Causal network inference using biochemical kinetics

Motivation: Networks are widely used as structural summaries of biochemical systems. Statistical estimation of networks is usually based on linear or discrete models. However, the dynamics of biochemical systems are generally non-linear, suggesting that suitable non-linear formulations may offer gains with respect to causal network inference and aid in associated prediction problems. Results: We present a general framework for network inference and dynamical prediction using time course data that is rooted in nonlinear biochemical kinetics. This is achieved by considering a dynamical system based on a chemical reaction graph with associated kinetic parameters. Both the graph and kinetic parameters are treated as unknown; inference is carried out within a Bayesian framework. This allows prediction of dynamical behavior even when the underlying reaction graph itself is unknown or uncertain. Results, based on (i) data simulated from a mechanistic model of mitogen-activated protein kinase signaling and (ii) phosphoproteomic data from cancer cell lines, demonstrate that non-linear formulations can yield gains in causal network inference and permit dynamical prediction and uncertainty quantification in the challenging setting where the reaction graph is unknown. © The Author 2014. Published by Oxford University Press

Heart Rate detection using Photoplethysmography using Android Phone

This paper includes Heart Rate Detector system implemented by some modern hardware ICs and simple sensor circuit with software executable on both PC and android platform. Very first the bio-signals are extracted via photoplethysmography concept using PPG sensor into electric signal. Now at the next stage microprocessor is used to convert the bio-signal from analog to digital format. Some application software running on Windows and Android phone have been developed to display heart rate information and time domain waveform to users for health care monitoring. Some of the applications running on the android platform few of them have been developed to display the heart rate information and some health care monitoring system. This project includes the RF modules which having the major impact and plays the predominant role in it. In future, pure wireless technology will be used instead of RF modules DOI: 10.17762/ijritcc2321-8169.15032

Dynamics of Hyporheic Flow and Heat Transport Across a Bed-to-Bank Continuum in a Large Regulated River

The lower Colorado River (LCR) near Austin, Texas is heavily regulated for hydropower generation. Daily water releases from a dam located 23 km upstream of our study site in the LCR caused the stage to fluctuate by more than 1.5 m about a mean depth of 1.3 m. As a result, the river switches from gaining to losing over a dam storage-release cycle, driving exchange between river water and groundwater. We assessed the hydrologic impacts of this by simultaneous temperature and head monitoring across a bed-to-bank transect. River-groundwater exchange flux is largest close to the bank and decreases away from the bank. Correspondingly, both the depth of the hyporheic zone and the exchange time are largest close to the bank. Adjacent to the bank, the streambed head response is hysteretic, with the hysteresis disappearing with distance from the bank, indicating that transient bank storage affects the magnitude and direction of vertical exchange close to the bank. Pronounced changes in streambed temperature are observed down to a meter. When the river stage is high, which coincides with when the river is coldest, downward advection of heat from a previous cycles\u27 warm-water pulse warms the streambed. When the river is at its lowest stage but warmest temperature, upwelling groundwater cools the streambed. Future research should consider and focus on a more thorough understanding of the impacts of dam regulation on the hydrologic, thermal, biogeochemical, and ecologic dynamics of rivers and their hyporheic and riparian zones

Kallikrein-related peptidase 6 regulates epithelial-to-mesenchymal transition and serves as prognostic biomarker for head and neck squamous cell carcinoma patients

Background: Dysregulated expression of Kallikrein-related peptidase 6 (KLK6) is a common feature for many human malignancies and numerous studies evaluated KLK6 as a promising biomarker for early diagnosis or unfavorable prognosis. However, the expression of KLK6 in carcinomas derived from mucosal epithelia, including head and neck squamous cell carcinoma (HNSCC), and its mode of action has not been addressed so far. Methods: Stable clones of human mucosal tumor cell lines were generated with shRNA-mediated silencing or ectopic overexpression to characterize the impact of KLK6 on tumor relevant processes in vitro. Tissue microarrays with primary HNSCC samples from a retrospective patient cohort (n = 162) were stained by immunohistochemistry and the correlation between KLK6 staining and survival was addressed by univariate Kaplan-Meier and multivariate Cox proportional hazard model analysis. Results: KLK6 expression was detected in head and neck tumor cell lines (FaDu, Cal27 and SCC25), but not in HeLa cervix carcinoma cells. Silencing in FaDu cells and ectopic expression in HeLa cells unraveled an inhibitory function of KLK6 on tumor cell proliferation and mobility. FaDu clones with silenced KLK6 expression displayed molecular features resembling epithelial-to-mesenchymal transition, nuclear β-catenin accumulation and higher resistance against irradiation. Low KLK6 protein expression in primary tumors from oropharyngeal and laryngeal SCC patients was significantly correlated with poor progression-free (p = 0.001) and overall survival (p < 0.0005), and served as an independent risk factor for unfavorable clinical outcome. Conclusions: In summary, detection of low KLK6 expression in primary tumors represents a promising tool to stratify HNSCC patients with high risk for treatment failure. These patients might benefit from restoration of KLK6 expression or pharmacological targeting of signaling pathways implicated in EMT

Kinome rewiring reveals AURKA limits PI3K-pathway inhibitor efficacy in breast cancer.

Dysregulation of the PI3K-AKT-mTOR signaling network is a prominent feature of breast cancers. However, clinical responses to drugs targeting this pathway have been modest, possibly because of dynamic changes in cellular signaling that drive resistance and limit drug efficacy. Using a quantitative chemoproteomics approach, we mapped kinome dynamics in response to inhibitors of this pathway and identified signaling changes that correlate with drug sensitivity. Maintenance of AURKA after drug treatment was associated with resistance in breast cancer models. Incomplete inhibition of AURKA was a common source of therapy failure, and combinations of PI3K, AKT or mTOR inhibitors with the AURKA inhibitor MLN8237 were highly synergistic and durably suppressed mTOR signaling, resulting in apoptosis and tumor regression in vivo. This signaling map identifies survival factors whose presence limits the efficacy of targeted therapies and reveals new drug combinations that may unlock the full potential of PI3K-AKT-mTOR pathway inhibitors in breast cancer

In Vitro Analysis of Integrated Global High-Resolution DNA Methylation Profiling with Genomic Imbalance and Gene Expression in Osteosarcoma

Genetic and epigenetic changes contribute to deregulation of gene expression and development of human cancer. Changes in DNA methylation are key epigenetic factors regulating gene expression and genomic stability. Recent progress in microarray technologies resulted in developments of high resolution platforms for profiling of genetic, epigenetic and gene expression changes. OS is a pediatric bone tumor with characteristically high level of numerical and structural chromosomal changes. Furthermore, little is known about DNA methylation changes in OS. Our objective was to develop an integrative approach for analysis of high-resolution epigenomic, genomic, and gene expression profiles in order to identify functional epi/genomic differences between OS cell lines and normal human osteoblasts. A combination of Affymetrix Promoter Tilling Arrays for DNA methylation, Agilent array-CGH platform for genomic imbalance and Affymetrix Gene 1.0 platform for gene expression analysis was used. As a result, an integrative high-resolution approach for interrogation of genome-wide tumour-specific changes in DNA methylation was developed. This approach was used to provide the first genomic DNA methylation maps, and to identify and validate genes with aberrant DNA methylation in OS cell lines. This first integrative analysis of global cancer-related changes in DNA methylation, genomic imbalance, and gene expression has provided comprehensive evidence of the cumulative roles of epigenetic and genetic mechanisms in deregulation of gene expression networks

Multimodal Biomarkers That Predict the Presence of Gleason Pattern 4: Potential Impact for Active Surveillance

AbstractPurpose:Latent grade group ≥2 prostate cancer can impact the performance of active surveillance protocols. To date, molecular biomarkers for active surveillance have relied solely on RNA or protein. We trained and independently validated multimodal (mRNA abundance, DNA methylation, and/or DNA copy number) biomarkers that more accurately separate grade group 1 from grade group ≥2 cancers.Materials and Methods:Low- and intermediate-risk prostate cancer patients were assigned to training (n=333) and validation (n=202) cohorts. We profiled the abundance of 342 mRNAs, 100 DNA copy number alteration loci, and 14 hypermethylation sites at 2 locations per tumor. Using the training cohort with cross-validation, we evaluated methods for training classifiers of pathological grade group ≥2 in centrally reviewed radical prostatectomies. We trained 2 distinct classifiers, PRONTO-e and PRONTO-m, and validated them in an independent radical prostatectomy cohort.Results:PRONTO-e comprises 353 mRNA and copy number alteration features. PRONTO-m includes 94 clinical, mRNAs, copy number alterations, and methylation features at 14 and 12 loci, respectively. In independent validation, PRONTO-e and PRONTO-m predicted grade group ≥2 with respective true-positive rates of 0.81 and 0.76, and false-positive rates of 0.43 and 0.26. Both classifiers were resistant to sampling error and identified more upgrading cases than a well-validated presurgical risk calculator, CAPRA (Cancer of the Prostate Risk Assessment; P &lt; .001).Conclusions:Two grade group classifiers with superior accuracy were developed by incorporating RNA and DNA features and validated in an independent cohort. Upon further validation in biopsy samples, classifiers with these performance characteristics could refine selection of men for active surveillance, extending their treatment-free survival and intervals between surveillance.Active surveillance (AS) is recommended for men with low- and favorable intermediate–risk prostate cancer.1 Compared to AS for low-risk men, AS for intermediate-risk men would likely benefit from more intensive surveillance to stave off disease progression. Despite increased use of advanced imaging tools, risk calculators, and molecular biomarkers, a third or more of men initially classified as low risk actually have intermediate or higher risk, heralded by subsequent detection of occult Gleason pattern 4.2,3 Strategies to identify such men have limited accuracy. They include attention to traditional risk factors such as age, tumor size and extent, and PSA level, measured by tests such as digital rectal examination, multiparametric (mp) MRI, and biopsy and blood analyses. Despite its increasing use in prostate cancer risk assessment, expert prostate mpMRI is a limited resource with low (circa 59%) sensitivity for intermediate-risk cases.4 A biomarker that more accurately distinguishes between grade group (GG) 1 and GG ≥2 could be helpful in deintensifying AS for men with truly low-risk cancers.Several commercially available and guideline-approved tests use gene (mRNA or protein) expression levels in prostate cancer biopsies to detect adverse pathology (AP; ie, GG ≥3 or nonorgan-confined disease) in the subsequent prostatectomy. However, no existing molecular test has been adopted in current guidelines as standard of care to distinguish between GG1 and GG ≥2 cancers.1,5,6 Despite indications that such tests could be useful,6,7 uptake has been limited, perhaps because of low accuracy, which in turn may derive from limitations in the number and types of molecular features included in each test. Since cardinal molecular features of early prostate carcinogenesis include not only altered gene expression but also DNA methylation events and copy number alterations (CNAs),8-10 we hypothesized that tests combining these features could provide superior performance in separating low-grade (GG1) cancers from their higher-grade (GG ≥2) counterparts.The personalized risk stratification for patients with early prostate cancer (PRONTO) program is a pan-Canadian effort that aims to develop a GG classifier to stratify risk in prostate cancer and achieve technical and clinical validation in statistically powered cohorts. Here, we report the development of 2 candidate classifiers comprising different types of molecular features. These classifiers, developed and independently validated, achieve superior performance by integrating tumor mRNA abundance, DNA copy number, and/or DNA methylation profiles. We demonstrate that these classifiers could add value above and beyond routinely captured clinical data and are remarkably resistant to sampling error. We discuss how adoption of classifiers with these attributes has the potential to improve current AS approaches without increasing patient morbidity. By identifying men at increased risk of occult GG ≥2 cancer, surveillance biopsies could be taken earlier to confirm the presence and extent of Gleason pattern 4 cancer. By confirming GG1 cancers, such biomarkers could identify men for whom it would be safe to forgo MRI or increase the intervals between surveillance biopsies, reducing burdens on health care systems and patients

Comparing Breast Cancer Multiparameter Tests in the OPTIMA Prelim Trial: No Test Is More Equal Than the Others

Background: Previous reports identifying discordance between multiparameter tests at the individual patient level have been largely attributed to methodological shortcomings of multiple in silico studies. Comparisons between tests, when performed using actual diagnostic assays, have been predicted to demonstrate high degrees of concordance. OPTIMA prelim compared predicted risk stratification and subtype classification of different multiparameter tests performed directly on the same population. Methods: Three hundred thirteen women with early breast cancer were randomized to standard (chemotherapy and endocrine therapy) or test-directed (chemotherapy if Oncotype DX recurrence score &gt;25) treatment. Risk stratification was also determined with Prosigna (PAM50), MammaPrint, MammaTyper, NexCourse Breast (IHC4-AQUA), and conventional IHC4 (IHC4). Subtype classification was provided by Blueprint, MammaTyper, and Prosigna. Results: Oncotype DX predicted a higher proportion of tumors as low risk (82.1%, 95% confidence interval [CI] = 77.8% to 86.4%) than were predicted low/intermediate risk using Prosigna (65.5%, 95% CI = 60.1% to 70.9%), IHC4 (72.0%, 95% CI = 66.5% to 77.5%), MammaPrint (61.4%, 95% CI = 55.9% to 66.9%), or NexCourse Breast (61.6%, 95% CI = 55.8% to 67.4%). Strikingly, the five tests showed only modest agreement when dichotomizing results between high vs low/intermediate risk. Only 119 (39.4%) tumors were classified uniformly as either low/intermediate risk or high risk, and 183 (60.6%) were assigned to different risk categories by different tests, although 94 (31.1%) showed agreement between four of five tests. All three subtype tests assigned 59.5% to 62.4% of tumors to luminal A subtype, but only 121 (40.1%) were classified as luminal A by all three tests and only 58 (19.2%) were uniformly assigned as nonluminal A. Discordant subtyping was observed in 123 (40.7%) tumors. Conclusions: Existing evidence on the comparative prognostic information provided by different tests suggests that current multiparameter tests provide broadly equivalent risk information for the population of women with estrogen receptor (ER)–positive breast cancers. However, for the individual patient, tests may provide differing risk categorization and subtype information

Why and How to Write a High-Impact Review Paper: Lessons From Eight Years of Editorial Board Service to Reviews of Geophysics

High-impact review papers describe and synthesize the current state of the art, the open questions and controversies, and provide ideas for future investigations. They are written not only for a specific scientific discipline but also for the broader Earth and space science community. They not only summarize the literature, but they also create a framework from which to understand the progress, problems, and connections between different communities, observations, models, and approaches. Here we describe how to write a high-impact review paper, and why you should consider writing one for Reviews of Geophysics

Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer.

BACKGROUND: High mitotic activity is associated with the genesis and progression of many cancers. Small molecule inhibitors of mitotic apparatus proteins are now being developed and evaluated clinically as anticancer agents. With clinical trials of several of these experimental compounds underway, it is important to understand the molecular mechanisms that determine high mitotic activity, identify tumor subtypes that carry molecular aberrations that confer high mitotic activity, and to develop molecular markers that distinguish which tumors will be most responsive to mitotic apparatus inhibitors. METHODS: We identified a coordinately regulated mitotic apparatus network by analyzing gene expression profiles for 53 malignant and non-malignant human breast cancer cell lines and two separate primary breast tumor datasets. We defined the mitotic network activity index (MNAI) as the sum of the transcriptional levels of the 54 coordinately regulated mitotic apparatus genes. The effect of those genes on cell growth was evaluated by small interfering RNA (siRNA). RESULTS: High MNAI was enriched in basal-like breast tumors and was associated with reduced survival duration and preferential sensitivity to inhibitors of the mitotic apparatus proteins, polo-like kinase, centromere associated protein E and aurora kinase designated GSK462364, GSK923295 and GSK1070916, respectively. Co-amplification of regions of chromosomes 8q24, 10p15-p12, 12p13, and 17q24-q25 was associated with the transcriptional upregulation of this network of 54 mitotic apparatus genes, and we identify transcription factors that localize to these regions and putatively regulate mitotic activity. Knockdown of the mitotic network by siRNA identified 22 genes that might be considered as additional therapeutic targets for this clinically relevant patient subgroup. CONCLUSIONS: We define a molecular signature which may guide therapeutic approaches for tumors with high mitotic network activity