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Updated: Apr 5, 2026

Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management
Published on: November 30, 2022
Strengthening biobank networks: A Latvian case study within the StoP project
Evita Gašenko1, Ilona Freiliba2, Ilona Kojalo2
1Clinic for Medical Treatment of Solid Tumours, Riga East University Hospital, Riga, Latvia; Institute of Clinical and Preventive Medicine, Faculty of Medicine, University of Latvia, Riga, Latvia.
Purpose:
This publication aims to provide an overview of the challenges involved in establishing connections between national and international research teams and biobanks for the purposes of sample collection, preservation, and data analysis, using the Stomach Cancer Pooling (StoP) project as a case study.
Materials And Methods:
The StoP project illustrates collaboration in gastric cancer risk factor analysis. Internationally, the project integrates 33 research teams from 15 countries and associated biobanks to support the collection, preservation, and analysis of samples for epidemiological and genetic studies. Within Latvia, project activities involved the systematic collection of epidemiological, clinical, and biological data across multiple institutions. Latvian contributions were integrated into the broader StoP consortium to support comprehensive analyses.
Results:
The collaborative effort has strengthened local biobanking infrastructure by expanding prospective data collection, updating standard operating procedures, and harmonizing retrospective datasets. It enhanced multi-institutional collaboration nationally and internationally. Key challenges were identified in data collection, harmonization, storage, funding, and sustainability. The StoP project working group has produced over forty scientific publications, with Latvian data contributing to five studies on smoking, Helicobacter pylori infection, sex-based differences, and proton pump inhibitor use. Current efforts focus on genome-wide association studies using collected biological specimens and epidemiological data.
Conclusions:
The methods from the StoP project can be replicated across other institutions by focusing on robust ethical frameworks and data-sharing agreements. Effective cross-institutional collaboration further supports these efforts. Together, these practices increase public trust and enhance the scalability of such initiatives globally.
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