The Development of Tools to Investigate Potential Sources of Sample Misidentification Within a Biorepository: Case Studies

Abstract

Introduction:

Precise sample identification is crucial for the success of any biomedical research project. To ensure quality, biobanks follow best practices standards. However, errors such as mislabeling, sample switching, and other mishandling issues can still happen at various stages of the sample lifecycle at collection sites, within the biobank, in research laboratories, or during data management and analysis.

Objective:

To ensure sample integrity, the biobank at the Chan Soon-Shiong Institute of Molecular Medicine at Windber maintains detailed and accurate documentation throughout all sample handling stages. The biobank also develops additional quality tools to thoroughly investigate and correct discrepancies such as sample misidentification.

Methods:

Between 2018 and 2020, the biobank recorded a total of four misidentifications out of 284 sample isolations, resulting in a 1.4% misidentification rate. Alongside effective quality documentation procedures, a flowchart was created to trace and identify potential causes of reported sample discrepancies, followed by a decision tree outlining the steps to resolve the observed issues.

Results and Conclusion:

Here, we report how record documentation, a flow chart, and decision tree helped the successful resolution of sample misidentifications. In the reported case studies, these tools allowed us to conclude, in one case, that the source of error most likely occurred outside the biobank, while the other pointed to a sample switch during batch DNA processing within the biobank. All outcomes were confirmed by short tandem repeat analysis. These quality assessment tools ensure efficient biobanking that promotes research integrity.