Opioid abuse is now the most common cause of accidental death in the US. Although opioids and most other drugs of abuse acutely increase signaling mediated by midbrain dopamine (DA)-synthesizing neurons, little is known about long-lasting changes in DA cells that may contribute to continued opioid abuse, craving, and relapse. A better understanding of the molecular and cellular bases of opioid abuse could lead to advancements in therapeutics. This study comprises, to our knowledge, the first unbiased examination of genome-wide changes in midbrain gene expression associated with human opioid abuse. Our analyses identified differentially expressed genes and distinct gene networks associated with opioid abuse, specific genes with predictive capability for subject assignment to the opioid abuse cohort, and genes most similarly affected in chronic opioid and cocaine abusers. We also identified differentially expressed long noncoding RNAs capable of regulating known drug-responsive protein-coding genes. Opioid-regulated genes identified in this study warrant further investigation as potential biomarkers and/or therapeutic targets for human substance abuse.
Macrophages in SHH subgroup medulloblastoma display dynamic heterogeneity that varies with treatment modality Graphical abstract Highlights d Sonic Hedgehog (SHH) subgroup of medulloblastoma (MB) recruits diverse macrophages d Radiation or molecular-targeted therapy alters macrophage distribution in SHH-MB d Radiation recruits immunosuppressive monocyte-derived macrophages (TAMoMacs) in SHH-MB d Radiation-induced TAMoMacs regulate CD8 T cell and neutrophil numbers in SHH-MB
Maintenance of the drug-addicted state is thought to involve changes in gene expression in different neuronal cell types and neural circuits. Midbrain dopamine (DA) neurons in particular mediate numerous responses to drugs of abuse. Long noncoding RNAs (lncRNAs) regulate CNS gene expression through a variety of mechanisms, but next to nothing is known about their role in drug abuse. The proportion of lncRNAs that are primate-specific provides a strong rationale for their study in human drug abusers. In this study, we determined a profile of dysregulated putative lncRNAs through the analysis of postmortem human midbrain specimens from chronic cocaine abusers and well-matched control subjects (n=11 in each group) using a custom lncRNA microarray. A dataset comprising 32 well-annotated lncRNAs with independent evidence of brain expression and robust differential expression in cocaine abusers is presented. For a subset of these lncRNAs, differential expression was validated by quantitative real-time PCR and cellular localization determined by in situ hybridization histochemistry. Examples of lncRNAs exhibiting DA cell-specific expression, different subcellular distributions, and covariance of expression with known cocaine-regulated protein-coding genes were identified. These findings implicate lncRNAs in the cellular responses of human DA neurons to chronic cocaine abuse.
The development of new therapeutic strategies for the treatment of complex brain disorders such as drug addiction is likely to be advanced by a more complete understanding of the underlying molecular pathophysiology. Although the study of postmortem human brain represents a unique resource in this regard, it can be challenging to disentangle the relative contribution of chronic pathological processes versus perimortem events to the observed changes in gene expression. To begin to unravel this issue, we analyzed by quantitative PCR the midbrain expression of numerous candidate genes previously associated with cocaine abuse. Data obtained from chronic cocaine abusers (and matched control subjects) dying of gunshot wounds were compared with a prior study of subjects with deaths directly attributable to cocaine abuse. Most of the genes studied (i.e., tyrosine hydroxylase, dopamine transporter, forkhead box A2, histone variant H3 family 3B, nuclear factor kappa B inhibitor alpha, growth arrest and DNA damage-inducible beta) were found to be differentially expressed in chronic cocaine abusers irrespective of immediate cause of death or perimortem levels of cocaine, suggesting that these may represent core pathophysiological changes arising with chronic drug abuse. On the other hand, chemokine C-C motif ligand 2 and jun proto-oncogene expression were unaffected in cocaine-abusing subjects dying of gunshot wounds, in contrast to the differential expression previously reported in cocaine-related fatalities. The possible influence of cause of death and other factors on the cocaine-responsiveness of these genes is discussed.
Pediatric brain and spinal cancer are the leading disease-related cause of death in children, thus we urgently need curative therapeutic strategies for these tumors. To accelerate such discoveries, the Children's Brain Tumor Network and Pacific Pediatric Neuro-Oncology Consortium created a systematic process for tumor biobanking, model generation, and sequencing with immediate access to harmonized data. We leverage these data to create OpenPBTA, an open collaborative project which establishes over 40 scalable analysis modules to genomically characterize 1,074 pediatric brain tumors. Transcriptomic classification reveals that TP53 loss is a significant marker for poor overall survival in ependymomas and H3 K28-altered diffuse midline gliomas and further identifies universal TP53 dysregulation in mismatch repair-deficient hypermutant high-grade gliomas. OpenPBTA is a foundational analysis platform actively being applied to other pediatric cancers and inform molecular tumor board decision-making, making it an invaluable resource to the pediatric oncology community.
Opioid abuse is now the primary cause of accidental deaths in the United States. Studies over several decades established the cyclical nature of abused drugs of choice, with a current resurgence of heroin abuse and, more recently, fentanyl’s emergence as a major precipitant of drug-related deaths. To better understand abuse trends and to explore the potential lethality of specific drug–drug interactions, we conducted statistical analyses of forensic toxicological data from the Wayne County Medical Examiner’s Office from 2012–2016. We observed clear changes in opioid abuse over this period, including the rapid emergence of fentanyl and its analogs as highly significant causes of lethality starting in 2014. We then used Chi-square Automatic Interaction Detector (CHAID)-based decision tree analyses to obtain insights regarding specific drugs, drug combinations, and biomarkers in blood most predictive of cause of death or circumstances surrounding death. The presence of the non-opioid drug acetaminophen was highly predictive of drug-related deaths, likely reflecting the abuse of various combined acetaminophen-opioid formulations. The short-lived cocaine adulterant levamisole was highly predictive of a short post-cocaine survival time preceding sudden non-drug-related death. The combination of the opioid methadone and the antidepressant citalopram was uniformly linked to drug death, suggesting a potential drug–drug interaction at the level of a pathophysiological effect on the heart and/or drug metabolism. The presence of fentanyl plus the benzodiazepine midazolam was diagnostic for in-hospital deaths following serious medical illness and interventions that included these drugs. These data highlight the power of decision tree analyses not only in the determination of cause of death, but also as a key surveillance tool to inform drug abuse treatment and public health policies for combating the opioid crisis.
Epigenetic marks operate at multiple chromosomal levels to regulate gene expression, from direct covalent modification of DNA to three-dimensional chromosomal structure. Research has shown that 5-methylcytosine (5-mC) and its oxidized form, 5-hydroxymethylcytosine (5-hmC), are stable epigenetic marks with distinct genomic distributions and separate regulatory functions. In addition, recent data indicate that 5-hmC plays a critical regulatory role in the mammalian brain, emphasizing the importance of considering this alternative DNA modification in the context of neuroepigenetics. Traditional bisulfite (BS) treatment-based methods to measure the methylome are not able to distinguish between 5-mC and 5-hmC, meaning much of the existing literature does not differentiate these two DNA modifications. Recently developed methods, including Tet-assisted bisulfite treatment and oxidative bisulfite treatment, allow for differentiation of 5-hmC and/or 5-mC levels at base-pair resolution when combined with next-generation sequencing or methylation arrays. Despite these technological advances, there remains a lack of clarity regarding the appropriate statistical methods for integration of 5-mC and 5-hmC data. As a result, it can be difficult to determine the effects of an experimental treatment on 5-mC and 5-hmC dynamics. Here, we propose a statistical approach involving mixed effects to simultaneously model paired 5-mC and 5-hmC data as repeated measures. We tested this approach using publicly available BS/oxidative bisulfite-450K array data and showed that our new approach detected far more CpG probes with paired changes in 5-mC and 5-hmC by Alzheimer’s disease status (n = 14,183 probes) compared with the overlapping differential probes generated from separate models for each epigenetic mark (n = 68). Of note, all 68 of the overlapping probe IDs from the separate models were also significant in our new modeling approach, supporting the sensitivity of our new analysis method. Using the proposed approach, it will be possible to determine the effects of an experimental treatment on both 5-mC and 5-hmC at the base-pair level.
Pediatric brain tumors comprise a heterogeneous molecular and histological landscape that challenges most current precision-medicine approaches. While recent large-scale efforts to molecularly characterize distinct histological entities have dramatically advanced the field’s capacity to classify and further define molecular subtypes, developing therapeutic and less toxic molecularly-defined clinical approaches remains a challenge. To define new approaches to meet these challenges and advance scalable, shared biospecimen- and data-resources for pediatric brain tumors, the Children’s Brain Tumor Network and Pacific Pediatric Neuro-Oncology Consortium, in partnership with the Alex’s Lemonade Stand Foundation Childhood Cancer Data Lab, launched OpenPBTA, a global open science Pediatric Brain Tumor Atlas initiative to comprehensively define the molecular landscape of pediatric brain tumors. The initiative contains multi-modal analyses of research- and clinical-trial based DNA and RNA sequences from nearly 1,000 subjects (with 1,256 tumors) along with their longitudinal clinical data. The OpenPBTA’s open science framework for analysis tests the capacity of crowd-sourced collaborative architectures to advance more rapid, iterative and integrated discovery of the underlying mechanisms of disease across pediatric brain and spinal cord tumors. Since the launch of the project, OpenPBTA has collaboratively created reproducible workflows for integrated consensus SNV, CNV, and fusion calling, enabled RNA-Seq-based classification of medulloblastoma subtypes, and more than 25 additional DNA- and RNA-based analyses. The open-science platform and associated datasets and processed results provide a continuously updated, global view of the integrated cross-disease molecular landscape of pediatric brain tumors. Such biospecimen- and clinically-linked scalable data resources provide unprecedented collaborative opportunities for precision-based, personalized therapeutic discovery and drug development with the upcoming further integration of proteomic sample data (N >300) and drug response datasets, additionally diversifying the multimodal discovery potential of crowd-sourced approaches for accelerated impact for children with brain tumors.
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