Automated Database and Pattern-guided Immunophenotypic Classification of Acute Leukaemia Using Next Generation Flow Cytometry

Bibawi, Hani (2021) Automated Database and Pattern-guided Immunophenotypic Classification of Acute Leukaemia Using Next Generation Flow Cytometry. Doctoral thesis (PhD), Manchester Metropolitan University.

Preview

Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (4MB) | Preview

Abstract

Acute leukaemia is a heterogeneous group of disorders characterized by clonal expansion of abnormal haemopoietic cells arrested at early stages of maturation. Appropriate management of these disorders requires accurate diagnosis and classification based on the WHO classification of tumors of haemopoietic and lymphoid tissues. Despite several advances in molecular pathology, flow cytometry still remains an essential tool for diagnosis of this group of haematological disorders. The aim of this study was to validate the EuroFlow acute leukaemia orientation tube (ALOT) and its corresponding database-guided interpretation tool using the FACS Canto II flow cytometer and following in-house cytometer settings, compensation and staining procedures. The study also aimed to use the principal component analysis (PCA) and automated population separator (APS) tools on the Infinicyt software to merge the standard flow cytometry files (FCS) from the in-house acute leukaemia panel in order to create and compare immunophenotypic profiles of acute leukaemia cases in this study. A total of 24 specimens from 16 acute leukaemia cases were tested using both the in-house acute panel as well as the ALOT tube under validation. Results showed 100% agreement between the two methods as well as the ALOT automated database-guided interpretation tool compared to the conventional hematopathologist (expert-based) approach of results interpretation. Furthermore, the flow cytometry merged files and immunophenotypic profiles were successfully used to build in-house ALOT and acute leukaemia database-guided interpretation tools. Results of these newly developed tools showed 100% agreement II between the in-house database-guided tools and the conventional expert-based interpretation of flow cytometry results. Unsupervised comparison of the immunophenotypic profiles of B- acute lymphoblastic leukaemia (B-ALL) cases in this study showed some overlap between some cases with similar immunophenotypic profile and subsequent cytogenetic translocations as well as cases presented with CNS involvement. Further analysis confirmed that all the cases with CNS involvement in this study were CD34 negative. Limitations of this new approach were discussed in more detail, including the additional costs of the ALOT tube and the automated database interpretation tool. In conclusion, results of this study confirmed the validity of ALOT tube and its corresponding database using local cytometer settings and procedures. Results also showed that using next generation flow cytometry with automated database-guided interpretation tools is a promising approach that can facilitate standardised interpretation of flow cytometry results in future.