Pan-cancer profiling of tumor-infiltrating natural killer cells through transcriptional reference mapping.

The functional diversity of natural killer (NK) cell repertoires stems from differentiation, homeostatic, receptor-ligand interactions and adaptive-like responses to viral infections. In the present study, we generated a single-cell transcriptional reference map of healthy human blood- and tissue-derived NK cells, with temporal resolution and fate-specific expression of gene-regulatory networks defining NK cell differentiation. Transfer learning facilitated incorporation of tumor-infiltrating NK cell transcriptomes (39 datasets, 7 solid tumors, 427 patients) into the reference map to analyze tumor microenvironment (TME)-induced perturbations. Of the six functionally distinct NK cell states identified, a dysfunctional stressed CD56bright state susceptible to TME-induced immunosuppression and a cytotoxic TME-resistant effector CD56dim state were commonly enriched across tumor types, the ratio of which was predictive of patient outcome in malignant melanoma and osteosarcoma. This resource may inform the design of new NK cell therapies and can be extended through transfer learning to interrogate new datasets from experimental perturbations or disease conditions.

Single-cell functional genomics reveals determinants of sensitivity and resistance to natural killer cells in blood cancers.

Cancer cells can evade natural killer (NK) cell activity, thereby limiting anti-tumor immunity. To reveal genetic determinants of susceptibility to NK cell activity, we examined interacting NK cells and blood cancer cells using single-cell and genome-scale functional genomics screens. Interaction of NK and cancer cells induced distinct activation and type I interferon (IFN) states in both cell types depending on the cancer cell lineage and molecular phenotype, ranging from more sensitive myeloid to less sensitive B-lymphoid cancers. CRISPR screens in cancer cells uncovered genes regulating sensitivity and resistance to NK cell-mediated killing, including adhesion-related glycoproteins, protein fucosylation genes, and transcriptional regulators, in addition to confirming the importance of antigen presentation and death receptor signaling pathways. CRISPR screens with a single-cell transcriptomic readout provided insight into underlying mechanisms, including regulation of IFN-γ signaling in cancer cells and NK cell activation states. Our findings highlight the diversity of mechanisms influencing NK cell susceptibility across different cancers and provide a resource for NK cell-based therapies.

Erythroid/megakaryocytic differentiation confers BCL-XL dependency and venetoclax resistance in acute myeloid leukemia.

Myeloid neoplasms with erythroid or megakaryocytic differentiation include pure erythroid leukemia, myelodysplastic syndrome with erythroid features, and acute megakaryoblastic leukemia (FAB M7) and are characterized by poor prognosis and limited treatment options. Here, we investigate the drug sensitivity landscape of these rare malignancies. We show that acute myeloid leukemia (AML) cells with erythroid or megakaryocytic differentiation depend on the antiapoptotic protein B-cell lymphoma (BCL)-XL, rather than BCL-2, using combined ex vivo drug sensitivity testing, genetic perturbation, and transcriptomic profiling. High-throughput screening of >500 compounds identified the BCL-XL-selective inhibitor A-1331852 and navitoclax as highly effective against erythroid/megakaryoblastic leukemia cell lines. In contrast, these AML subtypes were resistant to the BCL-2 inhibitor venetoclax, which is used clinically in the treatment of AML. Consistently, genome-scale CRISPR-Cas9 and RNAi screening data demonstrated the striking essentiality of BCL-XL-encoding BCL2L1 but not BCL2 or MCL1, for the survival of erythroid/megakaryoblastic leukemia cell lines. Single-cell and bulk transcriptomics of patient samples with erythroid and megakaryoblastic leukemias identified high BCL2L1 expression compared with other subtypes of AML and other hematological malignancies, where BCL2 and MCL1 were more prominent. BCL-XL inhibition effectively killed blasts in samples from patients with AML with erythroid or megakaryocytic differentiation ex vivo and reduced tumor burden in a mouse erythroleukemia xenograft model. Combining the BCL-XL inhibitor with the JAK inhibitor ruxolitinib showed synergistic and durable responses in cell lines. Our results suggest targeting BCL-XL as a potential therapy option in erythroid/megakaryoblastic leukemias and highlight an AML subgroup with potentially reduced sensitivity to venetoclax-based treatments.

Nintedanib targets KIT D816V neoplastic cells derived from induced pluripotent stem cells of systemic mastocytosis.

The KIT D816V mutation is found in >80% of patients with systemic mastocytosis (SM) and is key to neoplastic mast cell (MC) expansion and accumulation in affected organs. Therefore, KIT D816V represents a prime therapeutic target for SM. Here, we generated a panel of patient-specific KIT D816V induced pluripotent stem cells (iPSCs) from patients with aggressive SM and mast cell leukemia to develop a patient-specific SM disease model for mechanistic and drug-discovery studies. KIT D816V iPSCs differentiated into neoplastic hematopoietic progenitor cells and MCs with patient-specific phenotypic features, thereby reflecting the heterogeneity of the disease. CRISPR/Cas9n-engineered KIT D816V human embryonic stem cells (ESCs), when differentiated into hematopoietic cells, recapitulated the phenotype observed for KIT D816V iPSC hematopoiesis. KIT D816V causes constitutive activation of the KIT tyrosine kinase receptor, and we exploited our iPSCs and ESCs to investigate new tyrosine kinase inhibitors targeting KIT D816V. Our study identified nintedanib, a US Food and Drug Administration-approved angiokinase inhibitor that targets vascular endothelial growth factor receptor, platelet-derived growth factor receptor, and fibroblast growth factor receptor, as a novel KIT D816V inhibitor. Nintedanib selectively reduced the viability of iPSC-derived KIT D816V hematopoietic progenitor cells and MCs in the nanomolar range. Nintedanib was also active on primary samples of KIT D816V SM patients. Molecular docking studies show that nintedanib binds to the adenosine triphosphate binding pocket of inactive KIT D816V. Our results suggest nintedanib as a new drug candidate for KIT D816V-targeted therapy of advanced SM.

Ex vivo venetoclax sensitivity testing predicts treatment response in acute myeloid leukemia.

The BCL-2 inhibitor venetoclax has revolutionized the treatment of acute myeloid leukemia (AML) in patients not benefiting from intensive chemotherapy. Nevertheless, treatment failure remains a challenge, and predictive markers are needed, particularly for relapsed or refractory AML. Ex vivo drug sensitivity testing may correlate with outcomes, but its prospective predictive value remains unexplored. Here we report the results of the first stage of the prospective phase II VenEx trial evaluating the utility and predictiveness of venetoclax sensitivity testing using different cell culture conditions and cell viability assays in patients receiving venetoclax-azacitidine. Participants with de novo AML ineligible for intensive chemotherapy, relapsed or refractory AML, or secondary AML were included. The primary endpoint was the treatment response in participants showing ex vivo sensitivity and the key secondary endpoints were the correlation of sensitivity with responses and survival. Venetoclax sensitivity testing was successful in 38/39 participants. Experimental conditions significantly influenced the predictive accuracy. Blast-specific venetoclax sensitivity measured in conditioned medium most accurately correlated with treatment outcomes; 88% of sensitive participants achieved a treatment response. The median survival was significantly longer for participants who were ex vivo-sensitive to venetoclax (14.6 months for venetoclax-sensitive patients vs. 3.5 for venetoclax-insensitive patients, P<0.001). This analysis illustrates the feasibility of integrating drug-response profiling into clinical practice and demonstrates excellent predictivity. This trial is registered with ClinicalTrials.gov identifier: NCT04267081.

Integrated drug profiling and CRISPR screening identify essential pathways for CAR T-cell cytotoxicity.

Chimeric antigen receptor (CAR) T-cell therapy has proven effective in relapsed and refractory B-cell malignancies, but resistance and relapses still occur. Better understanding of mechanisms influencing CAR T-cell cytotoxicity and the potential for modulation using small-molecule drugs could improve current immunotherapies. Here, we systematically investigated druggable mechanisms of CAR T-cell cytotoxicity using >500 small-molecule drugs and genome-scale CRISPR-Cas9 loss-of-function screens. We identified several tyrosine kinase inhibitors that inhibit CAR T-cell cytotoxicity by impairing T-cell signaling transcriptional activity. In contrast, the apoptotic modulator drugs SMAC mimetics sensitized B-cell acute lymphoblastic leukemia and diffuse large B-cell lymphoma cells to anti-CD19 CAR T cells. CRISPR screens identified death receptor signaling through FADD and TNFRSF10B (TRAIL-R2) as a key mediator of CAR T-cell cytotoxicity and elucidated the RIPK1-dependent mechanism of sensitization by SMAC mimetics. Death receptor expression varied across genetic subtypes of B-cell malignancies, suggesting a link between mechanisms of CAR T-cell cytotoxicity and cancer genetics. These results implicate death receptor signaling as an important mediator of cancer cell sensitivity to CAR T-cell cytotoxicity, with potential for pharmacological targeting to enhance cancer immunotherapy. The screening data provide a resource of immunomodulatory properties of cancer drugs and genetic mechanisms influencing CAR T-cell cytotoxicity.

Data-driven characterization of molecular phenotypes across heterogeneous sample collections.

Existing large gene expression data repositories hold enormous potential to elucidate disease mechanisms, characterize changes in cellular pathways, and to stratify patients based on molecular profiles. To achieve this goal, integrative resources and tools are needed that allow comparison of results across datasets and data types. We propose an intuitive approach for data-driven stratifications of molecular profiles and benchmark our methodology using the dimensionality reduction algorithm t-distributed stochastic neighbor embedding (t-SNE) with multi-study and multi-platform data on hematological malignancies. Our approach enables assessing the contribution of biological versus technical variation to sample clustering, direct incorporation of additional datasets to the same low dimensional representation, comparison of molecular disease subtypes identified from separate t-SNE representations, and characterization of the obtained clusters based on pathway databases and additional data. In this manner, we performed an integrative analysis across multi-omics acute myeloid leukemia studies. Our approach indicated new molecular subtypes with differential survival and drug responsiveness among samples lacking fusion genes, including a novel myelodysplastic syndrome-like cluster and a cluster characterized with CEBPA mutations and differential activity of the S-adenosylmethionine-dependent DNA methylation pathway. In summary, integration across multiple studies can help to identify novel molecular disease subtypes and generate insight into disease biology.

T cells and cancer - why do the killers become exhausted?

Nascent tumors are mostly eliminated by the immune system. During carcinogenesis mutated cells find a way to escape from the immune system´s surveillance. As the tumor microenvironment evolves it becomes increasingly difficult for T cells to recognize and kill cancer cells. Recently, novel immunological targets have been recognized and potent immunomodulatory drugs discovered in clinical trials. This has resulted in the emergence of immunotherapy as a novel potent therapy for cancer in addition to chemotherapy, targeted therapy, operative therapy and radiotherapy.