Looking Beyond the Glioblastoma Mask: Is Genomics the Right Path?

Glioblastomas are the most frequent and malignant brain tumor hallmarked by an invariably poor prognosis. They have been classically differentiated into primary isocitrate dehydrogenase 1 or 2 (IDH1 -2) wild-type (wt) glioblastoma (GBM) and secondary IDH mutant GBM, with IDH wt GBMs being commonly associated with older age and poor prognosis. Recently, genetic analyses have been integrated with epigenetic investigations, strongly implementing typing and subtyping of brain tumors, including GBMs, and leading to the new WHO 2021 classification. GBM genomic and epigenomic profile influences evolution, resistance, and therapeutic responses. However, differently from other tumors, there is a wide gap between the refined GBM profiling and the limited therapeutic opportunities. In addition, the different oncogenes and tumor suppressor genes involved in glial cell transformation, the heterogeneous nature of cancer, and the restricted access of drugs due to the blood–brain barrier have limited clinical advancements. This review will summarize the more relevant genetic alterations found in GBMs and highlight their potential role as potential therapeutic targets

Epigenetic remodelling of Fxyd1 promoters in developing heart and brain tissues

FXYD1 is a key protein controlling ion channel transport. FXYD1 exerts its function by regulating Na+/K+-ATPase activity, mainly in brain and cardiac tissues. Alterations of the expression level of the FXYD1 protein cause diastolic dysfunction and arrhythmias in heart and decreased neuronal dendritic tree and spine formation in brain. Moreover, FXYD1, a target of MeCP2, plays a crucial role in the pathogenesis of the Rett syndrome, a neurodevelopmental disorder. Thus, the amount of FXYD1 must be strictly controlled in a tissue specific manner and, likely, during development. Epigenetic modifications, particularly DNA methylation, represent the major candidate mechanism that may regulate Fxyd1 expression. In the present study, we performed a comprehensive DNA methylation analysis and mRNA expression level measurement of the two Fxyd1 transcripts, Fxyd1a and Fxyd1b, in brain and heart tissues during mouse development. We found that DNA methylation at Fxyd1a increased during brain development and decreased during heart development along with coherent changes in mRNA expression levels. We also applied ultra-deep methylation analysis to detect cell to cell methylation differences and to identify possible distinct methylation profile (epialleles) distribution between heart and brain and in different developmental stages. Our data indicate that the expression of Fxyd1 transcript isoforms inversely correlates with DNA methylation in developing brain and cardiac tissues suggesting the existence of a temporal-specific epigenetic program. Moreover, we identified a clear remodeling of epiallele profiles which were distinctive for single developmental stage both in brain and heart tissues

SARS-CoV-2 multi-variant rapid detector based on graphene transistor functionalized with an engineered dimeric ACE2 receptor

Reliable point-of-care (POC) rapid tests are crucial to detect infection and contain the spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The emergence of several variants of concern (VOC) can reduce binding affinity to diagnostic antibodies, limiting the efficacy of the currently adopted tests, while showing unaltered or increased affinity for the host receptor, angiotensin converting enzyme 2 (ACE2). We present a graphene field-effect transistor (gFET) biosensor design, which exploits the Spike-ACE2 interaction, the crucial step for SARS-CoV-2 infection. Extensive computational analyses show that a chimeric ACE2-Fragment crystallizable (ACE2-Fc) construct mimics the native receptor dimeric conformation. ACE2-Fc functionalized gFET allows in vitro detection of the trimeric Spike protein, outperforming functionalization with a diagnostic antibody or with the soluble ACE2 portion, resulting in a sensitivity of 20 pg/mL. Our miniaturized POC biosensor successfully detects B.1.610 (pre-VOC), Alpha, Beta, Gamma, Delta, Omicron (i.e., BA.1, BA.2, BA.4, BA.5, BA.2.75 and BQ.1) variants in isolated viruses and patient's clinical nasopharyngeal swabs. The biosensor reached a Limit Of Detection (LOD) of 65 cps/mL in swab specimens of Omicron BA.5. Our approach paves the way for a new and reusable class of highly sensitive, rapid and variant-robust SARS-CoV-2 detection systems

A machine-learning based bio-psycho-social model for the prediction of non-obstructive and obstructive coronary artery disease

Background: Mechanisms of myocardial ischemia in obstructive and non-obstructive coronary artery disease (CAD), and the interplay between clinical, functional, biological and psycho-social features, are still far to be fully elucidated. Objectives: To develop a machine-learning (ML) model for the supervised prediction of obstructive versus non-obstructive CAD. Methods: From the EVA study, we analysed adults hospitalized for IHD undergoing conventional coronary angiography (CCA). Non-obstructive CAD was defined by a stenosis < 50% in one or more vessels. Baseline clinical and psycho-socio-cultural characteristics were used for computing a Rockwood and Mitnitski frailty index, and a gender score according to GENESIS-PRAXY methodology. Serum concentration of inflammatory cytokines was measured with a multiplex flow cytometry assay. Through an XGBoost classifier combined with an explainable artificial intelligence tool (SHAP), we identified the most influential features in discriminating obstructive versus non-obstructive CAD. Results: Among the overall EVA cohort (n = 509), 311 individuals (mean age 67 ± 11 years, 38% females; 67% obstructive CAD) with complete data were analysed. The ML-based model (83% accuracy and 87% precision) showed that while obstructive CAD was associated with higher frailty index, older age and a cytokine signature characterized by IL-1β, IL-12p70 and IL-33, non-obstructive CAD was associated with a higher gender score (i.e., social characteristics traditionally ascribed to women) and with a cytokine signature characterized by IL-18, IL-8, IL-23. Conclusions: Integrating clinical, biological, and psycho-social features, we have optimized a sex- and gender-unbiased model that discriminates obstructive and non-obstructive CAD. Further mechanistic studies will shed light on the biological plausibility of these associations. Clinical trial registration: NCT02737982

MGMT and Whole-Genome DNA Methylation Impacts on Diagnosis, Prognosis and Therapy of Glioblastoma Multiforme

: Epigenetic changes in DNA methylation contribute to the development of many diseases, including cancer. In glioblastoma multiforme, the most prevalent primary brain cancer and an incurable tumor with a median survival time of 15 months, a single epigenetic modification, the methylation of the O6-Methylguanine-DNA Methyltransferase (MGMT) gene, is a valid biomarker for predicting response to therapy with alkylating agents and also, independently, prognosis. More recently, the progress from single gene to whole-genome analysis of DNA methylation has allowed a better subclassification of glioblastomas. Here, we review the clinically relevant information that can be obtained by studying MGMT gene and whole-genome DNA methylation changes in glioblastomas, also highlighting benefits, including those of liquid biopsy, and pitfalls of the different detection methods. Finally, we discuss how changes in DNA methylation, especially in glioblastomas bearing mutations in the Isocitrate Dehydrogenase (IDH) 1 and 2 genes, can be exploited as targets for tailoring therapy

Methylome Profiling in Fabry Disease in Clinical Practice: A Proof of Concept

: Anderson-Fabry disease (FD) is an X-linked disease caused by a functional deficit of the α-galactosidase A enzyme. FD diagnosis relies on the clinical manifestations and research of GLA gene mutations. However, because of the lack of a clear genotype/phenotype correlation, FD diagnosis can be challenging. Recently, several studies have highlighted the importance of investigating DNA methylation patterns for confirming the correct diagnosis of different rare Mendelian diseases, but to date, no such studies have been reported for FD. Thus, in the present investigation, we analyzed for the first time the genome-wide methylation profile of a well-characterized cohort of patients with Fabry disease. We profiled the methylation status of about 850,000 CpG sites in 5 FD patients, all carrying the same mutation in the GLA gene (exon 6 c.901C>G) and presenting comparable low levels of α-Gal A activity. We found that, although the whole methylome profile did not discriminate the FD group from the unaffected one, several genes were significantly differentially methylated in Fabry patients. Thus, we provide here a proof of concept, to be tested in patients with different mutations and in a larger cohort, that the methylation state of specific genes can potentially identify Fabry patients and possibly predict organ involvement and disease evolution

Laser evaporation versus laser excision of oral leukoplakia: A retrospective study with long-term follow-up

none7noThe study makes a comparison between two surgical approaches for the treatment of oral leukoplakia (OL) in terms of recurrence in a well-defined cohort of patients with a long-term follow-up period.noneDel Corso, Giacomo; Gissi, Davide Bartolomeo; Tarsitano, Achille; Costabile, Enrico; Marchetti, Claudio; Montebugnoli, Lucio; Foschini, Maria PiaDel Corso, Giacomo; Gissi, Davide Bartolomeo; Tarsitano, Achille; Costabile, Enrico; Marchetti, Claudio; Montebugnoli, Lucio; Foschini, Maria Pi

Ultra-Deep DNA Methylation Analysis of X-Linked Genes: GLA and AR as Model Genes

Recessive X-linked disorders may occasionally evolve in clinical manifestations of variable severity also in female carriers. For some of such diseases, the frequency of the symptoms’ appearance during women’s life may be particularly relevant. This phenomenon has been largely attributed to the potential skewness of the X-inactivation process leading to variable phenotypes. Nonetheless, in many cases, no correlation with X-inactivation unbalance was demonstrated. However, methods for analyzing skewness have been mainly limited to Human Androgen Receptor methylation analysis (HUMARA). Recently, the X-inactivation process has been largely revisited, highlighting the heterogeneity existing among loci in the epigenetic state within inactive and, possibly, active X-chromosomes. We reasoned that gene-specific and ultra-deep DNA methylation analyses could greatly help to unravel details of the X-inactivation process and the roles of specific X genes inactivation in disease manifestations. We recently provided evidence that studying DNA methylation at specific autosomic loci at a single-molecule resolution (epiallele distribution analysis) allows one to analyze cell-to-cell methylation differences in a given cell population. We here apply the epiallele analysis at two X-linked loci to investigate whether females show allele-specific epiallelic patterns. Due to the high potential of this approach, the method allows us to obtain clearly distinct allele-specific epiallele profiles

Deep learning to detect significant coronary artery disease from plain chest radiographs AI4CAD

The predictive role of chest radiographs in patients with suspected coronary artery disease (CAD) is underestimated and may benefit from artificial intelligence (AI) applications

Desert dust contribution to PM10 loads in Italy: methods and recommendations addressing the relevant European Commission guidelines in support to the air quality directive 2008/50

In 2011 the European Commission (EC) released specific ‘Guidelines’ describing the methods to quantify and subtract the contribution of natural sources from the PM10 values regulated by the European Air Quality Directive (2008/50/EC). This work investigates the applicability to Italy of the EC-Methodology suggested for desert-dust, describes main limitations encountered and proposes specific modifications embedded within a ‘revised-Methodology’ to extend/improve its use. The revised-Methodology capabilities are evaluated using original, chemically-resolved mineral-dust mass concentration measurements, showing better performances in predicting timing and absolute values of the desert-dust contribution to the daily-PM10 with respect to the current EC-approach. The revised-Methodology is then translated into an automatic (user-independent) tool tailored to the expected final-users. This tool is applied over Central Italy across a 3-year long period (2012–2014), and over the whole Italian country for a calendar year (2012). The derived results confirm and extend to Italian regions never addressed before some previously observed features of the desert-dust impact over the country, such as a clear latitudinal dependence of the desert-dust impact on the yearly average PM10 (from more than 5 μg/m 3 to less than 0.5 μg/m 3 , going from south to north Italy). The modifications introduced within the revised-Methodology also suggest a non-negligible role of desert-dust resuspension in areas characterized by both high traffic levels and soil sealing (urban areas and along the major Italian routes). In the Rome area, such an effect is found to add a contribution of about 2 μg/m 3 (i.e., of 20%) to the mean desert-dust load per dust day (about 10 μg/m 3 ). At the national level, this effect contributes increasing the total number of desert-dust-driven exceedances of the PM10 daily limit value even in the northern regions, where the desert-dust impact on the PM10 yearly average is otherwise limited. These results also indicate the direction for possible mitigation strategies to be applied over impacted areas. The successful implementation of the revised-Methodology over Italy suggests it could represent a valid option for a nationwide standard procedure to quantify the desert-dust contribution to PM10, promoting the homogenisation of the relevant values annually reported to the EC. © 2017 Elsevier Lt