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Biomarkers in neomark European project for oral cancers

: Poli, T.; Copelli, C.; Lanfranco, D.; Salvi, D.; Exarchos, K.; Picone, M.; Ardigò, D.; Steger, S.; Fonseca, M.J.R. da; Fazio, M. de; Martinelli, E.; Sesenna, E.


Preedy, V.R.:
Biomarkers in Cancer
Dordrecht: Springer, 2015 (Biomarkers in disease. Methods, discoveries and applications)
ISBN: 978-94-007-7681-4 (online)
ISBN: 978-94-007-7680-7 (print)
Aufsatz in Buch
Fraunhofer IGD ()

Oral cavity cancers are the seventh tumor by diffusion worldwide with more than 90% being diagnosed as oral squamous cell carcinomas (OSCCs). According to the latestWHO statistics, OSCC accounts for 5% of the cancer deaths worldwide, being the eighth more lethal cancer entity. Early identification of cancer relapses would have the potentiality to improve the disease control and the patient survival. NeoMark is a European co-funded research project (Seventh Framework Program, Information and Communication Technologies: EU-FP7-ICT-2007-2-22483-NeoMark) that has the objective to identify relevant biomarkers of OSCC recurrence. It integrates high-throughput gene expression analysis in tumor cells and IT-assisted imaging with traditional staging and follow-up protocols to improve the recurrence risk stratification and to obtain the earlier identification of locoregional relapses. The architecture of the project is based on the following key points: â Creation of a web appl ication tool: A unified interface that helps the storage and management of all information â NeoMark database: The heterogeneous NeoMark data (demographics and risk factors; clinical, pathological, and immunohistochemical parameters; filtered and cleaned genomic and imaging data) are stored in a single database â the Integrated Health Record Repository (IHRR) â on a central NeoMark server. The server contains the marker definition functional environment (MDFE), a data analysis module. Based on the heterogeneous input data, it estimates the likelihood of a relapse and identifies OSCC risk factors. â Imaging biomarker extraction: Several biomarkers are obtained from medical images such as CT and MRI scans (size, amount of necrosis from tumor and lymph nodes, etc.). To extract those features, a custom software tool â called the NeoMark Image Processing Tool â has specifically been developed. â Genomic data cleaning and filtering: Extraction of genomic data and filtering of genes with low data quality a