Modeling Variation in the Human Lymphoma Microenvironment with the Eμ-Myc Mouse Model
Authors: Friedman Daphne R. , Rempel Rachel E. , Jiang Xiaolei , Nevins Joseph R. 
Published: October 2019

Abstract
Abstract 789

Background:
The spectrum of aggressive B-cell lymphomas includes Burkitt lymphoma (BL) and diffuse large B-cell lymphoma (DLBCL). Extensive clinical, biological, and genetic heterogeneity is present across these diseases. One example is the link between clinical outcomes and variation in the stromal microenvironment, immune infiltrate, and angiogenesis. Direct and indirect interactions between malignant cells and the microenvironment ultimately promote viability and maintenance of lymphomas. To experimentally evaluate this further, we utilized the transgenic Eμ-myc mouse model, which we previously demonstrated has genomic variation and mimics different entities across the aggressive B-cell lymphoma spectrum.

Methods:
Eμ-myc transgenic mice were monitored twice weekly for visible or palpable lumps, a hunched posture, tachypnea, a swollen belly, or ruffled fur, and were thereafter promptly sacrificed. Lymphoma tissue was collected at dissection, homogenized into single cell suspensions, and evaluated using gene expression microarrays and flow cytometry. Gene expression data was RMA normalized and controlled for batch effect with ComBat, when necessary. Gene Ontology was evaluated using DAVID, and pathway signature predictions were calculated using ScoreSignature on the Duke GenePattern server. Lymphoma cells were cultured in vitro on an irradiated 3T3 feeder layer with and without the addition of CD40 ligand (CD40L) and/or CpG ODN 1668. Surface expression of B220, CD3e, CD4, and CD8, and measurement of activated caspase-3, 7AAD, and BrdU incorporation were evaluated with flow cytometry.

Results:
Seventy-six Eμ-myc mice were monitored and developed lymphoma at a median age of 145 days (range 43 – 595). Unsupervised and supervised genomic analyses identified two reproducible clusters of lymphoma, which had significantly different time to lymphoma onset (p = 0.0003, log rank test). The early onset group (“Cluster 1”) was defined by gene ontology terms related to cell cycle, while the late onset group (“Cluster 2”) was defined by gene ontology terms related to immune function. Likewise, compared to Cluster 1, Cluster 2 lymphomas had significantly higher predictions of interferon α, interferon γ, and tumor necrosis factor α pathway activity, measured using genomic signatures of these pathways (p values all < 0.0001, Wilcoxon rank sum test). Cluster 1 lymphoma shares a genomic profile with human BL, while Cluster 2 lymphoma is genomically similar to DLBCL. The two clusters of Eμ-myc lymphoma also had significantly different grouping according to published stromal signatures that reflect extracellular matrix deposition/histiocytic infiltrate or angiogenesis in human lymphomas (p < 0.0001, Fisher's exact test). Eμ-myc lymphomas demonstrated a range of infiltrating CD3e+ T lymphocytes (median 7.2%, range 0.1 – 41.6%), with an equal expression of CD4 and CD8. Cluster 2 Eμ-myc lymphomas grouped by an angiogenesis stroma signature had a significantly higher extent of T-cell infiltrate than other lymphomas (p = 0.046, Kruskal-Wallis test). Lastly, after one day of culture on a feeder layer, Cluster 1 lymphoma cells were as viable but had higher levels of proliferation than Cluster 2 lymphoma cells. However, the addition of CD40L and/or CpG improved viability and induced proliferation to a greater extent in Cluster 2 lymphoma cells than Cluster 1 lymphoma cells (Tables 1 and 2, p = 0.04 for Table 1, p < 0.0001 for Table 2, Chi-squared test).

Conclusions:
Eμ-myc transgenic mice develop divergent types of lymphoma defined by heterogeneity in gene expression and lymphoma microenvironment. Cluster 1 lymphomas represent BL and proliferate in an autonomous fashion, while Cluster 2 lymphomas represent DLBCL and appear to be driven by immune processes and to respond to interactions with the immune microenvironment. These distinctions indicate that the Eμ-myc model could be useful for studying and understanding the effect of the microenvironment on aggressive human lymphomas.

Disclosures:
No relevant conflicts of interest to declare.