A unified atlas of CD8 T cell dysfunctional states in cancer and infection.

CD8 T cells play an essential role in defense against viral and bacterial infections and in tumor immunity. Deciphering T cell loss of functionality is complicated by the conspicuous heterogeneity of CD8 T cell states described across experimental and clinical settings. By carrying out a unified analysis of over 300 assay for transposase-accessible chromatin sequencing (ATAC-seq) and RNA sequencing (RNA-seq) experiments from 12 studies of CD8 T cells in cancer and infection, we defined a shared differentiation trajectory toward dysfunction and its underlying transcriptional drivers and revealed a universal early bifurcation of functional and dysfunctional T cell states across models. Experimental dissection of acute and chronic viral infection using single-cell ATAC (scATAC)-seq and allele-specific single-cell RNA (scRNA)-seq identified state-specific drivers and captured the emergence of similar TCF1+ progenitor-like populations at an early branch point, at which functional and dysfunctional T cells diverge. Our atlas of CD8 T cell states will facilitate mechanistic studies of T cell immunity and translational efforts.

Scalable and unbiased sequence-informed embedding of single-cell ATAC-seq data with CellSpace.

Standard scATAC sequencing (scATAC-seq) analysis pipelines represent cells as sparse numeric vectors relative to an atlas of peaks or genomic tiles and consequently ignore genomic sequence information at accessible loci. Here we present CellSpace, an efficient and scalable sequence-informed embedding algorithm for scATAC-seq that learns a mapping of DNA k-mers and cells to the same space, to address this limitation. We show that CellSpace captures meaningful latent structure in scATAC-seq datasets, including cell subpopulations and developmental hierarchies, and can score transcription factor activities in single cells based on proximity to binding motifs embedded in the same space. Importantly, CellSpace implicitly mitigates batch effects arising from multiple samples, donors or assays, even when individual datasets are processed relative to different peak atlases. Thus, CellSpace provides a powerful tool for integrating and interpreting large-scale scATAC-seq compendia.

Microenvironment-Driven Dynamic Chromatin Changes in Glioblastoma Recapitulate Early Neural Development at Single-Cell Resolution.

The tumor microenvironment is necessary for recapitulating the intratumoral heterogeneity and cell state plasticity found in human primary glioblastoma (GBM). Conventional models do not accurately recapitulate the spectrum of GBM cellular states, hindering elucidation of the underlying transcriptional regulation of these states. Using our glioblastoma cerebral organoid model, we profiled the chromatin accessibility of 28,040 single cells in five patient-derived glioma stem cell lines. Integration of paired epigenomes and transcriptomes within the context of tumor-normal host cell interactions was used to probe the gene-regulatory networks underlying individual GBM cellular states in a way not readily possible in other in vitro models. These analyses identified the epigenetic underpinnings of GBM cellular states and characterized dynamic chromatin changes reminiscent of early neural development that underlie GBM cell state transitions. Despite large differences between tumors, a shared cellular compartment made up of neural progenitor-like cells and outer radial glia-like cells was observed. Together, these results shed light on the transcriptional regulation program in GBM and offer novel therapeutic targets across a broad range of genetically heterogenous GBMs. SIGNIFICANCE: Single-cell analyses elucidate the chromatin landscape and transcriptional regulation of glioblastoma cellular states and identify a radial glia-like population, providing potential targets to disrupt cell states and improve therapeutic efficacy.

Sequential CRISPR gene editing in human iPSCs charts the clonal evolution of myeloid leukemia and identifies early disease targets.

Human cancers arise through the sequential acquisition of somatic mutations that create successive clonal populations. Human cancer evolution models could help illuminate this process and inform therapeutic intervention at an early disease stage, but their creation has faced significant challenges. Here, we combined induced pluripotent stem cell (iPSC) and CRISPR-Cas9 technologies to develop a model of the clonal evolution of acute myeloid leukemia (AML). Through the stepwise introduction of three driver mutations, we generated iPSC lines that, upon hematopoietic differentiation, capture distinct premalignant stages, including clonal hematopoiesis (CH) and myelodysplastic syndrome (MDS), culminating in a transplantable leukemia, and recapitulate transcriptional and chromatin accessibility signatures of primary human MDS and AML. By mapping dynamic changes in transcriptomes and chromatin landscapes, we characterize transcriptional programs driving specific transitions between disease stages. We identify cell-autonomous dysregulation of inflammatory signaling as an early and persistent event in leukemogenesis and a promising early therapeutic target.

Tumor Microenvironment Is Critical for the Maintenance of Cellular States Found in Primary Glioblastomas.

Glioblastoma (GBM), an incurable tumor, remains difficult to model and more importantly to treat due to its genetic/epigenetic heterogeneity and plasticity across cellular states. The ability of current tumor models to recapitulate the cellular states found in primary tumors remains unexplored. To address this issue, we compared single-cell RNA sequencing of tumor cells from 5 patients across four patient-specific glioblastoma stem cell (GSC)-derived model types, including glioma spheres, tumor organoids, glioblastoma cerebral organoids (GLICO), and patient-derived xenografts. We find that GSCs within the GLICO model are enriched for a neural progenitor-like cell subpopulation and recapitulate the cellular states and their plasticity found in the corresponding primary parental tumors. These data demonstrate how the contribution of a neuroanatomically accurate human microenvironment is critical and sufficient for recapitulating the cellular states found in human primary GBMs, a principle that may likely apply to other tumor models. SIGNIFICANCE: It has been unclear how well different patient-derived GBM models are able to recreate the full heterogeneity of primary tumors. Here, we provide a complete transcriptomic characterization of the major model types. We show that the microenvironment is crucial for recapitulating GSC cellular states, highlighting the importance of tumor-host cell interactions.See related commentary by Luo and Weiss, p. 907.This article is highlighted in the In This Issue feature, p. 890.