Mutation of the co-chaperone Tsc1 in bladder cancer diminishes Hsp90 acetylation and reduces drug sensitivity and selectivity

The molecular chaperone Heat shock protein 90 (Hsp90) is essential for the folding, stability, and activity of several drivers of oncogenesis. Hsp90 inhibitors are currently under clinical evaluation for cancer treatment, however their efficacy is limited by lack of biomarkers to optimize patient selection. We have recently identified the tumor suppressor tuberous sclerosis complex 1 (Tsc1) as a new co-chaperone of Hsp90 that affects Hsp90 binding to its inhibitors. Highly variable mutations of TSC1 have been previously identified in bladder cancer and correlate with sensitivity to the Hsp90 inhibitors. Here we showed loss of TSC1 leads to hypoacetylation of Hsp90-K407/K419 and subsequent decreased binding to the Hsp90 inhibitor ganetespib. Pharmacologic inhibition of histone deacetylases (HDACs) restores acetylation of Hsp90 and sensitizes Tsc1-mutant bladder cancer cells to ganetespib, resulting in apoptosis. Our findings suggest that TSC1 status may predict response to Hsp90 inhibitors in patients with bladder cancer, and co-targeting HDACs can sensitize tumors with Tsc1 mutations to Hsp90 inhibitors

NSAIDs May Protect Against Age-Related Brain Atrophy

The use of non-steroidal anti-inflammatory drugs (NSAIDs) in humans is associated with brain differences including decreased number of activated microglia. In animals, NSAIDs are associated with reduced microglia, decreased amyloid burden, and neuronal preservation. Several studies suggest NSAIDs protect brain regions affected in the earliest stages of AD, including hippocampal and parahippocampal regions. In this cross-sectional study, we examined the protective effect of NSAID use on gray matter volume in a group of middle-aged and older NSAID users (n = 25) compared to non-user controls (n = 50). All participants underwent neuropsychological testing and T1-weighted magnetic resonance imaging. Non-user controls showed smaller volume in portions of the left hippocampus compared to NSAID users. Age-related loss of volume differed between groups, with controls showing greater medial temporal lobe volume loss with age compared to NSAID users. These results should be considered preliminary, but support previous reports that NSAIDs may modulate age-related loss of brain volume

CSF T-Tau/Aβ42 Predicts White Matter Microstructure in Healthy Adults at Risk for Alzheimer’s Disease

Cerebrospinal fluid (CSF) biomarkers T-Tau and Aβ42 are linked with Alzheimer’s disease (AD), yet little is known about the relationship between CSF biomarkers and structural brain alteration in healthy adults. In this study we examined the extent to which AD biomarkers measured in CSF predict brain microstructure indexed by diffusion tensor imaging (DTI) and volume indexed by T1-weighted imaging. Forty-three middle-aged adults with parental family history of AD received baseline lumbar puncture and MRI approximately 3.5 years later. Voxel-wise image analysis methods were used to test whether baseline CSF Aβ42, total tau (T-Tau), phosphorylated tau (P-Tau) and neurofilament light protein predicted brain microstructure as indexed by DTI and gray matter volume indexed by T1-weighted imaging. T-Tau and T-Tau/Aβ42 were widely correlated with indices of brain microstructure (mean, axial, and radial diffusivity), notably in white matter regions adjacent to gray matter structures affected in the earliest stages of AD. None of the CSF biomarkers were related to gray matter volume. Elevated P-Tau and P-Tau/Aβ42 levels were associated with lower recognition performance on the Rey Auditory Verbal Learning Test. Overall, the results suggest that CSF biomarkers are related to brain microstructure in healthy adults with elevated risk of developing AD. Furthermore, the results clearly suggest that early pathological changes in AD can be detected with DTI and occur not only in cortex, but also in white matter

Tumor suppressor Tsc1 is a new Hsp90 co-chaperone that facilitates folding of kinase and non-kinase clients

The tumor suppressors Tsc1 and Tsc2 form the tuberous sclerosis complex (TSC), a regulator of mTOR activity. Tsc1 stabilizes Tsc2; however, the precise mechanism involved remains elusive. The molecular chaperone heat-shock protein 90 (Hsp90) is an essen- tial component of the cellular homeostatic machinery in eukary- otes. Here, we show that Tsc1 is a new co-chaperone for Hsp90 that inhibits its ATPase activity. The C-terminal domain of Tsc1 (998–1,164 aa) forms a homodimer and binds to both protomers of the Hsp90 middle domain. This ensures inhibition of both subunits of the Hsp90 dimer and prevents the activating co- chaperone Aha1 from binding the middle domain of Hsp90. Conversely, phosphorylation of Aha1-Y223 increases its affinity for Hsp90 and displaces Tsc1, thereby providing a mechanism for equilibrium between binding of these two co-chaperones to Hsp90. Our findings establish an active role for Tsc1 as a facilita- tor of Hsp90-mediated folding of kinase and non-kinase clients— including Tsc2—thereby preventing their ubiquitination and proteasomal degradation

Low HDL Cholesterol is Associated with Lower Gray Matter Volume in Cognitively Healthy Adults

Dyslipidemia is common in adults and contributes to high rates of cardiovascular disease and may be linked to subsequent neurodegenerative and neurovascular diseases. This study examined whether lower brain volumes and cognition associated with dyslipidemia could be observed in cognitively healthy adults, and whether apolipoprotein E (APOE) genotype or family history of Alzheimer's disease (FHAD) alters this effect. T1-weighted magnetic resonance imaging was used to examine regional brain gray matter (GM) and white matter (WM) in 183 individuals (58.4 ± 8.0 years) using voxel-based morphometry. A non-parametric multiple linear regression model was used to assess the effect of high-density lipoprotein (HDL) and non-HDL cholesterol, APOE, and FHAD on regional GM and WM volume. A post hoc analysis was used to assess whether any significant correlations found within the volumetric analysis had an effect on cognition. HDL was positively correlated with GM volume in the bilateral temporal poles, middle temporal gyri, temporo-occipital gyri, and left superior temporal gyrus and parahippocampal region. This effect was independent of APOE and FHAD. A significant association between HDL and the Brief Visuospatial Memory Test was found. Additionally, GM volume within the right middle temporal gyrus, the region most affected by HDL, was significantly associated with the Controlled Oral Word Association Test and the Center for Epidemiological Studies Depression Scale. These findings suggest that adults with decreased levels of HDL cholesterol may be experiencing cognitive changes and GM reductions in regions associated with neurodegenerative disease and therefore, may be at greater risk for future cognitive decline

A Statin-Loaded Reconstituted High-Density Lipoprotein Nanoparticle Inhibits Atherosclerotic Plaque Inflammation

Inflammation is a key feature of atherosclerosis and a target for therapy. Statins have potent anti-inflammatory properties but these cannot be fully exploited with oral statin therapy due to low systemic bioavailability. Here we present an injectable reconstituted high-density lipoprotein (rHDL) nanoparticle carrier vehicle that delivers statins to atherosclerotic plaques. We demonstrate the anti-inflammatory effect of statin-rHDL in vitro and show this effect is mediated through inhibition of the mevalonate pathway. We also apply statin-rHDL nanoparticles in vivo in an apolipoprotein E-knockout mouse model of atherosclerosis and show they accumulate in atherosclerotic lesions where they directly affect plaque macrophages. Finally we demonstrate that a three-month low-dose statin-rHDL treatment regimen inhibits plaque inflammation progression, while a one-week high-dose regimen markedly decreases inflammation in advanced atherosclerotic plaques. Statin-rHDL represents a novel potent atherosclerosis nanotherapy that directly affects plaque inflammation

N6-Methyladenosine Inhibits Local Ribonucleolytic Cleavage to Stabilize mRNAs in Arabidopsis

N6-methyladenosine (m6A) is a dynamic, reversible, covalently modified ribonucleotide that occurs predominantly toward 30 ends of eukaryotic mRNAs and is essential for their proper function and regulation. In Arabidopsis thaliana, many RNAs contain at least one m6A site, yet the transcriptome-wide function of m6A remains mostly unknown. Here, we show that manym6A-modified mRNAs in Arabidopsis have reduced abundance in the absence of this mark. The decrease in abundance is due to transcript destabilization caused by cleavage occurring 4 or 5 nt directly upstream of unmodified m6A sites. Importantly, we also find that, upon agriculturally relevant salt treatment, m6A is dynamically deposited on and stabilizes transcripts encoding proteins required for salt and osmotic stress response. Overall, our findings reveal that m6A generally acts as a stabilizing mark through inhibition of site-specific cleavage in plant transcriptomes, and this mechanism is required for proper regulation of the salt-stress-responsive transcriptome

Mining clinical relationships from patient narratives

Background The Clinical E-Science Framework (CLEF) project has built a system to extract clinically significant information from the textual component of medical records in order to support clinical research, evidence-based healthcare and genotype-meets-phenotype informatics. One part of this system is the identification of relationships between clinically important entities in the text. Typical approaches to relationship extraction in this domain have used full parses, domain-specific grammars, and large knowledge bases encoding domain knowledge. In other areas of biomedical NLP, statistical machine learning (ML) approaches are now routinely applied to relationship extraction. We report on the novel application of these statistical techniques to the extraction of clinical relationships. Results We have designed and implemented an ML-based system for relation extraction, using support vector machines, and trained and tested it on a corpus of oncology narratives hand-annotated with clinically important relationships. Over a class of seven relation types, the system achieves an average F1 score of 72%, only slightly behind an indicative measure of human inter annotator agreement on the same task. We investigate the effectiveness of different features for this task, how extraction performance varies between inter- and intra-sentential relationships, and examine the amount of training data needed to learn various relationships. Conclusion We have shown that it is possible to extract important clinical relationships from text, using supervised statistical ML techniques, at levels of accuracy approaching those of human annotators. Given the importance of relation extraction as an enabling technology for text mining and given also the ready adaptability of systems based on our supervised learning approach to other clinical relationship extraction tasks, this result has significance for clinical text mining more generally, though further work to confirm our encouraging results should be carried out on a larger sample of narratives and relationship types

The effect of body mass index on global brain volume in middle-aged adults: a cross sectional study

BACKGROUND: Obesity causes or exacerbates a host of medical conditions, including cardiovascular, pulmonary, and endocrine diseases. Recently obesity in elderly women was associated with greater risk of dementia, white matter ischemic changes, and greater brain atrophy. The purpose of this study was to determine whether body type affects global brain volume, a marker of atrophy, in middle-aged men and women. METHODS: T1-weighted 3D volumetric magnetic resonance imaging was used to assess global brain volume for 114 individuals 40 to 66 years of age (average = 54.2 years; standard deviation = 6.6 years; 43 men and 71 women). Total cerebrospinal fluid and brain volumes were obtained with an automated tissue segmentation algorithm. A regression model was used to determine the effect of age, body mass index (BMI), and other cardiovascular risk factors on brain volume and cognition. RESULTS: Age and BMI were each associated with decreased brain volume. BMI did not predict cognition in this sample; however elevated diastolic blood pressure was associated with poorer episodic learning performance. CONCLUSION: These findings suggest that middle-aged obese adults may already be experiencing differentially greater brain atrophy, and may potentially be at greater risk for future cognitive decline