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Projeto de investigação
LA - ICVS/3B's - Associate Laboratory
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Isolation of acute myeloid leukemia blasts from blood using a microfluidic device
Publication . Teixeira, Alexandra; Sousa-Silva, Maria; Chícharo, Alexandre; Oliveira, Kevin; Moura, André; Carneiro, Adriana; Piairo, Paulina; Águas, Hugo; Sampaio-Marques, Belém; Castro, Isabel; Mariz, José; Ludovico, Paula; Abalde-Cela, Sara; Diéguez, Lorena; DCM - Departamento de Ciência dos Materiais; CENIMAT-i3N - Centro de Investigação de Materiais (Lab. Associado I3N); UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias; RSC - Royal Society of Chemistry
Acute myeloid leukemia (AML) is the most common form of acute leukemia in adults and associated with poor prognosis. Unfortunately, most of the patients that achieve clinical complete remission after the treatment will ultimately relapse due to the persistence of minimal residual disease (MRD), that is not measurable using conventional technologies in the clinic. Microfluidics is a potential tool to improve the diagnosis by providing early detection of MRD. Herein, different designs of microfluidic devices were developed to promote lateral and vertical mixing of cells in microchannels to increase the contact area of the cells of interest with the inner surface of the device. Possible interactions between the cells and the surface were studied using fluid simulations. For the isolation of leukemic blasts, a positive selection strategy was used, targeting the cells of interest using a panel of specific biomarkers expressed in immature and aberrant blasts. Finally, once the optimisation was complete, the best conditions were used to process patient samples for downstream analysis and benchmarking, including phenotypic and genetic characterisation. The potential of these microfluidic devices to isolate and detect AML blasts may be exploited for the monitoring of AML patients at different stages of the disease.
A novel tool for multi-omics network integration and visualization
Publication . Coletti, Roberta; Carrilho, João F.; Martins, Eduarda P.; Gonçalves, Céline S.; Costa, Bruno M.; Lopes, Marta B.; CMA - Centro de Matemática e Aplicações; UNIDEMI - Unidade de Investigação e Desenvolvimento em Engenharia Mecânica e Industrial; DEMI - Departamento de Engenharia Mecânica e Industrial; Elsevier
Gliomas are highly heterogeneous tumors with generally poor prognoses. Leveraging multi-omics data and network analysis holds great promise in uncovering crucial signatures and molecular relationships that elucidate glioma heterogeneity. However, the complexity of the problem and the high dimensionality of the data increase the challenges of integrating information across various biological levels. This study develops a comprehensive framework aimed at identifying potential glioma-type-specific biomarkers through innovative variable selection and integrated network visualization. We designed a two-step framework for variable selection using sparse network estimation across various omics datasets. This framework incorporates MINGLE (Multi-omics Integrated Network for GraphicaL Exploration), a novel methodology designed to merge distinct multi-omics information into a single network, enabling the identification of underlying relations through an innovative integrated visualization. The analysis was conducted using glioma omics datasets, with patients grouped based on the latest glioma classification guidelines. Our investigation of the glioma data led to the identification of variables potentially serving as glioma-type-specific biomarkers. The integration of multi-omics data into a single network through MINGLE facilitated the discovery of molecular relationships that reflect glioma heterogeneity, supporting the biological interpretation. Scripts and files for reproducing the analysis or adapting it to other applications, are available in R software.
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Entidade financiadora
Fundação para a Ciência e a Tecnologia
Programa de financiamento
6817 - DCRRNI ID
Número da atribuição
UIDB/50026/2020