Abstract

Abstract

Abstract

Abstract
The cis-regulatory effects responsible for cancer development have not been as extensively studied as the perturbations of the protein coding genome in tumorigenesis. To better characterize colorectal cancer (CRC) development we conducted an RNA-sequencing experiment of 103 matched tumour and normal colon mucosa samples from Danish CRC patients, 90 of which were germline-genotyped. By investigating allele-specific expression (ASE) we show that the germline genotypes remain important determinants of allelic gene expression in tumours. Using the changes in ASE in matched pairs of samples we discover 71 genes with excess of somatic cis-regulatory effects in CRC, suggesting a cancer driver role. We correlate genotypes and gene expression to identify expression quantitative trait loci (eQTLs) and find 1,693 and 948 eQTLs in normal samples and tumours, respectively. We estimate that 36% of the tumour eQTLs are exclusive to CRC and show that this specificity is partially driven by increased expression of specific transcription factors and changes in methylation patterns. We show that tumour-specific eQTLs are more enriched for low CRC genome-wide association study (GWAS) P values than shared eQTLs, which suggests that some of the GWAS variants are tumour specific regulatory variants. Importantly, tumour-specific eQTL genes also accumulate more somatic mutations when compared to the shared eQTL genes, raising the possibility that they constitute germline-derived cancer regulatory drivers. Collectively the integration of genome and the transcriptome reveals a substantial number of putative somatic and germline cis-regulatory cancer changes that may have a role in tumorigenesis.

Abstract
Breast cancer is one of the most mediated malignant diseases, because of its high incidence and prevalence, but principally due to its physical and psychological invasiveness. Surgeons and patients have often many options to consider for undergoing the procedure. The ability to visualise the potential outcomes of the surgery and make decisions on their surgical options is, therefore, very important for patients and surgeons. In this paper we investigate the fitting of a 3d point cloud of the breast to a parametric model usable in surgery planning, obtaining very promising results with real data.

Abstract
The design of injection mold tools is a complex process for which market pressures demand ever-shorter development time and higher quality level. Thus, it is considered imperative to adopt new methods and tools to support the design process, in order to achieve a more effective mold design solution. Based on this assumption, a multidisciplinary framework was developed, centered on Design for Six Sigma methodology and reinforced with a set of highly valued techniques, namely: the European Customer Satisfaction, the Axiomatic Design and the Multidisciplinary Design Optimization. As a result, a platform was built to support the design of any mold tool without undercuts, which tackles the design of an injection mold as a fully integrated multidisciplinary optimization problem, oriented by customer preferences and their impositions. A set of specific analysis sub-modules is integrated through an overseeing optimization code system, responsible for the numerical simulation of the injection process. This platform was validated through the comparison with an existing mold, whose results attained highlight the great potential of the proposed framework to achieve mold design improvement. In particular, the value of mold solutions generated led to a global improvement on mold performance by 5 %.