Estimating the dynamics and dependencies of accumulating mutations with applications to HIV drug resistance

We introduce a new model called the observed time conjunctive Bayesian network (OT-CBN) that describes the accumulation of genetic events (mutations) under partial temporal ordering constraints. Unlike other CBN models, the OT-CBN model uses sampling time points of genotypes in addition to genotypes themselves to estimate model parameters. We developed an expectation-maximization algorithm to obtain approximate maximum likelihood estimates by accounting for this additional information. In a simulation study, we show that the OT-CBN model outperforms the continuous time CBN (CT-CBN) (Beerenwinkel and Sullivant, 2009. Markov models for accumulating mutations. Biometrika 96(3), 645-661), which does not take into account individual sampling times for parameter estimation. We also show superiority of the OT-CBN model on several datasets of HIV drug resistance mutations extracted from the Swiss HIV Cohort Study databas

Clinical Presentation and Microbial Analyses of Contact Lens Keratitis; an Epidemiologic Study

Introduction: Microbial keratitis is an infective process of the cornea with a potentially and serious visual impairments. Contact lenses are a major cause of microbial keratitis in the developed countries especially among young people. Therefore, the purpose of the present study was to evaluate the frequency and microbiological characteristic of CLK in patients referred to the emergency department (ED) of teaching hospitals, Babol, Iran. Methods: This is a cross-sectional study of all patients with contact lens induced corneal ulcers admitted to the teaching hospitals of Babol, Iran, from 2011- 2013. An ophthalmologist examined patients with the slit-lamp and clinical features of them were noted (including pain, redness, foreign body sensation, chemosis, epiphora, blurred vision, discomfort, photophobia, discharge, ocular redness and swelling). All suspected infectious corneal ulcers were scraped for microbial culture and two slides were prepared. Data were analyzed using SPSS software, version 18.0. Results: A total of 14 patients (17 eyes) were recruited into the study (100% female). The patients’ age ranged from 16-37 years old (mean age 21.58±7.23 years). The most prevalent observed clinical signs were pain and redness. Three samples reported as sterile. The most common isolated causative organism was pseudomonas aeroginosa (78.6%), Staphylococcus aureus 14.3%, and enterobacter 7.1%, respectively. Treatment outcome was excellent in 23.5%, good in 47.1%, and poor in 29.4% of cases. Conclusion: Improper lens wear and care as well as the lack of awareness about the importance of aftercare visits have been identified as potential risk factors for the corneal ulcer among contact lens wearers. Training and increasing the awareness of adequate lens care and disinfection practices, consulting with an ophthalmologist, and frequent replacement of contact lens storage cases would greatly help reducing the risk of microbial keratitis

Network-based integration of multi-omics data for prioritizing cancer genes

Several molecular events are known to be cancer-related, including genomic aberrations, hypermethylation of gene promoter regions, and differential expression of microRNAs. These aberration events are very heterogeneous across tumors and it is poorly understood how they affect the molecular makeup of the cell, including the transcriptome and proteome. Protein interaction networks can help decode the functional relationship between aberration events and changes in gene and protein expression.; We developed NetICS (Network-based Integration of Multi-omics Data), a new graph diffusion-based method for prioritizing cancer genes by integrating diverse molecular data types on a directed functional interaction network. NetICS prioritizes genes by their mediator effect, defined as the proximity of the gene to upstream aberration events and to downstream differentially expressed genes and proteins in an interaction network. Genes are prioritized for individual samples separately and integrated using a robust rank aggregation technique. NetICS provides a comprehensive computational framework that can aid in explaining the heterogeneity of aberration events by their functional convergence to common differentially expressed genes and proteins. We demonstrate NetICS' competitive performance in predicting known cancer genes and in generating robust gene lists using TCGA data from five cancer types.; NetICS is available at https://github.com/cbg-ethz/netics.; [email protected].; Supplementary data are available at Bioinformatics online

Systematic identification of novel cancer genes through analysis of deep shRNA perturbation screens.

Systematic perturbation screens provide comprehensive resources for the elucidation of cancer driver genes. The perturbation of many genes in relatively few cell lines in such functional screens necessitates the development of specialized computational tools with sufficient statistical power. Here we developed APSiC (Analysis of Perturbation Screens for identifying novel Cancer genes) to identify genetic drivers and effectors in perturbation screens even with few samples. Applying APSiC to the shRNA screen Project DRIVE, APSiC identified well-known and novel putative mutational and amplified cancer genes across all cancer types and in specific cancer types. Additionally, APSiC discovered tumor-promoting and tumor-suppressive effectors, respectively, for individual cancer types, including genes involved in cell cycle control, Wnt/β-catenin and hippo signalling pathways. We functionally demonstrated that LRRC4B, a putative novel tumor-suppressive effector, suppresses proliferation by delaying cell cycle and modulates apoptosis in breast cancer. We demonstrate APSiC is a robust statistical framework for discovery of novel cancer genes through analysis of large-scale perturbation screens. The analysis of DRIVE using APSiC is provided as a web portal and represents a valuable resource for the discovery of novel cancer genes

GATA3 and MDM2 are synthetic lethal in estrogen receptor-positive breast cancers.

Synthetic lethal interactions, where the simultaneous but not individual inactivation of two genes is lethal to the cell, have been successfully exploited to treat cancer. GATA3 is frequently mutated in estrogen receptor (ER)-positive breast cancers and its deficiency defines a subset of patients with poor response to hormonal therapy and poor prognosis. However, GATA3 is not yet targetable. Here we show that GATA3 and MDM2 are synthetically lethal in ER-positive breast cancer. Depletion and pharmacological inhibition of MDM2 significantly impaired tumor growth in GATA3-deficient models in vitro, in vivo and in patient-derived organoids/xenograft (PDOs/PDX) harboring GATA3 somatic mutations. The synthetic lethality requires p53 and acts via the PI3K/Akt/mTOR pathway. Our results present MDM2 as a therapeutic target in the substantial cohort of ER-positive, GATA3-mutant breast cancer patients. With MDM2 inhibitors widely available, our findings can be rapidly translated into clinical trials to evaluate in-patient efficacy

SL-scan identifies synthetic lethal interactions in cancer using metabolic networks

Abstract Exploiting synthetic lethality is a promising strategy for developing targeted cancer therapies. However, identifying clinically significant synthetic lethal (SL) interactions among a large number of gene combinations is a challenging computational task. In this study, we developed the SL-scan pipeline based on metabolic network modeling to discover SL interaction. The SL-scan pipeline identifies the association between simulated Flux Balance Analysis knockout scores and mutation data across cancer cell lines and predicts putative SL interactions. We assessed the concordance of the SL pairs predicted by SL-scan with those of obtained from analysis of the CRISPR, shRNA, and PRISM datasets. Our results demonstrate that the SL-scan pipeline outperformed existing SL prediction approaches based on metabolic networks in identifying SL pairs in various cancers. This study emphasizes the importance of integrating multiple data sources, particularly mutation data, when identifying SL pairs for targeted cancer therapies. The findings of this study may lead to the development of novel targeted cancer therapies

Clinical Presentation and Antibiotic Susceptibility of Contact Lens Associated Microbial Keratitis

Introduction. In recent years, the number of contact lens wearers has dramatically increased in Iran, particularly in youngsters. The purpose of current study was to assess the clinical presentation and antibiotic susceptibility of contact lens related microbial keratitis in Ahvaz, southwest of Iran. Methodology. A cross-sectional investigation of 26 patients (33 eyes) with contact lens induced corneal ulcers who were admitted to Imam Khomeini Hospital, Ahwaz City, from June 2012 to June 2013 was done. In order to study microbial culture and susceptibility of corneal ulcers, all of them were scraped. Results. Eight samples were reported as sterile. Pseudomonas aeruginosa (80%) in positive cultures was the most widely recognized causative organism isolated. This is followed by Staphylococcus aureus 12% and Enterobacter 8%. The results showed that 84% of the microorganism cases were sensitive to ciprofloxacin, while imipenem, meropenem, and ceftazidime were the second most effective antibiotics (76%). Conclusion. Results of current study show the importance of referring all contact lens wearers with suspected corneal infection to ophthalmologists for more cure. The corneal scraping culture and contact lens solution should be performed to guide antibiotic therapy