A Bayesian framework for inferring dynamic intercellular interactions from time-series single-cell data.

Characterizing cell-cell communication and tracking its variability over time are crucial for understanding the coordination of biological processes mediating normal development, disease progression, and responses to perturbations such as therapies. Existing tools fail to capture time-dependent intercellular interactions and primarily rely on databases compiled from limited contexts. We introduce DIISCO, a Bayesian framework designed to characterize the temporal dynamics of cellular interactions using single-cell RNA-sequencing data from multiple time points. Our method utilizes structured Gaussian process regression to unveil time-resolved interactions among diverse cell types according to their coevolution and incorporates prior knowledge of receptor-ligand complexes. We show the interpretability of DIISCO in simulated data and new data collected from T cells cocultured with lymphoma cells, demonstrating its potential to uncover dynamic cell-cell cross talk.

Dictionary of immune responses to cytokines at single-cell resolution.

Cytokines mediate cell-cell communication in the immune system and represent important therapeutic targets1-3. A myriad of studies have highlighted their central role in immune function4-13, yet we lack a global view of the cellular responses of each immune cell type to each cytokine. To address this gap, we created the Immune Dictionary, a compendium of single-cell transcriptomic profiles of more than 17 immune cell types in response to each of 86 cytokines (>1,400 cytokine-cell type combinations) in mouse lymph nodes in vivo. A cytokine-centric view of the dictionary revealed that most cytokines induce highly cell-type-specific responses. For example, the inflammatory cytokine interleukin-1ß induces distinct gene programmes in almost every cell type. A cell-type-centric view of the dictionary identified more than 66 cytokine-driven cellular polarization states across immune cell types, including previously uncharacterized states such as an interleukin-18-induced polyfunctional natural killer cell state. Based on this dictionary, we developed companion software, Immune Response Enrichment Analysis, for assessing cytokine activities and immune cell polarization from gene expression data, and applied it to reveal cytokine networks in tumours following immune checkpoint blockade therapy. Our dictionary generates new hypotheses for cytokine functions, illuminates pleiotropic effects of cytokines, expands our knowledge of activation states of each immune cell type, and provides a framework to deduce the roles of specific cytokines and cell-cell communication networks in any immune response.

DIISCO: A Bayesian framework for inferring dynamic intercellular interactions from time-series single-cell data.

Characterizing cell-cell communication and tracking its variability over time is essential for understanding the coordination of biological processes mediating normal development, progression of disease, or responses to perturbations such as therapies. Existing tools lack the ability to capture time-dependent intercellular interactions, such as those influenced by therapy, and primarily rely on existing databases compiled from limited contexts. We present DIISCO, a Bayesian framework for characterizing the temporal dynamics of cellular interactions using single-cell RNA-sequencing data from multiple time points. Our method uses structured Gaussian process regression to unveil time-resolved interactions among diverse cell types according to their co-evolution and incorporates prior knowledge of receptor-ligand complexes. We show the interpretability of DIISCO in simulated data and new data collected from CAR-T cells co-cultured with lymphoma cells, demonstrating its potential to uncover dynamic cell-cell crosstalk.

ZNF683 marks a CD8+ T cell population associated with anti-tumor immunity following anti-PD-1 therapy for Richter syndrome.

Unlike many other hematologic malignancies, Richter syndrome (RS), an aggressive B cell lymphoma originating from indolent chronic lymphocytic leukemia, is responsive to PD-1 blockade. To discover the determinants of response, we analyze single-cell transcriptome data generated from 17 bone marrow samples longitudinally collected from 6 patients with RS. Response is associated with intermediate exhausted CD8 effector/effector memory T cells marked by high expression of the transcription factor ZNF683, determined to be evolving from stem-like memory cells and divergent from terminally exhausted cells. This signature overlaps with that of tumor-infiltrating populations from anti-PD-1 responsive solid tumors. ZNF683 is found to directly target key T cell genes (TCF7, LMO2, CD69) and impact pathways of T cell cytotoxicity and activation. Analysis of pre-treatment peripheral blood from 10 independent patients with RS treated with anti-PD-1, as well as patients with solid tumors treated with anti-PD-1, supports an association of ZNF683high T cells with response.

Evolutionary history of transformation from chronic lymphocytic leukemia to Richter syndrome.

Richter syndrome (RS) arising from chronic lymphocytic leukemia (CLL) exemplifies an aggressive malignancy that develops from an indolent neoplasm. To decipher the genetics underlying this transformation, we computationally deconvoluted admixtures of CLL and RS cells from 52 patients with RS, evaluating paired CLL-RS whole-exome sequencing data. We discovered RS-specific somatic driver mutations (including IRF2BP2, SRSF1, B2M, DNMT3A and CCND3), recurrent copy-number alterations beyond del(9p21)(CDKN2A/B), whole-genome duplication and chromothripsis, which were confirmed in 45 independent RS cases and in an external set of RS whole genomes. Through unsupervised clustering, clonally related RS was largely distinct from diffuse large B cell lymphoma. We distinguished pathways that were dysregulated in RS versus CLL, and detected clonal evolution of transformation at single-cell resolution, identifying intermediate cell states. Our study defines distinct molecular subtypes of RS and highlights cell-free DNA analysis as a potential tool for early diagnosis and monitoring.

Reversal of viral and epigenetic HLA class I repression in Merkel cell carcinoma.

Cancers avoid immune surveillance through an array of mechanisms, including perturbation of HLA class I antigen presentation. Merkel cell carcinoma (MCC) is an aggressive, HLA-I-low, neuroendocrine carcinoma of the skin often caused by the Merkel cell polyomavirus (MCPyV). Through the characterization of 11 newly generated MCC patient-derived cell lines, we identified transcriptional suppression of several class I antigen presentation genes. To systematically identify regulators of HLA-I loss in MCC, we performed parallel, genome-scale, gain- and loss-of-function screens in a patient-derived MCPyV-positive cell line and identified MYCL and the non-canonical Polycomb repressive complex 1.1 (PRC1.1) as HLA-I repressors. We observed physical interaction of MYCL with the MCPyV small T viral antigen, supporting a mechanism of virally mediated HLA-I suppression. We further identify the PRC1.1 component USP7 as a pharmacologic target to restore HLA-I expression in MCC.

Improved T-cell Immunity Following Neoadjuvant Chemotherapy in Ovarian Cancer.

PURPOSE: Although local tissue-based immune responses are critical for elucidating direct tumor-immune cell interactions, peripheral immune responses are increasingly recognized as occupying an important role in anticancer immunity. We evaluated serial blood samples from patients with advanced epithelial ovarian cancer (EOC) undergoing standard-of-care neoadjuvant carboplatin and paclitaxel chemotherapy (including dexamethasone for prophylaxis of paclitaxel-associated hypersensitivity reactions) to characterize the evolution of the peripheral immune cell function and composition across the course of therapy. EXPERIMENTAL DESIGN: Serial blood samples from 10 patients with advanced high-grade serous ovarian cancer treated with neoadjuvant chemotherapy (NACT) were collected before the initiation of chemotherapy, after the third and sixth cycles, and approximately 2 months after completion of chemotherapy. T-cell function was evaluated using ex vivo IFNγ ELISpot assays, and the dynamics of T-cell repertoire and immune cell composition were assessed using bulk and single-cell RNA sequencing (RNAseq). RESULTS: T cells exhibited an improved response to viral antigens after NACT, which paralleled the decrease in CA125 levels. Single-cell analysis revealed increased numbers of memory T-cell receptor (TCR) clonotypes and increased central memory CD8+ and regulatory T cells throughout chemotherapy. Finally, administration of NACT was associated with increased monocyte frequency and expression of HLA class II and antigen presentation genes; single-cell RNAseq analyses showed that although driven largely by classical monocytes, increased class II gene expression was a feature observed across monocyte subpopulations after chemotherapy. CONCLUSIONS: NACT may alleviate tumor-associated immunosuppression by reducing tumor burden and may enhance antigen processing and presentation. These findings have implications for the successful combinatorial applications of immune checkpoint blockade and therapeutic vaccine approaches in EOC.

Coevolving JAK2V617F+relapsed AML and donor T cells with PD-1 blockade after stem cell transplantation: an index case.

Relapse of myeloproliferative neoplasms (MPNs) after allogeneic hematopoietic stem cell transplantation (HSCT) is associated with poor outcomes, as therapeutic approaches to reinstate effective graft-versus-leukemia (GVL) responses remain suboptimal. Immune escape through overexpression of PD-L1 in JAK2V617F-mutated MPN provides a rationale for therapeutic PD-1 blockade, and indeed, clinical activity of nivolumab in relapsed MPN post-HSCT has been observed. Elucidation of the features of response following PD-1 blockade in such patients could inform novel therapeutic concepts that enhance GVL. Here, we report an integrated high-dimensional analysis using single-cell RNA sequencing, T-cell receptor sequencing, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq), and assay for transposase-accessible chromatin using sequencing (scATAC-seq), together with mass cytometry, in peripheral blood mononuclear cells collected at 6 timepoints before, during, and after transient response to PD-1 blockade from an index case of relapsed MPN following HSCT. Before nivolumab infusion, acute myeloid leukemia (AML) blasts demonstrated high expression of chemokines, and T cells were characterized by expression of interferon-response genes. This baseline inflammatory signature disappeared after nivolumab infusion. Clinical response was characterized by transient expansion of a polyclonal CD4+ T-cell population and contraction of an AML subpopulation that exhibited megakaryocytic features and elevated PD-L1 expression. At relapse, the proportion of the AML subpopulation with progenitor-like features progressively increased, suggesting coevolution of AML blasts and donor-derived T cells. We thus demonstrate how single-cell technologies can provide complementary insight into cellular mechanisms underlying response to PD-1 blockade, motivating future longitudinal high-dimensional single-cell studies of GVL responses in relapsed myeloid disease.

Phenotype, specificity and avidity of antitumour CD8+ T cells in melanoma.

Interactions between T cell receptors (TCRs) and their cognate tumour antigens are central to antitumour immune responses1-3; however, the relationship between phenotypic characteristics and TCR properties is not well elucidated. Here we show, by linking the antigenic specificity of TCRs and the cellular phenotype of melanoma-infiltrating lymphocytes at single-cell resolution, that tumour specificity shapes the expression state of intratumoural CD8+ T cells. Non-tumour-reactive T cells were enriched for viral specificities and exhibited a non-exhausted memory phenotype, whereas melanoma-reactive lymphocytes predominantly displayed an exhausted state that encompassed diverse levels of differentiation but rarely acquired memory properties. These exhausted phenotypes were observed both among clonotypes specific for public overexpressed melanoma antigens (shared across different tumours) or personal neoantigens (specific for each tumour). The recognition of such tumour antigens was provided by TCRs with avidities inversely related to the abundance of cognate targets in melanoma cells and proportional to the binding affinity of peptide-human leukocyte antigen (HLA) complexes. The persistence of TCR clonotypes in peripheral blood was negatively affected by the level of intratumoural exhaustion, and increased in patients with a poor response to immune checkpoint blockade, consistent with chronic stimulation mediated by residual tumour antigens. By revealing how the quality and quantity of tumour antigens drive the features of T cell responses within the tumour microenvironment, we gain insights into the properties of the anti-melanoma TCR repertoire.

Longitudinal Single-Cell Dynamics of Chromatin Accessibility and Mitochondrial Mutations in Chronic Lymphocytic Leukemia Mirror Disease History.

While cancers evolve during disease progression and in response to therapy, temporal dynamics remain difficult to study in humans due to the lack of consistent barcodes marking individual clones in vivo. We employ mitochondrial single-cell assay for transposase-accessible chromatin with sequencing to profile 163,279 cells from 9 patients with chronic lymphocytic leukemia (CLL) collected across disease course and utilize mitochondrial DNA (mtDNA) mutations as natural genetic markers of cancer clones. We observe stable propagation of mtDNA mutations over years in the absence of strong selective pressure, indicating clonal persistence, but dramatic changes following tight bottlenecks, including disease transformation and relapse posttherapy, paralleled by acquisition of copy-number variants and changes in chromatin accessibility and gene expression. Furthermore, we link CLL subclones to distinct chromatin states, providing insight into nongenetic sources of relapse. mtDNA mutations thus mirror disease history and provide naturally occurring genetic barcodes to enable patient-specific study of cancer subclonal dynamics. SIGNIFICANCE: Single-cell multi-omic profiling of CLL reveals the utility of somatic mtDNA mutations as in vivo barcodes, which mark subclones that can evolve over time along with changes in accessible chromatin and gene expression profiles to capture dynamics of disease evolution. See related commentary by Hilton and Scott, p. 2965. This article is highlighted in the In This Issue feature, p. 2945.