Improved Microarray-Based Decision Support with Graph Encoded Interactome Data

In the past, microarray studies have been criticized due to noise and the limited overlap between gene signatures. Prior biological knowledge should therefore be incorporated as side information in models based on gene expression data to improve the accuracy of diagnosis and prognosis in cancer. As prior knowledge, we investigated interaction and pathway information from the human interactome on different aspects of biological systems. By exploiting the properties of kernel methods, relations between genes with similar functions but active in alternative pathways could be incorporated in a support vector machine classifier based on spectral graph theory. Using 10 microarray data sets, we first reduced the number of data sources relevant for multiple cancer types and outcomes. Three sources on metabolic pathway information (KEGG), protein-protein interactions (OPHID) and miRNA-gene targeting (microRNA.org) outperformed the other sources with regard to the considered class of models. Both fixed and adaptive approaches were subsequently considered to combine the three corresponding classifiers. Averaging the predictions of these classifiers performed best and was significantly better than the model based on microarray data only. These results were confirmed on 6 validation microarray sets, with a significantly improved performance in 4 of them. Integrating interactome data thus improves classification of cancer outcome for the investigated microarray technologies and cancer types. Moreover, this strategy can be incorporated in any kernel method or non-linear version of a non-kernel method

The effect of climate type on timescales of drought propagation in an ensemble of global hydrological models

Drought is a natural hazard that occurs at many temporal and spatial scales and has severe environmental and socioeconomic impacts across the globe. The impacts of drought change as drought evolves from precipitation deficits to deficits in soil moisture or streamflow. Here, we quantified the time taken for drought to propagate from meteorological drought to soil moisture drought and from meteorological drought to hydrological drought. We did this by cross-correlating the Standardized Precipitation Index (SPI) against standardized indices (SIs) of soil moisture, runoff, and streamflow from an ensemble of global hydrological models (GHMs) forced by a consistent meteorological dataset. Drought propagation is strongly related to climate types, occurring at sub-seasonal timescales in tropical climates and at up to multi-annual timescales in continental and arid climates. Winter droughts are usually related to longer SPI accumulation periods than summer droughts, especially in continental and tropical savanna climates. The difference between the seasons is likely due to winter snow cover in the former and distinct wet and dry seasons in the latter. Model structure appears to play an important role in model variability, as drought propagation to soil moisture drought is slower in land surface models (LSMs) than in global hydrological models, but propagation to hydrological drought is faster in land surface models than in global hydrological models. The propagation time from SPI to hydrological drought in the models was evaluated against observed data at 127 in situ streamflow stations. On average, errors between observed and modeled drought propagation timescales are small and the model ensemble mean is preferred over the use of a single model. Nevertheless, there is ample opportunity for improvement as substantial differences in drought propagation are found at 10&thinsp;% of the study sites. A better understanding and representation of drought propagation in models may help improve seasonal drought forecasting as well as constrain drought variability under future climate scenarios.</p

Synaptogyrin-3 mediates presynaptic dysfunction induced by Tau

Synaptic dysfunction is an early pathological feature of neurodegenerative diseases associated with Tau, including Alzheimer's disease. Interfering with early synaptic dysfunction may be therapeutically beneficial to prevent cognitive decline and disease progression, but the mechanisms underlying synaptic defects associated with Tau are unclear. In disease conditions, Tau mislocalizes into pre- and postsynaptic compartments; here we show that, under pathological conditions, Tau binds to presynaptic vesicles in Alzheimer's disease patient brain. We define that the binding of Tau to synaptic vesicles is mediated by the transmembrane vesicle protein Synaptogyrin-3. In fly and mouse models of Tauopathy, reduction of Synaptogyrin-3 prevents the association of presynaptic Tau with vesicles, alleviates Tau-induced defects in vesicle mobility, and restores neurotransmitter release. This work therefore identifies Synaptogyrin-3 as the binding partner of Tau on synaptic vesicles, revealing a new presynapse-specific Tau interactor, which may contribute to early synaptic dysfunction in neurodegenerative diseases associated with Tau

Early targets of miR-34a in neuroblastoma

Several genes encoding for proteins involved in proliferation, invasion, and apoptosis are known to be direct miR-34a targets. Here, we used proteomics to screen for targets of miR-34a in neuroblastoma (NBL), a childhood cancer that originates from precursor cells of the sympathetic nervous system. We examined the effect of miR-34a overexpression using a tetracycline inducible system in two NBL cell lines (SHEP and SH-SY5Y) at early time points of expression (6, 12, and 24 h). Proteome analysis using post-metabolic labeling led to the identification of 2,082 proteins, and among these 186 were regulated (112 proteins down-regulated and 74 up-regulated). Prediction of miR-34a targets via bioinformatics showed that 32 transcripts held miR-34a seed sequences in their 3′-UTR. By combining the proteomics data with Kaplan Meier geneexpression studies, we identified seven new gene products (ALG13, TIMM13, TGM2, ABCF2, CTCF, Ki67, and LYAR) that were correlated with worse clinical outcomes. These were further validated in vitro by 3′-UTR seed sequence regulation. In addition, Michigan Molecular Interactions searches indicated that together these proteins affect signaling pathways that regulate cell cycle and proliferation, focal adhesions, and other cellular properties that overall enhance tumor progression (including signaling pathways such as TGF-β, WNT, MAPK, and FAK). In conclusion, proteome analysis has here identified early targets of miR-34a with relevance to NBL tumorigenesis. Along with the results of previous studies, our data strongly suggest miR-34a as a useful tool for improving the chance of therapeutic success with NBL

Multi-center planning study of radiosurgery for intracranial metastases through Automation (MC-PRIMA) by crowdsourcing prior web-based plan challenge study

BACKGROUND: Planning radiosurgery to multiple intracranial metastases is complex and shows large variability in dosimetric quality among planners and treatment planning systems (TPS). This project aimed to determine whether autoplanning using the Muliple Brain Mets (AutoMBM) software can improve plan quality and reduce inter-planner variability by crowdsourcing results from prior international planning study. METHODS: Twenty-four institutions autoplanned with AutoMBM on a five metastases case from a prior international planning competition from which population statistics (means and variances) of 23 dosimetric metrics and resulting composite plan score (maximum score = 150) of other TPS (Eclipse, Monaco, RayStation, iPlan, GammaPlan, MultiPlan) were crowdsourced. Plan results of AutoMBM and each of the other TPS were compared using two sample t-tests for means and Levene's tests for variances. Plan quality of AutoMBM was correlated with the planner' experience and compared between academic and non-academic centers. RESULTS: AutoMBM produced plans with comparable composite plan score to GammaPlan, MultiPlan, Eclipse and iPlan (127.6 vs. 131.7 vs. 127.3 vs. 127.3 and 126.7; all p > 0.05) and superior to Monaco and RayStation (118.3 and 108.6; both p 0.05). CONCLUSIONS: By plan crowdsourcing prior international plan challenge, AutoMBM produces high and consistent plan quality independent of the planning experience and the institution that is crucial to addressing the technical bottleneck of SRS to intracranial metastases

Quantitative Proteome Profiling of C. burnetii under Tetracycline Stress Conditions

The recommended antibiotic regimen against Coxiella burnetii, the etiological agent of Q fever, is based on a semi-synthetic, second-generation tetracycline, doxycycline. Here, we report on the comparison of the proteomes of a C. burnetii reference strain either cultured under control conditions or under tetracycline stress conditions. Using the MS-driven combined fractional diagonal chromatography proteomics technique, out of the 531 proteins identified, 5 and 19 proteins were found significantly up- and down-regulated respectively, under tetracycline stress. Although the predicted cellular functions of these regulated proteins did not point to known tetracycline resistance mechanisms, our data clearly reveal the plasticity of the proteome of C. burnetii to battle tetracycline stress. Finally, we raise several plausible hypotheses that could further lead to more focused experiments on studying tetracycline resistance in C. burnetii and thus reduced treatment failures of Q fever

Melanoma addiction to the long non-coding RNA SAMMSON

Focal amplifications of chromosome 3p13-3p14 occur in about 10% of melanomas and are associated with a poor prognosis. The melanoma-specific oncogene MITF resides at the epicentre of this amplicon. However, whether other loci present in this amplicon also contribute to melanomagenesis is unknown. Here we show that the recently annotated long non-coding RNA (lncRNA) gene SAMMSON is consistently co-gained with MITF. In addition, SAMMSON is a target of the lineage-specific transcription factor SOX10 and its expression is detectable in more than 90% of human melanomas. Whereas exogenous SAMMSON increases the clonogenic potential in trans, SAMMSON knockdown drastically decreases the viability of melanoma cells irrespective of their transcriptional cell state and BRAF, NRAS or TP53 mutational status. Moreover, SAMMSON targeting sensitizes melanoma to MAPK-targeting therapeutics both in vitro and in patient-derived xenograft models. Mechanistically, SAMMSON interacts with p32, a master regulator of mitochondrial homeostasis and metabolism, to increase its mitochondrial targeting and pro-oncogenic function. Our results indicate that silencing of the lineage addiction oncogene SAMMSON disrupts vital mitochondrial functions in a cancer-cell-specific manner; this silencing is therefore expected to deliver highly effective and tissue-restricted anti-melanoma therapeutic responses

The EUFOREA pocket guide for chronic rhinosinusitis

Chronic rhinosinusitis (CRS) is known to affect around 5 % of the total population, with major impact on the quality of life of those severely affected (1). Despite a substantial burden on individuals, society and health economies, CRS often remains underdiagnosed, under-estimated and under-treated (2). International guidelines like the European Position Paper on Rhinosinusitis and Nasal Polyps (EPOS) (3) and the International Consensus statement on Allergy and Rhinology: Rhinosinusitis 2021 (ICAR) (4) offer physicians insight into the recommended treatment options for CRS, with an overview of effective strategies and guidance of diagnosis and care throughout the disease journey of CRS

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin