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Somatic structural variants (SVs) are widespread in cancer, but their impact on disease evolution is understudied due to a lack of methods to directly characterize their functional consequences. We present a computational method, scNOVA, which uses Strand-seq to perform haplotype-aware integration of SV discovery and molecular phenotyping in single cells by using nucleosome occupancy to infer gene expression as a readout. Application to leukemias and cell lines identifies local effects of copy-balanced rearrangements on gene deregulation, and consequences of SVs on aberrant signaling pathways in subclones. We discovered distinct SV subclones with dysregulated Wnt signaling in a chronic lymphocytic leukemia patient. We further uncovered the consequences of subclonal chromothripsis in T cell acute lymphoblastic leukemia, which revealed c-Myb activation, enrichment of a primitive cell state and informed successful targeting of the subclone in cell culture, using a Notch inhibitor. By directly linking SVs to their functional effects, scNOVA enables systematic single-cell multiomic studies of structural variation in heterogeneous cell populations.

Leukemia : normal and malignant hemopoiesis 35(11), 3152-3162 (2021). doi:10.1038/s41375-021-01198-1, Published by Springer Nature, London

Leukemia : normal and malignant hemopoiesis 35(8), 2311-2324 (2021). doi:10.1038/s41375-021-01136-1, Published by Springer Nature, London

The tumour microenvironment and genetic alterations collectively influence drug efficacy in cancer, but current evidence is limited to small scale studies and systematic analyses are lacking. We chose Chronic Lymphocytic Leukaemia (CLL), the most common leukaemia in adults, as a model disease to study this complex interplay systematically. We performed a combinatorial assay using 12 drugs individually co-applied with each of 17 microenvironmental stimuli in 192 primary CLL samples, generating a comprehensive map of drug-microenvironment interactions in CLL. This data was combined with whole-exome sequencing, DNA-methylation, RNA-sequencing and copy number variant annotation. Our assay identified four distinct CLL subgroups that differed in their responses to the panel of microenvironmental stimuli. These subgroups were characterized by distinct clinical outcomes independently of known prognostic markers. We investigated the effect of CLL- specific recurrent genetic alterations on microenvironmental responses and identified trisomy 12 as an amplifier of multiple microenvironmental stimuli. We further quantified the impact of microenvironmental stimuli on drug response, confirmed known interactions such as Interleukin (IL) 4 mediated resistance to B cell receptor (BCR) inhibitors, and identified new interactions such as Interferon-γ induced resistance to BCR inhibitors. Finally, we identified interactions which were limited to genetic subgroups. Resistance to chemotherapeutics, such as Fludarabine, induced by Toll-Like Receptor (TLR) agonists could be observed in IGHV unmutated patient samples and IGHV mutated samples with trisomy 12. In-vivo relevance was investigated in CLL-infiltrated lymph nodes, which showed increased IL4 and TLR signalling activity compared to healthy samples (pWe provide a publicly available resource (www.dietrichlab.de/CLL_Microenvironment/) which uncovers tumour cell extrinsic influences on drug response and disease progression in CLL, and how these interactions are modulated by cell intrinsic molecular features.

Bispecific antibodies (BsAbs) can induce long-term responses in patients with refractory and relapsed B-cell lymphoma. Nevertheless, response rates across patients are heterogeneous, and the factors determining quality and duration of responses are poorly understood. To identify key determinants of response to BsAbs, we established a primary, autologous culture model allowing us to mimic treatment with CD3xCD19 and CD3xCD20 BsAbs within the lymph node microenvironment ex vivo. T cell–mediated killing of lymphoma cells and proliferation of T cells varied significantly among patients but highly correlated between BsAbs targeting CD20 or CD19. Ex vivo response to BsAbs was significantly associated with expansion of T cells and secretion of effector molecules (eg, granzyme B, perforin) but not with expression of T-cell exhaustion (eg, PD1, TIM3) or activation markers (eg, CD25, CD69) or formation of intercellular contacts. In addition, we identified a distinct phenotype of regulatory T cells that was linked to ex vivo response independently from T-cell frequency at baseline. High expression levels of Aiolos (IKZF1), ICOS, and CXCR5 were positively associated with ex vivo response, whereas strong expression of Helios (IKZF2) had an unfavorable impact on ex vivo response to BsAbs. We further showed that lenalidomide, nivolumab, and atezolizumab improved ex vivo response to BsAbs by potentiating T-cell effector functions. In summary, our ex vivo study identified a distinct regulatory T-cell phenotype as a potential contributor to treatment failure of BsAbs and suggests drug combinations of high clinical relevance that could improve the efficacy of BsAbs.

The sterile alpha motif and histidine-aspartic domain-containing protein 1 (SAMHD1) has been demonstrated to predict the response to high-dose cytarabine consolidation treatment in acute myeloid leukemia patients. Here, we evaluated SAMHD1 as potential biomarker for the response to high-dose cytarabine in mantle cell lymphoma (MCL) patients. We quantified SAMHD1 protein expression and determined the mutation status in patients of the MCL Younger and Elderly trials (n = 189), who had received high-dose cytarabine- or fludarabine-based polychemotherapy. Additionally, we quantified SAMHD1 expression in B cell lymphoma cell lines and exposed them to cytarabine, fludarabine, and clinically relevant combinations. Across both trials investigated, SAMHD1 mutations had a frequency of 7.1% (n = 13) and did not significantly affect the failure-free survival (FFS, P = .47). In patients treated with high-dose cytarabine- or fludarabine-containing regimes, SAMHD1 expression was not significantly associated with FFS or complete remission rate. SAMHD1 expression in B cell lymphoma cell lines, however, inversely correlated with their in vitro response to cytarabine as single agent (R = .65, P = .0065). This correlation could be reversed by combining cytarabine with other chemotherapeutics, such as oxaliplatin and vincristine, similar to the treatment regime of the MCL Younger trial. We conclude that this might explain why we did not observe a significant association between SAMHD1 protein expression and the outcome of MCL patients upon cytarabine-based treatment.

Summary Most non-Hodgkin's lymphomas grow exclusively in the lymph node compartment protected by the tumor microenvironment. To better understand the cellular heterogeneity and the complex interaction between malignant and non-malignant cells, experiments with primary, patient-derived samples are often indispensable. Here, we describe a time-efficient but gentle protocol to process human lymph node samples. This protocol avoids enzymatic or mechanical stress and was optimized for the purpose of generating single-cell suspension suitable for delicate assays, such as single-cell RNA sequencing. For complete details on the use and execution of this protocol, please refer to Roider et al. (2020)., Graphical abstract, Highlights • Protocol to isolate and freeze lymphocyte suspensions from human lymph node samples • Avoiding enzymatic stress to preserve gene expression and epitope profiles • Optimized thawing and dead cell removal to meet the standards of single-cell sequencing, Most non-Hodgkin's lymphomas grow exclusively in the lymph node compartment protected by the tumor microenvironment. To better understand the cellular heterogeneity and the complex interaction between malignant and non-malignant cells, experiments with primary, patient-derived samples are often indispensable. Here, we describe a time-efficient but gentle protocol to process human lymph node samples. This protocol avoids enzymatic or mechanical stress and was optimized for the purpose of generating single-cell suspension suitable for delicate assays, such as single-cell RNA sequencing.

The transcription factor Eomesodermin (EOMES) promotes IL-10 production of CD4+T-cells, which has been linked to immunosuppressive and cytotoxic activities. We detected EOMES-expressing CD4+T-cells in lymph node samples of patients with chronic lymphocytic leukemia (CLL) or diffuse large B-cell lymphoma. This was in line with an observed expansion of EOMES-positive CD4+T-cells in leukemic Eµ-TCL1 mice, a well-established model of CLL, and upon adoptive transfer of TCL1 leukemia in mice. Transcriptome and flow cytometry analyses revealed that EOMES does not only drive the transcription of IL-10, but rather controls a unique differentiation program in CD4+T-cells. Moreover, EOMES was necessary for the accumulation of a specific CD4+T-cell subset that expresses IFNγ and IL-10, as well as inhibitory receptors, like PD-1 and LAG3. T-cell transfer studies in leukopenicRag2-/-mice showed that EOMES-deficient CD4+T-cells were inferior in controlling TCL1 leukemia development compared to wildtype T-cells, even though expansion ofEomes-/-CD4+T-cells was observed. We further showed that control of TCL1 leukemia was driven by IL-10 receptor-mediated signals, asIl10rb-deficient CD4+T-cells showed impaired anti-leukemia activity. Altogether, our data suggest that IL-10 producing PD-1+CD4+T-cells contribute to CLL control in an EOMES- and IL-10R-dependent manner.

Tumor heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is well-known to affect the efficacy of anti-cancer drugs, most personalized treatment approaches do not account for intratumor heterogeneity. We addressed this issue by studying the heterogeneity of lymph node-derived B cell non-Hodgkin lymphoma (B-NHL) by single cell RNA-sequencing (scRNA-seq) and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subclones and compared their drug response and genomic profiles. Malignant subclones of the same patient responded strikingly different to anti-cancer drugs ex vivo, which recapitulated subclone-specific drug sensitivity during in vivo treatment. Tumor infiltrating T cells represented the majority of non-malignant cells, whose gene expression signatures were similar across all donors, whereas the frequencies of T cell subsets varied significantly between the donors. Our data provide new insights into the heterogeneity of B-NHL and highlight the relevance of intratumor heterogeneity for personalized cancer therapies.

Tumour heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is known to affect the efficacy of cancer therapy, most personalized treatment approaches do not account for intratumour heterogeneity. We addressed this issue by studying the heterogeneity of nodal B-cell lymphomas by single-cell RNA-sequencing and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subpopulations and compared their drug-response and genomic profiles. Malignant subpopulations from the same patient responded strikingly differently to anti-cancer drugs ex vivo, which recapitulated subpopulation-specific drug sensitivity during in vivo treatment. Infiltrating T cells represented the majority of non-malignant cells, whose gene-expression signatures were similar across all donors, whereas the frequencies of T-cell subsets varied significantly between the donors. Our data provide insights into the heterogeneity of nodal B-cell lymphomas and highlight the relevance of intratumour heterogeneity for personalized cancer therapy.

High-dose therapy followed by autologous stem cell transplantation (ASCT) can improve outcomes for mantle cell lymphoma (MCL) but is associated with a high incidence of relapse. A retrospective study of 191 MCL patients who underwent ASCT at City of Hope was performed to examine prognostic factors for outcomes following ASCT. For all patients, the 5-year overall survival (OS) was 71% (confidence interval [CI]: 63% – 77%) and progression-free survival (PFS) was 53% (CI: 45% – 60%). The 5-year cumulative incidence of relapse was 41% (CI: 34% – 48%) with a continuous pattern of relapse events occurring at a median of 2.1 years (range: 0.2 – 13.4) after ASCT. In multivariate analysis, post-transplant maintenance rituximab was the factor most significantly associated with both OS (relative risk [RR] 0.17, CI: 0.07 – 0.38) and PFS (RR 0.25, CI: 0.14 – 0.44). For the subset of patients who had positron emission tomography (PET) data available and were in a PET-negative first complete remission (CR1) at ASCT (n = 105), Maintenance rituximab was significantly associated with superior OS (RR 0.17, CI: 0.05 – 0.59) and PFS (RR 0.20, CI: 0.09 – 0.43). These results support a benefit with maintenance rituximab for all MCL patients treated with ASCT.

Introduction and Methods To investigate the mechanisms by which microenvironmental signals induce treatment resistance in chronic lymphocytic leukemia (CLL) we conducted a high-throughput perturbation assay combining pairwise 15 clinically relevant drugs with 18 stimulations mimicking the tumor microenvironment. We combined this with multi-layer omics data using whole exome sequencing, genome-wide DNA-methylation profiles and RNA sequencing to investigate molecular determinants of microenvironmental drug resistance. In parallel we assessed the in-vivo relevance of investigated pathways in 100 CLL infiltrated- and 100 healthy lymph node (LN) biopsies by staining for stimulus specific downstream pathway components using immunohistochemistry (IHC). Results We initially clustered drugs and microenvironmental stimuli separately based on the similarity of their response profiles across all CLL samples. We found drug response profiles to be correlated closely for drugs targeting the same signaling-pathway, e.g. the B-cell receptor inhibitors Ibrutinib (BTK) and PRT062607 (Syk) (Pearson correlation coefficient: r=0.78, 95% CI: 0.72 - 0.83). In contrast, responses to microenvironmental stimuli were less correlated, indicating diverse effects are caused by the tumor microenvironment (e.g. Interleukin 4 (IL-4) vs. Interleukin 2, Pearson correlation coefficient: r=0.17, 95% CI: 0.03 - 0.31). Twelve of the 18 tested stimulations enhanced survival of CLL cells, whereas two reduced the viability of CLL cells in-vitro (comparisons yielded BH adjusted t-test p-values Ten of the 18 stimulation effects were modulated by genetic alterations in CLL cells, for 6 stimuli two or more response modulating genetic alterations were identified (FDR 10%). IGHV mutation status for instance modulated the effects of TLR 7/8/9 agonists as well as Interleukine-1β, CD40 ligand and TGF-β1. We will present a detailed analysis of how microenvironmental stimuli depend on specific genetic alterations in CLL. To understand how soluble stimuli interfere with drug response we searched for specific interactions between stimulations and drugs with the following linear model: Viability ~ drug-effect + stimulation-effect + drug-effect:stimulation-effect and tested for significance of the interaction term. This approach allowed us to dissect interactions independently of the individual effects. We discovered different types of drug-effect:stimulation-effect interactions: 1) The microenvironmental stimulus had a strong pro-survival effect on the baseline viability and interfered with the response to drugs (e.g. IL-4:Ibrutinib, p-value< 0.0001). 2) The microenvironmental stimulus had no major effect on baseline viability but significantly interfered with response to drugs (e.g. Interferon-γ:Ibrutinib, p-value: 0.014). 3) The microenvironmental stimulus and the drug exhibited no major individual effect on CLL cell survival, but together significantly increased CLL cell viability (e.g. Interferon-γ:Ralimetinib, p-value: < 0.0001). We will present a detailed analysis of microenvironmental stimuli and their influence on drug response. In the final step we investigated the biological relevance of selected microenvironmental stimuli in patient LN- and bone marrow biopsies by IHC. CLL infiltrated LN exhibited a higher signaling activity of the IL-4 and TLR pathway than non-neoplastic LN (t-test, p-values Conclusion We present a systematic investigation on the tumor microenvironment in CLL, the underlying molecular determinants as well its interference with drug response which will serve as a scientific resource and starting point for further mechanistical investigations. Figure Disclosures Kriegsmann: Celgene: Research Funding; Bristol-Myers Squibb: Research Funding; Sanofi: Research Funding; Morphosys: Research Funding. Müller-Tidow:MSD: Membership on an entity's Board of Directors or advisory committees.

Background: Signals provided by the microenvironment can modify and circumvent pathway activities that are therapeutically targeted by drugs. However, a systems-level understanding of how the microenvironment and the genetic and molecular alterations of the tumor interact with each other and contribute to drug resistance is lacking. Methods: To address this unmet need, we established an automated microscopy-based phenotyping platform that uses co-culture conditions mimicking the bone marrow environment. We cultured primary tumor cells from more than 100 leukemia patients (CLL, AML, MCL, T-PLL, HCL) with and without bone marrow stroma cell support in DMEM and 10% human serum and treated each condition with 57 drugs in 3 concentrations. After 72h of incubation, 22 000 images per patient were acquired and processed by our custom made image analysis pipeline. Our set-up allows us to increase sensitivity far beyond simple viability testing, as it reads out additional cell type specific features such as cell morphology, autophagy and cell-cell interactions. Results: Quality assessment revealed that in contrast to mono-culture conditions, assay plate edge effects can be avoided under stable stroma cell co-culture conditions. Correlation of replicated patient samples were comparable between mono- and co-cultures (R2>0.75). In the absence of their native microenvironment, primary leukemia cells undergo spontaneous apoptosis ex-vivo. Viability at culture start was always >90% and dropped to a median of 51% (viability range: 17%-90%) after 72h in mono-cultures. Among CLL samples spontaneous apoptosis was not dependent on either IGHV mutation status or any major cytogenetic risk group. Bone marrow stroma cell co-culture conditions protected tumor cells from spontaneous apoptosis (p=8.2e-6, paired t-test). Patient samples with a high degree of spontaneous apoptosis benefited most from co-culture conditions (p=7.2e-10, Pearson correlation). To model interactions of stroma cell conditions and drug-induced apoptosis we established the following linear model: Viability ~ drug-effect + culture-model + drug-effect:culture-model. While activity of some drugs was significantly altered under co-culture conditions, we could also identify drugs with similar activity in mono- and co-cultures. For instance, the activity of common chemotherapeutics (fludarabine: p=0.002 at 0.6µM, cytarabine: p=0.001 at 1.5µM, ANOVA) or bromodomain inhibitors (I-BET-762: p=5.9e-5 at 4.5µM, JQ1: p=1.5e-8 at 1.5µM, ANOVA) was significantly reduced under co-culture conditions. In contrast, PI3K inhibitors idelalisib and duvelisib had a similar activity in mono-culture and stroma co-culture conditions and might represent a starting point to overcome stroma cell mediated drug resistance. In CLL, we identified IGHV mutation status and trisomy 12 as important determinants of response to kinase inhibitors. We confirmed these findings in stroma cell co-cultures, e.g. a better activity of B-cell receptor inhibitors in trisomy 12 and IGHV unmutated CLL. A systematic comparison of ex-vivo drug response pattern in mono- and co-cultures across 171 drug conditions will be presented. Conclusion: Our results suggest that high throughput co-culture drug testing can be robustly performed and provide an unprecedented understanding of how the stroma cell microenvironment and the genetic make-up of tumor cells contribute to drug resistance and sensitivity. Figure: Over 2 million microscopy images were acquired and analysed to assess drug resistance and sensitivity in a co-culture model of primary leukemia and bone marrow stroma cells. blue= Hoechst33342, green=Calcein AM, red=lysosomal dye NIR Figure 1. Figure 1. Disclosures No relevant conflicts of interest to declare.