Reactive astrocytes promote proteostasis in Huntington's disease through the JAK2-STAT3 pathway.

Huntington's disease is a fatal neurodegenerative disease characterized by striatal neurodegeneration, aggregation of mutant Huntingtin and the presence of reactive astrocytes. Astrocytes are important partners for neurons and engage in a specific reactive response in Huntington's disease that involves morphological, molecular and functional changes. How reactive astrocytes contribute to Huntington's disease is still an open question, especially because their reactive state is poorly reproduced in experimental mouse models. Here, we show that the JAK2-STAT3 pathway, a central cascade controlling astrocyte reactive response, is activated in the putamen of Huntington's disease patients. Selective activation of this cascade in astrocytes through viral gene transfer reduces the number and size of mutant Huntingtin aggregates in neurons and improves neuronal defects in two complementary mouse models of Huntington's disease. It also reduces striatal atrophy and increases glutamate levels, two central clinical outcomes measured by non-invasive magnetic resonance imaging. Moreover, astrocyte-specific transcriptomic analysis shows that activation of the JAK2-STAT3 pathway in astrocytes coordinates a transcriptional program that increases their intrinsic proteolytic capacity, through the lysosomal and ubiquitin-proteasome degradation systems. This pathway also enhances their production and exosomal release of the co-chaperone DNAJB1, which contributes to mutant Huntingtin clearance in neurons. Together, our results show that the JAK2-STAT3 pathway controls a beneficial proteostasis response in reactive astrocytes in Huntington's disease, which involves bi-directional signalling with neurons to reduce mutant Huntingtin aggregation, eventually improving disease outcomes.

Methylated ccfDNA from plasma biomarkers of Alzheimer's disease using targeted bisulfite sequencing.

Aim: Noninvasive biomarkers such as methylated ccfDNA from plasma could help to support the diagnosis of Alzheimer's disease (AD). Methods: A targeted sequencing protocol was developed to identify candidate biomarkers of AD in methylated ccfDNA extracted from plasma. Results: The authors identified differentially methylated CpGs, regions of which were the same as those identified in previous AD studies. Specifically, a differentially methylated CpG of the LHX2 gene previously identified in a plasma study of AD was replicated in the study. The MBP and DUSP22 regions have been identified in other brain studies of AD and in the authors' study. Conclusion: Although these biomarkers must be validated in other cohorts, methylated ccfDNA could be a relevant noninvasive biomarker in AD.

Currently, the diagnosis of Alzheimer's disease (AD) is based on symptoms and medical imaging, and definitive clinical diagnosis is only possible postmortem. The identification of noninvasive biomarkers such as methylated ccfDNA is crucial for the diagnosis, prognosis and monitoring of AD. However, the analysis of ccfDNA from plasma is a challenge because it is highly fragmented and present in low amounts and originates from various tissues. The authors developed a targeted sequencing protocol using genes previously reported in AD literature (brain, blood and plasma) to identify potential noninvasive biomarkers in plasma. The authors identified positions identical to those in the literature as well as potential novel sites located in the promoter, exon and intron regions of these genes. Although these results must be validated in a large cohort, methylated ccfDNA could be a useful noninvasive biomarker for AD.

DEVEA: an interactive shiny application for Differential Expression analysis, data Visualization and Enrichment Analysis of transcriptomics data.

We are at a time of considerable growth in the use and development of transcriptomics studies and subsequent in silico analysis. RNA sequencing is one of the most widely used approaches, now integrated in many studies.  The processing of these data may typically require a noteworthy number of steps, statistical knowledge, and coding skills which is not accessible to all scientists. Despite the undeniable development of software applications over the years to address this concern, it is still possible to improve.  Here we present DEVEA, an R shiny application tool developed to perform differential expression analysis, data visualization and enrichment pathway analysis mainly from transcriptomics data, but also from simpler gene lists with or without statistical values.  Its intuitive and easy-to-manipulate interface facilitates gene expression exploration through numerous interactive figures and tables, statistical comparisons of expression profile levels between groups and further meta-analysis such as enrichment analysis, without bioinformatics expertise. DEVEA performs a thorough analysis from multiple and flexible input data representing distinct analysis stages. From them, it produces dynamic graphs and tables, to explore the expression levels and statistical differential expression analysis results. Moreover, it generates a comprehensive pathway analysis to extend biological insights. Finally, a complete and customizable HTML report can be extracted for further result exploration outside the application. DEVEA is accessible at https://shiny.imib.es/devea/ and the source code is available on our GitHub repository https://github.com/MiriamRiquelmeP/DEVEA.

Clonally Expanded T Cells Reveal Immunogenicity of Rhabdoid Tumors.

Rhabdoid tumors (RTs) are genomically simple pediatric cancers driven by the biallelic inactivation of SMARCB1, leading to SWI/SNF chromatin remodeler complex deficiency. Comprehensive evaluation of the immune infiltrates of human and mice RTs, including immunohistochemistry, bulk RNA sequencing and DNA methylation profiling studies showed a high rate of tumors infiltrated by T and myeloid cells. Single-cell RNA (scRNA) and T cell receptor sequencing highlighted the heterogeneity of these cells and revealed therapeutically targetable exhausted effector and clonally expanded tissue resident memory CD8+ T subpopulations, likely representing tumor-specific cells. Checkpoint blockade therapy in an experimental RT model induced the regression of established tumors and durable immune responses. Finally, we show that one mechanism mediating RTs immunogenicity involves SMARCB1-dependent re-expression of endogenous retroviruses and interferon-signaling activation.