Citations

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.

Abstract Venomous snakebite is an important cause of preventable death. The World Health Organization (WHO) set a goal to halve snakebite mortality by 2030. We used verbal autopsy and vital registration data to model the proportion of venomous animal deaths due to snakes by location, age, year, and sex, and applied these proportions to venomous animal contact mortality estimates from the Global Burden of Disease 2019 study. In 2019, 63,400 people (95% uncertainty interval 38,900–78,600) died globally from snakebites, which was equal to an age-standardized mortality rate (ASMR) of 0.8 deaths (0.5–1.0) per 100,000 and represents a 36% (2–49) decrease in ASMR since 1990. India had the greatest number of deaths in 2019, equal to an ASMR of 4.0 per 100,000 (2.3-5.0). We forecast mortality will continue to decline, but not sufficiently to meet the WHO’s goals. Improved data collection should be prioritized to help target interventions, improve burden estimation, and monitor progress.

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.

Abstract Objectives Numerous studies on malignant mesothelioma (MM) highlight the prognostic importance of histologic subtype, nuclear grade, and necrosis. This study compares these parameters in paired biopsy and resection specimens of pleural MM. Methods Histologic subtype, percentage of epithelioid morphology, nuclear grade, and the presence or absence of necrosis were compared in 429 paired biopsies and resection specimens of pleural MM from 19 institutions. Results Histologic subtype was concordant in 81% of cases (κ = 0.58). When compared with resection specimens, epithelioid morphology at biopsy had a positive predictive value (PPV) of 78.9% and a negative predictive value (NPV) of 93.5%; sarcomatoid morphology showed high PPV (92.9%) and NPV (99.3%), and biphasic morphology PPV was 89.7% and NPV was 79.7%. Agreement of the percentage of epithelioid morphology was fair (κ = 0.27). Nuclear grade and necrosis were concordant in 75% (κ = 0.59) and 81% (κ = 0.53) of cases, respectively. Nuclear grade showed moderate (κ = 0.53) and substantial (κ = 0.67) agreement from patients with and without neoadjuvant therapy, respectively, and necrosis showed moderate (κ = 0.47 and κ = 0.60) agreement, respectively, in the same subsets of paired specimens. Conclusions Paired biopsy-resection specimens from pleural MM show overall moderate agreement in pathologic parameters. These findings may help guide postbiopsy management and triage of patients with MM.

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.

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