Beyond the Warburg Effect: Oxidative and Glycolytic Phenotypes Coexist within the Metabolic Heterogeneity of Glioblastoma.

Glioblastoma (GBM) is the most aggressive primary brain tumor, with a median survival at diagnosis of 16–20 months. Metabolism represents a new attractive therapeutic target; however, due to high intratumoral heterogeneity, the application of metabolic drugs in GBM is challenging. We characterized the basal bioenergetic metabolism and antiproliferative potential of metformin (MF), dichloroacetate (DCA), sodium oxamate (SOD) and diazo-5-oxo-L-norleucine (DON) in three distinct glioma stem cells (GSCs) (GBM18, GBM27, GBM38), as well as U87MG. GBM27, a highly oxidative cell line, was the most resistant to all treatments, except DON. GBM18 and GBM38, Warburg-like GSCs, were sensitive to MF and DCA, respectively. Resistance to DON was not correlated with basal metabolic phenotypes. In combinatory experiments, radiomimetic bleomycin exhibited therapeutically relevant synergistic effects with MF, DCA and DON in GBM27 and DON in all other cell lines. MF and DCA shifted the metabolism of treated cells towards glycolysis or oxidation, respectively. DON consistently decreased total ATP production. Our study highlights the need for a better characterization of GBM from a metabolic perspective. Metabolic therapy should focus on both glycolytic and oxidative subpopulations of GSCs.post-print3439 K

DNA sequences within glioma-derived extracellular vesicles can cross the intact blood-brain barrier and be detected in peripheral blood of patients

Tumor-cell-secreted extracellular vesicles (EVs) can cross the disrupted bloodbrain barrier (BBB) into the bloodstream. However, in certain gliomas, the BBB remains intact, which might limit EVs release. To evaluate the ability of tumor-derived EVs to cross the BBB, we used an orthotopic xenotransplant mouse model of human glioma-cancer stem cells featuring an intact BBB. We demonstrated that all types of tumor cells-derived EVs−apoptotic bodies, shedding microvesicles and exosomes− cross the intact BBB and can be detected in the peripheral blood, which provides a minimally invasive method for their detection compared to liquid biopsies obtained from cerebrospinal fluid (CSF). Furthermore, these EVs can be readily distinguished from total murine EVs, since they carry human-specific DNA sequences relevant for GBM biology. In a small cohort of glioma patients, we finally demonstrated that peripheral blood EVs cargo can be successfully used to detect the presence of IDH1G395A, an essential biomarker in the current management of human gliomaWe are grateful for the financial support from the ‘Fondo de Investigaciones Sanitarias’ (FIS) (PI10/01069 and PI14/00077) and the ‘Miguel Servet Program’ (CP11/00147) from the ‘Instituto de Salud Carlos III’ (AAS), RTC-2015-3846-1 from Ministerio de Economía y Competitividad and FEDER fund

A comprehensive dataset of annotated brain metastasis MR images with clinical and radiomic data.

Brain metastasis (BM) is one of the main complications of many cancers, and the most frequent malignancy of the central nervous system. Imaging studies of BMs are routinely used for diagnosis of disease, treatment planning and follow-up. Artificial Intelligence (AI) has great potential to provide automated tools to assist in the management of disease. However, AI methods require large datasets for training and validation, and to date there have been just one publicly available imaging dataset of 156 BMs. This paper publishes 637 high-resolution imaging studies of 75 patients harboring 260 BM lesions, and their respective clinical data. It also includes semi-automatic segmentations of 593 BMs, including pre- and post-treatment T1-weighted cases, and a set of morphological and radiomic features for the cases segmented. This data-sharing initiative is expected to enable research into and performance evaluation of automatic BM detection, lesion segmentation, disease status evaluation and treatment planning methods for BMs, as well as the development and validation of predictive and prognostic tools with clinical applicability

BRAF V600E Detection in Liquid Biopsies from Pediatric Central Nervous System Tumors

Pediatric Central Nervous System (CNS) tumors are the most fatal cancer diseases in childhood. Due to their localization and infiltrative nature, some tumor resections or biopsies are not feasible. In those cases, the use of minimally invasive methods as diagnostic, molecular marker detection, prognostic or monitoring therapies are emerging. The analysis of liquid biopsies which contain genetic information from the tumor has been much more widely explored in adults than in children. We compare the detection of BRAF V600E targetable mutation by digital-PCR from cell-free-DNA and EV-derived DNA (ctDNA) in serum, plasma and cerebrospinal fluid (CSF) isolated from a cohort of 29 CNS pediatric patients. Here we demonstrate that ctDNA isolated from serum and plasma could be successfully analyzed to obtain tumor genetic information which could be used to guide critical treatment decisions

Growth exponents reflect evolutionary processes and treatment response in brain metastases

Abstract Tumor growth is the result of the interplay of complex biological processes in huge numbers of individual cells living in changing environments. Effective simple mathematical laws have been shown to describe tumor growth in vitro, or simple animal models with bounded-growth dynamics accurately. However, results for the growth of human cancers in patients are scarce. Our study mined a large dataset of 1133 brain metastases (BMs) with longitudinal imaging follow-up to find growth laws for untreated BMs and recurrent treated BMs. Untreated BMs showed high growth exponents, most likely related to the underlying evolutionary dynamics, with experimental tumors in mice resembling accurately the disease. Recurrent BMs growth exponents were smaller, most probably due to a reduction in tumor heterogeneity after treatment, which may limit the tumor evolutionary capabilities. In silico simulations using a stochastic discrete mesoscopic model with basic evolutionary dynamics led to results in line with the observed data

Universal scaling laws rule explosive growth in human cancers

International audienceMost physical and other natural systems are complex entities that are composed of a large number of interacting individual elements. It is a surprising fact that they often obey the so-called scaling laws that relate an observable quantity to a measure of the size of the system. Here, we describe the discovery of universal superlinear metabolic scaling laws in human cancers. This dependence underpins increasing tumour aggressiveness, owing to evolutionary dynamics, that leads to an explosive growth as the disease progresses. We validated this dynamic using longitudinal volumetric data of different histologies from large cohorts of patients with cancer. To explain our observations we tested complex, biologically inspired mathematical models that describe the key processes that govern tumour growth. Our models predict that the emergence of superlinear allometric scaling laws is an inherently three-dimensional phenomenon. Moreover, the scaling laws that we identified allowed us to define a set of metabolic metrics with prognostic value, which adds clinical utility to our findings

Agreement in the assessment of metastatic spine disease using scoring systems

Licensed under the Creative Commons Attribution-Non Commercial-No Derivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0

Diminishing benefits of urban living for children and adolescents’ growth and development

Optimal growth and development in childhood and adolescence is crucial for lifelong health and well-being1–6. Here we used data from 2,325 population-based studies, with measurements of height and weight from 71 million participants, to report the height and body-mass index (BMI) of children and adolescents aged 5–19 years on the basis of rural and urban place of residence in 200 countries and territories from 1990 to 2020. In 1990, children and adolescents residing in cities were taller than their rural counterparts in all but a few high-income countries. By 2020, the urban height advantage became smaller in most countries, and in many high-income western countries it reversed into a small urban-based disadvantage. The exception was for boys in most countries in sub-Saharan Africa and in some countries in Oceania, south Asia and the region of central Asia, Middle East and north Africa. In these countries, successive cohorts of boys from rural places either did not gain height or possibly became shorter, and hence fell further behind their urban peers. The difference between the age-standardized mean BMI of children in urban and rural areas was <1.1 kg m–2 in the vast majority of countries. Within this small range, BMI increased slightly more in cities than in rural areas, except in south Asia, sub-Saharan Africa and some countries in central and eastern Europe. Our results show that in much of the world, the growth and developmental advantages of living in cities have diminished in the twenty-first century, whereas in much of sub-Saharan Africa they have amplified