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Glioblastoma, the most aggressive and common malignant primary brain tumour, is characterized by infiltrative growth, abundant vascularization, and aggressive clinical evolution. Patients with glioblastoma often face poor prognoses, with a median survival of approximately 15 months. Technological progress and the subsequent improvement in understanding the pathophysiology of these tumours have not translated into significant achievements in therapies or survival outcomes for patients. Progress in molecular profiling has yielded new omics data for a more refined classification of glioblastoma. Several typical genetic and epigenetic alterations in glioblastoma include mutations in genes regulating receptor tyrosine kinase (RTK)/rat sarcoma (RAS)/phosphoinositide 3-kinase (PI3K), p53, and retinoblastoma protein (RB) signalling, as well as mutation of isocitrate dehydrogenase (IDH), methylation of O6-methylguanine-DNA methyltransferase (MGMT), amplification of epidermal growth factor receptor vIII, and codeletion of 1p/19q. Certain microRNAs, such as miR-10b and miR-21, have also been identified as prognostic biomarkers. Effective treatment options for glioblastoma are limited. Surgery, radiotherapy, and alkylating agent chemotherapy remain the primary pillars of treatment. Only promoter methylation of the gene MGMT predicts the benefit from alkylating chemotherapy with temozolomide and it guides the choice of first-line treatment in elderly patients. Several targeted strategies based on tumour-intrinsic dominant signalling pathways and antigenic tumour profiles are under investigation in clinical trials. This review explores the potential genetic and epigenetic biomarkers that could be deployed as analytical tools in the diagnosis and prognostication of glioblastoma. Recent clinical advancements in treating glioblastoma are also discussed, along with the potential of liquid biopsies to advance personalized medicine in the field of glioblastoma, highlighting the challenges and promises for the future. [ABSTRACT FROM AUTHOR]

(1) Background: High dose gradients and manual steps in brachytherapy treatment procedures can lead to dose errors which make the use of in vivo dosimetry (IVD) highly recommended for verifying brachytherapy treatments. A new procedure was presented to obtain a calibration factor which allows fast and robust calibration of plastic scintillation detector (PSD) probes for the geometry of a compact phantom using Monte Carlo simulations. Additionally, characterization of PSD energy, angular, and temperature dependences was performed. (2) Methods: PENELOPE/PenEasy code was used to obtain the calibration factor. To characterize the energy dependence of the PSD, the signal was measured at different radial and transversal distances. The sensitivity to the angular position was characterized in axial and azimuthal planes. (3) Results: The calibration factor obtained allows for an absorbed dose to water determination in full scatter conditions from ionization measured in a mini polymethylmethacrylate (PMMA) phantom. The energy dependence of the PSD along the radial distances obtained was (2.3 ± 2.1)% (k = 1). The azimuthal angular dependence measured was (2.6 ± 3.4)% (k = 1). The PSD response decreased by (0.19 ± 0.02)%/°C with increasing detector probe temperature. (4) Conclusions: The energy, angular, and temperature dependence of a PSD is compatible with IVD. [ABSTRACT FROM AUTHOR]

Heat shock protein 90 (HSP90) facilitates folding and stability and prevents the degradation of multiple client proteins. One of these HSP90 clients is BCR-ABL, the oncoprotein characteristic of chronic myeloid leukemia (CML) and the target of tyrosine kinase inhibitors, such as imatinib. Alvespimycin is an HSP90 inhibitor with better pharmacokinetic properties and fewer side effects than other similar drugs, but its role in overcoming imatinib resistance is not yet clarified. This work studied the therapeutic potential of alvespimycin in imatinib-sensitive (K562) and imatinib-resistant (K562-RC and K562-RD) CML cell lines. Metabolic activity was determined by the resazurin assay. Cell death, caspase activity, mitochondrial membrane potential, and cell cycle were evaluated by means of flow cytometry. Cell death was also analyzed by optical microscopy. HSPs expression levels were assessed by western blotting. Alvespimycin reduced metabolic activity in a time-, dose-, and cell line-dependent manner. Resistant cells were more sensitive to alvespimycin with an IC50 of 31 nM for K562-RC and 44 nM for K562-RD, compared to 50 nM for K562. This drug induced apoptosis via the mitochondrial pathway. In K562 cells, alvespimycin induced cell cycle arrest in G0/G1. As a marker of HSP90 inhibition, a significant increase in HSP70 expression was observed. Our results suggest that alvespimycin might be a new therapeutic approach to CML treatment, even in cases of resistance to imatinib. [ABSTRACT FROM AUTHOR]

The neurobiological mechanisms underlying Autism Spectrum Disorders (ASD) remains controversial. One factor contributing to this debate is the phenotypic heterogeneity observed in ASD, which suggests that multiple system disruptions may contribute to diverse patterns of impairment which have been reported between and within study samples. Here, we used SFARI data to address genetic imbalances affecting the dopaminergic system. Using complex network analysis, we investigated the relations between phenotypic profiles, gene dosage and gene ontology (GO) terms related to dopaminergic neurotransmission from a polygenic point-of-view. We observed that the degree of distribution of the networks matched a power-law distribution characterized by the presence of hubs, gene or GO nodes with a large number of interactions. Furthermore, we identified interesting patterns related to subnetworks of genes and GO terms, which suggested applicability to separation of clinical clusters (Developmental Delay (DD) versus ASD). This has the potential to improve our understanding of genetic variability issues and has implications for diagnostic categorization. In ASD, we identified the separability of four key dopaminergic mechanisms disrupted with regard to receptor binding, synaptic physiology and neural differentiation, each belonging to particular subgroups of ASD participants, whereas in DD a more unitary biological pattern was found. Finally, network analysis was fed into a machine learning binary classification framework to differentiate between the diagnosis of ASD and DD. Subsets of 1846 participants were used to train a Random Forest algorithm. Our best classifier achieved, on average, a diagnosis-predicting accuracy of 85.18% (sd 1.11%) on the test samples of 790 participants using 117 genes. The achieved accuracy surpassed results using genetic data and closely matched imaging approaches addressing binary diagnostic classification. Importantly, we observed a similar prediction accuracy when the classifier uses only 62 GO features. This result further corroborates the complex network analysis approach, suggesting that different genetic causes might converge to the dysregulation of the same set of biological mechanisms, leading to a similar disease phenotype. This new biology-driven ontological framework yields a less variable and more compact domain-related set of features with potential mechanistic generalization. The proposed network analysis, allowing for the determination of a clearcut biological distinction between ASD and DD (the latter presenting much lower modularity and heterogeneity), is amenable to machine learning approaches and provides an interesting avenue of research for the future. [ABSTRACT FROM AUTHOR]

Head and Neck Cancer (HNC) is characterized by phenotypic, biological, and clinical heterogeneity. Despite treatment modalities, approximately half of all patients will die of the disease. Several molecular biomarkers have been investigated, but until now, without clinical translation. Here, we identified an integrative nine-gene multi-omics signature correlated with HNC patients' survival independently of relapses or metastasis development. This prognosis multi-omic signature comprises genes mapped in the chromosomes 1q, 3p, 8q, 17q, 19p, and 19q and encompasses alterations at copy number, gene expression, and methylation. Copy number alterations in LMCD1-A1S and GRM7, the methylation status of CEACAM19, KRT17, and ST18, and the expression profile of RPL29, UBA7, FCGR2C, and RPSAP58 can predict the HNC patients' survival. The difference higher than two years observed in the survival of HNC patients that harbor this nine-gene multi-omics signature can represent a significant step forward to improve patients' management and guide new therapeutic targets development. [ABSTRACT FROM AUTHOR]

(1) Background: In brachytherapy, there are still many manual procedures that can cause adverse events which can be detected with in vivo dosimetry systems. Plastic scintillator dosimeters (PSD) have interesting properties to achieve this objective such as real-time reading, linearity, repeatability, and small size to fit inside brachytherapy catheters. The purpose of this study was to evaluate the performance of a PSD in postoperative endometrial brachytherapy in terms of source dwell time accuracy. (2) Methods: Measurements were carried out in a PMMA phantom to characterise the PSD. Patient measurements in 121 dwell positions were analysed to obtain the differences between planned and measured dwell times. (3) Results: The repeatability test showed a relative standard deviation below 1% for the measured dwell times. The relative standard deviation of the PSD sensitivity with accumulated absorbed dose was lower than 1.2%. The equipment operated linearly in total counts with respect to absorbed dose and also in count rate versus absorbed dose rate. The mean (standard deviation) of the absolute differences between planned and measured dwell times in patient treatments was 0.0 (0.2) seconds. (4) Conclusions: The PSD system is useful as a quality assurance tool for brachytherapy treatments. [ABSTRACT FROM AUTHOR]

Simple Summary: Despite the clinical benefit of new anticancer therapies, such as immune checkpoint inhibitors, lung cancer remains the most frequent cause of cancer-related death worldwide, thus supporting the need to develop novel anticancer treatments. Endothelial cells of the tumor-associated vasculature are easily accessible to drugs administered intravenously, besides having greater genetic stability than neoplastic cells and thus lowering the risk of developing drug resistance. In this respect, the identification of alternative targets, and therapeutic strategies, within the tumor vasculature is of high relevance. Accordingly, this work aimed at characterizing nucleolin expression in patient-derived pulmonary carcinomas and further validating nucleolin as a novel target to mediate successful therapeutic interventions against human lung cancers. The highlighted prognostic value of nucleolin points towards the applicability of nucleolin-based targeting strategies against nucleolinhigh pulmonary carcinomas, present in every disease stage, in a clinical trial setting. Notwithstanding the advances in the treatment of lung cancer with immune checkpoint inhibitors, the high percentage of non-responders supports the development of novel anticancer treatments. Herein, the expression of the onco-target nucleolin in patient-derived pulmonary carcinomas was characterized, along with the assessment of its potential as a therapeutic target. The clinical prognostic value of nucleolin for human pulmonary carcinomas was evaluated through data mining from the Cancer Genome Atlas project and immunohistochemical detection in human samples. Cell surface expression of nucleolin was evaluated by flow cytometry and subcellular fraction Western blotting in lung cancer cell lines. Nucleolin mRNA overexpression correlated with poor overall survival of lung adenocarcinoma cancer patients and further predicted the disease progression of both lung adenocarcinoma and squamous carcinoma. Furthermore, a third of the cases presented extra-nuclear expression, contrasting with the nucleolar pattern in non-malignant tissues. A two- to twelve-fold improvement in cytotoxicity, subsequent to internalization into the lung cancer cell lines of doxorubicin-loaded liposomes functionalized by the nucleolin-binding F3 peptide, was correlated with the nucleolin cell surface levels and the corresponding extent of cell binding. Overall, the results suggested nucleolin overexpression as a poor prognosis predictor and thus a target for therapeutic intervention in lung cancer. [ABSTRACT FROM AUTHOR]

The Cacheu Mangroves Natural Park (PNTC) was established in the year 2000 with the objective of protecting the coastal forests of Northern Guinea-Bissau, which have been subject to deforestation and are at risk. Concomitantly, the need to find sustainable financial revenues to support forest conservation motivated the development of projects that explore avoidance of deforestation and forest degradation (REDD+) as a potential income possibility. The 886,150 ha of forest in the PNTC include a mosaic of different villages where communities with different cultural and socio-economic habits reside. In addition to the uncontrolled expansion of subsistence agriculture with the associated shortening of fallow periods, forests may have also been subject to degradation from selective logging, fuel wood collection, and charcoal production. To contribute to a forest degradation baseline forest uses for household fuel consumption (wood and charcoal) were surveyed using questionnaires, interviews and focus groups. The data were collected from a representative sample of circa 200 households within a 2 km buffer of the PNTC. These data are analyzed and the results are discussed according to a scenario of ethnic diversity, i.e., a diversity of approaches relating to forest conservation. Even though the results indicate that fuel wood is the main (and almost sole) source of energy for cooking, they also show that the average daily fuel consumption per capita (1.21 kg) is well below the sub-Saharan average and that fuel is obtained from downed dead wood or dead trees. Therefore, it is concluded that reported forest degradation in PNTC cannot be attributed to fuel wood consumption by local populations. [ABSTRACT FROM AUTHOR]

The quantification of forest above-ground biomass (AGB) is important for such broader applications as decision making, forest management, carbon (C) stock change assessment and scientific applications, such as C cycle modeling. However, there is a great uncertainty related to the estimation of forest AGB, especially in the tropics. The main goal of this study was to test a combination of field data and Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) backscatter intensity data to reduce the uncertainty in the estimation of forest AGB in the Miombo savanna woodlands of Mozambique (East Africa). A machine learning algorithm, based on bagging stochastic gradient boosting (BagSGB), was used to model forest AGB as a function of ALOS PALSAR Fine Beam Dual (FBD) backscatter intensity metrics. The application of this method resulted in a coefficient of correlation (R) between observed and predicted (10-fold cross-validation) forest AGB values of 0.95 and a root mean square error of 5.03 Mg·ha-1. However, as a consequence of using bootstrap samples in combination with a cross validation procedure, some bias may have been introduced, and the reported cross validation statistics could be overoptimistic. Therefore and as a consequence of the BagSGB model, a measure of prediction variability (coefficient of variation) on a pixel-by-pixel basis was also produced, with values ranging from 10 to 119% (mean = 25%) across the study area. It provides additional and complementary information regarding the spatial distribution of the error resulting from the application of the fitted model to new observations. [ABSTRACT FROM AUTHOR]

Simple Summary: Targeted nanomedicine-based approaches that aim at the simultaneous delivery of synergistic drug combinations to multiple cellular populations are of high relevance for tackling heterogeneity on solid tumors. Considering that cancer stem cells (CSC) may originate from non-stem cancer cells, single-drug regimens targeting only one of these cell populations could enable tumors to evade treatments. As such, the identification of a common marker, such as nucleolin, might result in a therapeutic advantage. The results herein generated suggested a transversal role of nucleolin in the internalization of F3 peptide-targeted pegylated pH-sensitive liposomes into bulk ovarian cancer cells, including putative CSC-enriched ovarian cells. The intracellular delivery of a drug combination such as the one tested herein was relevant in the context of cell lines with higher intrinsic resistances to doxorubicin. The enhanced efficacy of the F3 peptide-targeted liposomal combination of doxorubicin/C6-ceramide was supported by the downregulation of the Akt pathway, within a specific range of basal level of expression. Targeting multiple cellular populations is of high therapeutic relevance for the tackling of solid tumors heterogeneity. Herein, the ability of pegylated and pH-sensitive liposomes, functionalized with the nucleolin-binding F3 peptide and containing doxorubicin (DXR)/C6-ceramide synergistic combination, to target, in vitro, ovarian cancer, including ovarian cancer stem cells (CSC), was assessed. The underlying molecular mechanism of action of the nucleolin-mediated intracellular delivery of C6-ceramide to cancer cells was also explored. The assessment of overexpression of surface nucleolin expression by flow cytometry was critical to dissipate differences identified by Western blot in membrane/cytoplasm of SKOV-3, OVCAR-3 and TOV-112D ovarian cancer cell lines. The former was in line with the significant extent of uptake into (bulk) ovarian cancer cells, relative to non-targeted and non-specific counterparts. This pattern of uptake was recapitulated with putative CSC-enriched ovarian SKOV-3 and OVCAR-3 sub-population (EpCAMhigh/CD44high). Co-encapsulation of DXR:C6-ceramide into F3 peptide-targeted liposomes improved cytotoxic activity relative to liposomes containing DXR alone, in an extent that depended on the intrinsic resistance to DXR and on the incubation time. The enhanced cytotoxicity of the targeted combination was mechanistically supported by the downregulation of PI3K/Akt pathway by C6-ceramide, only among the nucleolin-overexpressing cancer cells presenting a basal p-Akt/total Akt ratio lower than 1. [ABSTRACT FROM AUTHOR]

This study aims to evaluate whether mitochondrial changes occur in the early stages of bipolar disorder (BD). Using fibroblasts derived from BD patients and matched controls, the levels of proteins involved in mitochondrial biogenesis and dynamics (fission and fusion) were evaluated by Western Blot analysis. Mitochondrial membrane potential (MMP) was studied using the fluorescent probe TMRE. Mitochondrial morphology was analyzed with the probe Mitotracker Green and mitophagy was evaluated by quantifying the co-localization of HSP60 (mitochondria marker) and LC3B (autophagosome marker) by immunofluorescence. Furthermore, the activity of the mitochondrial respiratory chain and the glycolytic capacity of controls and BD patients-derived cells were also studied using the Seahorse technology. BD patient-derived fibroblasts exhibit fragmented mitochondria concomitantly with changes in mitochondrial dynamics and biogenesis in comparison with controls. Moreover, a decrease in the MMP and increased mitophagy was observed in fibroblasts obtained from BD patients when compared with control cells. Impaired energetic metabolism due to inhibition of the mitochondrial electron transport chain (ETC) and subsequent ATP depletion, associated with glycolysis stimulation, was also a feature of BD fibroblasts. Overall, these results support the fact that mitochondrial disturbance is an early event implicated in BD pathophysiology that might trigger neuronal changes and modification of brain circuitry. [ABSTRACT FROM AUTHOR]

The minimally—or non-invasive detection of circulating tumor-derived components in biofluids, such as blood, liquid biopsy is a revolutionary approach with significant potential for the management of cancer. Genomic and transcriptomic alterations can be accurately detected through liquid biopsies, which provide a more comprehensive characterization of the heterogeneous tumor profile than tissue biopsies alone. Liquid biopsies could assist diagnosis, prognosis, and treatment selection, and hold great potential to complement current surveilling strategies to monitor disease evolution and treatment response in real-time. In particular, these are able to detect minimal residual disease, to predict progression, and to identify mechanisms of resistance, allowing to re-orient treatment strategies in a timelier manner. In this review we gathered current knowledge regarding the role and potential of liquid biopsies for the diagnosis and follow-up of cancer patients. The presented findings emphasize the strengths of liquid biopsies, revealing their chance of improving the diagnosis and monitoring of several tumor types in the near future. However, despite growing evidence supporting their value as a management tool in oncology, some limitations still need to be overcome for their implementation in the routine clinical setting. [ABSTRACT FROM AUTHOR]

The continuous characterization of genome-wide diversity in population and case–cohort samples, allied to the development of new algorithms, are shedding light on host ancestry impact and selection events on various infectious diseases. Especially interesting are the long-standing associations between humans and certain bacteria, such as the case of Helicobacter pylori, which could have been strong drivers of adaptation leading to coevolution. Some evidence on admixed gastric cancer cohorts have been suggested as supporting Homo-Helicobacter coevolution, but reliable experimental data that control both the bacterium and the host ancestries are lacking. Here, we conducted the first in vitro coinfection assays with dual human- and bacterium-matched and -mismatched ancestries, in African and European backgrounds, to evaluate the genome wide gene expression host response to H. pylori. Our results showed that: (1) the host response to H. pylori infection was greatly shaped by the human ancestry, with variability on innate immune system and metabolism; (2) African human ancestry showed signs of coevolution with H. pylori while European ancestry appeared to be maladapted; and (3) mismatched ancestry did not seem to be an important differentiator of gene expression at the initial stages of infection as assayed here. [ABSTRACT FROM AUTHOR]

Helicobacter pylori, a stomach-colonizing Gram-negative bacterium, is the main etiological factor of various gastroduodenal diseases, including gastric adenocarcinoma. By establishing a life-long infection of the gastric mucosa, H. pylori continuously activates host-signaling pathways, in particular those associated with receptor tyrosine kinases. Using two different gastric epithelial cell lines, we show that H. pylori targets the receptor tyrosine kinase EPHA2. For long periods of time post-infection, H. pylori induces EPHA2 protein downregulation without affecting its mRNA levels, an effect preceded by receptor activation via phosphorylation. EPHA2 receptor downregulation occurs via the lysosomal degradation pathway and is independent of the H.pylori virulence factors CagA, VacA, and T4SS. Using small interfering RNA, we show that EPHA2 knockdown affects cell–cell and cell–matrix adhesion, invasion, and angiogenesis, which are critical cellular processes in early gastric lesions and carcinogenesis mediated by the bacteria. This work contributes to the unraveling of the underlying mechanisms of H. pylori–host interactions and associated diseases. Additionally, it raises awareness for potential interference between H. pylori infection and the efficacy of gastric cancer therapies targeting receptors tyrosine kinases, given that infection affects the steady-state levels and dynamics of some receptor tyrosine kinases (RTKs) and their signaling pathways. [ABSTRACT FROM AUTHOR]

The availability of cytogenetics and cytogenomics technologies improved the detection and identification of tumor molecular signatures as well as the understanding of cancer initiation and progression. The use of large-scale and high-throughput cytogenomics technologies has led to a fast identification of several cancer candidate biomarkers associated with diagnosis, prognosis, and therapeutics. The advent of array comparative genomic hybridization and next-generation sequencing technologies has significantly improved the knowledge about cancer biology, underlining driver genes to guide targeted therapy development, drug-resistance prediction, and pharmacogenetics. However, few of these candidate biomarkers have made the transition to the clinic with a clear benefit for the patients. Technological progress helped to demonstrate that cellular heterogeneity plays a significant role in tumor progression and resistance/sensitivity to cancer therapies, representing the major challenge of precision cancer therapy. A paradigm shift has been introduced in cancer genomics with the recent advent of single-cell sequencing, since it presents a lot of applications with a clear benefit to oncological patients, namely, detection of intra-tumoral heterogeneity, mapping clonal evolution, monitoring the development of therapy resistance, and detection of rare tumor cell populations. It seems now evident that no single biomarker could provide the whole information necessary to early detect and predict the behavior and prognosis of tumors. The promise of precision medicine is based on the molecular profiling of tumors being vital the continuous progress of high-throughput technologies and the multidisciplinary efforts to catalogue chromosomal rearrangements and genomic alterations of human cancers and to do a good interpretation of the relation genotype—phenotype. [ABSTRACT FROM AUTHOR]