A markov classification model for metabolic pathways

<p>Abstract</p> <p>Background</p> <p>This paper considers the problem of identifying pathways through metabolic networks that relate to a specific biological response. Our proposed model, HME3M, first identifies frequently traversed network paths using a Markov mixture model. Then by employing a hierarchical mixture of experts, separate classifiers are built using information specific to each path and combined into an ensemble prediction for the response.</p> <p>Results</p> <p>We compared the performance of HME3M with logistic regression and support vector machines (SVM) for both simulated pathways and on two metabolic networks, glycolysis and the pentose phosphate pathway for <it>Arabidopsis thaliana</it>. We use AltGenExpress microarray data and focus on the pathway differences in the developmental stages and stress responses of <it>Arabidopsis</it>. The results clearly show that HME3M outperformed the comparison methods in the presence of increasing network complexity and pathway noise. Furthermore an analysis of the paths identified by HME3M for each metabolic network confirmed known biological responses of <it>Arabidopsis</it>.</p> <p>Conclusions</p> <p>This paper clearly shows HME3M to be an accurate and robust method for classifying metabolic pathways. HME3M is shown to outperform all comparison methods and further is capable of identifying known biologically active pathways within microarray data.</p

Incorporating tumour pathology information into breast cancer risk prediction algorithms.

INTRODUCTION: Mutations in BRCA1 and BRCA2 confer high risks of breast cancer and ovarian cancer. The risk prediction algorithm BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) may be used to compute the probabilities of carrying mutations in BRCA1 and BRCA2 and help to target mutation screening. Tumours from BRCA1 and BRCA2 mutation carriers display distinctive pathological features that could be used to better discriminate between BRCA1 mutation carriers, BRCA2 mutation carriers and noncarriers. In particular, oestrogen receptor (ER)-negative status, triple-negative (TN) status, and expression of basal markers are predictive of BRCA1 mutation carrier status. METHODS: We extended BOADICEA by treating breast cancer subtypes as distinct disease end points. Age-specific expression of phenotypic markers in a series of tumours from 182 BRCA1 mutation carriers, 62 BRCA2 mutation carriers and 109 controls from the Breast Cancer Linkage Consortium, and over 300,000 tumours from the general population obtained from the Surveillance Epidemiology, and End Results database, were used to calculate age-specific and genotype-specific incidences of each disease end point. The probability that an individual carries a BRCA1 or BRCA2 mutation given their family history and tumour marker status of family members was computed in sample pedigrees. RESULTS: The cumulative risk of ER-negative breast cancer by age 70 for BRCA1 mutation carriers was estimated to be 55% and the risk of ER-positive disease was 18%. The corresponding risks for BRCA2 mutation carriers were 21% and 44% for ER-negative and ER-positive disease, respectively. The predicted BRCA1 carrier probabilities among ER-positive breast cancer cases were less than 1% at all ages. For women diagnosed with breast cancer below age 50 years, these probabilities rose to more than 5% in ER-negative breast cancer, 7% in TN disease and 24% in TN breast cancer expressing both CK5/6 and CK14 cytokeratins. Large differences in mutation probabilities were observed by combining ER status and other informative markers with family history. CONCLUSIONS: This approach combines both full pedigree and tumour subtype data to predict BRCA1/2 carrier probabilities. Prediction of BRCA1/2 carrier status, and hence selection of women for mutation screening, may be substantially improved by combining tumour pathology with family history of cancer.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Publisher Correction: The genome of the stable fly, Stomoxys calcitrans, reveals potential mechanisms underlying reproduction, host interactions, and novel targets for pest control (BMC Biology, (2021), 19, 1, (41), 10.1186/s12915-021-00975-9)

Following publication of the original article [1], it was reported that the article copyright was incorrect. The correct copyright statement is: © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2021. The original article [1] has been corrected

Genomic Insights Into The Ixodes scapularis Tick Vector Of Lyme Disease

Ticks transmit more pathogens to humans and animals than any other arthropod. We describe the 2.1 Gbp nuclear genome of the tick, Ixodes scapularis (Say), which vectors pathogens that cause Lyme disease, human granulocytic anaplasmosis, babesiosis and other diseases. The large genome reflects accumulation of repetitive DNA, new lineages of retrotransposons, and gene architecture patterns resembling ancient metazoans rather than pancrustaceans. Annotation of scaffolds representing B57% of the genome, reveals 20,486 protein-coding genes and expansions of gene families associated with tick–host interactions. We report insights from genome analyses into parasitic processes unique to ticks, including host ‘questing’, prolonged feeding, cuticle synthesis, blood meal concentration, novel methods of haemoglobin digestion, haem detoxification, vitellogenesis and prolonged off-host survival. We identify proteins associated with the agent of human granulocytic anaplasmosis, an emerging disease, and the encephalitis-causing Langat virus, and a population structure correlated to life-history traits and transmission of the Lyme disease agent

Genomic Insights Into The Ixodes scapularis Tick Vector Of Lyme Disease

Ticks transmit more pathogens to humans and animals than any other arthropod. We describe the 2.1 Gbp nuclear genome of the tick, Ixodes scapularis (Say), which vectors pathogens that cause Lyme disease, human granulocytic anaplasmosis, babesiosis and other diseases. The large genome reflects accumulation of repetitive DNA, new lineages of retrotransposons, and gene architecture patterns resembling ancient metazoans rather than pancrustaceans. Annotation of scaffolds representing B57% of the genome, reveals 20,486 protein-coding genes and expansions of gene families associated with tick–host interactions. We report insights from genome analyses into parasitic processes unique to ticks, including host ‘questing’, prolonged feeding, cuticle synthesis, blood meal concentration, novel methods of haemoglobin digestion, haem detoxification, vitellogenesis and prolonged off-host survival. We identify proteins associated with the agent of human granulocytic anaplasmosis, an emerging disease, and the encephalitis-causing Langat virus, and a population structure correlated to life-history traits and transmission of the Lyme disease agent

Mapping genetic variations to three- dimensional protein structures to enhance variant interpretation: a proposed framework

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods

Brain Penetration of the ROS1/ALK Inhibitor Lorlatinib Confirmed by PET

The Massachusetts General Hospital Radiochemistry Program, in collaboration with Pfizer, has developed unique 11C and 18F-labeling strategies to synthesize isotopologs of lorlatinib (PF-06463922) which is undergoing phase III clinical trial investigations for treatment of non-small-cell lung cancers with specific molecular alterations. A major goal in cancer therapeutics is to measure the concentrations of this drug in the brain metastases of patients with lung cancer, and penetration of the blood–brain barrier is important for optimal therapeutic outcomes. Our recent publication in Nature Communications employed radiolabeled lorlatinib and positron emission tomography (PET) studies in preclinical models including nonhuman primates (NHPs) that demonstrated high brain permeability of this compound. Our future work with radiolabeled lorlatinib will include advanced PET evaluations in rodent tumor models and normal NHPs with the goal of clinical translation

Population pharmacokinetics and exposure-overall survival analysis of the transforming growth factor-\u3b2 inhibitor galunisertib in patients with pancreatic cancer

PurposeTo evaluate the exposure-overall survival (OS) relationship in patients with advanced pancreatic cancer treated with galunisertib plus gemcitabine (GG) or gemcitabine plus placebo (GP).MethodsGalunisertib 300 mg/day was given orally as intermittent dosing and gemcitabine as per label. Galunisertib exposure metrics for each patient in the GG arm (n=99) of a phase 2 study of pancreatic cancer were calculated. Parametric survival models were used to identify influential baseline and response covariates on OS.ResultsThe population pharmacokinetics dataset included data from 297 patients/healthy subjects (age: 22-84 years, weight: 39-126 kg) across multiple studies, including this pancreatic cancer study. Galunisertib was rapidly absorbed with peak concentrations attained within 0.5-2 h and had an elimination half-life of 8 h. Between-subject variance on apparent clearance was estimated to be 47%. Age was the only characteristic to have a statistically significant effect on apparent clearance. A parametric Weibull survival model with treatment effect (dose) estimated a hazard ratio of 0.796, after adjusting for patient baseline factors that were significantly associated with OS. There was also a flat daily exposure-OS relationship within the observed exposure range, once all significant baseline covariates were included. Response covariates, such as reduction in CA19-9, time on treatment, and cumulative exposure over treatment cycles were also identified as significant factors for OS for patients with pancreatic cancer.ConclusionsThis analysis suggests that 300 mg/day galunisertib administered as 150 mg twice daily for 14 days on/14 days off treatment is an appropriate dosing regimen for patients with pancreatic cancer