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Background: T-cell large granular lymphocytic leukemia (T-LGLL), a rare lymphoproliferative disorder of mature T cells, is characterized by the accumulation of activated effector T cells leading to a clonally restricted T-cell receptor (TCR) repertoire. Chronic antigen stimulation together with activating somatic STAT3 mutations have been proposed to lead to clonal expansion of leukemic cells. However, no holistic research has been done to show how leukemic and non-leukemic cells liaise to sustain abnormal immune reactivity in T-LGLL. Methods: We investigated the transcriptome and TCR repertoire in T-LGLL using: 1) single-cell RNA and TCR (scRNA+TCRαβ) sequencing from CD45+ sorted blood cells (T-LGLL n=11, healthy n=6), 2) TCRβ sequencing from blood mononuclear cells (T-LGLL n=48, healthy n=823), 3) bulk RNA sequencing (T-LGLL n=15, healthy n=5), 4) plasma cytokine profiling (T-LGLL n=9, healthy n=9), and 5) flow cytometry validations (T-LGLL n=6, healthy n=6) (Figure) Results: ScRNA+TCRαβ-seq data revealed that in healthy controls, hyperexpanded CD8+ T-cell clones (at least 10 cells with identical TCRs) preferentially had an effector memory phenotype, whereas in T-LGLL, the hyperexpanded clonotypes represented a more cytotoxic (increased expression of GZMB, PRF1, KLRB1) and exhausted (LAG3 and TIGIT) phenotype. Using flow cytometry, we confirmed that upon anti-CD3/CD28/CD49 antibody stimulation, T-LGLL clones (CD8+CD57+) expressed higher levels of cytotoxic proteins (GZMA /GZMB , PRF1) but were deficient in degranulation responses and cytokine secretion as measured by expression of CD107a/b and TNFα/IFNγ, respectively. Focused re-clustering of the extracted T-LGLL clones from the scRNA+TCRαβ-seq data revealed considerable heterogeneity among the T-LGLL clones and partly separated the mutated (mt) STAT3 and wild type (wt) STAT3 clones. STAT3wt clones upregulated T-cell activation and TCR signaling pathways, with a higher cytotoxicity and lower exhaustion score as compared to STAT3mt clones. This was validated with bulk RNA-seq data. To understand the antigen specificities of the T-LGLL clones, we combined previously profiled T-LGLL TCRs with our data to form the largest described dataset of 200 T-LGLL clones from 170 patients. Notably, T-LGLL clones were found to be private to each patient. Furthermore, the analysis by GLIPH2 algorithm grouping TCRs did not reveal detectable structural similarities, suggesting the absence of a unifying antigen in T-LGLL. However, in 67% of T-LGLL patients, the TCRs of leukemic clones shared amino acid level similarities with the rest of the non-leukemic TCR repertoire suggesting that the clonal and non-clonal immune repertoires are connected via common target antigens. To analyze the non-clonal immune repertoire in T-LGLL in detail, we compared our data to other published scRNAseq data from solid tumors (n=4) and hematologic cancers (n=8) and healthy controls (n=6). The analysis revealed that in T-LGLL also the non-leukemic CD8+ and CD4+ T cells were more mature, cytotoxic, and clonally restricted. When compared to healthy controls and other cancer patients, in non-leukemic T-LGLL the most upregulated pathway was IFNγ response. Finally, most of the upregulated cytokines in T-LGLL (e.g., CCL2/3/7, CXCL10/11, IL15RA) were secreted predominantly by monocytes and dendritic cells, which also had upregulated HLA class II expression and enhanced scavenging potential in T-LGLL patients. Ligand-receptor analysis with CellPhoneDB revealed that the number of predicted cell-cell interactions was significantly higher in T-LGLL as compared to reactive T-cell clones in healthy controls. The most co-stimulatory interactions (e.g., CD2-CD58, TNFSF14-TNFRSF14) occurred between the IFNγ secreting T-LGLL clones and the pro-inflammatory cytokine secreting monocytes. Conclusions: Our study shows a synergistic interplay between the leukemic and non-leukemic immune cell repertoires in T-LGLL, where an aberrant antigen-driven immune response including hyperexpanded CD8+ T-LGLL cells, non-leukemic CD8+ cells, CD4+ cells, and monocytes contribute to the persistence of the T-LGLL clones. Our results provide a rationale to prioritize therapies that target the entire immune repertoire and not only the T-LGLL clones in patients with T-LGLL. Figure 1 Figure 1. Disclosures Loughran: Kymera Therapeutics: Membership on an entity's Board of Directors or advisory committees; Bioniz Therapeutics: Membership on an entity's Board of Directors or advisory committees; Keystone Nano: Membership on an entity's Board of Directors or advisory committees; Dren Bio: Membership on an entity's Board of Directors or advisory committees. Maciejewski: Alexion: Consultancy; Novartis: Consultancy; Regeneron: Consultancy; Bristol Myers Squibb/Celgene: Consultancy. Mustjoki: Novartis: Research Funding; BMS: Research Funding; Janpix: Research Funding; Pfizer: Research Funding.

Background The success of allogeneic stem cell transplantation supports the notion that immunotherapy can have curative potential in AML, but immune checkpoint therapies (e.g., anti-PD1) have shown only modest clinical efficacy. TIM3 is an immune-checkpoint molecule expressed both on immune and leukemic cells but not on healthy hematopoietic stem cells (HSCs), making it a particularly interesting target in AML. In myeloid malignancies, the combination of anti-TIM3 therapy with hypomethylating agents (HMA), which may prime the tumor microenvironment for immune therapies, has shown promising initial response rates up to 50%-60% of patients, but their mechanism of action is not fully understood. Methods We analyzed the effects of anti-TIM3 (sabatolimab, MBG453) in combination with decitabine in 11 refractory/relapsed AML patients and 1 MDS patient recruited in a phase Ib trial (NCT03066648), with 5/12 responders (3 CR, 2 CRi). We studied paired bone-marrow (BM) and peripheral blood samples with scRNA+TCRαβ-seq enriched for CD45+ immune cells (90% of input) and blast cells (10%) and flow cytometry. Additionally, to explore the expression of TIM3 and other immune checkpoints in different cell populations, we combined scRNAseq data from 160 BM aspirate samples across 10 different hematological malignancies and healthy controls. Results Our pan-heme scRNA-seq data analysis of over 500'000 cells revealed that unlike PD1 and CTLA4, HAVCR2 (TIM3) was primarily expressed in NK and myeloid cells (including dendritic cells [DCs], macrophages, and monocytes). In healthy controls, the expression of HAVCR2 was low in T-cells, but in patients with heme-malignancies, expression was seen on activated T-cells. In HSC populations, AML patients had generally upregulated HAVCR2 expression compared with healthy subjects. ScRNAseq data of 20 samples (n=7 patients) treated with anti-TIM3+HMA revealed that at baseline, DCs were more highly represented in samples from the responding (n=4) than from the non-responding patients (n=3). Following anti-TIM3+HMA treatment, DCs expanded significantly, and upregulated pathways related to interleukin production (IL-1b, IL-18) in responders, suggestive of an activated inflammasome response. At baseline, the most expanded NK-phenotype expressed the highest amounts of HAVCR2, which varied between patients from CD56 bright to adaptive NK cells. Anti-TIM3+HMA therapy modulated NK cells especially in responders, in which NK cells downregulated HAVCR2 and upregulated the NF-κB pathway. Importantly, the NF-κB pathway was upregulated in other cell types in responding patients, but not in non-responding patients. In contrast, the IFN-γ response was downregulated in both responding and non-responding patients in multiple different cell types. The highest expression of HAVCR2 in T cells was seen in cells co-expressing NK-receptors and with the highest cytotoxicity. Analysis of the scTCRαβ-seq revealed that the combination treatment did not have a marked effect on T-cell clonality, but one patient with CR had a significantly expanded large granular lymphocyte (LGL) clone covering 4%-25% of the repertoire. In responding patients, HAVCR2+ regulatory T-cells were more numerous at baseline, contracted following therapy, and lost response to IFN-γ, a pattern not seen in non-responding patients. The analysis of predicted cell-cell interactions between leukemic and immune cells did not show significant interactions between inhibitory PD1 or CTLA4, and their ligands, but ubiquitous LGALS9 - HAVCR2 interactions were predicted in leukemic bone marrows. Responding patients had more these interactions, which decreased following therapy. Non-responding patients had multiple interactions between T/NK cells and blasts via PVR and its ligands which were not seen in responding patients, which represent a putative resistance mechanism for anti-TIM3+HMA therapy. Conclusions Unlike PD1 and CTLA4, TIM3 is expressed on leukemic, DC, myeloid, and NK cells, and consistent with this finding, the effects of TIM3 blockade in vivo were mainly observed in these cell types. In responding patients, NFκB pathway was activated in T/NK cells following anti-TIM3 and HMA treatment concomitant with a decrease in inhibitory interactions. Our results pinpoint the differential effects of TIM3-blockade on immune cells and may aid in developing predictive biomarkers for treatment outcome. Figure 1 Figure 1. Disclosures Kreutzman: Novartis: Current Employment. Kontro: Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding. Orlando: Novartis: Current Employment. Cremasco: Novartis: Current Employment. Wagner: Novartis: Current Employment, Current holder of individual stocks in a privately-held company. Pelletier: Novartis: Current Employment. Sabatos-Peyton: Novartis: Current Employment. Rinne: Novartis: Current Employment; Qiagen: Consultancy. Mustjoki: Janpix: Research Funding; Novartis: Research Funding; Pfizer: Research Funding; BMS: Research Funding.

Only half of chronic myeloid leukemia (CML) patients in deep molecular remission are able to maintain treatment free remission (TFR) after tyrosine kinase inhibitor (TKI) discontinuation. Identifying predictive markers for TFR remains a key issue. The immunological control or eradication of TKI insensitive leukemic stem cells may contribute to successful cessation, as recent work has demonstrated that differences in immune cell compositions can be associated with better probability of TFR. In order to understand the precise immunological changes in CML, we profiled over 170,000 cells from 25 CML samples from different clinical phases (untreated, during TKI therapy and after TKI cessation) using single-cell RNA and T cell receptor (TCR) αβ sequencing (scRNA+TCRab-seq). We profiled both CD45+ sorted peripheral blood samples (n=20) and CD34+ sorted bone marrow samples (n=5). To understand antigen-specific responses, we profiled TCRs specific to tumor-antigen PR1 (n=12) and compared these to unsorted TCRβ-sequenced samples from CML (n=137) and healthy donors (n=786). To understand the distinctive immunological features in CML, we compared the immune system in CML (n=20) to those in other hematological and solid malignancies profiled with scRNA+TCRab-seq (n=9). We discovered NK cells to be the most unique feature in CML, as NK CD56dim cells were more abundant in CML patients (Padj We sought to understand whether the immunological activity differs before and after TKI discontinuation in different clinical outcomes following discontinuation. Therefore, we reclustered the discontinuation samples from three different outcomes: TFR, early relapse (6 months). In all clinical outcomes, TKI cessation invigorated NK cell exhaustion and the most upregulated pathways included IFNg and TNFa via NFkB pathways. Patients with successful TFR had less differences in their immune system after cessation in comparison to relapsing patients, which could hint that their immune subsets were better prepared for the cessation. Unlike the early relapse patients' quiescent immune cells, the late relapse patients' immune subsets were active, but under pronounced inhibitory Treg signals, providing a clinically interesting approach to alter the outcome of these patients. Next, to understand how malignant CML cells evade or interact with the immune system, we analyzed CD34+ cells and calculated a BCR-ABL1 activity score. The most primitive CD34+ cells had lower BCR-ABL1 score and not as many immunological ligand-receptor pairs as their less primitive, highly BCR-ABL1 pathway expressing, counterparts (P Finally, we found that tumor-antigen PR1 is preferentially expressed on CD34+ cells with high BCR-ABL1 score. Most TCRs recognizing PR1 are restricted to individuals, but they share short amino-acid motifs that are shared across patients. Thus, we were able to generate an in silico tool to recognize PR1-specific TCRs from unsorted TCR-seq samples with high accuracy (AUC 0.91 from 10-fold cross validation). With our tool, we were able to show that anti-PR1 responses were more frequent in CML than in healthy donors (P In conclusion, our results provide high-resolution insights into anti-leukemic immune responses in CML and how we could harness and monitor them to enable successful TKI cessations. Figure Disclosures Olsson-Strömberg: Pfizer: Research Funding. Hjorth-Hansen:Pfizer: Honoraria, Research Funding; Austrian Orphan Pharma: Honoraria, Research Funding; Bristol-Myers Squibb: Research Funding. Mustjoki:Pfizer: Research Funding; Novartis: Research Funding; BMS: Honoraria, Research Funding.

Changes in the immune system induced by tyrosine kinase inhibitors (TKI) have been shown to positively correlate with therapy responses in chronic myeloid leukemia (CML). However, only a few longitudinal studies exist and no randomized comparisons between two TKIs have been reported. Therefore, we prospectively analyzed the immune system of newly diagnosed CML patients treated with imatinib (n = 20) or bosutinib (n = 13), that participated in the randomized BFORE trial (NCT02130557). Comprehensive immunophenotyping, plasma protein profiling, and functional assays to determine activation levels of T and NK cells were performed at diagnosis, 3, and 12 months after therapy start. All results were correlated with clinical parameters such as Sokal risk and BCR-ABL load measured according to IS%. At diagnosis, low Sokal risk CML patients had a higher frequency of cytotoxic cells (CD8 + T and NK cells), increased cytotoxic potential of NK cells and lower frequency of naïve and central memory CD4 + T cells. Further, soluble plasma protein profile divided patients into two distinct clusters with different disease burden at diagnosis. During treatment, BCR-ABL IS% correlated with immunological parameters such as plasma proteins, together with different memory subsets of CD4+ and CD8 + T cells. Interestingly, the proportion and cytotoxic potential of NK cells together with several soluble proteins increased during imatinib treatment. In contrast, no major immunological changes were observed during bosutinib treatment. In conclusion, imatinib and bosutinib were shown to have differential effects on the immune system in this randomized clinical trial. Increased number and function of NK cells were especially observed during imatinib therapy. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.

Recent studies suggest that a proportion of chronic myeloid leukemia (CML) patients in deep molecular remission can discontinue the tyrosine kinase inhibitor (TKI) treatment without disease relapse. In this multi-center, prospective clinical trial (EURO-SKI, NCT01596114) we analyzed the function and phenotype of T and NK cells and their relation to successful TKI cessation. Lymphocyte subclasses were measured from 100 imatinib-treated patients at baseline and 1 month after the discontinuation, and functional characterization of NK and T cells was done from 45 patients. The proportion of NK cells was associated with the molecular relapse-free survival as patients with higher than median NK-cell percentage at the time of drug discontinuation had better probability to stay in remission. Similar association was not found with T or B cells or their subsets. In non-relapsing patients the NK-cell phenotype was mature, whereas patients with more naive CD56(bright) NK cells had decreased relapse-free survival. In addition, the TNF-alpha/IFN-gamma cytokine secretion by NK cells correlated with the successful drug discontinuation. Our results highlight the role of NK cells in sustaining remission and strengthen the status of CML as an immunogenic tumor warranting novel clinical trials with immunomodulating agents. Funding Agencies|Nordic Cancer Union; Finnish Society of Hematology; Biomedicum Helsinki Foundation; Research Foundation of Blood Diseases in Finland; Academy of Finland; Finnish Cancer Organizations; Signe and Ane Gyllenberg Foundation; Finnish Cancer Institute; Doctoral Programme in Clinical Research in the University of Helsinki

The potential of immune checkpoint inhibition in many hematological malignancies such as chronic myeloid leukemia (CML) has not been characterized in detail. CML is a hematopoietic stem cell disease driven by the BCR-ABL fusion gene. Tyrosine kinase inhibitor (TKI) therapy is able to induce remissions in the majority of patients. Despite treatment responses, leukemic stem cells persist in the bone marrow (BM). Enhancing antitumor immune responses has been suggested as a potential strategy of enabling treatment discontinuation and disease control in CML. We hypothesized that the bone marrow may represent a distinct immunological milieu in CML patients. Furthermore, TKI therapy has been shown to induce immunological changes. Therefore, we evaluated the expression of immune checkpoint molecules in paired samples from BM and peripheral blood (PB) in chronic phase CML patients at diagnosis and during treatment with TKIs. In addition, we monitored changes in the BM T cell receptor (TCR) repertoire induced by TKI therapy and disease resolution. We performed multicolor flow cytometry on frozen PB and BM samples from chronic phase CML patients at diagnosis and during treatment with the tyrosine kinase inhibitors imatinib, dasatinib and nilotinib as well as healthy controls. We analyzed the expression of PD-1, CTLA-4, LAG-3, ICOS and TIM-3 on T cells and PD-L1, PD-L2, CD80 and CD86 on antigen-presenting cells and CD34+ leukemic progenitor cells. TCR repertoire was assayed by deep sequencing of the CDR3 region using the immunoSEQ assay. At diagnosis, CD8+ T cells in the bone marrow exhibited a more exhausted phenotype compared to peripheral blood as measured by PD-1 positivity (26.1 vs. 12.7%, p = 0.001). This difference was recapitulated in all T cell subsets, including effector memory (TEM), terminally differentiated (TEMRA), central memory (TCM) and naïve, with the highest PD-1 positivity in TEM and TEMRA cells. In addition, dendritic cells as well as leukemic CD34+ progenitor cells expressed higher levels of PD-L1 and CD86 in BM compared to PB at diagnosis. Interestingly, TKI therapy led to a reduction of PD-1-positive CD8+ T cells in the BM after 1 and 6 months of treatment. This was accompanied by a concomitant decrease in PD-L1 and CD86 positivity on dendritic cells. Finally, treatment with dasatinib led to a reduction in TCR repertoire diversity and increased clonality at 6 months, whereas imatinib or nilotinib did not alter the repertoire diversity. In conclusion, BM and PB seem to exhibit different immunological milieus in terms of expression of immune checkpoint molecules in CML. During TKI therapy both PD-1 and PD-L1 levels decrease, suggesting at least partial reversal of immune cell exhaustion. Treatment with the TKI dasatinib is able to drive the TCR repertoire towards a more clonal composition, which has been associated with good responses to checkpoint blockade. Thus, targeted therapies such as TKIs are able to modulate immune checkpoints and T cell activity in unexpected ways, providing a potential strategy for enhancing immunotherapies in combination treatment regimens. Citation Format: Olli Dufva, Tiina Kasanen, Mohamed El Missiry, Judith Klievink, Hanna Lähteenmäki, Satu Mustjoki. Tyrosine kinase inhibitor therapy modulates immune checkpoints and TCR repertoire diversity in chronic myeloid leukemia [abstract]. In: Proceedings of the Second CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; 2016 Sept 25-28; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(11 Suppl):Abstract nr A115.

Background: Tyrosine kinase inhibitors (TKIs) have significantly improved the treatment of CML. Even though TKI treatment is generally not considered curative, recent studies have shown that nearly half of CML patients who have achieve good and durable responses are able to stop the TKI treatment. However, patients who have successfully discontinued TKI treatment still have residual disease. We hypothesized that the immune system plays a role in treatment free remission (TFR), and our preliminary results in the EURO-SKI trial showed that patients who relapse early after imatinib discontinuation have decreased numbers and frequencies of NK cells. In EURO-SKI trial relapse was defined as the loss of major molecular response (MMR). We now aimed to analyze in more detail the phenotype and function of the NK cells in order to understand their role in TFR. Methods: Lymphocyte subclass analysis (the number of NK-, T- and B-cells) was performed at the time of therapy discontinuation and 1 month after the imatinib discontinuation in patients participating in the EURO-SKI stopping trial in the Nordic countries (n=105, results are presented from patients who have reached 6 months follow-up). More detailed immune phenotype and functional assays (NK-cell degranulation and secretion of Th1 type of cytokines IFN-γ/TNF-α) were analyzed from a proportion of patients (n=31). Results: Imatinib treated patients remaining in remission for 6 months (non-relapsing, n=48, median age 60,5 years) displayed an increased amount of NK cells at the time of drug discontinuation (18.6% vs. 11.0%, p=0.02, NK-cell count 0.25 x109 cells/L vs. 0.184 x109 cells/L m, p=0.059) compared to patients who relapsed early (before 5 months, n=29, median age 60,5 years). Furthermore, the NK cell frequency in non-relapsing patients was even higher than in healthy controls (11.5%, n=48, p=0.001). T and B cell counts and frequencies showed no differences between the groups. Detailed analysis of the NK cell compartment displayed a more mature phenotype for the NK cells in non-relapsing patients. Larger frequencies of NK cells from early relapsing patients was CD56bright compared to non-relapsing patients (4.8% vs. 2.7% of CD56 NK cells, p=0.04). Furthermore, patients who had higher frequencies of CD56bright NK cells than median had decreased TFR at 6 months (42%) compared to patients with lower frequency (70%, p=0.01). In addition, there was a trend towards more CD57pos (78% (n=21) vs. 66% (n=10), p=0.09) CD56dim NK cells in non-relapsing patients. To further study the mature NK cells in non-relapsing patients, recently identified markers (FceRgneg, PLZFneg, SYKneg, EAT-2neg) for adaptive NK cells were analyzed. Interestingly, there was a trend that non-relapsing patients had higher frequencies of adaptive-like NK cells. For example, non-relapsing patients had more CD56dim NK cells that had down regulated EAT-2 (2.8% (n=6) vs. 1.3% (n=5) of lymphocytes, p=0.03) and more CD56dim NK cells expressing NKG2D (11.2% vs. 2.6% of lymphocytes, p=0.02) and NKp46 (13.6% vs. 3.9% of lymphocytes, p=0.05). Moreover, after imatinib discontinuation the expression of transcription factor Eomes increased in the CD56dim NK cells of the early relapsing group (baseline MFI 2045 vs. 1 month 3480, p=0.06), while in non-relapsing group it seemed to even decrease (baseline MFI 2273 vs. 1 month 1980, p=0.13) pointing towards an adaptive phenotype. No significant differences between the groups were observed when degranulation against K562 cell line was studied. However, CD16neg NK cells from non-relapsing patients responded to K562 stimulation by secreting more TNFα/IFNγ compared to the early relapsing patients (21% vs. 13% of CD56pos CD16neg NK cells, p=0.01). Furthermore, patients whose CD16neg NK cells had higher than median TNFα/IFNγ secretion when stimulated with K562 cells showed an increased TFR at 6 months (78%) compared to patients who had lower TNFα/IFNγ secretion than median (37%, p=0.005). Conclusions: CML patients who successfully discontinued imatinib therapy displayed a higher number and frequency of peripheral blood mature, adaptive-like NK cells capable of secreting cytokines TNFα/IFNγ relative to relapsing patients. How such NK cells may contribute to maintenance of treatment free remission is still unknown. Nonetheless, our results warrant further clinical studies with NK-cell modulating agents. Disclosures Muller: Novartis: Honoraria, Other: Consulting or Advisory Role, Research Funding; ARIAD Pharmaceuticals Inc.: Honoraria, Other: Consulting & Advisory Role, Research Funding; BMS: Honoraria, Other: Consulting or Advisory Role, Research Funding. Hjorth-Hansen:Novartis: Honoraria; Ariad: Honoraria; Bristol-Myers Squibb: Research Funding; Pfizer: Honoraria, Research Funding. Saussele:Pfizer: Honoraria, Other: Travel grant; BMS: Honoraria, Other: Travel grant, Research Funding; Novartis Pharma: Honoraria, Other: Travel grant, Research Funding; ARIAD: Honoraria. Mahon:ARIAD: Consultancy; Novartis: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Pfizer: Consultancy. Porkka:Bristol-Myers Squibb: Honoraria; Celgene: Honoraria; Novartis: Honoraria; Pfizer: Honoraria. Richter:Ariad: Honoraria; Bristol-Myers Squibb: Honoraria; Novartis: Honoraria. Mustjoki:the Finnish Cancer Societies: Research Funding; Pfizer: Honoraria, Research Funding; Academy of Finland: Research Funding; Sigrid Juselius Foundation: Research Funding; Finnish Cancer Institute: Research Funding; Signe and Ane Gyllenberg Foundation: Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria, Research Funding.