Cellular states are coupled to genomic and viral heterogeneity in HPV-related oropharyngeal carcinoma.

Head and neck squamous cell carcinoma (HNSCC) includes a subset of cancers driven by human papillomavirus (HPV). Here we use single-cell RNA-seq to profile both HPV-positive and HPV-negative oropharyngeal tumors, uncovering a high level of cellular diversity within and between tumors. First, we detect diverse chromosomal aberrations within individual tumors, suggesting genomic instability and enabling the identification of malignant cells even at pathologically negative margins. Second, we uncover diversity with respect to HNSCC subtypes and other cellular states such as the cell cycle, senescence and epithelial-mesenchymal transitions. Third, we find heterogeneity in viral gene expression within HPV-positive tumors. HPV expression is lost or repressed in a subset of cells, which are associated with a decrease in HPV-associated cell cycle phenotypes, decreased response to treatment, increased invasion and poor prognosis. These findings suggest that HPV expression diversity must be considered during diagnosis and treatment of HPV-positive tumors, with important prognostic ramifications.

CAR T cell killing requires the IFNγR pathway in solid but not liquid tumours.

Chimeric antigen receptor (CAR) therapy has had a transformative effect on the treatment of haematologic malignancies1-6, but it has shown limited efficacy against solid tumours. Solid tumours may have cell-intrinsic resistance mechanisms to CAR T cell cytotoxicity. Here, to systematically identify potential resistance pathways in an unbiased manner, we conducted a genome-wide CRISPR knockout screen in glioblastoma, a disease in which CAR T cells have had limited efficacy7,8. We found that the loss of genes in the interferon-γ receptor (IFNγR) signalling pathway (IFNGR1, JAK1 or JAK2) rendered glioblastoma and other solid tumours more resistant to killing by CAR T cells both in vitro and in vivo. However, loss of this pathway did not render leukaemia or lymphoma cell lines insensitive to CAR T cells. Using transcriptional profiling, we determined that glioblastoma cells lacking IFNγR1 had lower upregulation of cell-adhesion pathways after exposure to CAR T cells. We found that loss of IFNγR1 in glioblastoma cells reduced overall CAR T cell binding duration and avidity. The critical role of IFNγR signalling in susceptibility of solid tumours to CAR T cells is surprising, given that CAR T cells do not require traditional antigen-presentation pathways. Instead, in glioblastoma tumours, IFNγR signalling was required for sufficient adhesion of CAR T cells to mediate productive cytotoxicity. Our work demonstrates that liquid and solid tumours differ in their interactions with CAR T cells and suggests that enhancing binding interactions between T cells and tumour cells may yield improved responses in solid tumours.

Unannotated proteins expand the MHC-I-restricted immunopeptidome in cancer.

Tumor-associated epitopes presented on MHC-I that can activate the immune system against cancer cells are typically identified from annotated protein-coding regions of the genome, but whether peptides originating from novel or unannotated open reading frames (nuORFs) can contribute to antitumor immune responses remains unclear. Here we show that peptides originating from nuORFs detected by ribosome profiling of malignant and healthy samples can be displayed on MHC-I of cancer cells, acting as additional sources of cancer antigens. We constructed a high-confidence database of translated nuORFs across tissues (nuORFdb) and used it to detect 3,555 translated nuORFs from MHC-I immunopeptidome mass spectrometry analysis, including peptides that result from somatic mutations in nuORFs of cancer samples as well as tumor-specific nuORFs translated in melanoma, chronic lymphocytic leukemia and glioblastoma. NuORFs are an unexplored pool of MHC-I-presented, tumor-specific peptides with potential as immunotherapy targets.

Single-Cell Deconvolution of Head and Neck Squamous Cell Carcinoma.

Complexities in cell-type composition have rightfully led to skepticism and caution in the interpretation of bulk transcriptomic analyses. Recent studies have shown that deconvolution algorithms can be utilized to computationally estimate cell-type proportions from the gene expression data of bulk blood samples, but their performance when applied to tumor tissues, including those from head and neck, remains poorly characterized. Here, we use single-cell data (~6000 single cells) collected from 21 head and neck squamous cell carcinoma (HNSCC) samples to generate cell-type-specific gene expression signatures. We leverage bulk RNA-seq data from >500 HNSCC samples profiled by The Cancer Genome Atlas (TCGA), and using single-cell data as a reference, apply two newly developed deconvolution algorithms (CIBERSORTx and MuSiC) to the bulk transcriptome data to quantitatively estimate cell-type proportions for each tumor in TCGA. We show that these two algorithms produce similar estimates of constituent/major cell-type proportions and that a high T-cell fraction correlates with improved survival. By further characterizing T-cell subpopulations, we identify that regulatory T-cells (Tregs) were the major contributor to this improved survival. Lastly, we assessed gene expression, specifically in the Treg population, and found that TNFRSF4 (Tumor Necrosis Factor Receptor Superfamily Member 4) was differentially expressed in the core Treg subpopulation. Moreover, higher TNFRSF4 expression was associated with greater survival, suggesting that TNFRSF4 could play a key role in mechanisms underlying the contribution of Treg in HNSCC outcomes.

Chromatin Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin.

Cell differentiation and function are regulated across multiple layers of gene regulation, including modulation of gene expression by changes in chromatin accessibility. However, differentiation is an asynchronous process precluding a temporal understanding of regulatory events leading to cell fate commitment. Here we developed simultaneous high-throughput ATAC and RNA expression with sequencing (SHARE-seq), a highly scalable approach for measurement of chromatin accessibility and gene expression in the same single cell, applicable to different tissues. Using 34,774 joint profiles from mouse skin, we develop a computational strategy to identify cis-regulatory interactions and define domains of regulatory chromatin (DORCs) that significantly overlap with super-enhancers. During lineage commitment, chromatin accessibility at DORCs precedes gene expression, suggesting that changes in chromatin accessibility may prime cells for lineage commitment. We computationally infer chromatin potential as a quantitative measure of chromatin lineage-priming and use it to predict cell fate outcomes. SHARE-seq is an extensible platform to study regulatory circuitry across diverse cells in tissues.

Epigenomic State Transitions Characterize Tumor Progression in Mouse Lung Adenocarcinoma.

Regulatory networks that maintain functional, differentiated cell states are often dysregulated in tumor development. Here, we use single-cell epigenomics to profile chromatin state transitions in a mouse model of lung adenocarcinoma (LUAD). We identify an epigenomic continuum representing loss of cellular identity and progression toward a metastatic state. We define co-accessible regulatory programs and infer key activating and repressive chromatin regulators of these cell states. Among these co-accessibility programs, we identify a pre-metastatic transition, characterized by activation of RUNX transcription factors, which mediates extracellular matrix remodeling to promote metastasis and is predictive of survival across human LUAD patients. Together, these results demonstrate the power of single-cell epigenomics to identify regulatory programs to uncover mechanisms and key biomarkers of tumor progression.

A large peptidome dataset improves HLA class I epitope prediction across most of the human population.

Prediction of HLA epitopes is important for the development of cancer immunotherapies and vaccines. However, current prediction algorithms have limited predictive power, in part because they were not trained on high-quality epitope datasets covering a broad range of HLA alleles. To enable prediction of endogenous HLA class I-associated peptides across a large fraction of the human population, we used mass spectrometry to profile >185,000 peptides eluted from 95 HLA-A, -B, -C and -G mono-allelic cell lines. We identified canonical peptide motifs per HLA allele, unique and shared binding submotifs across alleles and distinct motifs associated with different peptide lengths. By integrating these data with transcript abundance and peptide processing, we developed HLAthena, providing allele-and-length-specific and pan-allele-pan-length prediction models for endogenous peptide presentation. These models predicted endogenous HLA class I-associated ligands with 1.5-fold improvement in positive predictive value compared with existing tools and correctly identified >75% of HLA-bound peptides that were observed experimentally in 11 patient-derived tumor cell lines.

Lineage Tracing in Humans Enabled by Mitochondrial Mutations and Single-Cell Genomics.

Lineage tracing provides key insights into the fate of individual cells in complex organisms. Although effective genetic labeling approaches are available in model systems, in humans, most approaches require detection of nuclear somatic mutations, which have high error rates, limited scale, and do not capture cell state information. Here, we show that somatic mutations in mtDNA can be tracked by single-cell RNA or assay for transposase accessible chromatin (ATAC) sequencing. We leverage somatic mtDNA mutations as natural genetic barcodes and demonstrate their utility as highly accurate clonal markers to infer cellular relationships. We track native human cells both in vitro and in vivo and relate clonal dynamics to gene expression and chromatin accessibility. Our approach should allow clonal tracking at a 1,000-fold greater scale than with nuclear genome sequencing, with simultaneous information on cell state, opening the way to chart cellular dynamics in human health and disease.

Induction and transcriptional regulation of the co-inhibitory gene module in T cells.

The expression of co-inhibitory receptors, such as CTLA-4 and PD-1, on effector T cells is a key mechanism for ensuring immune homeostasis. Dysregulated expression of co-inhibitory receptors on CD4+ T cells promotes autoimmunity, whereas sustained overexpression on CD8+ T cells promotes T cell dysfunction or exhaustion, leading to impaired ability to clear chronic viral infections and diseases such as cancer1,2. Here, using RNA and protein expression profiling at single-cell resolution in mouse cells, we identify a module of co-inhibitory receptors that includes not only several known co-inhibitory receptors (PD-1, TIM-3, LAG-3 and TIGIT) but also many new surface receptors. We functionally validated two new co-inhibitory receptors, activated protein C receptor (PROCR) and podoplanin (PDPN). The module of co-inhibitory receptors is co-expressed in both CD4+ and CD8+ T cells and is part of a larger co-inhibitory gene program that is shared by non-responsive T cells in several physiological contexts and is driven by the immunoregulatory cytokine IL-27. Computational analysis identified the transcription factors PRDM1 and c-MAF as cooperative regulators of the co-inhibitory module, and this was validated experimentally. This molecular circuit underlies the co-expression of co-inhibitory receptors in T cells and identifies regulators of T cell function with the potential to control autoimmunity and tumour immunity.

Ultrashort time-to-echo MRI of the cartilaginous endplate: technique and association with intervertebral disc degeneration.

INTRODUCTION: The purpose of this study was to report the feasibility of the ultrashort time-to-echo (UTE) MRI technique to assess cartilaginous endplate (CEP) defects in humans in vivo and to assess their relationship with intervertebral disc (IVD) degeneration. METHODS: Nine volunteer subjects (mean age = 43.9 years; range = 22-61 years) were recruited, representing 54 IVDs and 108 CEPs. The subjects underwent T2-weighted and UTE MRI to assess for the presence and severity of IVD degeneration, and for the presence of CEP defects, respectively, from T12 to S1. IVD degeneration was graded according to the Schneiderman et al. classification on T2-weighted MRI. CEP defects were defined on UTE MRI as discontinuity of high signal over four consecutive images and were independently assessed by two observers. RESULTS: Thirty-seven out of 108 (34.3%) CEPs had defects, which mainly occurred at T12/L1, L1/L2 and L4/L5 (P = 0.008). Multivariate logistic regression revealed that lower body mass index (P = 0.009) and younger (P = 0.034) individuals had a decreased likelihood of having CEP defects. A statistically significant association was found to exist between the presence of CEP defects and IVD degeneration (P = 0.036). A higher prevalence of degenerated IVDs with CEP defects was found at L4/5 and L5/S1, while degenerated IVDs with no CEP defects were found throughout the whole lumbar region. Mean IVD degeneration scores of the L4/5 and L5/S1 levels with CEP defects were higher in comparison with those with no CEP defects. CONCLUSIONS: Our study demonstrates the feasibility of using UTE MRI in humans in vivo to assess the integrity of the CEP. A statistically significant association was found to exist between the presence of CEP defects and IVD degeneration. In the lower lumbar region, more severe degeneration was found to occur in the IVDs with CEP defects than in those without defects.