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.

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.

Genome-wide association studies identified a single-nucleotide polymorphism (SNP) affecting the transcription factor Eomesodermin (EOMES) associated with a significantly increased risk to develop chronic lymphocytic leukemia (CLL). Epigenetic analyses, RNA sequencing, and flow cytometry revealed that EOMES is not expressed in CLL cells, but in CD8⁺ T cells for which EOMES is a known master regulator. We thus hypothesized that the increased CLL risk associated with the EOMES SNP might be explained by its negative impact on CD8⁺ T-cell-mediated immune control of CLL. Flow cytometry analyses revealed a higher EOMES expression in CD8⁺ T cells of CLL patients compared to healthy individuals, and an accumulation of PD-1⁺ EOMES⁺ CD8⁺ T cells in lymph nodes rather than blood or bone marrow in CLL. This was in line with an observed expansion of EOMES⁺ CD8⁺ T cells in the spleen of leukemic Eµ-TCL1 mice. As EOMES expression was highest in CD8⁺ T cells that express inhibitory receptors, an involvement of EOMES in T-cell exhaustion and dysfunction seems likely. Interestingly, Eomes-deficiency in CD8⁺ T cells resulted in their impaired expansion associated with decreased CLL control in mice. Overall, these observations suggest that EOMES is essential for CD8⁺ T-cell expansion and/or maintenance, and therefore involved in adaptive immune control of CLL.

The transcription factor eomesodermin (EOMES) promotes interleukin (IL)-10 expression in CD4⁺ T cells, which has been linked to immunosuppressive and cytotoxic activities. We detected cytotoxic, programmed cell death protein-1 (PD-1) and EOMES co-expressing CD4⁺ T cells in lymph nodes (LNs) of patients with chronic lymphocytic leukemia (CLL) or diffuse large B-cell lymphoma. Transcriptome and flow cytometry analyses revealed that EOMES does not only drive IL-10 expression, but rather controls a unique transcriptional signature in CD4⁺ T cells, that is enriched in genes typical for T regulatory type 1 (T_R1) cells. The T_R1 cell identity of these CD4⁺ T cells was supported by their expression of interferon gamma and IL-10, as well as inhibitory receptors including PD-1. T_R1 cells with cytotoxic capacity accumulate also in Eµ-TCL1 mice that develop CLL-like disease. Whereas wild-type CD4⁺ T cells control TCL1 leukemia development after adoptive transfer in leukopenic Rag2^−/− mice, EOMES-deficient CD4⁺ T cells failed to do so. We further show that T_R1 cell-mediated control of TCL1 leukemia requires IL-10 receptor (IL-10R) signaling, as Il10rb-deficient CD4⁺ T cells showed impaired antileukemia activity. Altogether, our data demonstrate that EOMES is indispensable for the development of IL-10-expressing, cytotoxic T_R1 cells, which accumulate in LNs of CLL patients and control TCL1 leukemia in mice in an IL-10R-dependent manner.

Ex vivo drug response profiling is a powerful tool to study genotype–drug response associations and is being explored as a tool set for precision medicine in cancer. Here we conducted a prospective non-interventional trial to investigate feasibility of ex vivo drug response profiling for treatment guidance in hematologic malignancies (SMARTrial,NCT03488641). The primary endpoint to provide drug response profiling reports within 7 d was met in 91% of all study participants (N = 80). Secondary endpoint analysis revealed that ex vivo resistance to chemotherapeutic drugs predicted chemotherapy treatment failure in vivo. We confirmed the predictive value of ex vivo response to chemotherapy in a validation cohort of 95 individuals with acute myeloid leukemia treated with daunorubicin and cytarabine. Ex vivo drug response profiles improved ELN-22 risk stratification in individuals with adverse risk. We conclude that ex vivo drug response profiling is clinically feasible and has the potential to predict chemotherapy response in individuals with hematologic malignancies beyond clinically established genetic markers.

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.