Sophie A. Herbst

The transcription factor lymphoid enhancer-binding factor 1 (LEF1) is aberrantly expressed across all subtypes and stages of chronic lymphocytic leukemia (CLL), yet the molecular mechanisms underlying its contribution to CLL pathogenesis remain poorly defined. Here, we conducted a comprehensive mechanistic dissection of LEF1 function in CLL using extensive functional analyses of patient-derived samples. We identified that, although LEF1 messenger RNA levels remain stable, patients with clinically aggressive disease show elevated LEF1 protein levels due to enhanced protein stability. LEF1 protein abundance is selectively modulated by lymph node–derived stimuli, including T-cell interactions and B-cell receptor signaling. Importantly, we uncovered a dual, context-dependent role for LEF1 that is determined by its protein levels. Low LEF1 protein, characteristic of indolent disease, supports B-cell activation, whereas increased protein abundance in aggressive disease promotes proliferation through the binding and induction of cell cycle and metabolic gene networks. We further showed that LEF1 exon 6 skipping is enriched in proliferative and aggressive CLL. Both in vitro and in vivo experiments revealed that LEF1-driven proliferation is mediated by these short, alternative spliced isoforms. Although all LEF1 isoforms bind to a core set of proliferation- and activation-related genes, they induce distinct transcriptional programs; full-length LEF1 promotes a quiescence gene signature and limits leukemic growth, whereas exon 6-skipping isoforms drive proliferation. Our findings establish LEF1 as an oncogenic transcription factor in CLL whose biological and clinical effects are modulated posttranscriptionally by both protein abundance and isoform composition.

Previous studies have reported that chronic lymphocytic leukemia (CLL) shows a de novo chromatin activation pattern compared with normal B cells. Here, we explored whether the level of chromatin activation is related to the clinical behavior of CLL. We identified that, in some regulatory regions, increased de novo chromatin activation is linked to clinical progression, whereas, in other regions, it is associated with an indolent course. We next developed 2 prognostic scores for progressive and indolent disease, respectively, calculated a single score representing the balance between them, and further generated surrogate scores based on gene and protein expression of the target genes. The balance score outperformed the clinical impact of the 2 individual scores, because it seemed to capture the prognostic information provided by each of them. Biologically, CLLs with higher balance score showed increased activation of tumor necrosis factor alpha (TNF-α)/NF-κB and mTOR signaling pathways. Regulatory programs related to progression were predominantly activated in the lymph node microenvironment, whereas those linked to indolent disease appeared to be microenvironment independent. Finally, we thoroughly validated the balance score as a powerful and independent quantitative prognostic factor for time to first treatment across independent CLL cohorts and data modalities, such as chromatin, transcriptome, or proteome data. Our findings support the concept that de novo acquisition of chromatin changes in CLL cells plays a dual biological role, and the balance between proprogression and proindolence is a strong independent determinant of CLL prognosis.

The T-box transcription factor T-bet is known as a master regulator of the T-cell response but its role in malignant B cells has not been sufficiently explored. Here, we conducted single-cell resolved multi-omics analyses of malignant B cells from patients with chronic lymphocytic leukemia (CLL) and studied a CLL mouse model with a genetic knockout of Tbx21. We found that T-bet acts as a tumor suppressor in malignant B cells by decreasing their proliferation rate. NF-κB activity, induced by inflammatory signals provided by the microenvironment, triggered T-bet expression, which affected promoter-proximal and distal chromatin coaccessibility and controlled a specific gene signature by mainly suppressing transcription. Gene set enrichment analysis identified a positive regulation of interferon signaling and negative control of proliferation by T-bet. In line, we showed that T-bet represses cell cycling and is associated with longer overall survival of patients with CLL. Our study uncovered a novel tumor suppressive role of T-bet in malignant B cells via its regulation of inflammatory processes and cell cycling, which has implications for the stratification and therapy of patients with CLL. Linking T-bet activity to inflammation explains the good prognostic role of genetic alterations in the inflammatory signaling pathways in CLL.

Large-scale compound screens are a powerful model system for understanding variability of treatment response and discovering druggable tumor vulnerabilities of hematological malignancies. However, as mostly performed in a monoculture of tumor cells, these assays disregard modulatory effects of the in vivo microenvironment. It is an open question whether and to what extent coculture with bone marrow stromal cells could improve the biological relevance of drug testing assays over monoculture. Here, we established a high-throughput platform to measure ex vivo sensitivity of 108 primary blood cancer samples to 50 drugs in monoculture and coculture with bone marrow stromal cells. Stromal coculture conferred resistance to 52% of compounds in chronic lymphocytic leukemia (CLL) and 36% of compounds in acute myeloid leukemia (AML), including chemotherapeutics, B–cell receptor inhibitors, proteasome inhibitors, and Bromodomain and extraterminal domain inhibitors. Only the JAK inhibitors ruxolitinib and tofacitinib exhibited increased efficacy in AML and CLL stromal coculture. We further confirmed the importance of JAK-STAT signaling for stroma-mediated resistance by showing that stromal cells induce phosphorylation of STAT3 in CLL cells. We genetically characterized the 108 cancer samples and found that drug-gene associations strongly correlated between monoculture and coculture. However, effect sizes were lower in coculture, with more drug-gene associations detected in monoculture than in coculture. Our results justify a 2-step strategy for drug perturbation testing, with large-scale screening performed in monoculture, followed by focused evaluation of potential stroma-mediated resistances in coculture.

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.

Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterize the proteome and transcriptome alongside genetic and ex-vivo drug response profiling in a clinically annotated CLL discovery cohort (n = 68). Unsupervised clustering of the proteome data reveals six subgroups. Five of these proteomic groups are associated with genetic features, while one group is only detectable at the proteome level. This new group is characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). Classifiers developed to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n = 165, n = 169) confirm that ASB-CLL comprises about 20% of CLL patients. The inferior overall survival in ASB-CLL is also independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling.

The tumour microenvironment and genetic alterations collectively influence drug efficacy in cancer, but current evidence is limited and systematic analyses are lacking. Using chronic lymphocytic leukaemia (CLL) as a model disease, we investigated the influence of 17 microenvironmental stimuli on 12 drugs in 192 genetically characterised patient samples. Based on microenvironmental response, we identified four subgroups with distinct clinical outcomes beyond known prognostic markers. Response to multiple microenvironmental stimuli was amplified in trisomy 12 samples. Trisomy 12 was associated with a distinct epigenetic signature. Bromodomain inhibition reversed this epigenetic profile and could be used to target microenvironmental signalling in trisomy 12 CLL. We quantified the impact of microenvironmental stimuli on drug response and their dependence on genetic alterations, identifying interleukin 4 (IL4) and Toll‐like receptor (TLR) stimulation as the strongest actuators of drug resistance. IL4 and TLR signalling activity was increased in CLL‐infiltrated lymph nodes compared with healthy samples. High IL4 activity correlated with faster disease progression. The publicly available dataset can facilitate the investigation of cell‐extrinsic mechanisms of drug resistance and disease progression.

Summary: Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterized the proteome and transcriptome in-depth alongside genetic and ex-vivo drug response profiling in a clinically well annotated CLL discovery cohort (n= 68). Unsupervised clustering of the proteome data revealed six subgroups. Five of these proteomic groups were associated with genetic features, while one group was only detectable at the proteome level. This new group was characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). We developed classifiers to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n= 165, n= 169) and confirmed that ASB-CLL comprises about 20 % of CLL patients. The inferior overall survival observed in ASB-CLL was independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling. Single sentence summary: We performed the largest proteogenomic analysis of CLL, linked proteomic profiles to clinical outcomes, and discovered a new poor outcome subgroup (ASB-CLL).

Large-scale compound screens are a powerful model system for understanding variability of treatment response and for discovering druggable tumor vulnerabilities of hematological malignancies. However, as mostly performed in a monoculture of tumor cells, these assays disregard modulatory effects of the in vivo microenvironment. It is an open question whether and to what extent coculture with bone marrow stromal cells could improve the biological relevance of drug testing assays over monoculture. Here, we measured ex vivo sensitivity of 108 primary blood cancer samples to 50 drugs in monoculture and in coculture with bone marrow stromal cells. Stromal coculture conferred resistance to 52 % of compounds in chronic lymphocytic leukemia (CLL) and to 36% of compounds in acute myeloid leukemia (AML), including chemotherapeutics, BCR inhibitors, proteasome inhibitors and BET inhibitors. While most of the remaining drugs were similarly effective in mono- and coculture, only the JAK inhibitors ruxolitinib and tofacitinib exhibited increased efficacy in AML and CLL stromal coculture. We further confirmed the importance of JAK-STAT signaling for stroma-mediated resistance by showing that stromal cells induce phosphorylation of STAT3 in CLL cells. We genetically characterized the 108 cancer samples and found that drug-gene associations agreed well between mono- and coculture. Overall, effect sizes were lower in coculture, thus more drug-gene associations were detected in monoculture than in coculture. Our results suggest a two-step strategy for drug perturbation testing, with large-scale screening performed in monoculture, followed by focused evaluation of potential stroma-mediated resistances in coculture.