Etude du lien entre EMG et signaux cinématiques par relations temporelles et courbes COR

Des signaux électromyographiques (EMG) des muscles du cou et des signaux cinématiques (véhicule et tête du sujet) sont mesurés, dans une voiture, pendant un trajet routier, afin de quantifier le confort postural de l'appui-tête. Cet article présente l'étude du lien entre ces signaux. Ils sont tout d'abord considérés localement : segmentation pour les EMG et analyse statistique pour les accélérations. Les relations temporelles entre événements caractéristiques (bouffées EMG et fortes accélérations) sont ensuite étudiées. Des courbes COR sont déduites. Cette méthode a mis en évidence l'absence de relation entre forte accélération du véhicule et bouffées EMG. Mais elle a permis de classer les bouffées selon le type de mouvement de tête associé

Deep Proteomic Analysis on Biobanked Paraffine-Archived Melanoma with Prognostic/Predictive Biomarker Read-Out

SIMPLE SUMMARY: Malignant melanoma is one of the most aggressive cancer types among the solid tumors; therefore, more clinically applicable protein biomarkers predicting survival and therapy response have mandatory importance, impacting patient treatment. The aim of the study was to discover new proteins in biobanked FFPE samples that relate to progression-free survival and response to targeted- and immuno-therapies in patients with melanoma. Protein expressions were detected and quantified by high-resolution mass spectrometry and were integrated with the clinical data and in-depth histopathology characterization. Sample groups with distinct protein expression profiles were connected to longer and shorter survival as well as other clinicopathologic features. In addition, key regulating proteins were assigned, as predictive of progression-free survival in immuno- and/or targeted therapy. Some of the proteins exhibited functionally important correlations to progression and therapy response, which ultimately contributes to a better understanding of melanoma pathology. ABSTRACT: The discovery of novel protein biomarkers in melanoma is crucial. Our introduction of formalin-fixed paraffin-embedded (FFPE) tumor protocol provides new opportunities to understand the progression of melanoma and open the possibility to screen thousands of FFPE samples deposited in tumor biobanks and available at hospital pathology departments. In our retrospective biobank pilot study, 90 FFPE samples from 77 patients were processed. Protein quantitation was performed by high-resolution mass spectrometry and validated by histopathologic analysis. The global protein expression formed six sample clusters. Proteins such as TRAF6 and ARMC10 were upregulated in clusters with enrichment for shorter survival, and proteins such as AIFI1 were upregulated in clusters with enrichment for longer survival. The cohort’s heterogeneity was addressed by comparing primary and metastasis samples, as well comparing clinical stages. Within immunotherapy and targeted therapy subgroups, the upregulation of the VEGFA-VEGFR2 pathway, RNA splicing, increased activity of immune cells, extracellular matrix, and metabolic pathways were positively associated with patient outcome. To summarize, we were able to (i) link global protein expression profiles to survival, and they proved to be an independent prognostic indicator, as well as (ii) identify proteins that are potential predictors of a patient’s response to immunotherapy and targeted therapy, suggesting new opportunities for precision medicine developments

Cost-Effectiveness of Web-Based Patient-Reported Outcome Surveillance in Patients With Lung Cancer

Introduction: A multicenter randomized clinical trial in France found an overall survival benefit of web-based patient-reported outcome (PRO)–based surveillance after initial treatment for lung cancer compared with conventional surveillance. The aim of this study was to assess the cost-effectiveness of this PRO-based surveillance in lung cancer patients. Methods: This medico-economic analysis used data from the clinical trial, augmented by abstracted chart data and costs of consultations, imaging, transportations, information technology, and treatments. Costs were calculated based on actual reimbursement rates in France, and health utilities were estimated based on scientific literature review. Willingness-to-pay thresholds of €30,000 per quality-adjusted life year (QALY) and €90,000 per QALY were used to define a very cost-effective and cost-effective strategy, respectively. Average annual costs of experimental and control surveillance approaches were calculated. The incremental cost-effectiveness ratio was expressed as cost per life-year gained and QALY gained, from the health insurance payer perspective. One-way and multivariate probabilistic sensitivity analyses were performed. Results: Average annual cost of surveillance follow-up was €362 lower per patient in the PRO arm (€941/year/patient) compared to control (€1,304/year/patient). The PRO approach presented an incremental cost-effectiveness ratio of €12,127 per life-year gained and €20,912 per QALY gained. The probabilities that the experimental strategy is very cost-effective and cost-effective were 97% and 100%, respectively. Conclusions: Surveillance of lung cancer patients using web-based PRO reduced the follow-up costs. Compared to conventional monitoring, this surveillance modality represents a cost-effective strategy and should be considered in cancer care delivery

GO Explorer: A gene-ontology tool to aid in the interpretation of shotgun proteomics data

<p>Abstract</p> <p>Background</p> <p>Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge.</p> <p>Results</p> <p>Here we present a new algorithm, termed GO Explorer (GOEx), that leverages the gene ontology (GO) to aid in the interpretation of proteomic data. GOEx stands out because it combines data from protein fold changes with GO over-representation statistics to help draw conclusions. Moreover, it is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. Its usefulness is demonstrated by applying it to help interpret the effects of perillyl alcohol, a natural chemotherapeutic agent, on glioblastoma multiform cell lines (A172). We used a new multi-surfactant shotgun proteomic strategy and identified more than 2600 proteins; GOEx pinpointed key sets of differentially expressed proteins related to cell cycle, alcohol catabolism, the Ras pathway, apoptosis, and stress response, to name a few.</p> <p>Conclusion</p> <p>GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics. GOEx is available at <url>http://pcarvalho.com/patternlab</url>.</p