We present the genome-wide chromatin accessibility profiles of 410 tumor samples spanning 23 cancer types from The Cancer Genome Atlas. We identify 562,709 transposase-accessible DNA elements that substantially extend the compendium of known cis-regulatory elements. Integration of ATAC-seq with TCGA multi-omic data identifies a large number of putative distal enhancers that distinguish molecular subtypes of cancers, uncovers specific driving transcription factors via protein-DNA footprints, and nominates long-range gene-regulatory interactions in cancer. These data reveal genetic risk loci of cancer predisposition as active DNA regulatory elements in cancer, identify gene-regulatory interactions underlying cancer immune evasion, and pinpoint noncoding mutations that drive enhancer activation and may impact patient survival. These results suggest a systematic approach to understand the noncoding genome in cancer to advance diagnosis and therapy.

The advent of single-cell chromatin accessibility profiling has accelerated the ability to map gene regulatory landscapes but has outpaced the development of scalable software to rapidly extract biological meaning from these data. Here we present a software suite for single-cell analysis of regulatory chromatin in R (ArchR; https://www.archrproject.com/) that enables fast and comprehensive analysis of single-cell chromatin accessibility data. ArchR provides an intuitive, user-focused interface for complex single-cell analyses, including doublet removal, single-cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing (scRNA-seq). Enabling the analysis of over 1.2 million single cells within 8 h on a standard Unix laptop, ArchR is a comprehensive software suite for end-to-end analysis of single-cell chromatin accessibility that will accelerate the understanding of gene regulation at the resolution of individual cells.

Immunotherapies that block inhibitory checkpoint receptors on T cells have transformed the clinical care of cancer patients 1 . However, whether the T cell response to checkpoint blockade relies on reinvigoration of pre-existing tumor infiltrating T cells (TILs) or on recruitment of novel T cells remains unclear 2 – 4 . Here, we performed paired single-cell RNA (scRNA) and T cell receptor (TCR)- sequencing on 79,046 cells from site-matched tumors from patients with basal cell carcinoma (BCC) or squamous cell carcinoma (SCC) pre- and post-anti-PD-1 therapy. Tracking TCR clones and transcriptional phenotypes revealed a coupling of tumor-recognition, clonal expansion, and T cell dysfunction marked by clonal expansions of CD8 + CD39 + T cells, which co-expressed markers of chronic T cell activation and exhaustion. However, this expansion did not derive from pre-existing TIL clones; rather, it was comprised of novel clonotypes not previously observed in the same tumor. Clonal replacement of T cells was preferentially observed in exhausted CD8 + T cells and evident in BCC and SCC patients. These results demonstrate that pre-existing tumor-specific T cells may have limited reinvigoration capacity, and that the T cell response to checkpoint blockade derives from a distinct repertoire of T cell clones that may have just recently entered the tumor.

Boundless Bio, Inc. (BB), and serve as consultants. V.B. is a co-founder, and has equity interest in Boundless Bio, inc. (BB) and Digital Proteomics, LLC (DP), and receives income from DP. The terms of this arrangement have been reviewed and approved by the University of California, San Diego in accordance with its conflict of interest policies. BB and DP were not involved in the research presented here. Data Availability. Whole genome-, RNA-, ATAC-, MNase-, ChIP-, PLAC-Seq data are deposited in the NCBI Sequence Read Archive (BioProject: PRJNA506071). The source data files of the pixel quantification of ATAC-see on metaphase chromosome spread images to create Extended Data Figure 7d are available on Figshare (

The challenge of linking intergenic mutations to target genes has limited molecular understanding of human diseases. Here we show that H3K27ac HiChIP generates high-resolution contact maps of active enhancers and target genes in rare primary human T cell subtypes and coronary artery smooth muscle cells. Differentiation of naive T cells into T helper 17 cells or regulatory T cells creates subtype-specific enhancer–promoter interactions, specifically at regions of shared DNA accessibility. These data provide a principled means of assigning molecular functions to autoimmune and cardiovascular disease risk variants, linking hundreds of noncoding variants to putative gene targets. Target genes identified with HiChIP are further supported by CRISPR interference and activation at linked enhancers, by the presence of expression quantitative trait loci, and by allele-specific enhancer loops in patient-derived primary cells. The majority of disease-associated enhancers contact genes beyond the nearest gene in the linear genome, leading to a fourfold increase in the number of potential target genes for autoimmune and cardiovascular diseases.

Understanding complex tissues requires single-cell deconstruction of gene regulation with precision and scale. Here, we assess the performance of a massively parallel droplet-based method Reprints and permissions information is available at www.nature.com/reprints.

CAR T cells mediate antitumor effects in a small subset of cancer patients 1-3 , but dysfunction due to T cell exhaustion is an important barrier to progress 4-6. To investigate the biology of exhaustion in human T cells expressing CAR receptors, we used a model system employing a tonically signaling CAR, which induces hallmark features of exhaustion 6. Exhaustion was associated with a profound defect in IL-2 production alongside increased chromatin accessibility of AP-1 Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

Author contributions L.M.M. and S.K. conceived the project and designed the experiments. L.M.M., M.L., E.G. and R.M. curated patient samples. S.K. led data production and performed the experiments together with A.S.K., A.M. and L.M.M. G.X.Y.Z. provided healthy bone marrow and peripheral blood CITE-seq data. S.K. analyzed the scADT-seq data with contribution from B.P. M.R.C. performed data analysis. J.M.G. conceived the analytical workflows and performed the data analysis for scATAC-seq and scRNA-seq supervised by H.Y.C. and