Modeling T cell temporal response to cancer immunotherapy rationalizes development of combinatorial treatment protocols.

Successful immunotherapy relies on triggering complex responses involving T cell dynamics in tumors and the periphery. Characterizing these responses remains challenging using static human single-cell atlases or mouse models. To address this, we developed a framework for in vivo tracking of tumor-specific CD8 T cells over time and at single-cell resolution.

Bispecific dendritic-T cell engager potentiates anti-tumor immunity.

Immune checkpoint inhibition treatment using aPD-1 monoclonal antibodies is a promising cancer immunotherapy approach. However, its effect on tumor immunity is narrow, as most patients do not respond to the treatment or suffer from recurrence. We show that the crosstalk between conventional type I dendritic cells (cDC1) and T cells is essential for an effective aPD-1-mediated anti-tumor response.

MCProj: metacell projection for interpretable and quantitative use of transcriptional atlases.

We describe MCProj-an algorithm for analyzing query scRNA-seq data by projections over reference single-cell atlases. We represent the reference as a manifold of annotated metacell gene expression distributions. We then interpret query metacells as mixtures of atlas distributions while correcting for technology-specific gene biases.

Inflammatory signals from fatty bone marrow support DNMT3A driven clonal hematopoiesis.

Both fatty bone marrow (FBM) and somatic mutations in hematopoietic stem cells (HSCs), also termed clonal hematopoiesis (CH) accumulate with human aging. However it remains unclear whether FBM can modify the evolution of CH. To address this question, we herein present the interaction between CH and FBM in two preclinical male mouse models: after sub-lethal irradiation or after castration.

Metacell-2: a divide-and-conquer metacell algorithm for scalable scRNA-seq analysis.

Scaling scRNA-seq to profile millions of cells is crucial for constructing high-resolution maps of transcriptional manifolds. Current analysis strategies, in particular dimensionality reduction and two-phase clustering, offer only limited scaling and sensitivity to define such manifolds. We introduce Metacell-2, a recursive divide-and-conquer algorithm allowing efficient decomposition of scRNA-seq datasets of any size into small and cohesive groups of cells called metacells.

Single-cell analysis of regions of interest (SCARI) using a photosensitive tag.

The functional activity and differentiation potential of cells are determined by their interactions with surrounding cells. Approaches that allow unbiased characterization of cell states while at the same time providing spatial information are of major value to assess this environmental influence. However, most current techniques are hampered by a tradeoff between spatial resolution and cell profiling depth.

Recurrent deletions in clonal hematopoiesis are driven by microhomology-mediated end joining.

The mutational mechanisms underlying recurrent deletions in clonal hematopoiesis are not entirely clear. In the current study we inspect the genomic regions around recurrent deletions in myeloid malignancies, and identify microhomology-based signatures in CALR, ASXL1 and SRSF2 loci. We demonstrate that these deletions are the result of double stand break repair by a PARP1 dependent microhomology-mediated end joining (MMEJ) pathway.

MetaCell: analysis of single-cell RNA-seq data using K-nn graph partitions.

scRNA-seq profiles each represent a highly partial sample of mRNA molecules from a unique cell that can never be resampled, and robust analysis must separate the sampling effect from biological variance. We describe a methodology for partitioning scRNA-seq datasets into metacells: disjoint and homogenous groups of profiles that could have been resampled from the same cell. Unlike clustering analysis, our algorithm specializes at obtaining granular as opposed to maximal groups.

Dysfunctional CD8 T Cells Form a Proliferative, Dynamically Regulated Compartment within Human Melanoma.

Tumor immune cell compositions play a major role in response to immunotherapy, but the heterogeneity and dynamics of immune infiltrates in human cancer lesions remain poorly characterized. Here, we identify conserved intratumoral CD4 and CD8 T cell behaviors in scRNA-seq data from 25 melanoma patients. We discover a large population of CD8 T cells showing continuous progression from an early effector "transitional" into a dysfunctional T cell state.