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.
Introduction: Reliable preoperative identification of patients at high risk for early postoperative complications occurring within 24 h (EPC) of intracranial tumor surgery can improve patient safety and postoperative management. Statistical analysis using machine learning algorithms may generate models that predict EPC better than conventional statistical methods.
Objective: To train such a model and to assess its predictive ability.
Methods: This cohort study included patients from an ongoing prospective patient registry at a single tertiary care center with an intracranial tumor that underwent elective neurosurgery between June 2015 and May 2017. EPC were categorized based on the Clavien-Dindo classification score. Conventional statistical methods and different machine learning algorithms were used to predict EPC using preoperatively available patient, clinical, and surgery-related variables. The performance of each model was derived from examining classification performance metrics on an out-of-sample test dataset.
Results: EPC occurred in 174 (26%) of 668 patients included in the analysis. Gradient boosting machine learning algorithms provided the model best predicting the probability of an EPC. The model scored an accuracy of 0.70 (confidence interval [CI] 0.59-0.79) with an area under the curve (AUC) of 0.73 and a sensitivity and specificity of 0.80 (CI 0.58-0.91) and 0.67 (CI 0.53-0.77) on the test set. The conventional statistical model showed inferior predictive power (test set: accuracy: 0.59 (CI 0.47-0.71); AUC: 0.64; sensitivity: 0.76 (CI 0.64-0.85); specificity: 0.53 (CI 0.41-0.64)).
Conclusion: Using gradient boosting machine learning algorithms, it was possible to create a prediction model superior to conventional statistical methods. While conventional statistical methods favor patients' characteristics, we found the pathology and surgery-related (histology, anatomical localization, surgical access) variables to be better predictors of EPC.
Materials of the all-Russian scientific-practical conference with international participation
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.
Little is known about the burden of common mental disorders in Russia despite high levels of suicide and alcohol-related mortality. Here we investigated levels of symptoms, self-reports of ever having received a diagnosis and treatment of anxiety and depression in two Russian cities.
The study population was men and women aged 35–69 years old participating in cross-sectional population-based studies in the cities of Arkhangelsk and Novosibirsk (2015–18). Participants completed an interview which included the PHQ-9 and GAD-7 scales, questions on whether participants had ever received a diagnosis of depression or anxiety, and health service use in the past year. Participants also reported current medication use and medications were coded in line with the WHO anatomical therapeutic classification (ATC). Depression was defined as PHQ-9 ≥ 10 and Anxiety as GAD-7 ≥ 10.
Age-standardised prevalence of PHQ-9 ≥ 10 was 10.7% in women and 5.4% in men (GAD-7 ≥ 10 6.2% in women; 3.0% in men). Among those with PHQ-9 ≥ 10 17% reported ever having been diagnosed with depression (equivalent finding for anxiety 29%). Only 1.5% of those with PHQ-9 ≥ 10 reported using anti-depressants and 0.6% of those with GAD-7 ≥ 10 reported using anxiolytics. No men with PHQ-9 ≥ 10 and/or GAD-7 ≥ 10 reported use of anti-depressants or anxiolytics. Use of health services increased with increasing severity of both depression and anxiety.
There was a large gap between symptoms and reporting of past diagnosis and treatment of common mental disorders in two Russian cities. Interventions aimed at improving mental health literacy and reducing stigma could be of benefit in closing this substantial treatment gap.
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.