meta-analysis of 70 studies that compares a fluoride toothpaste treatment to placebo for preventing dental caries in children. A simple simulated example is used to illustrate the steps of the proposed methodology, and a small-scale simulation study is conducted to evaluate the performance of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.

[(99m)Tc]Demotate 2 in the detection of sst(2)-positive tumours: a preclinical comparison with [(111)In]DOTA-tate

PURPOSE: The aim of this study was to evaluate [(99m)Tc]Demotate 2 ([(99m)Tc-N(4) (0-1),Asp(0),Tyr(3)]octreotate) as a candidate for in vivo imaging of sst(2)-positive tumours and to compare it with [(111)In]DOTA-tate ([(111)In-DOTA(0),Tyr(3)]octreotate). METHODS: Labelling of Demotate 2 with (99m)Tc was performed at room temperature using SnCl(2) as reductant in the presence of citrate at alkaline pH. Radiochemical analysis involved ITLC and HPLC methods. Peptide conjugate affinities for sst(2) were determined by receptor autoradiography on rat brain cortex sections using [DOTA(0),(125)I-Tyr(3)]octreotate as the radioligand. The affinity profile of Demotate 2 for human sst(1)-sst(5) was studied by receptor autoradiography in cell preparations using the universal somatostatin radioligand [(125)I][Leu(8),(D: )Trp(22),Tyr(25)]somatostatin-28. The internalisation rates of [(99m)Tc]Demotate 2 and [(111)In]DOTA-tate were compared in sst(2)-positive and -negative control cell lines. Biodistribution of radiopeptides was studied in male Lewis rats bearing CA20948 tumours. RESULTS: Peptide conjugates showed selectivity and a high affinity binding for sst(2) (Demotate 2 IC(50)=3.2 nM and DOTA-tate IC(50)=5.4 nM). [(99m)Tc]Demotate 2, like [(111)In]DOTA-tate, internalised rapidly in all sst(2)-positive cells tested, but not in sst(2)-negative control cells. After injection in CA20948 tumour-bearing rats both radiopeptides showed high and specific uptake in the sst(2)-positive organs and in the implanted tumour and rapid excretion from non-target tissues via the kidneys. CONCLUSION: [(99m)Tc]Demotate 2, similarly to the known sst(2)-targeting agent [(111)In]DOTA-tate, showed promising biological qualities for application in the scintigraphy of sst(2)-positive tumours.

Detection of degenerative cartilage disease: comparison of high-resolution morphological MR and quantitative T2 mapping at 3.0 Tesla

The aim of the study was to investigate the association of T2 relaxation times of the knee with early degenerative cartilage changes. Furthermore the impact of unloading the knee on T2 values was evaluated.

Detection of convergent genome-wide signals of adaptation to tropical forests in humans

Tropical forests are believed to be very harsh environments for human life. It is unclear whether human beings would have ever subsisted in those environments without external resources. It is therefore possible that humans have developed recent biological adaptations in response to specific selective pressures to cope with this challenge. To understand such biological adaptations we analyzed genome-wide SNP data under a Bayesian statistics framework, looking for outlier markers with an overly large extent of differentiation between populations living in a tropical forest, as compared to genetically related populations living outside the forest in Africa and the Americas. The most significant positive selection signals were found in genes related to lipid metabolism, the immune system, body development, and RNA Polymerase III transcription initiation. The results are discussed in the light of putative tropical forest selective pressures, namely food scarcity, high prevalence of pathogens, difficulty to move, and inefficient thermoregulation. Agreement between our results and previous studies on the pygmy phenotype, a putative prototype of forest adaptation, were found, suggesting that a few genetic regions previously described as associated with short stature may be evolving under similar positive selection in Africa and the Americas. In general, convergent evolution was less pervasive than local adaptation in one single continent, suggesting that Africans and Amerindians may have followed different routes to adapt to similar environmental selective pressures.