Immune checkpoint therapy has resulted in remarkable improvements in the outcome for certain cancers. To broaden the clinical impact of checkpoint targeting, we devised a strategy that couples targeting of the cytokine-inducible SH2-containing (CIS) protein, a key negative regulator of interleukin (IL)-15 signaling, with fourth generation 'armored' chimeric antigen receptor (CAR-IL-15) engineering of cord blood (CB) derived natural killer (NK) cells. This combined strategy boosted NK cell effector function through enhancing the Akt/mTORC1 axis and c-MYC signaling, resulting in increased aerobic glycolysis. When tested in a lymphoma mouse model, this combined approach improved NK cell anti-tumor activity more than either alteration alone, eradicating lymphoma xenografts without signs of any measurable toxicity. We conclude that targeting a cytokine checkpoint further enhances the antitumor activity of IL-15 secreting armored CAR-NK cells by promoting their metabolic fitness and anti-tumor activity. This combined approach represents a promising milestone in the development of the next generation of NK cells for cancer immunotherapy.

Targeting the αv integrin-TGF-β axis improves natural killer cell function against glioblastoma stem cells Running title-GBM induce NK cell dysfunction via integrin-TGF- axis

Purpose: Natural killer (NK)-cell recognition and function against NK-resistant cancers remain substantial barriers to the broad application of NK-cell immunotherapy. Potential solutions include bispecific engagers that target NK-cell activity via an NK-activating receptor when simultaneously targeting a tumor-specific antigen, as well as enhancing functionality using IL12/15/18 cytokine pre-activation. Experimental Design: We assessed single-cell NK-cell responses stimulated by the tetravalent bispecific antibody AFM13 that binds CD30 on leukemia/lymphoma targets and CD16A on various types of NK cells using mass cytometry and cytotoxicity assays. The combination of AFM13 and IL12/15/18 pre-activation of blood and cord blood–derived NK cells was investigated in vitro and in vivo. Results: We found heterogeneity within AFM13-directed conventional blood NK cell (cNK) responses, as well as consistent AFM13-directed polyfunctional activation of mature NK cells across donors. NK-cell source also impacted the AFM13 response, with cNK cells from healthy donors exhibiting superior responses to those from patients with Hodgkin lymphoma. IL12/15/18-induced memory-like NK cells from peripheral blood exhibited enhanced killing of CD30+ lymphoma targets directed by AFM13, compared with cNK cells. Cord-blood NK cells preactivated with IL12/15/18 and ex vivo expanded with K562-based feeders also exhibited enhanced killing with AFM13 stimulation via upregulation of signaling pathways related to NK-cell effector function. AFM13–NK complex cells exhibited enhanced responses to CD30+ lymphomas in vitro and in vivo. Conclusions: We identify AFM13 as a promising combination with cytokine-activated adult blood or cord-blood NK cells to treat CD30+ hematologic malignancies, warranting clinical trials with these novel combinations.

Integration of single-cell multiomics profiles generated by different single-cell technologies from the same biological sample is still challenging. Previous approaches based on shared features have only provided approximate solutions. Here, we present a novel mathematical solution named bi-order canonical correlation analysis (bi-CCA), which extends the widely used CCA approach to iteratively align the rows and the columns between data matrices. Bi-CCA is generally applicable to combinations of any two single-cell modalities. Validations using co-assayed ground truth data and application to a CAR-NK study and a fetal muscle atlas demonstrate its capability in generating accurate multimodal co-embeddings and discovering cellular identity.

We present a Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) algorithm that infers the evolution history of a cell population based on single-cell copy number (SCCN) profiles, and a statistical routine named lineage speciation analysis (LSA), whichty facilitates discovery of fitness-associated alterations and genes from SCCN lineage trees. MEDALT appears more accurate than phylogenetics approaches in reconstructing copy number lineage. From data from 20 triple-negative breast cancer patients, our approaches effectively prioritize genes that are essential for breast cancer cell fitness and predict patient survival, including those implicating convergent evolution.The source code of our study is available at https://github.com/KChen-lab/MEDALT.