ESR1 and EGF genetic variation in relation to breast cancer risk and survival

The main purposes of this thesis were to analyse common genetic variation in candidate genes and candidate pathways in relation to breast cancer risk, prognosticators and survival, to develop statistical methods for genetic association analysis for evaluating the joint importance of genes, and to investigate the potential impact of adding genetic information to clinical risk factors for projecting individualised risk of developing breast cancer over specific time periods. In Paper I we studied genetic variation in the estrogen receptor α and epidermal growth factor genes in relation to breast cancer risk and survival. We located a region in the estrogen receptor α gene which showed a moderate signal for association with breast cancer risk but were unable to link common variation in the epidermal growth factor gene with breast cancer aetiology or prognosis. In Paper II we investigated whether suspected breast cancer risk SNPs within genes involved in androgen-to-estrogen conversion are associated with breast cancer prognosticators grade, lymph node status and tumour size. The strongest association was observed for a marker within the CYP19A1 gene with histological grade. We also found evidence that a second marker from the same gene is associated with histological grade and tumour size. In Paper III we developed a novel test of association which incorporates multivariate measures of categorical and continuous heterogeneity. In this work we described both a single-SNP and a global multi-SNP test and used simulated data to demonstrate the power of the tests when genetic effects differ across disease subtypes. In Paper IV we assessed the extent to which recently associated genetic risk variants improve breast cancer risk-assessment models. We investigated empirically the performance of eighteen breast cancer risk SNPs together with mammographic density and clinical risk factors in predicting absolute risk of breast cancer. We also examined the usefulness of various prediction models considered at a population level for a variety of individualised breast cancer screening approaches. The goal of a genetic association study is to establish statistical associations between genetic variants and disease states. Each variant linked to a disease can lead the way to a better understanding of the underlying biological mechanisms that govern the development of a disease. Increased knowledge of molecular variation provides the opportunity to stratify populations according to genetic makeup, which in turn has the potential to lead to improved disease prevention programs and improved patient care

Microbial Dysregulation of the Gut-Lung Axis in Bronchiectasis

This is the author accepted manuscript. The final version is available from the American Thoracic Society via the DOI in this recordIntroduction: Emerging data supports the existence of a microbial ‘gut-lung’ axis that remains unexplored in bronchiectasis. Methods: Prospective and concurrent sampling of gut (stool) and lung (sputum) was performed in a cohort of n=57 individuals with bronchiectasis and subjected to bacteriome (16S rRNA) and mycobiome (18S ITS) sequencing (total 228 microbiomes). Shotgun metagenomics was performed in a subset (n=15; 30 microbiomes). Data from gut and lung compartments were ‘integrated’ by weighted Similarity Network Fusion (wSNF), clustered and subjected to co-occurrence analysis to evaluate ‘gut-lung’ networks. Murine experiments were undertaken to validate specific Pseudomonas-driven ‘gut-lung’ interactions. Results: Microbial communities in stable bronchiectasis demonstrate significant ‘gut-lung’ interaction. Multi-biome integration followed by unsupervised clustering reveals two patient clusters, differing by ‘gut-lung’ interactions and with contrasting clinical phenotypes. A ‘high gut-lung interaction’ cluster characterized by lung Pseudomonas, gut Bacteroides and gut Saccharomyces associates with increased exacerbations, greater radiological and overall bronchiectasis severity while the ‘low gut-lung interaction’ cluster demonstrates an overrepresentation of lung commensals including Prevotella, Fusobacterium and Porphyromonas with gut Candida. The lung Pseudomonas-gut Bacteroides relationship, observed in the ‘high gut-lung interaction’ bronchiectasis cluster, was validated in a murine model of lung Pseudomonas aeruginosa (PAO1) infection. This interaction was abrogated following antibiotic (imipenem) pre-treatment in mice confirming the relevance and therapeutic potential of targeting the gut microbiome to influence the ‘gut-lung’ axis. Metagenomics in a subset of individuals with bronchiectasis corroborated our findings from targeted analyses. Conclusion: A dysregulated ‘gut-lung’ axis, driven by lung Pseudomonas, associates with poorer clinical outcomes in bronchiectasis.Engineering and Physical Sciences Research Council (EPSRC)National Medical Research Council, Singapore Ministry of HealthFondazione IRCCS Cà Grand

Common genetic variability in ESR1 and EGF in relation to endometrial cancer risk and survival

We investigated common genetic variation in the entire ESR1 and EGF genes in relation to endometrial cancer risk, myometrial invasion and endometrial cancer survival. We genotyped a dense set of single-nucleotide polymorphisms (SNPs) in both genes and selected haplotype tagging SNPs (tagSNPs). The tagSNPs were genotyped in 713 Swedish endometrial cancer cases and 1567 population controls and the results incorporated into logistic regression and Cox proportional hazards models. We found five adjacent tagSNPs covering a region of 15 kb at the 5′ end of ESR1 that decreased the endometrial cancer risk. The ESR1 variants did not, however, seem to affect myometrial invasion or endometrial cancer survival. For the EGF gene, no association emerged between common genetic variants and endometrial cancer risk or myometrial invasion, but we found a five-tagSNP region that covered 51 kb at the 5′ end of the gene where all five tagSNPs seemed to decrease the risk of dying from endometrial cancer. One of the five tagSNPs in this region was in strong linkage disequilibrium (LD) with the untranslated A61G (rs4444903) EGF variant, earlier shown to be associated with risk for other forms of cancer

Search for Dark Matter and Supersymmetry with a Compressed Mass Spectrum in the Vector Boson Fusion Topology in Proton-Proton Collisions at root s=8 TeV

Peer reviewe

Search for lepton flavour violating decays of the Higgs boson to eτand eμin proton–proton collisions at √s=8TeV

A direct search for lepton flavour violating decays of the Higgs boson (H) in the H →eτand H →eμchannels is described. The data sample used in the search was collected in proton–proton collisions at √s=8TeVwith the CMS detector at the LHC and corresponds to an integrated luminosity of 19.7fb−1. No evidence is found for lepton flavour violating decays in either final state. Upper limits on the branching fractions, B(H →eτ) <0.69%and B(H →eμ) <0.035%, are set at the 95% confidence level. The constraint set on B(H →eτ)is an order of magnitude more stringent than the existing indirect limits. The limits are used to constrain the corresponding flavour violating Yukawa couplings, absent in the standard model

Measurement of the WZ production cross section in pp collisions at root s=13 Tev

Peer reviewe

Measurements of the t(t)over-bar production cross section in lepton plus jets final states in pp collisions at 8 and ratio of 8 to 7 TeV cross sections

Peer reviewe

Relative Modification of Prompt psi(2S) and J/psi Yields from pp to PbPb Collisions at root(S)(NN)=5.02 TeV

Peer reviewe

Measurements of the Upsilon(1S), Upsilon(2S), and Upsilon(3S) differential cross sections in pp collisions at root s=7 TeV

Peer reviewe