Feasibility of Targeting Glioblastoma Stem Cells: From Concept to Clinical Trials
Objective: Glioblastoma is a highly aggressive and invasive brain and Central Nervous System (CNS) tumor. Current treatment options do not prolong overall survival significantly because the disease is highly prone to relapse. Therefore, research to find new therapies is of paramount importance. It has been discovered that glioblastomas contain a population of cells with stem-like properties and that these cells are may be responsible for tumor recurrence.
Methods: A review of relevant papers and clinical trials in the field was conducted. A PubMed search with related keywords was used to gather the data. For example, “glioblastoma stem cells AND WNT signaling” is an example used to find information on clinical trials using the database ClinicalTrials.gov.
Results: Cancer stem cell research has several fundamental issues and uncertainties that should be taken into consideration. Theoretically, a number of treatment options that target glioblastoma stem cells are available for patients. However, only a few of them have obtained promising results in clinical trials. Several strategies are still under investigation.
Conclusion: The majority of treatments to target cancer stem cells have failed during clinical trials. Taking into account a number of biases in the field and the number of unsuccessful investigations, the application of the cancer stem cells concept is questionable in clinical settings, at least with respect to glioblastoma.
Materials of the all-Russian scientific-practical conference with international participation
Mechanical performances of titanium biomedical implants manufactured by superplastic forming are strongly related to the process parameters: the thickness distribution along the formed sheet has a key role in the evaluation of post-forming characteristics of the prosthesis. In this work, a finite element model able to reliably predict the thickness distribution after the superplastic forming operation was developed and validated in a case study. The material model was built for the investigated titanium alloy (Ti6Al4V-ELI) upon results achieved through free inflation tests in different pressure regimes. Thus, a strain and strain rate dependent material behaviour was implemented in the numerical model. It was found that, especially for relatively low strain rates, the strain rate sensitivity index of the investigated titanium alloy significantly decreases during the deformation process. Results on the case study highlighted that the strain rate has a strong influence on the thickness profile, both on its minimum value and on the position in which such a minimum is found.
Data management and analysis is one of the fastest growing and most challenging areas of research and development in both academia and industry. Numerous types of applications and services have been studied and re-examined in this field resulting in this edited volume which includes chapters on effective approaches for dealing with the inherent complexity within data management and analysis. This edited volume contains practical case studies, and will appeal to students, researchers and professionals working in data management and analysis in the business, education, healthcare, and bioinformatics areas.
Background: Chromosomal rearrangements are the typical phenomena in cancer genomes causing gene disruptions and fusions, corruption of regulatory elements, damage to chromosome integrity. Among the factors contributing to genomic instability are non-B DNA structures with stem-loops and quadruplexes being the most prevalent. We aimed at investigating the impact of specifically these two classes of non-B DNA structures on cancer breakpoint hotspots using machine learning approach.
Methods: We developed procedure for machine learning model building and evaluation as the considered data are extremely imbalanced and it was required to get a reliable estimate of the prediction power. We built logistic regression models predicting cancer breakpoint hotspots based on the densities of stem-loops and quadruplexes, jointly and separately. We also tested Random Forest models varying different resampling schemes (leave-one-out cross validation, train-test split, 3-fold cross-validation) and class balancing techniques (oversampling, stratification, synthetic minority oversampling).
Results: We performed analysis of 487,425 breakpoints from 2234 samples covering 10 cancer types available from the International Cancer Genome Consortium. We showed that distribution of breakpoint hotspots in different types of cancer are not correlated, confirming the heterogeneous nature of cancer. It appeared that stem-loop- based model best explains the blood, brain, liver, and prostate cancer breakpoint hotspot profiles while quadruplex- based model has higher performance for the bone, breast, ovary, pancreatic, and skin cancer. For the overall cancer profile and uterus cancer the joint model shows the highest performance. For particular datasets the constructed models reach high predictive power using just one predictor, and in the majority of the cases, the model built on both predictors does not increase the model performance.
Conclusion: Despite the heterogeneity in breakpoint hotspots’ distribution across different cancer types, our results demonstrate an association between cancer breakpoint hotspots and stem-loops and quadruplexes. Approximately for half of the cancer types stem-loops are the most influential factors while for the others these are quadruplexes. This fact reflects the differences in regulatory potential of stem-loops and quadruplexes at the tissue-specific level, which yet to be discovered at the genome-wide scale. The performed analysis demonstrates that influence of stem- loops and quadruplexes on breakpoint hotspots formation is tissue-specific.
Given many developing economies depend on primary commodities, the fluctuations of commodity prices may imply significant effects for the wellbeing of children. To investigate, this paper examines the relationship between child mortality and commodity price movements as reflected by country-specific commodity terms-of-trade. Employing a panel of 69 low and lower-middle income countries over the period 1970-2010, we show that commodity terms-of-trade volatility increases child mortality in highly commodity-dependent importers suggesting a type of ‘scarce’ resource curse. Strikingly however, good institutions appear able to mitigate the negative impact of volatility. The paper concludes by highlighting this tripartite relationship between child mortality, volatility and good institutions and posits that an effective approach to improving child wellbeing in low to lower-middle income countries will combine hedging, import diversification and improvement of institutional quality.
This volume presents new results in the study and optimization of information transmission models in telecommunication networks using different approaches, mainly based on theiries of queueing systems and queueing networks .
The paper provides a number of proposed draft operational guidelines for technology measurement and includes a number of tentative technology definitions to be used for statistical purposes, principles for identification and classification of potentially growing technology areas, suggestions on the survey strategies and indicators. These are the key components of an internationally harmonized framework for collecting and interpreting technology data that would need to be further developed through a broader consultation process. A summary of definitions of technology already available in OECD manuals and the stocktaking results are provided in the Annex section.