Associate Laboratory of  Energy, Transports and Aeronautics

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Publicações

Twiner: correlation-based regularization for identifying common cancer gene signatures

Publication . Lopes, Marta B.; Casimiro, Sandra; Vinga, Susana

Background: Breast and prostate cancers are typical examples of hormone-dependent cancers, showing remarkable similarities at the hormone-related signaling pathways level, and exhibiting a high tropism to bone. While the identification of genes playing a specific role in each cancer type brings invaluable insights for gene therapy research by targeting disease-specific cell functions not accounted so far, identifying a common gene signature to breast and prostate cancers could unravel new targets to tackle shared hormone-dependent disease features, like bone relapse. This would potentially allow the development of new targeted therapies directed to genes regulating both cancer types, with a consequent positive impact in cancer management and health economics. Results: We address the challenge of extracting gene signatures from transcriptomic data of prostate adenocarcinoma (PRAD) and breast invasive carcinoma (BRCA) samples, particularly estrogen positive (ER+), and androgen positive (AR+) triple-negative breast cancer (TNBC), using sparse logistic regression. The introduction of gene network information based on the distances between BRCA and PRAD correlation matrices is investigated, through the proposed twin networks recovery (twiner) penalty, as a strategy to ensure similarly correlated gene features in two diseases to be less penalized during the feature selection procedure. Conclusions: Our analysis led to the identification of genes that show a similar correlation pattern in BRCA and PRAD transcriptomic data, and are selected as key players in the classification of breast and prostate samples into ER+ BRCA/AR+ TNBC/PRAD tumor and normal tissues, and also associated with survival time distributions. The results obtained are supported by the literature and are expected to unveil the similarities between the diseases, disclose common disease biomarkers, and help in the definition of new strategies for more effective therapies.

2019Artigo científico

Acesso aberto

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Primary stability analysis of stemless shoulder implants

Publication . Quental, C.; Folgado, J.; Comenda, M.; Monteiro, Jacinto; Sarmento, Marco

Although the primary stability of joint implants is fundamental for successful osseointegration, little is know about this issue in the context of stemless shoulder implants. Considering 3D finite element models, the purpose of this study was to evaluate the primary stability of five stemless designs, based on the Sidus, SMR, Simpliciti, Eclipse, and Global Icon stemless systems. Three alternative bone quality conditions were considered for cancellous bone. For the Sidus, SMR, and Simpliciti designs, which do not possess a collar that sits on the cortical rim of the humeral resected surface, contact and no contact conditions were considered between the bone surface and the humeral head components. Micromotions at bone-implant interfaces promoting osseointegration were computed as a measure of primary stability for eight load cases consisting of peak in vivo joint loads measured during selected upper limb activities. Under good bone quality conditions, all stemless designs presented micromotions below 150 μm. The Eclipse-based and Global-Icon based designs were the least sensitive to bone quality. Stemless designs presenting a solid collar or contact between the humeral head component and bone provided more stability. Overall, the Eclipse-based and Global Icon-based designs presented the best performance from the primary stability point of view. However, if bone adaptation data available in the literature are considered along with the primary stability data computed here, the Global Icon-based design, as well as other designs, might be considered superior long-term options due to their better compromise between primary stability and impact on bone adaptation.

2020Artigo científico

Acesso restrito

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Entidade financiadora

Fundação para a Ciência e a Tecnologia

Programa de financiamento

6817 - DCRRNI ID

Número da atribuição

UID/EMS/50022/2019