Multimodal and spatially resolved profiling identifies distinct patterns of T cell infiltration in nodal B cell lymphoma entities.

The redirection of T cells has emerged as an attractive therapeutic principle in B cell non-Hodgkin lymphoma (B-NHL). However, a detailed characterization of lymphoma-infiltrating T cells across B-NHL entities is missing. Here we present an in-depth T cell reference map of nodal B-NHL, based on cellular indexing of transcriptomes and epitopes, T cell receptor sequencing, flow cytometry and multiplexed immunofluorescence applied to 101 lymph nodes from patients with diffuse large B cell, mantle cell, follicular or marginal zone lymphoma, and from healthy controls. This multimodal resource revealed quantitative and spatial aberrations of the T cell microenvironment across and within B-NHL entities. Quantitative differences in PD1+ TCF7- cytotoxic T cells, T follicular helper cells or IKZF3+ regulatory T cells were linked to their clonal expansion. The abundance of PD1+ TCF7- cytotoxic T cells was associated with poor survival. Our study portrays lymphoma-infiltrating T cells with unprecedented comprehensiveness and provides a unique resource for the investigation of lymphoma biology and prognosis.

Proteogenomics refines the molecular classification of chronic lymphocytic leukemia.

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.

Processing human lymph node samples for single-cell assays.

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).

An autologous culture model of nodal B-cell lymphoma identifies ex vivo determinants of response to bispecific antibodies.

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.