Sofia Fernandes
Name: Sofia Fernandes
E-mail: sfernandes@ipatimup.pt
Extension: 
225570700
Academic Degree: PhD


Sofia Fernandes
Sofia Fernandes
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Short CV

Sofia Fernandes is a Junior Researcher at the Intercellular Communication and Cancer Group, led by Professor José Carlos Machado. Sofia Fernandes graduated in Biochemistry (2001) by the Faculty of Sciences of the University of Porto and obtained her MSc (2003) and PhD (2008) in Human Reproductive Biology at Imperial College London. Following her PhD and over the last years, Sofia Fernandes has been a Postdoc/Junior Researcher at Ipatimup/i3S at the Epithelial Interactions in Cancer (EPIC) Group led by Professor Raquel Seruca. She also joined Instituto Superior Técnico (IST)-Institute for Systems and Robotics (ISR). Sofia Fernandes has been interested in the areas of Oncobiology, Applied Cancer Research, Computational Bioimaging and Technological and Translational Research. Specifically, her research has been focusing on exploring many aspects of epithelial cancers, in particular in unravelling novel cancer biomarkers and developing novel technological strategies for early cancer detection and monitor cancer progression with impact in patient stratification and therapeutic approaches. Sofia Fernandes (Fernandes MS) is author and co-author of several publications in international peer-review journals.


Highlights
Colorectal cancer is one of the leading causes of cancer mortality worldwide. Patients diagnosed with metastatic colorectal cancer have a poor prognosis and the available therapies are limited. In recent years, as an attempt to improve the survival rates of patients, new targeted biological therapies have been developed, namely EGFR-targeted therapies, and used in combination with the standard chemotherapy regimens. However, such therapies are only efficient in a subgroup of patients. It is therefore urgent to unravel new therapy approaches. The current work focuses on the investigation of alternative therapy strategies for colorectal cancer and on the identification of putative biomarkers able to predict therapy resistance.

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