Cho EH, et al. J Gynecol Oncol. 2024 Mar;35:e72. https://doi.org/10.3802/jgo.2024.35.e72

Objectives: Despite its utility, interpreting multiparameter flow cytometry (MFC) data for hematologic malignancy remains time-intensive and complex. This study evaluated the applicability of two dimensionality reduction (DR) algorithms, t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP), to MFC data of hematologic malignancy. Methods: A total of 237 samples were re-analyzed by t-SNE- and UMAP-based gating: 80 with acute leukemia orientation tube panel, 42 with B-cell lymphoma (BCL) panel, 45 with multiple myeloma (MM) panel, 40 and 30 with measurable residual disease (MRD) panels for B-cell acute lymphoblastic leukemia (B-MRD) and MM (MM-MRD), respectively. Each result was compared to the manual gating, and sensitivity and precision were assessed using BCL and B-MRD panels. Results: Compared to manual gating, DR-based gating demonstrated agreements over 95.0 % for all MFC panels, and quantitative correlations ( ρ ) exceeded 0.94. Both t-SNE- and UMAP-based gating showed a sensitivity and negative predictive value of 100 %. Also, in one sample each from the BCL and MM-MRD panels, DR-based gating identified populations that were missed by manual gating. Sensitivity evaluation showed that both t-SNE- and UMAP-based gating successfully identified MRD populations down to the lowest MRD level of 10 ^−5.30 when applying primary-gating strategy for CD19-positive population. Precision evaluation showed coefficient of variation below 10 % across all levels. Conclusions: This study shows that DR-based gating streamlines data interpretation and minimizes overlooked populations, demonstrating significant potential as a valuable tool in MFC analysis for hematologic malignancies.

Park MS, et al. Ann Lab Med. 2019 Sep;39(5):430-437. https://doi.org/10.3343/alm.2019.39.5.430

Min-Seung Park, M.D., Hyun-Young Kim, M.D., Jae Joon Lee, M.D., Duck Cho, M.D., Chul Won Jung, M.D., Hee-Jin Kim, M.D., and Sun-Hee Kim, M.D.. Ann Lab Med 2023;43:310-4. https://doi.org/10.3343/alm.2023.43.3.310

Min-Seung Park, M.D., Boram Kim, M.D., Jun Ho Jang, M.D., Ph.D., Chul Won Jung, M.D., Ph.D., Hee-Jin Kim, M.D., Ph.D., and Hyun-Young Kim, M.D., Ph.D.. Ann Lab Med -0001;0:. https://doi.org/10.3343/alm.2024.0190