NSD1 mutations deregulate transcription and DNA methylation of bivalent developmental genes in Sotos syndrome.

Sotos syndrome (SS), the most common overgrowth with intellectual disability (OGID) disorder, is caused by inactivating germline mutations of NSD1, which encodes a histone H3 lysine 36 methyltransferase. To understand how NSD1 inactivation deregulates transcription and DNA methylation (DNAm), and to explore how these abnormalities affect human development, we profiled transcription and DNAm in SS patients and healthy control individuals. We identified a transcriptional signature that distinguishes individuals with SS from controls and was also deregulated in NSD1-mutated cancers. Most abnormally expressed genes displayed reduced expression in SS; these downregulated genes consisted mostly of bivalent genes and were enriched for regulators of development and neural synapse function. DNA hypomethylation was strongly enriched within promoters of transcriptionally deregulated genes: overexpressed genes displayed hypomethylation at their transcription start sites while underexpressed genes featured hypomethylation at polycomb binding sites within their promoter CpG island shores. SS patients featured accelerated molecular aging at the levels of both transcription and DNAm. Overall, these findings indicate that NSD1-deposited H3K36 methylation regulates transcription by directing promoter DNA methylation, partially by repressing polycomb repressive complex 2 (PRC2) activity. These findings could explain the phenotypic similarity of SS to OGID disorders that are caused by mutations in PRC2 complex-encoding genes.

The impact of pre-morbid headaches on headache features and long-term health outcomes following traumatic brain injury: Insights from the American Registry for Migraine Research.

OBJECTIVE: To investigate the impact of having headaches prior to traumatic brain injury (TBI) on headache features and long-term patient health outcomes. BACKGROUND AND METHODS: This was an exploratory analysis of patients with TBI who were enrolled in the American Registry for Migraine Research (ARMR), a multicenter, prospective, longitudinal patient registry composed of patients with International Classification of Headache Disorders, 3rd edition (ICHD-3)-defined headache diagnoses. The ARMR study enrolled 2,707 patients between February 1, 2016 and May 6, 2020, 565 of whom qualified for this analysis. Those with headaches prior to their TBI were compared to those without headaches prior to their TBI for ICHD-3 diagnoses, headache frequency and intensity, headache-related disability (Migraine Disability Assessment score), symptoms of anxiety (General Anxiety Disorder [GAD-7]), depression (two items from Patient Health Questionnaire-9), post-traumatic stress disorder (PTSD), cutaneous allodynia (12-item Allodynia Symptom Checklist [ASC-12]), cognitive dysfunction (Migraine Attacks Subjective Cognitive Impairments Scale [Mig-SCog]), pain interference (Patient-Reported Outcomes Measurement Information System-Pain Interference), and work productivity (Work Productivity and Activity Impairment). RESULTS: Among 565 participants with TBI, 350 had headaches prior to their TBI. Those with pre-TBI headaches were less likely to receive a diagnosis of post-traumatic headache (PTH; 14/350 [4.0%] vs. 21/215 [9.8%], p = 0.006), even though 25.7% reported new or worsening headaches within 7 days of their TBI. Those with pre-TBI headaches had higher ASC-12 scores (2.4 ± 3.5 vs. 1.8 ± 3.4, p = 0.030), Mig-SCog scores (9.3 ± 4.7 vs. 8 ± 4.9, p = 0.004), and GAD-7 scores (6.9 ± 5.1 vs. 6.2 ± 5.4, p = 0.039), and were more likely to have a migraine diagnosis (335/350 [95.7%] vs. 192/215 [89.3%], p = 0.003). CONCLUSIONS: Those with headaches prior to TBI are less likely to receive a diagnosis of PTH. They have more severe symptoms of cutaneous allodynia, cognitive impairment, and generalized anxiety. This analysis suggests that pre-TBI headaches might impact post-TBI headache diagnoses and associated features.

The impact of DNA methylation on the cancer proteome.

Aberrant DNA methylation disrupts normal gene expression in cancer and broadly contributes to oncogenesis. We previously developed MethylMix, a model-based algorithmic approach to identify epigenetically regulated driver genes. MethylMix identifies genes where methylation likely executes a functional role by using transcriptomic data to select only methylation events that can be linked to changes in gene expression. However, given that proteins more closely link genotype to phenotype recent high-throughput proteomic data provides an opportunity to more accurately identify functionally relevant abnormal methylation events. Here we present a MethylMix analysis that refines nominations for epigenetic driver genes by leveraging quantitative high-throughput proteomic data to select only genes where DNA methylation is predictive of protein abundance. Applying our algorithm across three cancer cohorts we find that using protein abundance data narrows candidate nominations, where the effect of DNA methylation is often buffered at the protein level. Next, we find that MethylMix genes predictive of protein abundance are enriched for biological processes involved in cancer including functions involved in epithelial and mesenchymal transition. Moreover, our results are also enriched for tumor markers which are predictive of clinical features like tumor stage and we find clustering using MethylMix genes predictive of protein abundance captures cancer subtypes.

MethylMix 2.0: an R package for identifying DNA methylation genes.

Summary: DNA methylation is an important mechanism regulating gene transcription, and its role in carcinogenesis has been extensively studied. Hyper and hypomethylation of genes is a major mechanism of gene expression deregulation in a wide range of diseases. At the same time, high-throughput DNA methylation assays have been developed generating vast amounts of genome wide DNA methylation measurements. We developed MethylMix, an algorithm implemented in R to identify disease specific hyper and hypomethylated genes. Here we present a new version of MethylMix that automates the construction of DNA-methylation and gene expression datasets from The Cancer Genome Atlas (TCGA). More precisely, MethylMix 2.0 incorporates two major updates: the automated downloading of DNA methylation and gene expression datasets from TCGA and the automated preprocessing of such datasets: value imputation, batch correction and CpG sites clustering within each gene. The resulting datasets can subsequently be analyzed with MethylMix to identify transcriptionally predictive methylation states. We show that the Differential Methylation Values created by MethylMix can be used for cancer subtyping. Availability and implementation: MethylMix 2.0 was implemented as an R package and is available in bioconductor. https://www.bioconductor.org/packages/release/bioc/html/MethylMix.html.

Development of prognostic signatures for intermediate-risk papillary thyroid cancer.

BACKGROUND: The incidence of Papillary thyroid carcinoma (PTC), the most common type of thyroid malignancy, has risen rapidly worldwide. PTC usually has an excellent prognosis. However, the rising incidence of PTC, due at least partially to widespread use of neck imaging studies with increased detection of small cancers, has created a clinical issue of overdiagnosis, and consequential overtreatment. We investigated how molecular data can be used to develop a prognostics signature for PTC. METHODS: The Cancer Genome Atlas (TCGA) recently reported on the genomic landscape of a large cohort of PTC cases. In order to decrease unnecessary morbidity associated with over diagnosing PTC patient with good prognosis, we used TCGA data to develop a gene expression signature to distinguish between patients with good and poor prognosis. We selected a set of clinical phenotypes to define an 'extreme poor' prognosis group and an 'extreme good' prognosis group and developed a gene signature that characterized these. RESULTS: We discovered a gene expression signature that distinguished the extreme good from extreme poor prognosis patients. Next, we applied this signature to the remaining intermediate risk patients, and show that they can be classified in clinically meaningful risk groups, characterized by established prognostic disease phenotypes. Analysis of the genes in the signature shows many known and novel genes involved in PTC prognosis. CONCLUSIONS: This work demonstrates that using a selection of clinical phenotypes and treatment variables, it is possible to develop a statistically useful and biologically meaningful gene signature of PTC prognosis, which may be developed as a biomarker to help prevent overdiagnosis.

Chronic migraine is associated with reduced corneal nerve fiber density and symptoms of dry eye.

BACKGROUND: We used in vivo corneal confocal microscopy to investigate structural differences in the sub-basal corneal nerve plexus in chronic migraine patients and a normal population. We used a validated questionnaire and tests of lacrimal function to determine the prevalence of dry eye in the same group of chronic migraine patients. Activation of the trigeminal system is involved in migraine. Corneal nociceptive sensation is mediated by trigeminal axons that synapse in the gasserian ganglion and the brainstem, and serve nociceptive, protective, and trophic functions. Noninvasive imaging of the corneal sub-basal nerve plexus is possible with in vivo corneal confocal microscopy. METHODS: For this case-control study, we recruited chronic migraine patients and compared them with a sex- and age-similar group of control subjects. Patients with peripheral neuropathy, a disease known to be associated with a peripheral neuropathy, or prior corneal or intraocular surgery were excluded. Participants underwent in vivo corneal confocal microscopy using a Heidelberg Retinal Tomography III confocal microscope with a Rostock Cornea Module. Nerve fiber length, nerve branch density, nerve fiber density, and tortuosity coefficient were measured using established methodologies. Migraine participants underwent testing of basal tear production with proparacaine, corneal sensitivity assessment with a cotton-tip applicator, measurement of tear break-up time, and completion of a validated dry eye questionnaire. RESULTS: A total of 19 chronic migraine patients and 30 control participants completed the study. There were no significant differences in age or sex. Nerve fiber density was significantly lower in migraine patients compared with controls (48.4 ± 23.5 vs. 71.0 ± 15.0 fibers/mm2 , P < .001). Nerve fiber length was decreased in the chronic migraine group compared with the control group, but this difference was not statistically significant (21.5 ± 11.8 vs. 26.8 ± 5.9 mm/mm2, P < .084). Nerve branch density was similar in the two groups (114.0 ± 92.4 vs. 118.1 ± 55.9 branches/mm2 , P < .864). Tortuosity coefficient and log tortuosity coefficient also were similar in the chronic migraine and control groups. All migraine subjects had symptoms consistent with a diagnosis of dry eye syndrome. CONCLUSIONS: We found that in the sample used in this study, the presence of structural changes in nociceptive corneal axons lends further support to the hypothesis that the trigeminal system plays a critical role in the pathogenesis of migraine. In vivo corneal confocal microscopy holds promise as a biomarker for future migraine research as well as for studies examining alterations of corneal innervation. Dry eye symptoms appear to be extremely prevalent in this population. The interrelationships between migraine, corneal nerve architecture, and dry eye will be the subject of future investigations.

Expression of GBGT1 is epigenetically regulated by DNA methylation in ovarian cancer cells.

BACKGROUND: The GBGT1 gene encodes the globoside alpha-1,3-N-acetylgalactosaminyltransferase 1. This enzyme catalyzes the last step in the multi-step biosynthesis of the Forssman (Fs) antigen, a pentaglycosyl ceramide of the globo series glycosphingolipids. While differential GBGT1 mRNA expression has been observed in a variety of human tissues being highest in placenta and ovary, the expression of GBGT1 and the genes encoding the glycosyltransferases and glycosidases involved in the biosynthesis of Fs as well as the possible involvement of DNA methylation in transcriptional regulation of GBGT1 expression have not yet been investigated. RESULTS: RT-qPCR profiling showed high GBGT1 expression in normal ovary surface epithelial (HOSE) cell lines and low GBGT1 expression in all (e.g. A2780, SKOV3) except one (OVCAR3) investigated ovarian cancer cell lines, a finding that was confirmed by Western blot analysis. Hierarchical cluster analysis showed that GBGT1 was even the most variably expressed gene of Fs biosynthesis-relevant glycogenes and among the investigated cell lines, whereas NAGA which encodes the alpha-N-acetylgalactosaminidase hydrolyzing Fs was not differentially expressed. Bisulfite- and COBRA-analysis of the CpG island methylation status in the GBGT1 promoter region demonstrated high or intermediate levels of GBGT1 DNA methylation in all ovarian cancer cell lines (except for OVCAR3) but marginal levels of DNA methylation in the two HOSE cell lines. The extent of DNA methylation inversely correlated with GBGT1 mRNA and protein expression. Bioinformatic analysis of GBGT1 in The Cancer Genome Atlas ovarian cancer dataset demonstrated that this inverse correlation was also found in primary ovarian cancer tissue samples confirming our cell line-based findings. Restoration of GBGT1 mRNA and protein expression in low GBGT1-expressing A2780 cells was achieved by 5-aza-2'-deoxycytidine treatment and these treated cells exhibited increased helix pomatia agglutinin-staining, reflecting the elevated presence of Fs disaccharide on these cells. CONCLUSIONS: GBGT1 expression is epigenetically silenced through promoter hypermethylation in ovarian cancer. Our findings not only suggest an involvement of DNA methylation in the synthesis of Fs antigen but may also explain earlier studies showing differential GBGT1 expression in various human tissue samples and disease stages.

Association of School Instructional Mode with Community COVID-19 Incidence during August-December 2020 in Cuyahoga County, Ohio.

Remote and hybrid modes of instruction were employed as alternatives to in-person instruction as part of early mitigation efforts in response to the COVID-19 pandemic. We investigated the impact of a public school district's instructional mode on cumulative incidence and transmission in the surrounding community by employing a generalized estimating equations approach to estimate the association with weekly COVID-19 case counts by zip code in Cuyahoga County, Ohio, from August to December 2020. Remote instruction only (RI) was employed by 7 of 20 school districts; 13 used some non-remote instruction (NRI) (2-15 weeks). Weekly incidence increased in all zip codes from August to peak in late fall before declining. The zip code cumulative incidence within NRI school districts was higher than in those offering only RI (risk ratio = 1.12, p = 0.01; risk difference = 519 per 100,000, 95% confidence interval (123-519)). The mean effect for NRI on emergent cases 2 weeks after mode exposure, controlling for Social Vulnerability Index (SVI), was significant only for high SVI zip codes 1.30, p < 0.001. NRI may be associated with increased community COVID-19 incidence, particularly in communities with high SVI. Vulnerable communities may need more resources to open schools safely.

Gene expression and epigenetic discovery screen reveal methylation of SFRP2 in prostate cancer.

Aberrant activation of Wnts is common in human cancers, including prostate. Hypermethylation associated transcriptional silencing of Wnt antagonist genes SFRPs (Secreted Frizzled-Related Proteins) is a frequent oncogenic event. The significance of this is not known in prostate cancer. The objectives of our study were to (i) profile Wnt signaling related gene expression and (ii) investigate methylation of Wnt antagonist genes in prostate cancer. Using TaqMan Low Density Arrays, we identified 15 Wnt signaling related genes with significantly altered expression in prostate cancer; the majority of which were upregulated in tumors. Notably, histologically benign tissue from men with prostate cancer appeared more similar to tumor (r = 0.76) than to benign prostatic hyperplasia (BPH; r = 0.57, p < 0.001). Overall, the expression profile was highly similar between tumors of high (≥ 7) and low (≤ 6) Gleason scores. Pharmacological demethylation of PC-3 cells with 5-Aza-CdR reactivated 39 genes (≥ 2-fold); 40% of which inhibit Wnt signaling. Methylation frequencies in prostate cancer were 10% (2/20) (SFRP1), 64.86% (48/74) (SFRP2), 0% (0/20) (SFRP4) and 60% (12/20) (SFRP5). SFRP2 methylation was detected at significantly lower frequencies in high-grade prostatic intraepithelial neoplasia (HGPIN; 30%, (6/20), p = 0.0096), tumor adjacent benign areas (8.82%, (7/69), p < 0.0001) and BPH (11.43% (4/35), p < 0.0001). The quantitative level of SFRP2 methylation (normalized index of methylation) was also significantly higher in tumors (116) than in the other samples (HGPIN = 7.45, HB = 0.47, and BPH = 0.12). We show that SFRP2 hypermethylation is a common event in prostate cancer. SFRP2 methylation in combination with other epigenetic markers may be a useful biomarker of prostate cancer.

EpiMix: an integrative tool for epigenomic subtyping using DNA methylation.

DNA methylation (DNAme) is a major epigenetic factor influencing gene expression with alterations leading to cancer, immunological, and cardiovascular diseases. Recent technological advances enable genome-wide quantification of DNAme in large human cohorts. So far, existing methods have not been evaluated to identify differential DNAme present in large and heterogeneous patient cohorts. We developed an end-to-end analytical framework named "EpiMix" for population-level analysis of DNAme and gene expression. Compared to existing methods, EpiMix showed higher sensitivity in detecting abnormal DNAme that was present in only small patient subsets. We extended the model-based analyses of EpiMix to cis-regulatory elements within protein-coding genes, distal enhancers, and genes encoding microRNAs and lncRNAs. Using cell-type specific data from two separate studies, we discovered novel epigenetic mechanisms underlying childhood food allergy and survival-associated, methylation-driven non-coding RNAs in non-small cell lung cancer.

EpiMix is an integrative tool for epigenomic subtyping using DNA methylation.

DNA methylation (DNAme) is a major epigenetic factor influencing gene expression with alterations leading to cancer and immunological and cardiovascular diseases. Recent technological advances have enabled genome-wide profiling of DNAme in large human cohorts. There is a need for analytical methods that can more sensitively detect differential methylation profiles present in subsets of individuals from these heterogeneous, population-level datasets. We developed an end-to-end analytical framework named "EpiMix" for population-level analysis of DNAme and gene expression. Compared with existing methods, EpiMix showed higher sensitivity in detecting abnormal DNAme that was present in only small patient subsets. We extended the model-based analyses of EpiMix to cis-regulatory elements within protein-coding genes, distal enhancers, and genes encoding microRNAs and long non-coding RNAs (lncRNAs). Using cell-type-specific data from two separate studies, we discover epigenetic mechanisms underlying childhood food allergy and survival-associated, methylation-driven ncRNAs in non-small cell lung cancer.

Identifying key multifunctional components shared by critical cancer and normal liver pathways via SparseGMM.

Despite the abundance of multimodal data, suitable statistical models that can improve our understanding of diseases with genetic underpinnings are challenging to develop. Here, we present SparseGMM, a statistical approach for gene regulatory network discovery. SparseGMM uses latent variable modeling with sparsity constraints to learn Gaussian mixtures from multiomic data. By combining coexpression patterns with a Bayesian framework, SparseGMM quantitatively measures confidence in regulators and uncertainty in target gene assignment by computing gene entropy. We apply SparseGMM to liver cancer and normal liver tissue data and evaluate discovered gene modules in an independent single-cell RNA sequencing (scRNA-seq) dataset. SparseGMM identifies PROCR as a regulator of angiogenesis and PDCD1LG2 and HNF4A as regulators of immune response and blood coagulation in cancer. Furthermore, we show that more genes have significantly higher entropy in cancer compared with normal liver. Among high-entropy genes are key multifunctional components shared by critical pathways, including p53 and estrogen signaling.

Targeting KDM2A Enhances T-cell Infiltration in NSD1-Deficient Head and Neck Squamous Cell Carcinoma.

In head and neck squamous cell carcinoma (HNSCC), a significant proportion of tumors have inactivating mutations in the histone methyltransferase NSD1. In these tumors, NSD1 inactivation is a driver of T-cell exclusion from the tumor microenvironment (TME). A better understanding of the NSD1-mediated mechanism regulating infiltration of T cells into the TME could help identify approaches to overcome immunosuppression. Here, we demonstrated that NSD1 inactivation results in lower levels of H3K36 dimethylation and higher levels of H3K27 trimethylation, the latter being a known repressive histone mark enriched on the promoters of key T-cell chemokines CXCL9 and CXCL10. HNSCC with NSD1 mutations had lower levels of these chemokines and lacked responses to PD-1 immune checkpoint blockade. Inhibition of KDM2A, the primary lysine demethylase that is selective for H3K36, reversed the altered histone marks induced by NSD1 loss and restored T-cell infiltration into the TME. Importantly, KDM2A suppression decreased growth of NSD1-deficient tumors in immunocompetent, but not in immunodeficient, mice. Together, these data indicate that KDM2A is an immunotherapeutic target for overcoming immune exclusion in HNSCC. SIGNIFICANCE: The altered epigenetic landscape of NSD1-deficient tumors confers sensitivity to inhibition of the histone-modifying enzyme KDM2A as an immunotherapeutic strategy to stimulate T-cell infiltration and suppress tumor growth.

Loss of p53-DREAM-mediated repression of cell cycle genes as a driver of lymph node metastasis in head and neck cancer.

BACKGROUND: The prognosis for patients with head and neck cancer (HNC) is poor and has improved little in recent decades, partially due to lack of therapeutic options. To identify effective therapeutic targets, we sought to identify molecular pathways that drive metastasis and HNC progression, through large-scale systematic analyses of transcriptomic data. METHODS: We performed meta-analysis across 29 gene expression studies including 2074 primary HNC biopsies to identify genes and transcriptional pathways associated with survival and lymph node metastasis (LNM). To understand the biological roles of these genes in HNC, we identified their associated cancer pathways, as well as the cell types that express them within HNC tumor microenvironments, by integrating single-cell RNA-seq and bulk RNA-seq from sorted cell populations. RESULTS: Patient survival-associated genes were heterogenous and included drivers of diverse tumor biological processes: these included tumor-intrinsic processes such as epithelial dedifferentiation and epithelial to mesenchymal transition, as well as tumor microenvironmental factors such as T cell-mediated immunity and cancer-associated fibroblast activity. Unexpectedly, LNM-associated genes were almost universally associated with epithelial dedifferentiation within malignant cells. Genes negatively associated with LNM consisted of regulators of squamous epithelial differentiation that are expressed within well-differentiated malignant cells, while those positively associated with LNM represented cell cycle regulators that are normally repressed by the p53-DREAM pathway. These pro-LNM genes are overexpressed in proliferating malignant cells of TP53 mutated and HPV + ve HNCs and are strongly associated with stemness, suggesting that they represent markers of pre-metastatic cancer stem-like cells. LNM-associated genes are deregulated in high-grade oral precancerous lesions, and deregulated further in primary HNCs with advancing tumor grade and deregulated further still in lymph node metastases. CONCLUSIONS: In HNC, patient survival is affected by multiple biological processes and is strongly influenced by the tumor immune and stromal microenvironments. In contrast, LNM appears to be driven primarily by malignant cell plasticity, characterized by epithelial dedifferentiation coupled with EMT-independent proliferation and stemness. Our findings postulate that LNM is initially caused by loss of p53-DREAM-mediated repression of cell cycle genes during early tumorigenesis.

SMYD3 represses tumor-intrinsic interferon response in HPV-negative squamous cell carcinoma of the head and neck.

Cancers often display immune escape, but the mechanisms are incompletely understood. Herein, we identify SMYD3 as a mediator of immune escape in human papilloma virus (HPV)-negative head and neck squamous cell carcinoma (HNSCC), an aggressive disease with poor response to immunotherapy with pembrolizumab. SMYD3 depletion induces upregulation of multiple type I interferon (IFN) response and antigen presentation machinery genes in HNSCC cells. Mechanistically, SMYD3 binds to and regulates the transcription of UHRF1, encoding for a reader of H3K9me3, which binds to H3K9me3-enriched promoters of key immune-related genes, recruits DNMT1, and silences their expression. SMYD3 further maintains the repression of immune-related genes through intragenic deposition of H4K20me3. In vivo, Smyd3 depletion induces influx of CD8+ T cells and increases sensitivity to anti-programmed death 1 (PD-1) therapy. SMYD3 overexpression is associated with decreased CD8 T cell infiltration and poor response to neoadjuvant pembrolizumab. These data support combining SMYD3 depletion strategies with checkpoint blockade to overcome anti-PD-1 resistance in HPV-negative HNSCC.

Peripheral blood DNA methylation profiles predict future development of B-cell Non-Hodgkin Lymphoma.

Lack of accurate methods for early lymphoma detection limits the ability to cure patients. Since patients with Non-Hodgkin lymphomas (NHL) who present with advanced disease have worse outcomes, accurate and sensitive methods for early detection are needed to improve patient care. We developed a DNA methylation-based prediction tool for NHL, based on blood samples collected prospectively from 278 apparently healthy patients who were followed for up to 16 years to monitor for NHL development. A predictive score was developed using machine learning methods in a robust training/validation framework. Our predictive score incorporates CpG DNA methylation at 135 genomic positions, with higher scores predicting higher risk. It was 85% and 78% accurate for identifying patients at risk of developing future NHL, in patients with high or low epigenetic mitotic clock respectively, in a validation cohort. It was also sensitive at detecting active NHL (96.3% accuracy) and healthy status (95.6% accuracy) in additional independent cohorts. Scores optimized for specific NHL subtypes showed significant but lower accuracy for predicting other subtypes. Our score incorporates hyper-methylation of Polycomb and HOX genes, which have roles in NHL development, as well as PAX5 - a master transcriptional regulator of B-cell fate. Subjects with higher risk scores showed higher regulatory T-cells, memory B-cells, but lower naïve T helper lymphocytes fractions in the blood. Future prospective studies will be required to confirm the utility of our signature for managing patients who are at high risk for developing future NHL.

Accurate detection of benign and malignant renal tumor subtypes with MethylBoostER: An epigenetic marker-driven learning framework.

Current gold standard diagnostic strategies are unable to accurately differentiate malignant from benign small renal masses preoperatively; consequently, 20% of patients undergo unnecessary surgery. Devising a more confident presurgical diagnosis is key to improving treatment decision-making. We therefore developed MethylBoostER, a machine learning model leveraging DNA methylation data from 1228 tissue samples, to classify pathological subtypes of renal tumors (benign oncocytoma, clear cell, papillary, and chromophobe RCC) and normal kidney. The prediction accuracy in the testing set was 0.960, with class-wise ROC AUCs >0.988 for all classes. External validation was performed on >500 samples from four independent datasets, achieving AUCs >0.89 for all classes and average accuracies of 0.824, 0.703, 0.875, and 0.894 for the four datasets. Furthermore, consistent classification of multiregion samples (N = 185) from the same patient demonstrates that methylation heterogeneity does not limit model applicability. Following further clinical studies, MethylBoostER could facilitate a more confident presurgical diagnosis to guide treatment decision-making in the future.

Biphasic direct current shift, haemoglobin desaturation and neurovascular uncoupling in cortical spreading depression.

Cortical spreading depression is a propagating wave of depolarization that plays important roles in migraine, stroke, subarachnoid haemorrhage and brain injury. Cortical spreading depression is associated with profound vascular changes that may be a significant factor in the clinical response to cortical spreading depression events. We used a combination of optical intrinsic signal imaging, electro-physiology, potassium sensitive electrodes and spectroscopy to investigate neurovascular changes associated with cortical spreading depression in the mouse. We identified two distinct phases of altered neurovascular function, one during the propagating cortical spreading depression wave and a second much longer phase after passage of the wave. The direct current shift associated with the cortical spreading depression wave was accompanied by marked arterial constriction and desaturation of cortical haemoglobin. After recovery from the initial cortical spreading depression wave, we observed a second phase of prolonged, negative direct current shift, arterial constriction and haemoglobin desaturation, lasting at least an hour. Persistent disruption of neurovascular coupling was demonstrated by a loss of coherence between electro-physiological activity and perfusion. Extracellular potassium concentration increased during the cortical spreading depression wave, but recovered and remained at baseline after passage of the wave, consistent with different mechanisms underlying the first and second phases of neurovascular dysfunction. These findings indicate that cortical spreading depression is associated with a multiphasic alteration in neurovascular function, including a novel second direct current shift accompanied by arterial constriction and decrease in tissue oxygen supply, that is temporally and mechanistically distinct from the initial propagated cortical spreading depression wave. Vascular/metabolic uncoupling with cortical spreading depression may have important clinical consequences, and the different phases of dysfunction may represent separate therapeutic targets in the disorders where cortical spreading depression occurs.

Characterization of community-wide transmission of SARS-CoV-2 in congregate living settings and local public health-coordinated response during the initial phase of the COVID-19 pandemic.

BACKGROUND: Clusters of COVID-19 cases amplify the pandemic and are critical targets for intervention, but comprehensive cluster-level data are not collected systematically by federal or most state public health entities. This analysis characterizes COVID-19 clusters among vulnerable populations housed in congregate living settings across an entire community and describes early mitigation efforts. METHODS: The Cuyahoga County Board of Health identified and interviewed COVID-19 cases and exposed contacts, assessing possible connections to congregate living facilities within its jurisdiction from March 7, 2020, to May 15, 2020, during the first phase of the pandemic, while state of Ohio stay-at-home orders were in effect. A multi-disciplinary team-based response network was mobilized to support active case finding and develop facility-focused containment strategies. RESULTS: We identified a cascade of 45 COVID-19 clusters across community facilities (corrections, nursing, assisted living, intermediate care, extended treatment, shelters, group homes). Attack rates were highest within small facilities (P < .01) and large facilities requiring extensive support to implement effective containment measures. For 25 clusters, we identified an index case who frequently (88%) was a healthcare worker. Engagement of clinical, community, and government partners through public health coordination efforts created opportunities to rapidly develop and coordinate effective response strategies to support the facilities facing the dawning impact of the pandemic. CONCLUSIONS: Active cluster investigations can uncover the dynamics of community transmission affecting both residents of congregate settings and their caregivers and help to target efforts toward populations with ongoing challenges in access to detection and control resources.

Bradykinin increases resensitization of purinergic receptor signaling in glioma cells.

BACKGROUND: Purinergic receptor-mediated signaling plays an important role in the function of glial cells, including glial tumor cells. Bradykinin is also an important paracrine mediator which is highly expressed in brain tumors and may correlate with their pathological grade. Interaction between bradykinin and purinergic signaling may therefore be involved in the regulation of glial tumor cells. RESULTS: We examined the effect of bradykinin on glial purinergic signaling in an immortalized glioma cell line. Confocal calcium imaging revealed that ATP evokes an increase in [Ca2+]i in the U87 human astrocytoma cell line. This response was reduced with repetitive application of ATP, likely due to receptor desensitization. However exposure to bradykinin increased the Ca2+ response to a second application of ATP, consistent with increased resensitization. The bradykinin effect on resensitization was similar in the absence of extracellular Ca2+ or in the presence of the PKC activator PMA, but was inhibited by the protein phosphatase inhibitor okadaic acid and the PI3K inhibitor LY294002. CONCLUSIONS: Modulation of protein phosphatases and the PI3K pathway may represent a mechanism by which bradykinin potentiates purinergic signaling in glial cells.