The mPower Study, Parkinson Disease Mobile Data Collected Using Researchkit

Current measures of health and disease are often insensitive, episodic, and subjective. Further, these measures generally are not designed to provide meaningful feedback to individuals. The impact of high-resolution activity data collected from mobile phones is only beginning to be explored. Here we present data from mPower, a clinical observational study about Parkinson disease conducted purely through an iPhone app interface. The study interrogated aspects of this movement disorder through surveys and frequent sensor-based recordings from participants with and without Parkinson disease. Benefitting from large enrollment and repeated measurements on many individuals, these data may help establish baseline variability of real-world activity measurement collected via mobile phones, and ultimately may lead to quantification of the ebbs-and-flows of Parkinson symptoms. App source code for these data collection modules are available through an open source license for use in studies of other conditions. We hope that releasing data contributed by engaged research participants will seed a new community of analysts working collaboratively on understanding mobile health data to advance human health

Patient-Specific Metrics of Invasiveness Reveal Significant Prognostic Benefit of Resection in a Predictable Subset of Gliomas

Object Malignant gliomas are incurable, primary brain neoplasms noted for their potential to extensively invade brain parenchyma. Current methods of clinical imaging do not elucidate the full extent of brain invasion, making it difficult to predict which, if any, patients are likely to benefit from gross total resection. Our goal was to apply a mathematical modeling approach to estimate the overall tumor invasiveness on a patient-by-patient basis and determine whether gross total resection would improve survival in patients with relatively less invasive gliomas. Methods In 243 patients presenting with contrast-enhancing gliomas, estimates of the relative invasiveness of each patient's tumor, in terms of the ratio of net proliferation rate of the glioma cells to their net dispersal rate, were derived by applying a patient-specific mathematical model to routine pretreatment MR imaging. The effect of varying degrees of extent of resection on overall survival was assessed for cohorts of patients grouped by tumor invasiveness. Results We demonstrate that patients with more diffuse tumors showed no survival benefit (P = 0.532) from gross total resection over subtotal/biopsy, while those with nodular (less diffuse) tumors showed a significant benefit (P = 0.00142) with a striking median survival benefit of over eight months compared to sub-totally resected tumors in the same cohort (an 80% improvement in survival time for GTR only seen for nodular tumors). Conclusions These results suggest that our patient-specific, model-based estimates of tumor invasiveness have clinical utility in surgical decision making. Quantification of relative invasiveness assessed from routinely obtained pre-operative imaging provides a practical predictor of the benefit of gross total resection

Role of gp120 Trimerization on HIV Binding Elucidated with Brownian Adhesive Dynamics

AbstractWe simulated the docking of human immunodeficiency virus (HIV) with a cell membrane using Brownian adhesive dynamics. The main advance in the current version of Brownian adhesive dynamics is that we use a simple bead-spring model to coarsely approximate the role of gp120 trimerization on HIV docking. We used our simulations to elucidate the effect of env spike density on the rate and probability of HIV binding, as well as the probability that each individual gp120 trimer is fully engaged. We found that for typical CD4 surface densities, viruses expressing as few as 8 env spikes will dock with binding rate constants comparable to viruses expressing 72 spikes. We investigated the role of cellular receptor diffusion on the degree of binding achieved by the virus on both short timescales (where binding has reached steady state but before substantial receptor accumulation in the viral-cell contact zone has occurred) and long timescales (where the system has reached steady state). On short timescales, viruses with 10–23 env trimers most efficiently form fully engaged trimers. On long timescales, all gp120 in the contact area will become bound to CD4. We found that it takes seconds for engaged trimers to cluster CD4 molecules in the contact zone, which partially explains the deleay in viral entry

Abstract 359: An age-related 99-gene signature from glioblastoma implicates differences in survival related to RAS activation

Abstract Background: Glioblastoma (GBM) is the most common primary brain tumor with universally poor prognosis despite treatment with surgery, radiation and chemotherapy. One of the most significant prognostic factors is the patient's age at onset of disease, with younger patients demonstrating longer survival despite similar therapies. The aim of this work is to examine genomic differences that are tied to the age of onset that could explain the differences in outcomes. Methods: We used the gene expression profiles from 559 GBM patients (pts) included in the Cancer Genome Atlas (TCGA) to build a gene expression model of the expression of 12185 genes to predict patient age using elasticnet with 500 bootstraps. This model was used to predict the age of patients in a testing set of 419 pts with gliomas included in Repository for Brain Neoplasia Data (REMBRANDT) (99 grade II, 71 grade III and 125 grade IV and 124 with no grade). Receiver-operating characteristic (ROC) and survival analysis were performed to measure the performance of the model in predicting age, gene-set enrichment analysis (GSEA) was used to reveal network topology perturbations, Cox proportional hazards were used to predict survival of the different predicted classes. Results: Using a FDR cutoff of p=0.005, the bootstrapped elasticnet discovered 99 genes that were highly correlated with age in GBM patients that predicts age in the testing set of patients with gliomas with an area under the ROC curve of 0.97. GSEA motifs within these genes related to RAS activation in multiple cell lines, as well as genes related to immune modulation and increased CpG methylation. Survival analysis of the REMBRANDT pts showed that the cohort with an “older” gene signature had worse survival (median 27 months versus 15 months, log-rank p&amp;lt;0.00005). When applied to pts in REMBRANDT for whom age was not recorded (n=36), the model predicted classes also had significantly different survival (median 6 versus 10 months, log-rank p=0.001). Conclusions: We have developed a gene expression model related to age of onset of GBM, to investigate the differences inherent in the biology that may lead to better prognosis in younger patients. Of the 99 genes that are strongly predictive of age in an external validation set, many were related to RAS activation in cell lines, immune modulation and CpG methylation. RAS perturbations have been previously shown to induce gliomas in mice, and this study shows a relationship between RAS gene network activation and age that may play a role in the different survival outcomes between different ages. Future work will include the use of RAS targeted agents to elucidate their role in the management of gliomas for select pts. Citation Format: Andrew D. Trister, Robert Rostomily, Stephen H. Friend. An age-related 99-gene signature from glioblastoma implicates differences in survival related to RAS activation. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 359. doi:10.1158/1538-7445.AM2014-359</jats:p