Citations

Abstract The role and immunological constitution of the tumor microenvironment (TME) in splenic marginal zone lymphoma (sMZL) is largely unknown and studies on the phenotype and subset composition of intratumoral T cells are lacking. In the present study, we evaluated 36 sMZL spleen specimens by single cell analysis to gain a better understanding of the TME in sMZL. Using mass cytometry (CyTOF), we observed that the TME in sMZL is distinct from that of control non-malignant reactive spleen (rSP). We found that the number of TFH cells varied greatly in sMZL, ICOS+ TFH cells were more abundant in sMZL than rSP, and TFH cells positively correlated with increased numbers of memory B cells. Treg cell analysis revealed that TIGIT+ Treg cells are enriched in sMZL and correlate with suppression of TH17 and TH22 cells. Intratumoral CD8+ T cells were comprised of subsets of short-lived, exhausted and late-stage differentiated cells, thereby functionally impaired. We observed that T-cell exhaustion was present in sMZL and TIM-3 expression on PD-1low cells identified cells with severe immune dysfunction. Gene expression profiling by CITE-seq analysis validated this finding. Taken together, our data sugget that the TME as a whole, and T-cell population specifically, are heterogenous in sMZL and immune exhaustion is one of the major factors impairing T-cell function.

Abstract Purpose: Regulatory T-cells (Treg) are essential to Tregs homeostasis and modulate the antitumor immune response in patients with lymphoma. However, the biology and prognostic impact of Tregs in splenic marginal zone lymphoma (SMZL) have not been studied. Experimental Design: Biopsy specimens from 24 patients with SMZL and 12 reactive spleens (rSP) from individuals without lymphoma were analyzed by using CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing), CyTOF (mass cytometry) analysis, and flow cytometry to explore the phenotype, transcriptomic profile, and clinical significance of intratumoral Tregs and their subsets. The biological characteristics and cell signaling pathways of intratumoral Treg subsets were confirmed by in vitro functional assays. Results: We found that Tregs are more abundant in SMZL patients' spleens than rSP, and Tregs from patients with SMZL and rSP can be separated into CD161+Treg and CD26+Treg subsets. CD161+Tregs are increased in SMZL but have dysregulated immune function. We found that CD161+Treg and CD26+Tregs have unique gene expression and phenotypic profiles and are differentially correlated with patient outcomes. Specifically, increased CD161+Tregs are significantly associated with a favorable prognosis in patients with SMZL, whereas CD26+Tregs are associated with a poor prognosis. Furthermore, activation of the IL2/STAT5 pathway contributes to the induction of CD26+Tregs and can be reversed by STAT5 inhibition. Conclusions: IL2/STAT5-mediated expansion of CD26+Tregs contributes to a poor clinical outcome in SMZL and may represent a therapeutic opportunity in this disease.

Abstract IgM MGUS and Waldenstrom Macroglobulinemia (WM) represent a disease spectrum with highly dissimilar therapeutic management ranging from observation to chemoimmunotherapy. The current classification relies solely on clinical features and does not explain the heterogeneity that exists within each of these conditions. To shed light on the biology that may account for the clinical differences, we used bone marrow (BM) CD19+/CD138+ sorted cells and matched BM plasma from 32 patients (pts) (7 IgM MGUS, 25 WM) and 5 healthy controls to perform the first comprehensive multiomics approach including whole exome sequencing, RNA seq, proteomics and metabolomics. Applying principal component analysis to gene expression profiling, most of WM pts clustered together, while a small subset of them grouped separately with MGUS pts, suggesting a biologic dichotomy within WM. The healthy controls formed a distinct group from most WM and MGUS. We then applied a non-negative matrix factorization consensus clustering to the gene expression data and identified three robust clusters. Cluster 1 (C1) included only WM pts, cluster 2 (C2) included both WM and MGUS pts, and cluster 3 (C3) included all controls as well as a small number of WM and MGUS pts. When mutations commonly identified in WM were analyzed, there was no difference among the three groups (excluding controls) in mutation burden of MYD88 L265P and CXCR4. Interestingly, aberrant expression of TNFAIP3 seemed a distinct feature of C1 as deletion of 6q (which encodes for TNFAIP3) and TNFAIP3 mutations were each significantly enriched in C1 (47%) compared to C2 (0%) and C3 (20%; p=0.04). Individual clusters associated with specific transcriptional signature and clinical features. While C1 displayed enrichment of cell growth, downregulation of inflammatory pathways (eg IL6 and IL8 signaling) and aggressive behavior, C2 showed increased inflammatory signaling and cell survival with indolent behavior. C3 had an intermediate feature with combined proliferative and inflammatory signatures. In accordance with the transcriptomic data, the hallmark of C1 was upregulation of proliferation-associated proteins (eg AKT, MAPK) and downregulation of inflammatory proteins (eg IL4, IL10) while the opposite was observed in C2. Once more, C3 confirmed intermediate features with combined upregulation of proliferation and inflammatory proteins. The metabolism was rewired towards fatty acid catabolism in C1, glycolysis in C2 and anabolism in C3. Accordingly, C1 showed undetectable concentration of 3-hydroxybutyric acid as opposed to C2 which had increased levels of malic and lactic acids, as end products of fatty acid oxidation and glycolysis respectively. Those metabolites had intermediate levels in C3. In conclusion, we identified three molecular clusters with distinct clinical, proteomic and metabolomic features, suggesting a potential biologic classification that may have therapeutic implications. Citation Format: Patrizia Mondello, Jonas Paludo, Joseph Novak, Kerstin Wenzl, Shahrzad Jalali, Jordan Krull, Esteban Braggio, Surendra Dasari, Michelle Manske, Jithma Abeykoon, Asher Chanan-Khan, Robert Kyle, Morie Gertz, Zhi Zhang Yang, Anne Novak, Stephen Ansell. Molecular clusters and functional drivers of IgM monoclonal gammopathies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3487.

Abstract Previous studies have found that the prevalence of subtypes of T cells may be associated with patient outcomes, but a comprehensive analysis of the immune profile in the TM of FL has not been done. In the present study, we identified groups of FL patients with discretely unique TMEs and determined whether the T-cell phenotypes in the TME differed among groups. Using a cohort of 82 FL patients with biopsy specimens collected before treatment, we defined the type of TME based on the content of major lineages (T, B, monocytes/macrophages and NK cells) determined by CyTOF analysis. Hierarchical clustering of this cohort stratified patients into 4 groups with different TME: group 1 (G1) included patients with a high percentage of monocyte/macrophages/NK cells; patients from G2 and G3 were enriched for intratumoral T and B cells, respectively. Patients with intermediate numbers of T and B cells were included in G4. CITRUS analysis revealed that T-cell clusters with phenotypes expressing KLRG1, CD57, PD-1dim and rich in TEMRA cells were significantly more abundant in G1 when compared to G2, G3 or G4. In contrast, T-cell clusters with phenotypes containing CD127, CD45RA, CCR7 or PD-1high cells were significantly less abundant in G1 when compared to other groups. When compared to G3 or G4, 2 classes of T cell clusters, all from CD4+ T cells, were significantly more (CD127+KLRG1-) or less (CD57+PD-1high) abundant in G2, respectively. Clusters with a phenotype rich in short-lived effector cells (SLEC) (from CD8+) were upregulated in G3 when compared to G4. These results suggest that patient groups with distinct TME exhibited variable T-cell phenotypes. To determine the role of T-cell differentiation in predicting patient outcome in FL, we identified T-cell subsets using tSNE plots based on the expression of T-cell maturation markers. We identified 18 subsets (S1-S18) of T cells (11 from CD4, 6 from CD8 and 1 from CD4-CD8-) in each sample. Four subsets - S4 (CD4+TN), S5 (CD4+TCM), S7 (CD8+TN) and S10 (CD8+MEPCs) - were considered to be naïve cells or cells in the early stages of differentiation. Four additional subsets - S8 (CD57+TFH), S9 (CD4+TEXH), S13 (CD8+SLECs) and S17 (CD4+PD-1+Treg) - were memory cells with expression of surface markers indicting late-stage differentiation. We found that the 4 subsets (S4: p=0.08, S5: p=0.01, S7: p=0.04 and S10: p<0.01) with an early-stage phenotype were associated with a favorable clinical outcome. In contrast, subsets (S8: p=0.02, S9: p=0.04, S13: p=0.07 and S17: p=0.06) with a late-stage differentiation phenotype had an unfavorable survival. Supporting this finding, we observed that increased numbers of CD45RA+ T cells correlated with a favorable survival. These results indicate that the differentiation stage may determine the role of T cells in predicting patient outcome in FL. Citation Format: Zhi-Zhang Yang, Hyo Jin Kim, Hongyan Wu, Xinyi Tang, Jordan Krull, Patrizia Mondello, Jose Villasboas, Anne Novak, Stephen Ansell. T-cell phenotype and differentiation vary in the tumor microenvironment of follicular lymphoma and are associated with patient outcome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2529.

Abstract The tumor microenvironment plays a crucial role in mediating the tumor immune response, thereby affecting patient outcomes in follicular lymphoma (FL). Using CyTOF, we analyzed single cell suspensions created from pre-treatment biopsies in a cohort of 82 FL patients and retrospectively extracted patient clinical parameters. Hierarchical analysis of the tumor microenvironment composition stratified these patients into 4 groups: group 1 represents patients with high percentage of monocyte/macrophages/NK cells; patients from group 2 and 3 are rich of intratumoral T and B cells, respectively. Patients with intermediate number of T and B cells are classed into group 4. Intratumoral T cells from these 4 groups exhibited distinct phenotypical characteristics. Group 1 was enriched with KLRG1 +CD8 + T cells, while group 4 showed increased number of CXCR3 - T EM and CD4 + T N cells. Patients from group 2 and 3 featured with increased number of ICOS + T reg cells and CD57 + T FH cells, respectively. We observed that higher numbers of T cells significantly correlated with early disease stage, lack of B-symptoms, event-free survival at 24 months (EFS24) and a favorable overall and EFS survival in patients with histological grade 1 and 2. However, this association was not seen in patients with histological grade 3a and b, suggesting that T cell-mediated anti-tumor immunity is preserved in low grade patients, but overridden in higher grade patients. CITRUS analysis revealed that a cluster that is CD57 + and PD-1 high was significantly more abundant in patients who had disease progression than patients who had a complete response to therapy, suggesting a role of CD57 + T FH cells in promoting malignant cell growth in FL. Consistent with this finding, we observed that higher number of CD57 + T FH cells correlated with an inferior survival in FL. Using CITE-seq technology, we found that CD57 + T FH cells exhibited a substantially different transcriptome when compared to CD57 - T FH cells. Genes that were differentially upregulated in CD57 + T FH cells when compared to CD57 - T FH cells included genes involved in cell survival, compromised inflammatory response, and metabolism activation including GZMK, CCL4, CST7, DUSP2, LGALS3, CYTOR, CHI3L2, SYNE2, CXCL13, CD27 and FABP5. Taken together, our results indicate different tumor microenvironments among FL patient groups that is associated with variable T-cell phenotype. We found that CD57 + T FH cells play an important role in predicting disease progression and patient prognosis in FL. Figure 1 Figure 1. Disclosures Novak: Celgene/BMS: Research Funding. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding.

Abstract Background: Follicular lymphoma (FL) exhibits significant clinical, cellular, molecular, and genetic heterogeneity. Our understanding of FL biology and molecular classifications of FL, to date, has largely been driven by pathologic classification (Grade 1-3b), genetic classification (m7-FLIPI), or gene expression profiling (IR-1/2; Huet-23), along with limited studies on small cohorts or targeted panels. In order to further understand the biological underpinnings and complexity of FL, large-scale and integrated whole exome sequencing (WES) and RNA sequencing (RNAseq) studies are needed. Using a highly-annotated cohort of 93 FL tumors with matched RNAseq, WES, and CyTOF data, we have explored the transcriptomic signature of purified FL B cells and identified unique molecular subsets that are defined by distinct pathway activation, immune content, and genomic signatures. Methods: Frozen cell suspensions from 93 untreated FL (Grade 1-3b) patients' tumor biopsies, 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. RNAseq and WES were performed in the Mayo Clinic Genome Analysis Core. RNAseq and WES data were processed using a standard pipeline and novel driver genes were identified using Chasm+ driver analysis. Copy number variants were identified from WES data using GISTIC 2.0. NMF clustering and single sample gene set testing for B cell lineage and tumor microenvironment (TME) signatures were performed in R using the NMF and singscore packages. Results: Unsupervised clustering of RNAseq data identified three distinct expression programs which separated patient B cell samples into 3 groups: Group 1 (G1, n=20), Group 2 (G2, n=24), Group 3 (G3, n=43). While no clinical attributes were defined by any single group, G1 consisted of cases that had less aggressive characteristics (63% Stage I-II, 79% FLIPI 0-1). To identify unique transcriptional pathways driving the three expression programs, we scored gene level contributions to NMF expression programs and employed gene set enrichment analysis. This revealed significant pathway association with type-I IFN signaling (G1), DNA repair and stress response (G2), and epigenetic modulation (G3) as differentiating programs between the 3 groups (FDR q<0.001). VIPER master regulator activity inferencing revealed that these pathways were likely being controlled by differential activity in NF-kB, IRFs, STAT1, BCL6, and FOXO1. Each program significantly enriched for, but were not defined by, portions of specific germinal center programs, such as pre-memory (G1), light-zone-to-dark-zone transition (G2), and a pre-light-zone intermediate (G3). We next assessed the connection between B cell programs and the tumor microenvironment (TME) using available paired CyTOF data on 67 cases, which revealed an active TME in G1, with an abundance of CD8 T cell and NK cell populations, a wide variety of immune content in G2 that consisted mostly of Tfh and myeloid cells, and a poorly populated immune compartment in G3 compared to G1 and G2. Finally, somatic driver mutations and copy number alterations from WES were identified and associated with the three clusters. The three groups distinguished themselves by significant enrichment of copy number alterations (TNFAIP3-loss , 1q23-gain, 1q32-gain) in G2, while 10q-loss and mutations in BCL2 and chromatin modifiers (KMT2D and CREBBP) enriched in G3. G1, overall, had lower alteration burden and had weak associations with any specific alterations, suggesting an alternative mechanism for driving the G1 program. Conclusion: In this study, we have identified three unique FL tumor B cell groups, defined by specific transcriptional programs. Pathways such as inflammation, DNA damage response, and chromatin modification contribute most to the differences between B cell samples and group membership. Additionally, each program associated with specific genetic events as well as TME composition, highlighting potential drivers of these B cell states. This study improves the understanding of the mechanisms driving FL tumors and motivates further investigation into transcriptional consequences of genetic events as well as potential tumor intrinsic factors that may influence the TME. Figure 1 Figure 1. Disclosures Maurer: BMS: Research Funding; Genentech: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite Pharma: 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. Rimsza: NanoString Technologies: Other: Fee-for-service contract. Link: MEI: Consultancy; Genentech/Roche: Consultancy, Research Funding; Novartis, Jannsen: Research Funding. Habermann: Tess Therapeutics: Other: Data Monitoring Committee; Seagen: Other: Data Monitoring Committee; Incyte: Other: Scientific Advisory Board; Morphosys: Other: Scientific Advisory Board; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. King: Celgene/BMS: Research Funding. Cerhan: Genentech: Research Funding; Regeneron Genetics Center: Other: Research Collaboration; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding. Novak: Celgene/BMS: Research Funding.

Abstract Objective: To report 2 cases of relapsed or refractory classical Hodgkin lymphoma with bulky lung involvement who failed PD-1 blockade, obtained long-term complete remission after treatment with PD-1 blockade in combination with ICE chemotherapy, and provide an alternative regimen for this kind of patient. Methods: The clinical data of 2 patients suffering refractory or relapsed Hodgkin's lymphoma with bulky lung involvement who were resistant to PD-1 monoclonal antibody were collected, the treatment processes, efficacy and toxic side effects of the patients were summarized. Results: Both HL patients relapsed after multi-line chemotherapies and radiotherapy. One patient relapsed after autologous hematopoietic stem cell transplantation. The main manifestations were cough and dyspnea caused by large lung masses. Both patients received 3 kinds of PD-1 blockade. One progressed after stopping Nivolumab and enrolled the clinical trial of decitabine and Camrelizumab for 6 courses and got stable disease（SD）, then changed to Camrelizumab combined with ICE for 4 cycles and obtain complete metabolic remission（CMR）. The other patient progressed with Nivolumab or Camrelizumab combined with A (B) VD regimen, and 2 courses of BV. She was then treated with Sintilimab combined with ICE for 4 cycles and obtain CMR. Both patients' cough and dyspnea were significantly improved, and lung lesions were significantly reduced after receiving 1 cycle of PD-1 blockade with ICE regimen and the quality of life was greatly improved. After 4 courses of treatment, the PET/CT assessment achieved CMR. The main side effect was a second-degree bone marrow suppression and can be tolerable for the patient. Conclusion: PD-1 blockade combined with ICE regimen chemotherapy has significant curative effect and mild adverse reactions, can be used to treat cases of relapsed or refractory classic HL with bulky lung involvement resistant to PD-1 blockade. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Background CD8+ T-lymphocyte subsets defined by killer lectin-like receptor G1 (KLRG1) and CD127 expression have been reported to have an important role in infection, but their role in the setting of lymphoid malignancies, specifically follicular lymphoma (FL), has not been studied. Methods To characterize the phenotype of KLRG1/CD127-defined CD8+ subsets, surface and intracellular markers were measured by flow cytometry and Cytometry by time of flight (CyTOF), and the transcriptional profile of these cells was determined by CITE-Seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing). The functional capacity of each subset was determined, as was their impact on overall survival (OS) and event-free survival (EFS) of patients with FL. Results We found that intratumoral CD8+ cells in FL are skewed toward effector cell subsets, particularly KLRG+CD127- and KLRG1-CD127- cells over memory cell subsets, such as KLRG1-CD127+ and KLRG1+CD127+ cells. While effector subsets exhibited increased capacity to produce cytokines/granules when compared with memory subsets, their proliferative capacity and viability were found to be substantially inferior. Clinically, a skewed distribution of intratumoral CD8+ T cells favoring effector subtypes was associated with an inferior outcome in patients with FL. Increased numbers of CD127+KLRG1- and CD127+KLRG1+ were significantly associated with a favorable OS and EFS, while CD127-KLRG1- correlated with a poor EFS and OS in patients with FL. Furthermore, we demonstrated that interleukin (IL)-15 promotes CD127-KLRG1+ cell development in the presence of dendritic cells via a phosphoinositide 3-kinase (PI3K)-dependent mechanism, and treatment of CD8+ T cells with a PI3K inhibitor downregulated the transcription factors responsible for CD127-KLRG1+ differentiation. Conclusions Taken together, these results reveal not only a biological and prognostic role for KLRG1/CD127-defined CD8+ subsets in FL but also a potential role for PI3K inhibitors to manipulate the differentiation of CD8+ T cells, thereby promoting a more effective antitumor immune response.

Abstract Richter's transformation (RT) is a clinically challenging and aggressive transformation of CLL (Chronic lymphocytic leukemia) to lymphoma. Immune-checkpoint therapy has improved outcomes in selective lymphoma types. Nearly 40% of RT patients respond to anti-PD1, while the underlying CLL do not show any response, and 10% of CLL patients progress post-anti-PD1 treatment. Previous studies mostly focused on T-cell responses elicited by anti-PD1, however, intrinsic changes in CLL and RT B-cells induced by the treatment remains elusive. We hypothesized that pre-existing active transcriptional circuitry and distinct B-cell subsets in the CLL and RT B-cells may determine the response to anti-PD1 treatment. Peripheral blood mononuclear cells (PBMCs) from 3 patients who received pembrolizumab(anti-PD1) as a single agent. Samples were obtained at baseline and 3 months post-treatment initiation. Among these patients, 2 are progressors while 1 is a responder. We performed single-cell RNAseq (10X Genomics) on B-cells enriched from PBMCs derived from 3 samples (1 Responder: RS2, 2 progressors: CLL14 and CLL17) before and after treatment using chromium single cell 3' gene expression library. A total of ~10000 cells were captured with an average detection of 1000 genes/sample. To delineate the transcriptional changes upon the anti-PD1 treatment, we first integrated the single-cell data from 6 samples (before and after Pembro) and performed unsupervised clustering analysis using UMAP (Uniform Manifold Approximation and projection). We identified 8 different clusters based on highly expressed marker genes. Cluster 2(C2) was increased in the responder as compared to the progressors post-pem treatment. To determine the activated pathways in each cluster, we performed gene-set enrichment analysis (GSEA) using the Enrichr method. This analysis revealed upregulation of distinct pathways related to IFNG/MYC(C1), IFNG(C2), ER stress(C3), B-cell dependent T cell activation related pathway(C4), MYC targets/TNFα(C5,6,7) indicating intra-tumor transcriptional heterogeneity. To decipher the intratumor cell differentiation changes, we performed pseudotime trajectory analysis using Monocle 2 coupled with B cell developmental stage markers. We identified 7 different states, with distinct changes of state in responder sample RS2 (State 4,5, 6, and 7 were increased in RS2 post-treatment) while CLL samples(progressors) did not have distinct changes. Integration with B cell development revealed that aggressive B cells with CD38 expression were highly induced upon anti-PD1 in responder RS2 while regulatory (CD1d) and memory B cells (CD27) remained the same, suggesting PD1 induced intrinsic changes contributing to the disease response. We identified distinct transcriptional states in B cells within responders and progressors which may govern the intra-tumor and inter-tumor heterogeneity to the anti-PD1 response. Citation Format: Prajish Sundaram Iyer, Lu Yang, Yang Zhi Zhang, Hyo Jin Kim, Charla Secreto, Sutapa Sinha, Neil Kay, Stephen Ansell, Wei Ding, Lili Wang. Tumor intrinsic changes determine immune-checkpoint response in Richter's transformation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1612.