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Data on the prognostic impact of pretherapy 18F-fluorodeoxyglucose–positron emission tomography (FDG-PET) in follicular lymphoma (FL) is conflicting. The predictive utility of pretherapy total metabolic tumor volume (TMTV) and maximum standardized uptake value (SUVmax) on outcome appears to vary between regimens. Chemoimmunotherapies vary in the extent of T-cell depletion they induce. The role of intratumoral T cells on pretherapy FDG-PET parameters is undefined. We assessed pretherapy FDG-PET parameters and quantified intratumoral T cells by multiple methodologies. Low intratumoral T cells associated with approximately sixfold higher TMTV, and FL nodes from patients with high TMTV showed increased malignant B-cell infiltration and fewer clonally expanded intratumoral CD8+ and CD4+ T-follicular helper cells than those with low TMTV. However, fluorescently labeled glucose uptake was higher in CD4+ and CD8+ T cells than intratumoral B cells. In patients with FDG-PET performed prior to excisional biopsy, SUVmax within the subsequently excised node associated with T cells but not B cells. In summary, TMTV best reflects the malignant B-cell burden in FL, whereas intratumoral T cells influence SUVmax. This may contribute to the contradictory results between the prognostic role of different FDG-PET parameters, particularly between short- and long-term T-cell–depleting chemoimmunotherapeutic regimens. The impact of glucose uptake in intratumoral T cells should be considered when interpreting pretherapy FDG-PET in FL.

Blockade of the PD-1 axis has modest efficacy in diffuse large B-cell lymphoma (DLBCL), but data regarding LAG3 are sparse. The impact of LAG3 digital gene expression was tested in 309 patients with DLBCL treated with standard chemoimmunotherapy. Cellular distribution of LAG3 protein was determined by immunohistochemistry and flow cytometry. In tumor-infiltrating lymphocytes (TILs), LAG3 expression was highest on CD4+ regulatory T cells (Tregs) and was also highly expressed on CD8+ T cells compared with CD4+ non-Tregs (both P = .008). LAG3high TILs were enriched in PD-1 and TIM-3. LAG3 was also expressed on a proportion of malignant B cells, and these patients had significantly higher LAG3 messenger RNA in their biopsies (P = .03). LAG3high gene expression was associated with inferior survival in discovery/validation cohorts, independent of cell of origin and the international prognostic index. Patients who were PD-L1high were fivefold more likely to be LAG3high (P < .0001). Patients who were LAG3high/PD-L1high had an inferior progression-free survival (P = .011) and overall survival (P = .005) compared with patients who were LAG3low/PD-L1high. Digital spatial protein analysis confirms LAG3 expression on T cells and, surprisingly, tumor-associated macrophages (TAMs) at higher levels than found on CD20+ B cells in the tumor microenvironment. LAG3 is frequently expressed on CD4+ Tregs and CD8+ TILs, typically with other immune checkpoints, and is also present in a proportion of malignant B cells in DLBCL and in areas enriched for TAMs. LAG3high expression is associated with poor outcome independent of conventional prognosticators.

Introduction. Intra-tumoral T-cell infiltration is associated with R-CHOP responsiveness in aggressive B-cell lymphoma (Keane, Lancet Haem 2015). These patients also have a broad (i.e. diverse) intra-tumoral T-cell receptor (TCR) repertoire with a ~20% superior survival compared to those with a narrow (i.e. clonal) repertoire after R-CHOP therapy. Here, the major contributor to the TCR clonal expansion were CD8+ T cells (Keane, CCR 2017). Paradoxically, our recent results in Follicular Lymphoma (FL) (Tobin, JCO in press) found that clonal T-cell expansions were markedly enriched in those patients that experienced progression of disease within 24 months (POD24). Given that FL is a histological subtype associated with a tumor microenvironment distinct from DLBCL including numerous CD4+ T-follicular helper cells (TFH), we now expand upon these findings by comparing TCR repertoires across histological subtypes. We then established whether the TCR repertoire in FL is related to differential TCR clonal expansions between different T-cell subsets and immune checkpoints. Finally, the overlap between tissue and blood TCR repertoires was investigated. Methods. Firstly, unbiased, high-throughput TCRβ sequencing (ImmunoSEQ, Adaptive Biotechnologies) was compared in 164 FFPE tissues (12 healthy nodes, 40 FL, 88 DLBCL, and as a comparator tumor known to be sensitive to checkpoint blockade and to have a high neoantigen burden, 24 melanoma tissues). Next, to determine the contribution of individual T-cell subsets to overall clonality, a further 21 fresh de-aggregated/cryopreserved FL tumor samples were FACS sorted into four T-cell groupings: CD8+ cytotoxic T-lymphocytes (CTLs), CD4+ TFH, CD4+ regulatory T-cells (TREGs) and 'other' (non-TFH/TREG) CD4+ T-cells. Flow cytometry quantified the expression of the checkpoints LAG3, TIM3 and PD1. Then, 5 FL paired tissue/blood samples were tested for shared TCR clones. Results. FL exhibited strikingly reduced TCR repertoire clonality (higher diversity) compared to DLBCL, melanoma and healthy lymph nodes (Fig 1A). Analysis of de-aggregated sorted nodal T-cells revealed a more complex TCR repertoire. The outcome measure was median clonality index (CIx ranging from '0' or minimal, to '1' or maximal clonality). Large T-cell clones in FL (CIx=0.12) predominantly resided within the CTL subset (34% all T-cells). By contrast, there was marked T-cell diversity in TFH (CIx=0.04; 27% all T-cells), TREG (CIx=0.02; 7% all T-cells) and 'other' CD4+ T-cells (CIx=0.02; 32% all T-cells) (Fig 1B). The CTL population had a bimodal expression for PD1 (+51%/-49%), a marker in FL that has been shown to remain functionally active unless co-expressed with LAG3 and/or TIM3 (Yang, Oncotarget 2017). These dual-checkpoint expressing CTLs have reduced capacity to produce cytokines or lytic granules (i.e. they are 'exhausted'). Notably, 54% of the PD1+ CTLs co-expressed either LAG3 or TIM3. Put together, these results are consistent with expanded CTL clones that are frequently functionally exhausted. In contrast, TFH, TREG and 'other' CD4+ T-cells had a low expression of LAG3 and TIM3, although PD1 was frequently found (as expected, particularly in the TFH cells). Finally, in paired tissue/blood samples, there was weak overlap between the circulating and intra-tumoral TCR repertoire in CTLs and TFH T-cells. Conclusion. Although FL has a markedly less clonal TCR repertoire compared to DLBCL, melanoma and even healthy nodes, this result is misleading. Detailed analysis on sorted intra-tumoral T-cell subsets in FL revealed large clonal expansions in CTLs, with approximately half of these classified as functionally exhausted (dual-positive for PD1 and LAG3 and/or TIM3), a state potentially amenable to reversal by dual-checkpoint blockade. The explanation for TCR repertoire diversity lies in CD4+ T-cells (representing approximately two-thirds of T-cells, including the large TFH subset). T-cells in blood did not reflect FL tissue T-cell clones, further highlighting the need for sorted intra-tumoral nodal tissues to accurately assess TCR repertoires in FL. Further characterization of the neo-antigenic targets that CTL clones potentially recognize is required. These results have implications for therapeutic vaccine design and selective recruitment of patients for immune checkpoint blockade. Disclosures Keane: MSD: Consultancy; Gilead: Consultancy; Celgene: Consultancy; Roche: Consultancy, Other: Travel Grant; BMS: Research Funding. Gandhi:Roche: Honoraria, Other: Travel Support; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Honoraria, Research Funding.

LAG3 is an immune checkpoint expressed on a variety of immune cells including a sub-population of 'exhausted' effector T cells and TREGs. Early-phase studies of anti-LAG3 mAb show promise in solid and haematological cancers. We have previously demonstrated LAG3 is enriched within the tumor microenvironment in Hodgkin Lymphoma (Gandhi et al. Blood 2006). Data in the aggressive B-cell lymphoma DLBCL is lacking. We used a conventional discovery/ validation approach in two population based Australian cohorts (discovery: Brisbane/Canberra; validation: Sydney) totalling 250 patients treated with R-CHOP with >4 year follow-up. Digital gene expression (NanoString) using a consistent LAG3 cut-off showed inferior 5-year overall survival (OS) in both cohorts (discovery: 54% vs. 82%, HR 3.13, p=0.003; validation: 63% vs. 86%, HR 2.95, p=0.025 respectively). In a multivariate model, LAG3HI(p=0.001) was a predictor of OS independent of R-IPI and Cell-of-Origin (by NanoString LST assay). PD-L1 expression was also a predictor of survival though to a lesser degree than LAG3. Notably, LAG3 expression stratified PD-L1HIpatients into two sub-groups with differential survival, with dual LAG3 and PD-L1 positivity conferring particularly poor OS (PD-L1HI/LAG3HI39% vs. 81% PD-L1HI/LAG3LO, HR 3.65, p=0.023). Next, the discovery/validation cohorts were combined with 129 additional DLBCL cases from the ALLG biobank (in whom tissue but no outcome data was available), to test for biological associations and correlations. In these 379 cases, LAG3HIwas enriched in the ABC/UC (66%) subtype vs. LAG3LO(p=0.003). LAG3 was positively correlated with numerous immune checkpoints/effectors including CD4, CD8, PD-1, PD-L1, PD-L2, TIM-3 and CD163 (all p LAG3 gene expression was highly correlated with protein expression by tissue microarray based immunohistochemistry (r=0.79, p Finally, levels of soluble LAG3 (sol-LAG3) were quantified within paired plasma of patients enrolled into the ALLG NHL21 PET-adapted prospective DLBCL study. Samples taken pre-therapy and following 4 cycles of R-CHOP (at the time of interim-PET) were compared. Sol-LAG3 levels were higher in patients with DLBCL at diagnosis compared to healthy controls (p In conclusion, high expression of LAG3 in DLBCL is enriched in the non-GCB phenotype, and is associated with poor outcome independent of clinical and biological prognosticators. Dual PD-L1HI/LAG3HIexpression confers particularly poor outcome after conventional front-line immuno-chemotherapy. Intratumoral LAG3 expression is high on PD-1+ CD8+ and TREG subsets. Sol-LAG3 appears to a circulating disease response biomarker. The results combined indicate a key role for LAG3 within the immunobiology of DLBCL and provide a strong rationale for early phase clinical trials utilising anti-LAG3 and anti-PD1 mAb combinations. Disclosures Keane: BMS: Research Funding; Roche: Other: Education Support, Speakers Bureau; Celgene: Consultancy, Research Funding; Takeda: Other: Educational Meeting; Merck: Consultancy. Gould:Novo Nordisk: Other: Educational Travel. Abro:Novartis: Consultancy; Amgen: Other: education support congress attendance; Janssen: Other: education support congress attendance; Bristol-Myers Squibb: Speakers Bureau; Celgene: Other: education support congress attendance. Tobin:Celgene: Research Funding; Amgen: Other: Educational Travel. Birch:Medadvance: Equity Ownership. Talaulikar:Novartis: Honoraria, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Takeda: Research Funding; Roche: Honoraria, Speakers Bureau; Amgen: Consultancy, Honoraria. Bird:Amgen, Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Hertzberg:Amgen: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; MSD: Membership on an entity's Board of Directors or advisory committees. Gandhi:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Merck: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria; Takeda: Honoraria; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding.

In classical Hodgkin lymphoma (CHL) the tumor microenvironment (TME) is enriched in T cells that modulate antitumor immunity. PD1 blockade partially restores anti-tumoral T cell function, to induce impressive responses in a proportion of patients with relapsed/refractory CHL (Chen et al JCO 2017). Further characterisation of T cell immune evasion mechanisms in CHL will permit the rational development of enhanced immunotherapeutic strategies. Lymphocyte-activation gene 3 (LAG3) is a cell surface molecule known to be expressed on a subset of immune effector T cells and intratumoral regulatory T cells (Tregs) in solid-organ tumors, with combination PD1/LAG3 mAb blockade showing early promise (Ascierto et al 2017 JCO abst 9520). In contrast, data in haematological malignancies is limited, although it is known that LAG3+ T cells suppress anti-tumoral immunity in CHL and B-CLL (Gandhi et al Blood 2006; Shapiro et al Haematologica 2017). Interestingly, in B-CLL LAG3 is found on both T cells and malignant B cells. Whether Hodgkin Reed-Sternberg (HRS) cells express LAG3 is unknown. To characterise in detail intratumoral and circulating LAG3 in CHL we used a conventional discovery / validation approach. The local institutional discovery cohort was drawn from Princess Alexandra Hospital in Brisbane (Australia), and validated in samples from the prospective randomised phase III international "RATHL" trial (Johnson et al NEJM 2016). Firstly, LAG3 gene expression (GEP) was digitally quantified by NanoString in FFPE tissues in the discovery cohort and compared to normal control nodes and DLBCL tissues. Normalised LAG3 mRNA counts were 5-10-fold higher in CHL than in controls (P < 0.001) and 3-5-fold higher than in DLBCL (P < 0.001), whereas PD1 and TIM3 mRNA counts did not differ. In CHL samples LAG3 mRNA counts were markedly increased compared to PD-1 axis molecules and TIM3 (P < 0.001) (Figure 1a). Higher levels of LAG3 mRNA counts were correlated with infiltration by T cells (CD4 r = 0.55; P < 0.00001; CD8 r = 0.51, P < 0.0001), and macrophages (CD68 r = 0.45; P = 0.002). Findings were replicated in the RATHL cohort. Next, intratumoral LAG3 cellular distribution was established. Flow cytometry was used to quantify LAG3 in T cell subsets and CD30+CD3- HRS cells in 6 de-aggregated freshly frozen CHL nodes (TILs). LAG3 was evenly distributed between CD8+ T cells, CD127LOCD25HI natural-Tregs (nTregs) and CD127LOCD25LO induced-Tregs (iTregs), but with minimal expression on CD4 non-Tregs, with the latter constituting the majority of intratumoral T cells. LAG3+ T cells typically co-expressed PD1 and/or TIM3. LAG3 was expressed on CD30+CD3+ cells but not on CD30+CD3- cells, consistent with LAG3 expression on activated T cells. Multispectral immunofluorescence (mIF) image analysis confirmed these findings in histological tumor samples (Figure 1b). Also, there was negligible expression of LAG3 on HRS-lines. Finally, the potential role of soluble LAG3 (sLAG3) as a rapid-turnaround circulating biomarker applicable to the routine diagnostic laboratory, was assessed in serum samples using the MSD R-PLEX assay. In the discovery cohort sLAG3 was 3-4-fold increased at pre-therapy compared to controls and 3-6M post-therapy serum (P = 0.001). Results from pre-therapy RATHL serum samples were similar (P < 0.05). Notably in RATHL samples at interim restaging after 2 ABVD cycles sLAG3 had reduced by ~5-fold compared to pre-therapy (P < 0.0001) in patients with PET/CT responsive disease (Figures 1 c + d). Twelve months post therapy sLAG remained significantly lower than pre-therapy (P < 0.05) and was equivalent to control samples. Pre-therapy serum sLAG3 demonstrated a modest correlation with tissue LAG3 mRNA counts (r = 0.45; P = 0.02). In conclusion in CHL, LAG3 mRNA expression was markedly increased relative to control and DLBCL tissues. Within CHL tissues LAG3 mRNA was markedly increased compared to other immune checkpoint molecules. Interrogation of the TME using flow cytometry of TILs and mIF demonstrated LAG3 is evenly distributed between CD8+, nTregs and iTRreg. In tumor samples we did not find evidence of LAG3 expression on HRS cells. To our knowledge this is the first study to demonstrate sLAG3 as a cell free circulating disease response biomarker in CHL. Taken together these findings provide a convincing rationale for further exploration of single and/or combined checkpoint blockade incorporating LAG3 inhibition to treat CHL. Disclosures Abro: Bristol-Myers Squibb: Speakers Bureau; Janssen: Other: education support congress attendance; Celgene: Other: education support congress attendance; Novartis: Consultancy; Amgen: Other: education support congress attendance. Keane:BMS: Research Funding; Roche: Other: Education Support, Speakers Bureau; Celgene: Consultancy, Research Funding; Takeda: Other: Educational Meeting; Merck: Consultancy. Birch:Medadvance: Equity Ownership. Tobin:Amgen: Other: Educational Travel; Celgene: Research Funding. Johnson:Kite: Consultancy; Celgene: Honoraria; Eisai: Research Funding; Incyte: Consultancy; Takeda: Honoraria, Travel, accommodations, expenses; Janssen: Consultancy, Research Funding; Genmab: Consultancy; Novartis: Honoraria; Zenyaku Kogyo: Other: Travel, accommodations, expenses; Bristol-Myers Squibb: Honoraria; Boeringher Ingelheim: Consultancy; Epizyme: Consultancy, Honoraria, Research Funding. Trotman:F. Hoffman-La Roche: Other: Travel to meeting, Unremunerated member of Ad Board, Research Funding; PCYC: Research Funding; Janssen: Other: Unremunerated member of Ad Board, Research Funding; Takeda: Other: Unremunerated member of Ad Board; Celgene: Other: Unremunerated member of Ad Board, Research Funding; Beigene: Research Funding. Bird:Amgen, Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Gill:Janssen: Other: TRAVEL, ACCOMMODATIONS, EXPENSES, Speakers Bureau. Gandhi:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Merck: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria; Takeda: Honoraria; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding.