NIBIT Annual Meeting

Lymphoid malignancies present significant diagnostic challenges due to overlapping immunophenotypic features between tumor cells and reactive background cells, complicating the distinction between indolent lymphomas and benign lymph node hyperplasia [Nicolae A, Hemato, 2024, DOI:10.3390/hemato5030026]. Moreover, some Hodgkin lymphoma (HL) subtypes, such as lymphocyte-rich (LRHL) and nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) and certain variants of diffuse large B-cell lymphoma (DLBCL), exhibit similar phenotypic profiles despite having different therapeutic implications [PMID: 35741318]. This study aims to leverage sequential immunofluorescence (seqIF™, PMID: 37813886) for the spatial profiling of lymphoma to improve differential diagnosis and to uncover spatial patterns unique to each lymphoma subtype, providing insights into potential predictors of immunotherapy response. 

Here, we optimized a seqIF™ panel of 21 markers, using antibodies approved for clinical immunohistochemistry (IHC), to phenotype mature B-cell lymphomas on the COMET™ platform. This panel was applied to tissue microarrays prepared from representative cases of DLBCL, HL, indolent lymphomas, and benign lymph node hyperplasia. Each marker of the optimized panel was visually validated by certified pathologists, comparing seqIF™ results against corresponding IHC images.  

Computation of spatial matrix successfully identified tumor cells and reactive cells using thresholding of fluorescence intensity and cell diameter, particularly in HL and DLBCL cases that exhibited similar immunophenotypes at first glance. This enabled us to map classified cell events back to the tissue sections, allowing direct spatial correlation with stained images for a comprehensive analysis of cell distribution. Ongoing work aims at refining our lymphoma spatial profiles through the integration of spatial transcriptomics readout on the same sample cohort.

Together these results highlight the potential of multiplex immunofluorescence (mIF) for the diagnostic phenotyping of lymphoma, transferring clinically validated antibodies into a mIF panel. The ability to assess both phenotypic and spatial characteristics of tumor and reactive cells will enhance our understanding of lymphoma biology and provide new insights into predictive markers for immunotherapy responses.