Citations

Multiple myeloma (MM) is characterized by clonal expansion of malignant plasma cells (PCs) and aberrant production of monoclonal immunoglobulin detected as an M spike using serum protein electrophoresis. In the United States, MM represents ~15% of hematologic malignancies and is one of the few cancers increasing in incidence (e.g., 14,400 in 1996 to 32,270 in 2020, from SEER). Despite recent treatment advances, patients diagnosed with high risk/refractory MM (hrrMM) have an overall survival of only three years. Recently, our lab developed the first genetically engineered NrasQ61R; Myc-driven myeloma model (VQ mice). The VQ model recapitulates most biological and clinical features of hrrMM. VQ cells are serially transplantable into syngeneic recipients and can be propagated in vitro. As such, the VQ model could serve as a robust pre-clinical platform for drug screening and in vivo testing of new therapies to treat hrrMM. Whole exome sequencing (WES) of CD138+ cells from five primary VQ mice identified eight recurrently mutated genes. Of these eight genes, two have been previously identified as recurrently mutated in MM patients while the remainder appear to be unique to VQ myeloma. Meanwhile, RNA sequencing of CD138+ cells taken from both primary VQ mice and secondary VQ recipients show differential gene expression for five of these eight genes. Gene ontology analysis of recurrently mutated genes indicates that these genes play a role in interferon signaling, as well as receptor tyrosine kinase signaling. Here, we report the results of a high-throughput repurposing screen using the NCI's AOD IX library, which consists of 147 FDA-approved anti-cancer drugs. VQ cells were treated with 0.1 and 1µM of each compound in the presence or absence of 10nM of Trametinib (Tra), a potent MEK inhibitor. Screening results returned expected positive hits that were previously FDA approved for MM treatment (green dots, Panel 1B), such as proteasome inhibitors, histone deacetylase inhibitors, and chemotherapy drugs. Importantly, VQ cells were resistant to some compounds currently used to treat MM, including the BCL-2 inhibitor Venetoclax, the alkylating agent Melphalan, and the topoisomerase II inhibitor Etoposide (red dots, Panel 1B). De novo resistance to these therapies further indicates that the VQ cells model a multi-drug resistant MM. Two compounds were chosen for further testing: the protein translation inhibitor Omacetaxine (Oma) based on its single agent efficacy, and the multi-receptor tyrosine kinase inhibitor Ponatinib (Pot) based on its high synergy with Tra. Combination Index testing confirmed initial drug screening results but showed some antagonism between combination Oma and Pot treatment. We proceeded with in vivo testing of two novel combination therapies, in which 3-week treatment cycles were followed by a 1-week rest period between cycles: Three weeks of daily Tra and Pot treatment (TP), or two weeks of Tra and Pot treatment followed by one week of Oma (TPO) treatment. Vehicle (Veh) treated and Tra only treated mice were used as controls. Treatment efficacy was assessed against VQ-D1 MM, which grows primarily in the bone marrow (BM) and metastasizes to the spleen and liver of recipient mice. Four weeks post-treatment, myeloma growth in the BM was significantly reduced in both combo treatment groups, while MM burden in the spleen was also reduced. Overall, both TP and TPO treatment significantly extended survival compared to Veh or Tra treated mice, and significantly reduced liver extramedullary disease. To further test the range of Tra/Pot synergy in vivo, Tra dosage was reduced and treatment was administered daily. Interestingly, both low dose Tra monotherapy and TP combo therapy significantly extended survival compared to Veh control or Pot alone, and TP treated mice had increased survival compared to the Tra only treated mice. Taken together, our results show that low dose daily Trametinib treatment is superior to cycling dosage, and that Ponatinib treatment synergizes with both dosing schedules to extend survival in vivo. Our study demonstrates the utility of the VQ model for identifying new treatments for hrrMM and testing their efficacy in vivo. As part of our ongoing drug repurposing experiments, we have expanded our screening to a panel of 2,580 FDA-approved drugs, including but not limited to anti-cancer and anti-inflammatory drugs. Figure Disclosures Callander: Cellectar: Research Funding; University of Wisconsin: Current Employment.

BACKGROUND: Angioimmunoblastic T cell lymphoma (AITL) has a unique histological profile comprised of a relatively small number of malignant CD4+ T-cells of TFH phenotype inter-mixed with an extensive infiltrate of multi-lineage immune cells. In our study, we have utilized mass cytometry, high-dimensional analysis, and single-cell transcriptome analysis to provide novel insights into the unique phenotypes that comprise this intra-tumoral microenvironment. We then extended this work to explore clinical associations including peripheral serum analysis of AITL patients and normal controls. To our knowledge, this represents the first such analysis of its kind in AITL. METHODS: We designed two novel CyTOF antibody (Ab) panels to identify and characterize cells of T, B, NK, monocyte and fDC lineages. Samples analyzed included a cohort of 25 biopsy specimens from 8 histologically confirmed AITL patients (5 lymph node (LN), 3 spleen (SP)) and 17 normal controls across key comparator immune tissue types (7 LN, 6 SP, 4 tonsil (TL)). Extensive high-dimensional analysis of CyTOF data was then performed to provide novel insights into key phenotypes and trends of malignant and non-malignant populations in AITL. We then performed CITE-Seq on control and AITL samples to gain further insight into the RNA transcriptome of key T cell populations at the cellular level. Finally, peripheral serum analysis of cytokines, soluble immune receptors, and ligands were then measured by multiplex ELISA from a separate cohort of 22 samples (5 AITL, 17 control) distinct from the individuals analyzed in the original high-dimensional study cohort. RESULTS: While the presence of "reactive" CD8+ populations is a known histologic hallmark of AITL, we describe the gross expansion of novel CD8+ populations with distinctive immunophenotypic features which have not previously been detailed in this malignancy. Using single-cell protein expression data from CyTOF, these expanded CD8+ populations can be broadly categorized as "effector memory" (CCR7-, CD45RO+, CD45RA-) and further characterized phenotypically by markers of progressive exhaustion, checkpoint inhibition, and terminal differentiation (PD1++, TIGIT++, ICOS+, TIM3+). Further analysis of the single-cell transcriptome from these expanded CD8+ populations via CITE-Seq revealed an expression signature consistent with dysfunction and limited cytotoxic activity (including significant down-regulation of granzyme, perforin, and IFN-g) when compared to benign and malignant controls. Interestingly, when compared to CD8+ populations of identical phenotype found in control tissues, these cells also featured marked upregulation of XCL2 and XCL1 in AITL. Additionally, global shifts in infiltrating CD19+ B cell phenotypes were seen in AITL, marked specifically by diminished expression of both CXCR5 and CD73. Finally, soluble PD-1 and other key immune molecules implicated in the expanded tumor microenvironment were found to be significantly increased in the peripheral serum of AITL patients compared to controls (1567.9 pg/mL (1109.3 S.E.) in AITL vs 29.79 (8.84 S.E.) in controls; P<0.0001). CONCLUSIONS: High-dimensional and single-cell transcriptome analysis of the AITL microenvironment yielded several novel insights which have not been previously described in this malignancy. Highlights include the gross expansion of distinct CD8+ populations - the majority of which are of an exhausted, dysfunctional phenotype featuring marked upregulation of XCL2 and XCL1 - and the global loss of CXCR5 and CD73 expression among AITL CD19+ B cell populations. Taken together, this suggests the presence of aberrant non-malignant immune subsets within the AITL microenvironment which may contribute to novel mechanisms of immune escape. Disclosures Cerhan: NanoString: Research Funding; BMS/Celgene: Research Funding. Ansell:Bristol Myers Squibb: Research Funding; ADC Therapeutics: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; AI Therapeutics: Research Funding; Trillium: Research Funding; Takeda: Research Funding.

Abstract BACKGROUND Radiotherapy, combined with surgical resection and chemotherapy, remains a first-line treatment for infiltrative gliomas. However, these tumors are not surgically curable, and often recur, even within the prior radiation field, and may demonstrate a more aggressive phenotype. Importantly, high grade gliomas display diverse molecular phenotypes, and whether this genetic variability leads to divergent behaviour in the radiated tumor microenvironment is unknown. Herein, we characterize the effects of the irradiated brain microenvinroment on nine additional unique GBM cell lines to better understand the nuances of how tumor molecular phenotypes influence cellular dynamics. METHODS Female athymic nude mice were randomly divided into cranial radiation (15 Gy) and non-radiated groups. Mice then underwent intracranial implantation with one of the selected patient-derived xenograft (PDX) GBM cell lines (GBM 6, 10, 12, 39, 46, 76, 123, 164, 196; total n=8-15, per group, per line). Kaplan-Meyer (K-M) and log-rank tests were performed to compare the survival between irradiated and non-irradiated groups. RESULT Of nine previously untested human GBM lines, we found that five demonstrated shorter survival in the pre-radiated brain (GBM 6, 46, 76, 164, 196). However, two lines yielded prolonged survival in the pre-radiated brain (GBM 10, 12); GBM 39, 123 whose rate of growth was not impacted by the radiated brain. CONCLUSION These results highlight the likely critical impact of the irradiated microenvironment on tumor behaviour, yet illustrate that different tumors may exhibit opposing responses. Although further evaluation will be needed to understand mechanisms of divergent behavior, our data suggest the increased rate of growth in the radiated microenvironment may not apply to the fastest-growing tumor lines, which could instead demonstrate a paradoxical response.

Despite recent developments in the therapy of chronic lymphocytic leukemia (CLL), Richter's transformation (RT), an aggressive lymphoma, remains a clinical challenge. Immune checkpoint inhibitor (ICI) therapy has shown promise in selective lymphoma types, however, only 30-40% RT patients respond to anti-PD1 pembrolizumab; while the underlying CLL failed to respond and 10% CLL patients progress rapidly within 2 months of treatment. Studies indicate pre-existing T cells in tumor biopsies are associated with a greater anti-PD1 response, hence we hypothesized that pre-existing T cell subset characteristics and regulation in anti-PD1 responders differed from those who progressed in CLL. We used mass cytometry (CyTOF) to analyze T cell subsets isolated from peripheral blood mononuclear cells (PBMCs) from 19 patients with who received pembrolizumab as a single agent. PBMCs were obtained baseline(pre-therapy) and within 3 months of therapy initiation. Among this cohort, 3 patients had complete or partial response (responders), 2 patients had rapid disease progression (progressors) (Fig. A), and 14 had stable disease (non-responders) within the first 3 months of therapy. CyTOF analysis revealed that Treg subsets in responders as compared with progressors or non-responders (MFI -55 vs.30, p=0.001) at both baseline and post-therapy were increased (Fig. B). This quantitative analysis indicated an existing difference in Tregs and distinct molecular dynamic changes in response to pembrolizumab between responders and progressors. To delineate the T cell characteristics in progressors and responders, we performed single-cell RNA-seq (SC-RNA-seq; 10X Genomics platform) using T (CD3+) cells enriched from PBMCs derived from three patients (1 responder: RS2; 2 progressors: CLL14, CLL17) before and after treatment. A total of ~10000 cells were captured and an average of 1215 genes was detected per cell. Using a clustering approach (Seurat V3.1.5), we identified 7 T cell clusters based on transcriptional signature (Fig.C). Responders had a larger fraction of Tregs (Cluster 5) as compared with progressors (p=0.03, Fig. D), and these Tregs showed an IFN-related gene signature (Fig. E). To determine any changes in the cellular circuitry in Tregs between responders and progressors, we used FOXP3, CD25, and CD127 as markers for Tregs in our SC-RNA-seq data. We saw a greater expression of FOXP3, CD25, CD127, in RS2 in comparison to CLL17 and CLL14. Gene set enrichment analysis (GSEA) revealed the upregulation of genes involved in lymphocyte activation and FOXP3-regulated Treg development-related pathways in the responder's Tregs (Fig.F). Together, the greater expression of genes involved in Treg activation may reduce the suppressive functions of Tregs, which led to the response to anti-PD1 treatment seen in RS2 consistent with Tregs in melanoma. To delineate any state changes in T cells between progressors and responder, we performed trajectory analysis using Monocle (R package tool) and identified enrichment of MYC/TNF/IFNG gene signature in state 1 and an effector T signature in state 3 For RS2 after treatment (p=0.003), indicating pembrolizumab induced proliferative and functional T cell signatures in the responder only. Further, our single-cell results were supported by the T cell receptor (TCR beta) repertoire analysis (Adaptive Biotechnology). As an inverse measure of TCR diversity, productive TCR clonality in CLL14 and CLL17 samples was 0.638 and 0.408 at baseline, respectively. Fifty percent of all peripheral blood T cells were represented by one large TCR clone in CLL14(progressor) suggesting tumor related T-cell clone expansion. In contrast, RS2(responder) contained a profile of diverse T cell clones with a clonality of 0.027 (Fig. H). Pembrolizumab therapy did not change the clonality of the three patients during the treatment course (data not shown). In summary, we identified enriched Treg signatures delineating responders from progressors on pembrolizumab treatment, paradoxical to the current understanding of T cell subsets in solid tumors. However, these data are consistent with the recent observation that the presence of Tregs suggests a better prognosis in Hodgkin lymphoma, Follicular lymphoma, and other hematological malignancies. Figure 1 Disclosures Kay: Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Sunesis: Research Funding; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; MEI Pharma: Research Funding. Ansell:AI Therapeutics: Research Funding; Takeda: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol Myers Squibb: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; ADC Therapeutics: Research Funding. Ding:Astra Zeneca: Research Funding; Abbvie: Research Funding; Octapharma: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees; DTRM: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding. OffLabel Disclosure: pembrolizumab

Background: Follicular Lymphoma (FL) is the second most common non-Hodgkin lymphoma and presents with significant clinical, cellular, molecular, and genetic heterogeneity. Despite the name and defining microanatomic location, the genetic and molecular identity and pathogenesis of the FL tumor cell is largely uncharacterized. Prior clinical and molecular classifications of FL have been primarily driven by pathologic classification (Grade 1-3b), genetic classification (M7-FLIPI), or gene expression profiling (IR-1/2). Using a unique cohort of 93 FL tumors, we have explored the transcriptomic signature of purified FL B cells, along with their matched whole tumor, and identified unique molecular subsets which are defined by distinct pathway activation, immune content, and genomic signatures identified through whole exome sequencing (WES). Methods: Frozen tumor biopsies from 93 untreated FL (Grade 1-3b) patients enrolled in the University of Iowa/Mayo Clinic Lymphoma SPORE were used for the study. DNA was isolated from whole tumor cell suspensions and RNA was isolated from both whole tumor and B cell enriched cell suspensions. RNA sequencing (RNAseq) and WES was performed in the Mayo Clinic Genome Analysis Core. RNAseq and WES data were processed using the Mayo Clinic standard pipeline and novel driver genes were identified using 20/20+ driver analysis. Copy number variants were identified using GISTIC 2.0. NMF clustering and single sample gene set testing, for B cell lineage and tumor microenvironment (TME) signatures, was performed in R using the NMF and SingScore packages. Results: NMF consensus clustering of FL B cell RNAseq data identified two distinct subsets, C1 (n=32) and C2 (n=57). Clinically, C1 was associated with being FL grade 3 (p<0.001) and more aggressive therapy (e.g. immunochemotherapy) at diagnosis while other clinical factors were similar between the groups. To determine the biologic underpinnings that drove the NMF analysis, the top NMF metagenes were incorporated (n=389 for C1 and n=293 for C2) for GO analysis. Among those genes were AICDA, IRF4, and EZH2 in C1, and BCL2 in C2. Additionally, we identified significant gene set enrichment with NMF metagenes and calculated differential gene set expression comparing C1, C2, and normal B cells (n=5). Together, these analyses suggest C1 displays significantly (p<0.05) enhanced DNA replication and metabolic activity, whereas C2 displays significantly enhanced cytoskeleton rearrangement, repressed inflammatory cytokine signaling, and NF-kB activity. Based on recent scRNAseq data suggesting that FL derives from distinct germinal center B cells, the B lineage difference between C1 and C2 was explored. Both subgroups were heterogeneous for dark (DZ), intermediate (INT), light (LZ) zones, and plasmablast (PBL) gene signatures. When compared to benign B cell samples, C1 was enriched for a pre-PBL (p<0.01), and C2 for an INT phenotype related to a LZ signature (p<0.01). To define if a genomic signature was associated with C1 and C2, mutations and copy number variants (>5% frequency) were examined. TNFAIP3, TP53, and BCL6 alterations were enriched in C1 samples, whereas C2 associated with alterations in BCL2, KMT2D, CREBBP, REL, and MYC. Finally, B cell clusters were analyzed for TME signatures. C1 samples displayed significant enrichment of macrophage, cytotoxic cell, gamma-delta-Tcell, and endothelial cell TME elements (p<0.05) consistent with an inflamed/hot tumor. In contrast, C2 samples exhibited significantly lower signatures (p<0.05) in all entities except for the fibroblast signature, compared to C1 and normal, consistent with an immune desert phenotype. Conclusion: Our results suggest that B cells from FL patients display two distinct transcriptomic signatures. C1 identifies an immunologically active tumor, driven by TNFAIP3 alterations, with pre-PBL characteristics, DNA replication and repair, inflammatory cytokine secretion/signaling, and hyper-metabolic characteristics. C2 identifies an immunologically quiet tumor, driven by alterations in BCL2 and chromatin modifiers, with an intermediate GC phenotype, repressed cytokine signaling, and active cell cycle progression and cytoskeleton rearrangement. This study improves our understanding of the mechanisms driving FL tumors and motivates further investigation into the relationship between tumor intrinsic factors that may influence the TME. Disclosures Maurer: Morphosys: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding; Celgene / BMS: Research Funding. Ansell:ADC Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; AI Therapeutics: Research Funding; Takeda: Research Funding; Seattle Genetics: Research Funding; Bristol Myers Squibb: Research Funding. Cerhan:NanoString: Research Funding; BMS/Celgene: Research Funding. Novak:Celgene/BMS: Research Funding.

Background The importance of the immune system in modulating the trajectory of lymphoma outcomes has been increasingly recognized. We recently showed that CD4+ cells are associated with clinical outcomes in a prospective cohort of almost 500 patients with follicular lymphoma (FL). Specifically, we showed that the absence of CD4+ cells inside follicles was independently associated with increased risk of early clinical failure. These data suggest that the composition, as well as the spatial distribution of immune cells within the tumor microenvironment (TME), play an important role in FL. To further define the architecture of the TME in FL we analyzed a FL tumor section using the Co-Detection by Indexing (CODEX) multiplex immunofluorescence system. Methods An 8-micron section from a formalin-fixed paraffin-embedded block containing a lymph node specimen from a patient with FL was stained with a cocktail of 15 CODEX antibodies. Five regions of interest (ROIs) were imaged using a 20X air objective. Images underwent single-cell segmentation using a Unet neural network, trained on manually segmented cells (Fig 1A). Cell type assignment was done after scaling marker expression and clustering using Phenograph. Each ROI was manually masked to indicate areas inside follicles (IF) and outside follicles (OF). Relative and absolute frequencies of cell types were calculated for each region. Cellular contacts were measured as number and types of cell-cell contacts within two cellular diameters. To identify proximity communities, we clustered cells based on number and type of neighboring masks using Phenograph. The number of cell types and cellular communities were calculated inside and outside follicles after adjustment for total IF and OF areas. The significance of cell contact was measured using a random permutation test. Results We identified 13 unique cell subsets (11 immune, 1 endothelial, 1 unclassified) in the TME of our FL section (Fig. 1A). The unique phenotype of each subset was confirmed using a dimensionality reduction tool (t-SNE). The global composition of the TME varied minimally across ROIs and consisted primarily of B cells, T cells, and macrophages subsets - in decreasing order of frequency. Higher spatial heterogeneity across ROIs was observed in the frequency of T cell subsets in comparison to B cells subsets. Inspecting the spatial distribution of T cell subsets (Fig. 1B), we observed that cytotoxic T cells were primarily located in OF areas, whereas CD4+ T cells were found in both IF and OF areas. Notably, the majority of CD4+ T cells inside the follicles expressed CD45RO (memory phenotype), while most of the CD4+ T cells outside the follicles did not. Statistical analysis of the spatial distribution of CD4+ memory T cell subsets confirmed a significant increase in their frequency inside follicles compared to outside (20.4% vs 11.2%, p < 0.001; Fig. 1D). Cell-cell contact analysis (Fig 1C) showed increased homotypic contact for all cell types. We also found a higher frequency of heterotypic contact between Ki-67+CD4+ memory T cells and Ki-67+ B cells. Pairwise analysis showed these findings were statistically significant, indicating these cells are organized in niches rather than randomly distributed across image. Analysis of cellular communities (Fig. 1C) identified 13 niches, named according to the most frequent type of cell-cell contact. All CD4+ memory T cell subsets were found to belong to the same neighborhood (CD4 Memory community). Analysis of the spatial distribution of this community confirmed that these niches were more frequently located inside follicles rather than outside (26.3±4% vs 0.004%, p < 0.001, Fig. 1D). Conclusions Analysis of the TME using CODEX provides insights on the complex composition and unique architecture of this FL case. Cells were organized in a pattern characterized by (1) high degree of homotypic contact and (2) increased heterotypic interaction between activated B cells and activated CD4+ memory T cells. Spatial analysis of both individual cell subsets and cellular neighborhoods demonstrate a statistically significant increase in CD4+ memory T cells inside malignant follicles. This emerging knowledge about the specific immune-architecture of FL adds mechanistic details to our initial observation around the prognostic value of the TME in this disease. These data support future studies using modulation of the TME as a therapeutic target in FL. Figure 1 Disclosures Galkin: BostonGene: Current Employment, Patents & Royalties. Svekolkin:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Postovalova:BostonGene: Current Employment, Current equity holder in private company. Bagaev:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Ovcharov:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Varlamova:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Novak:Celgene/BMS: Research Funding. Witzig:AbbVie: Consultancy; MorphSys: Consultancy; Incyte: Consultancy; Acerta: Research Funding; Karyopharm Therapeutics: Research Funding; Immune Design: Research Funding; Spectrum: Consultancy; Celgene: Consultancy, Research Funding. Nowakowski:Nanostrings: Research Funding; Seattle Genetics: Consultancy; Curis: Consultancy; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other; Kymera: Consultancy; Denovo: Consultancy; Kite: Consultancy; Celgene/BMS: Consultancy, Research Funding; Roche: Consultancy, Research Funding; MorphoSys: Consultancy, Research Funding. Cerhan:BMS/Celgene: Research Funding; NanoString: Research Funding. Ansell:Trillium: Research Funding; Takeda: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Bristol Myers Squibb: Research Funding; AI Therapeutics: Research Funding; ADC Therapeutics: Research Funding.

Abstract Diffuse large B-cell lymphoma (DLBCL) is a molecularly heterogeneous group of malignancies with frequent genetic abnormalities. G-quadruplex (G4) DNA structures may facilitate this genomic instability through association with activation-induced cytidine deaminase (AID), an antibody diversification enzyme implicated in mutation of oncogenes in B-cell lymphomas. Chromatin immunoprecipitation sequencing analyses in this study revealed that AID hotspots in both activated B cells and lymphoma cells in vitro were highly enriched for G4 elements. A representative set of these targeted sequences was validated for characteristic, stable G4 structure formation including previously unknown G4s in lymphoma-associated genes, CBFA2T3, SPIB, BCL6, HLA-DRB5 and MEF2C, along with the established BCL2 and MYC structures. Frequent genome-wide G4 formation was also detected for the first time in DLBCL patient-derived tissues using BG4, a structure-specific G4 antibody. Tumors with greater staining were more likely to have concurrent BCL2 and MYC oncogene amplification and BCL2 mutations. Ninety-seven percent of the BCL2 mutations occurred within G4 sites that overlapped with AID binding. G4 localization at sites of mutation, and within aggressive DLBCL tumors harboring amplified BCL2 and MYC, supports a role for G4 structures in events that lead to a loss of genomic integrity, a critical step in B-cell lymphomagenesis.

AbstractWe previously demonstrated that cancer‐associated fibroblasts (CAFs) promoted the proliferation of gallbladder cancer (GBC) cells, but the mechanism is not clear. Neuropilin‐1 (NRP‐1) plays an important role in various malignancies as transmembrane glycoprotein. Our goal was to reveal the relationship between CAFs and NRP‐1 and their potential functions in GBC. In this study, we found NRP‐1 was overexpressed in GBC tissue, associated with poor survival and was up‐regulated by CAFs. The cytokine array cluster analysis revealed IL‐8 secreted by CAFs facilitated the up‐regulation of NRP‐1 in tumour cells. NRP‐1 knockdown suppressed tumour growth in vivo. Gene expression microarray analysis showed 581 differentially regulated genes under NRP‐1 knockdown conditions. Ingenuity pathway analysis demonstrated that NRP‐1 knockdown may inhibit tumour progression by affecting cell proliferation. We then confirmed that NRP‐1 knockdown in NOZ and GBC‐SD cells significantly inhibited cell proliferation. Additionally, the IL‐8 mediated MDM2 and CCNA2 expression were affected by NRP‐1 knockdown. Our findings suggested that NRP‐1 was up‐regulated by CAF‐secreted IL‐8, which subsequently promoted GBC cell proliferation, and these molecules may serve as useful prognostic biomarkers and therapeutic targets for GBC.

Abstract Background: The soluble form of the low affinity Interleukin 2 receptor alpha subunit (sCD25) is often elevated and correlates with inferior outcome in cancers, including follicular B lymphoma (FL). We recently reported a novel RNA aptamer-based assay designated as the LIRECAP assay (for Ligand-Receptor Complex-binding Aptamers) that allows for specific measurement of the fraction of CD25 occupied by IL2 in a biospecimen. The LIRECAP assay demonstrated that the fraction of sCD25 that circulates as an IL2-sCD25 complex varies considerably in B cell lymphoma patients (from 10% to 96% occupancy of sCD25 by IL2) and that this fractional occupancy was significantly higher in FL compared to diffuse large B cell lymphoma (Cancer Immunol Res. 2019. 7: 1511-1522). The prognostic significance of IL2-occupied and unoccupied sCD25 fractions is not known and the current studies were designed to study their effect on FL outcome. Methods: Determining total, unoccupied and IL2-occupied sCD25 levels: Using the LIRECAP assay, we evaluated the fractional IL2 occupancy of sCD25 in pretherapy serum samples from FL patients who were subsequently treated with standard chemoimmunotherapy. In addition, total sCD25 was determined by a commercially available Luminex assay kit. Levels of total sCD25, unoccupied sCD25, IL2-occupied sCD25 and ratios of unoccupied to IL2-occupied sCD25 were then calculated for each sample. Patients were followed for 24 months following therapy to determine whether they achieved or failed to achieve event-free survival (EFS 24) (N=10 per group). Results: Unoccupied sCD25 levels correlates with poor prognosis: Total sCD25 and IL2-occupied sCD25 levels did not correlate with EFS24 (p=0.085 and 0.404, respectively). However, levels of unoccupied sCD25 and the ratio of unoccupied to IL2-occupied sCD25 were significantly higher in patients who failed to achieve EFS24 (p=0.048 both). Conclusions and significance: Unoccupied sCD25, but not IL2-occupied sCD25, in FL patient serum correlates with poor outcome. This could, in part, be due to the ability of IL2-occupied sCD25, but not unoccupied sCD25, to induce Tregs, as we have reported previously. A higher Treg infiltration has also been shown to correlate with a better FL outcome. Taken together, these data suggest that unoccupied sCD25 can serve as an independent prognostic marker in FL. Further analysis in a larger cohort of patients, and assessment of the biological effects of unoccupied and IL2-occupied sCD25 is ongoing. Citation Format: Suresh Veeramani, Sue E. Blackwell, Paula Banuelos, Zhi-Zhang Yang, Stephen M. Ansell, George J. Weiner. Unoccupied and IL2-occupied soluble CD25 have distinct prognostic effects in follicular lymphoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4333.