Alfredo Carrato
- Ramon y Cajal University Hospital, Department of Medical Oncology
- Madrid - Spain
Bozena Smolkova
- Biomedical Research Center, Slovak Academy of Sciences, Cancer Research Institute, Department of Molecular Oncology
- Bratislava - Slovakia
Vita Rovite
- Latvian Biomedical Research and Study Centre, Human Genetics and Molecular Medicine
- Riga - Latvia
Manousos Konstadoulakis
- National and Kapodistrian University of Athens, 1st Department of Propaedeutic Surgery
- Athens - Greece
David Hevia
- Bioquochem Company, Department of Research and Development
- Llanera, Asturias - Spain

Background and rationale: Standardized clinical management of pancreatic neuroendocrine tumours (PNETs) is restricted by different aspects of the disease, as its relative rarity, heterogeneous presentation, the limited understanding of tumour biology and the lack of risk stratification systems. While surgical excision remains the primary therapy, most patients are not candidates for resection.
Hypothesis: Prompt, specific and sensitive detection and characterisation of PNETs could lead to early detection, increasing the chance for surgical intervention and improve patients’ survival. Circulating tumour cells (CTCs) are considered attractive biomarkers for liquid biopsy as they represent an early step in blood-borne metastasis.
Aims: By building up a tissue bank of genetically characterized tumours, development of patient-derived xenografts (PDXs) and organoids, we aim to identify PNET-specific biomarkers urgently needed to design a NExT generation nanotechnology based microfluidic device and integrate the technology of minimally invasive liquid biopsy in the early detection of PNETs.
Methods: Serum and tissue samples will be collected from PNET patients and their clinical and lab records will be recorded. In clinical samples an expression study and genomic analysis will be performed by different molecular techniques whereas, in parallel organdies, PDX and CTC-derived xenografts (CDX) will be established. Based on the acquired data a NExT generation microfluidic device will be developed for PNET-detection and follow-up.
Expected results and potential impact: Better understanding of the etiopathogenetic determinants involved in PNETs formation resulting from the multidisciplinary collaboration within ‘NExT” consortium will hopefully deliver a nanotechnology-based microfluidic (next generation) device that by means of CTCs detection will present a powerful tool for the early detection of PNET tumors and patients follow-up, contributing to better medical treatment.

Due to their rarity, pancreatic neuroendocrine tumors (PanNETs) present significant challenges in their management. These challenges include difficulties in detecting early recurrence, determining which patients would benefit from additional therapy, and assessing the response to treatment in a timely manner. By identifying specific novel biomarkers and developing methods for the early detection of PanNETs, the NExT project aimed to address these challenges. Thanks to the collaborative effort, a biobank of 121 tissue and blood samples from PanNET patients was established, and these samples were analyzed to study the molecular characteristics of the tumors. The analysis revealed distinct patterns of gene activity in the tumor tissue, nearby normal tissue, lymph nodes, and tumors that had spread to other organs. By comparing these patterns, several genes were identified that showed potential as diagnostic and prognostic markers for PanNETs. Protocols were also developed for growing PanNET cells in the laboratory using tissue samples obtained during surgery, enabling studying these cells more closely and testing potential treatments. Additionally, a microfluidic device combined with specialized software showed promise in detecting individual PanNET cells, which could be useful for early detection. The efficient international collaboration enabled young researchers to develop new skills and gain access to additional resources, ultimately helping advance PanNET research.

NExT

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