# The Evolving Landscape of Flowcytometric Minimal Residual Disease Monitoring in B-Cell Precursor Acute Lymphoblastic Leukemia

**Authors:** Martijn W. C. Verbeek, Vincent H. J. van der Velden

PMC · DOI: 10.3390/ijms25094881 · 2024-04-30

## TL;DR

This paper reviews how flow cytometry is used to detect minimal residual disease in B-cell precursor acute lymphoblastic leukemia and highlights recent advancements and challenges in the field.

## Contribution

The paper introduces novel flow cytometry markers and discusses challenges and future directions in MRD monitoring due to targeted therapies.

## Key findings

- Novel markers like CD58 and CD81 improve MRD detection in BCP-ALL.
- Eight-color flow cytometry protocols can achieve sensitivities comparable to PCR-based methods.
- CD19-negative relapses pose challenges for MRD analysis, prompting the use of alternative markers like CD22.

## Abstract

Detection of minimal residual disease (MRD) is a major independent prognostic marker in the clinical management of pediatric and adult B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL), and risk stratification nowadays heavily relies on MRD diagnostics. MRD can be detected using flow cytometry based on aberrant expression of markers (antigens) during malignant B-cell maturation. Recent advances highlight the significance of novel markers (e.g., CD58, CD81, CD304, CD73, CD66c, and CD123), improving MRD identification. Second and next-generation flow cytometry, such as the EuroFlow consortium’s eight-color protocol, can achieve sensitivities down to 10−5 (comparable with the PCR-based method) if sufficient cells are acquired. The introduction of targeted therapies (especially those targeting CD19, such as blinatumomab or CAR-T19) introduces several challenges for flow cytometric MRD analysis, such as the occurrence of CD19-negative relapses. Therefore, innovative flow cytometry panels, including alternative B-cell markers (e.g., CD22 and CD24), have been designed. (Semi-)automated MRD assessment, employing machine learning algorithms and clustering tools, shows promise but does not yet allow robust and sensitive automated analysis of MRD. Future directions involve integrating artificial intelligence, further automation, and exploring multicolor spectral flow cytometry to standardize MRD assessment and enhance diagnostic and prognostic robustness of MRD diagnostics in BCP-ALL.

## Linked entities

- **Proteins:** CD58 (CD58 molecule), CD81 (CD81 molecule), NRP1 (neuropilin 1), NT5E (5'-nucleotidase ecto), CEACAM6 (CEA cell adhesion molecule 6), IL3RA (interleukin 3 receptor subunit alpha), CD19 (CD19 molecule), CD22 (CD22 molecule), CD24 (CD24 molecule)

## Full-text entities

- **Genes:** IL3RA (interleukin 3 receptor subunit alpha) [NCBI Gene 3563] {aka CD123, IL-3R-alpha, IL3R, IL3RAY, IL3RX, IL3RY}, NRP1 (neuropilin 1) [NCBI Gene 8829] {aka BDCA4, CD304, NP1, NRP, VEGF165R}, CD24 (CD24 molecule) [NCBI Gene 100133941] {aka CD24A}, CD58 (CD58 molecule) [NCBI Gene 965] {aka LFA-3, LFA3, ag3}, CD22 (CD22 molecule) [NCBI Gene 933] {aka SIGLEC-2, SIGLEC2}, NT5E (5'-nucleotidase ecto) [NCBI Gene 4907] {aka CALJA, CD73, E5NT, NT, NT5, NTE}, CEACAM6 (CEA cell adhesion molecule 6) [NCBI Gene 4680] {aka CD66c, CEAL, NCA, NCA-50/90}, CD81 (CD81 molecule) [NCBI Gene 975] {aka CVID6, S5.7, TAPA1, TSPAN28}, CD19 (CD19 molecule) [NCBI Gene 930] {aka B4, CVID3}
- **Diseases:** Acute Lymphoblastic Leukemia (MESH:D054198), BCP-ALL (MESH:D015452)
- **Chemicals:** blinatumomab (MESH:C510808)

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC11084622/full.md

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Source: https://tomesphere.com/paper/PMC11084622