Laying the groundwork for the Biobank of Rare Malignant Neoplasms at the service of the Hellenic Network of Precision Medicine on Cancer

Abstract

Biobanks constitute an integral part of precision medicine. They provide a repository of biospecimens that may be used to elucidate the pathophysiology, support diagnoses, and guide the treatment of diseases. The pilot biobank of rare malignant neoplasms has been established in the context of the Hellenic Network of Precision Medicine on Cancer and aims to enhance future clinical and/or research studies in Greece by collecting, processing, and storing rare malignant neoplasm samples with associated data. The biobank currently comprises 553 samples; 384 samples of hematopoietic and lymphoid tissue malignancies, 72 samples of pediatric brain tumors and 97 samples of malignant skin neoplasms. In this article, sample collections and their individual significance in clinical research are described in detail along with computational methods developed specifically for this project. A concise review of the Greek biobanking landscape is also delineated, in addition to recommended technologies, methodologies and protocols that were integrated during the creation of the biobank. This project is expected to re‑enforce current clinical and research studies, introduce advances in clinical and genetic research and potentially aid in future targeted drug discovery. It is our belief that the future of medical research is entwined with accessible, effective, and ethical biobanking and that our project will facilitate research planning in the '‑omic' era by contributing high‑quality samples along with their associated data.

Keywords: Biobank; ELSI; FFPE; cancer; precision medicine; rare neoplasms.

Figure 1

Sample distribution by department and tumor type. Each disease collection is illustrated by the same color palette as the department to which it belongs, while the part of the circle it occupies is proportional to the number of samples it contains. Specifically, collections of hematopoietic and lymphoid tissue malignancies (384 samples) from the 1st Department of Pathology are represented with green (follicular lymphomas, diffuse large b-cell lymphomas, hodgkin lymphomas, mantle cell lymphomas, hairy cell leukemias, cutaneous lymphomas, acute myelogenous leukemias, acute lymphoblastic leukemias), pediatric brain tumors (72 samples) from the Department of Biological Chemistry with blue (pilocytic astrocytomas, astrocytomas grade ll, astrocytomas grade lll, glioblastomas, medulloblastomas, ependymomas, atypical teratoid/rhabdoid tumors, craniopharyngiomas, gangliogliomas, primitive neuroectodermal tumors) and lastly malignant skin neoplasms (97 samples) from the 'Andreas Syggros' Hospital are rendered in gray (melanomas, normal skin surrounding melanomas, metastatic melanoma sites, cutaneous squamous cell carcinomas, metastatic cSCC lymph nodes). This graph was illustrated with the open-source visual 'Chord', a PowerBI business analytics service add-on by Microsoft. cSCC, cutaneous squamous cell carcinoma.

Figure 2

MIABIS information and governance model. The core components (Biobank, Sample Collection and Study) are represented in yellow. The individual-level components (Sample, Sample Donor and Event) are represented in orange. Any and all data included in this figure were taken directly from the MIABIS GitHub repository (https://github.com/BBMRI-ERIC/miabis) and were used in the creation of this project in order to comply with the European 'gold-standard' model. Merino-Martinez et al (43).