Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
December 8, 2025BloodOpen Access

Computational immunophenotypic profiling of multiple myeloma by flow cytometry and bioinformatics integration

View Full Paper
Ask AI
Bookmark
Share

Authors

ÁMÁyslla MartinsUniversidade Federal do Rio Grande do NorteAPAldair Sousa PaivaInstitute of Applied Economic ResearchSMSandra Márcia MuxelUniversidade de São Paulo

Discussion

Loading...

Member takes

Implication

Computational analysis reveals immunophenotypic changes in plasma cell dyscrasias, suggesting diagnostic improvements.

Key Points

  • To explore the immunophenotypic profile of plasma cell dyscrasias using R-based computational analysis.
  • Analyzed multiparameter flow cytometry data from 145 patients with multiple myeloma and inconclusive diagnoses.
  • Utilized FlowSOM for cell cluster identification and conducted statistical comparisons.
  • Data preprocessing in R included compensation, log transformation, and plasma cell gating.
  • FlowSOM indicated increased plasma cell populations in multiple myeloma cases.
  • Median fluorescence intensity variability revealed maturation defects and clonal expansion.
  • Association analysis highlighted significant relationships between CD38/CD138 and aberrant markers like CD117.

Cite This Study

Martins et al. (2025) studied this question.

synapsesocial.com/papers/693624d74fa91c937236d0a9https://doi.org/10.1182/blood-2025-2244
View Full Paper
Ask AI
Bookmark
Share