Conserved transcriptional connectivity of regulatory T cells in the tumor microenvironment informs new combination cancer therapy strategies.

While regulatory T (Treg) cells are traditionally viewed as professional suppressors of antigen presenting cells and effector T cells in both autoimmunity and cancer, recent findings of distinct Treg cell functions in tissue maintenance suggest that their regulatory purview extends to a wider range of cells and is broader than previously assumed. To elucidate tumoral Treg cell 'connectivity' to diverse tumor-supporting accessory cell types, we explored immediate early changes in their single-cell transcriptomes upon punctual Treg cell depletion in experimental lung cancer and injury-induced inflammation. Before any notable T cell activation and inflammation, fibroblasts, endothelial and myeloid cells exhibited pronounced changes in their gene expression in both cancer and injury settings. Factor analysis revealed shared Treg cell-dependent gene programs, foremost, prominent upregulation of VEGF and CCR2 signaling-related genes upon Treg cell deprivation in either setting, as well as in Treg cell-poor versus Treg cell-rich human lung adenocarcinomas. Accordingly, punctual Treg cell depletion combined with short-term VEGF blockade showed markedly improved control of PD-1 blockade-resistant lung adenocarcinoma progression in mice compared to the corresponding monotherapies, highlighting a promising factor-based querying approach to elucidating new rational combination treatments of solid organ cancers.

Transcriptional Basis of Mouse and Human Dendritic Cell Heterogeneity.

Dendritic cells (DCs) play a critical role in orchestrating adaptive immune responses due to their unique ability to initiate T cell responses and direct their differentiation into effector lineages. Classical DCs have been divided into two subsets, cDC1 and cDC2, based on phenotypic markers and their distinct abilities to prime CD8 and CD4 T cells. While the transcriptional regulation of the cDC1 subset has been well characterized, cDC2 development and function remain poorly understood. By combining transcriptional and chromatin analyses with genetic reporter expression, we identified two principal cDC2 lineages defined by distinct developmental pathways and transcriptional regulators, including T-bet and RORγt, two key transcription factors known to define innate and adaptive lymphocyte subsets. These novel cDC2 lineages were characterized by distinct metabolic and functional programs. Extending our findings to humans revealed conserved DC heterogeneity and the presence of the newly defined cDC2 subsets in human cancer.

Recovering Gene Interactions from Single-Cell Data Using Data Diffusion.

Single-cell RNA sequencing technologies suffer from many sources of technical noise, including under-sampling of mRNA molecules, often termed "dropout," which can severely obscure important gene-gene relationships. To address this, we developed MAGIC (Markov affinity-based graph imputation of cells), a method that shares information across similar cells, via data diffusion, to denoise the cell count matrix and fill in missing transcripts. We validate MAGIC on several biological systems and find it effective at recovering gene-gene relationships and additional structures. Applied to the epithilial to mesenchymal transition, MAGIC reveals a phenotypic continuum, with the majority of cells residing in intermediate states that display stem-like signatures, and infers known and previously uncharacterized regulatory interactions, demonstrating that our approach can successfully uncover regulatory relations without perturbations.

Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment.

Knowledge of immune cell phenotypes in the tumor microenvironment is essential for understanding mechanisms of cancer progression and immunotherapy response. We profiled 45,000 immune cells from eight breast carcinomas, as well as matched normal breast tissue, blood, and lymph nodes, using single-cell RNA-seq. We developed a preprocessing pipeline, SEQC, and a Bayesian clustering and normalization method, Biscuit, to address computational challenges inherent to single-cell data. Despite significant similarity between normal and tumor tissue-resident immune cells, we observed continuous phenotypic expansions specific to the tumor microenvironment. Analysis of paired single-cell RNA and T cell receptor (TCR) sequencing data from 27,000 additional T cells revealed the combinatorial impact of TCR utilization on phenotypic diversity. Our results support a model of continuous activation in T cells and do not comport with the macrophage polarization model in cancer. Our results have important implications for characterizing tumor-infiltrating immune cells.

Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.

It has long been the dream of biologists to map gene expression at the single-cell level. With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between genes and pathways. Recently, RNA sequencing has achieved single-cell resolution. What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing. We have developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing. The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. We analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after leukemia inhibitory factor (LIF) withdrawal. The reproducibility of these high-throughput single-cell data allowed us to deconstruct cell populations and infer gene expression relationships. VIDEO ABSTRACT.

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.

Natural Genetic Variation Reveals Key Features of Epigenetic and Transcriptional Memory in Virus-Specific CD8 T Cells.

Stable changes in chromatin states and gene expression in cells of the immune system form the basis for memory of infections and other challenges. Here, we used naturally occurring cis-regulatory variation in wild-derived inbred mouse strains to explore the mechanisms underlying long-lasting versus transient gene regulation in CD8 T cells responding to acute viral infection. Stably responsive DNA elements were characterized by dramatic and congruent chromatin remodeling events affecting multiple neighboring sites and required distinct transcription factor (TF) binding motifs for their accessibility. Specifically, we found that cooperative recruitment of T-box and Runx family transcription factors to shared targets mediated stable chromatin remodeling upon T cell activation. Our observations provide insights into the molecular mechanisms driving virus-specific CD8 T cell responses and suggest a general mechanism for the formation of transcriptional and epigenetic memory applicable to other immune and non-immune cells.

A gene-environment-induced epigenetic program initiates tumorigenesis.

Tissue damage increases the risk of cancer through poorly understood mechanisms1. In mouse models of pancreatic cancer, pancreatitis associated with tissue injury collaborates with activating mutations in the Kras oncogene to markedly accelerate the formation of early neoplastic lesions and, ultimately, adenocarcinoma2,3. Here, by integrating genomics, single-cell chromatin assays and spatiotemporally controlled functional perturbations in autochthonous mouse models, we show that the combination of Kras mutation and tissue damage promotes a unique chromatin state in the pancreatic epithelium that distinguishes neoplastic transformation from normal regeneration and is selected for throughout malignant evolution. This cancer-associated epigenetic state emerges within 48 hours of pancreatic injury, and involves an 'acinar-to-neoplasia' chromatin switch that contributes to the early dysregulation of genes that define human pancreatic cancer. Among the factors that are most rapidly activated after tissue damage in the pre-malignant pancreatic epithelium is the alarmin cytokine interleukin 33, which recapitulates the effects of injury in cooperating with mutant Kras to unleash the epigenetic remodelling program of early neoplasia and neoplastic transformation. Collectively, our study demonstrates how gene-environment interactions can rapidly produce gene-regulatory programs that dictate early neoplastic commitment, and provides a molecular framework for understanding the interplay between genetic and environmental cues in the initiation of cancer.

Rapid non-uniform adaptation to conformation-specific KRAS(G12C) inhibition.

KRAS GTPases are activated in one-third of cancers, and KRAS(G12C) is one of the most common activating alterations in lung adenocarcinoma1,2. KRAS(G12C) inhibitors3,4 are in phase-I clinical trials and early data show partial responses in nearly half of patients with lung cancer. How cancer cells bypass inhibition to prevent maximal response to therapy is not understood. Because KRAS(G12C) cycles between an active and inactive conformation4-6, and the inhibitors bind only to the latter, we tested whether isogenic cell populations respond in a non-uniform manner by studying the effect of treatment at a single-cell resolution. Here we report that, shortly after treatment, some cancer cells are sequestered in a quiescent state with low KRAS activity, whereas others bypass this effect to resume proliferation. This rapid divergent response occurs because some quiescent cells produce new KRAS(G12C) in response to suppressed mitogen-activated protein kinase output. New KRAS(G12C) is maintained in its active, drug-insensitive state by epidermal growth factor receptor and aurora kinase signalling. Cells without these adaptive changes-or cells in which these changes are pharmacologically inhibited-remain sensitive to drug treatment, because new KRAS(G12C) is either not available or exists in its inactive, drug-sensitive state. The direct targeting of KRAS oncoproteins has been a longstanding objective in precision oncology. Our study uncovers a flexible non-uniform fitness mechanism that enables groups of cells within a population to rapidly bypass the effect of treatment. This adaptive process must be overcome if we are to achieve complete and durable responses in the clinic.

RNA cytometry of single-cells using semi-permeable microcapsules.

Analytical tools for gene expression profiling of individual cells are critical for studying complex biological systems. However, the techniques enabling rapid measurements of gene expression on thousands of single-cells are lacking. Here, we report a high-throughput RNA cytometry for digital profiling of single-cells isolated in liquid droplets enveloped by a thin semi-permeable membrane (microcapsules). Due to the selective permeability of the membrane, the desirable enzymes and reagents can be loaded, or replaced, in the microcapsule at any given step by simply changing the reaction buffer in which the microcapsules are dispersed. Therefore, complex molecular biology workflows can be readily adapted to conduct nucleic acid analysis on encapsulated mammalian cells, or other biological species. The microcapsules support sequential multi-step enzymatic reactions and remain intact under different biochemical conditions, freezing, thawing, and thermocycling. Combining microcapsules with conventional FACS provides a high-throughput approach for conducting RNA cytometry of individual cells based on their digital gene expression signature.

Increasing Fluid Viscosity Ensures Consistent Single-Cell Encapsulation.

High-throughput single-cell analysis typically relies on the isolation of cells of interest in separate compartments for subsequent phenotypic or genotypic characterization. Using microfluidics, this is achieved by isolating individual cells in microdroplets or microwells. However, due to cell-to-cell variability in size, shape, and density, the cell capture efficiencies may vary significantly. This variability can negatively impact the measurements and introduce undesirable artifacts when trying to isolate and characterize heterogeneous cell populations. In this study, we show that single-cell isolation biases in microfluidics can be circumvented by increasing the viscosity of fluids in which cells are dispersed. At a viscosity of 40-50 cP (cP), the cell sedimentation is effectively reduced, resulting in a steady cell flow inside the microfluidics chip and consistent encapsulation in water-in-oil droplets over extended periods of time. This approach allows nearly all cells in a sample to be isolated with the same efficiency, irrespective of their type. Our results show that increased fluid viscosity, rather than cell-adjusted density, provides a more reliable approach to mitigate single-cell isolation biases.

Single-Cell Transcriptional Profiling Reveals Signatures of Helper, Effector, and Regulatory MAIT Cells during Homeostasis and Activation.

Mucosal-associated invariant T (MAIT) cells are innate-like lymphocytes that recognize microbial vitamin B metabolites and have emerging roles in infectious disease, autoimmunity, and cancer. Although MAIT cells are identified by a semi-invariant TCR, their phenotypic and functional heterogeneity is not well understood. Here we present an integrated single cell transcriptomic analysis of over 76,000 human MAIT cells during early and prolonged Ag-specific activation with the MR1 ligand 5-OP-RU and nonspecific TCR stimulation. We show that MAIT cells span a broad range of homeostatic, effector, helper, tissue-infiltrating, regulatory, and exhausted phenotypes, with distinct gene expression programs associated with CD4+ or CD8+ coexpression. During early activation, MAIT cells rapidly adopt a cytotoxic phenotype characterized by high expression of GZMB, IFNG and TNF In contrast, prolonged stimulation induces heterogeneous states defined by proliferation, cytotoxicity, immune modulation, and exhaustion. We further demonstrate a FOXP3 expressing MAIT cell subset that phenotypically resembles conventional regulatory T cells. Moreover, scRNAseq-defined MAIT cell subpopulations were also detected in individuals recently exposed to Mycobacterium tuberculosis, confirming their presence during human infection. To our knowledge, our study provides the first comprehensive atlas of human MAIT cells in activation conditions and defines substantial functional heterogeneity, suggesting complex roles in health and disease.

Microfluidics for Cancer Biomarker Discovery, Research, and Clinical Application.

Currently, cancer is the leading cause of death and its incidence and mortality is growing rapidly all over the world. One of the confounding factors contributing to the failure of conventional cancer diagnostics and treatment strategies is a high degree of intratumoral and intertumoral heterogeneity at the single-cell and molecular levels. Recent innovations in microfluidic techniques have revolutionized single-cell and single-molecule research and challenged the conventional definition of a "biomarker." Alongside classic cancer biomarkers such as circulating tumor DNA or circulating tumor cells (CTC), tumor cell heterogeneity, transcriptional and epigenetic cell states and their abundance in the tumor microenvironment have been demonstrated to impact disease progression and treatment response. Utilizing high-throughput, robust microfluidic techniques for the detection, isolation, and analysis of various cancer biomarkers, valuable information about the tumor can be obtained for clinical decision-making. This chapter presents clinically relevant advances of cancer biomarker research using microfluidics technology and identifies the emerging applications for disease diagnosis, monitoring, and personalized treatment.

Inhibition of Carbonic Anhydrase IX Suppresses Breast Cancer Cell Motility at the Single-Cell Level.

Protein Carbonic Anhydrase IX (CA IX), which is expressed in various hypoxic solid tumors in order to maintain proper pH, is also related to cancer cell adhesion, invasion, and metastasis processes. Here, we investigated whether CA IX inhibition by a highly CA IX selective agent benzenesulfonamide VD11-4-2 triggers changes in individual cell motility. We seeded breast cancer cells on an extracellular matrix-coated glass-bottomed dish and in a microfluidic device with a gradient flow of epidermal growth factor (EGF), tracked individual cell movement, calculated their migration speeds, and/or followed movement direction. Our results showed that the inhibitor VD11-4-2 decreased the speed of CA IX positive breast cancer cells by 20-26% while not affecting non-cancerous cell migration. The inhibitor suppressed the cell migration velocity increment and hindered cells from reaching their maximum speed. VD11-4-2 also reduced CA IX, expressing cell movement towards the growth factor as a chemoattractant. Such a single cell-based migration assay enabled the comprehensive investigation of the cell motility and revealed that VD11-4-2 shows the ability to suppress breast cancer cell migration at a lower concentration than previously tested CA IX inhibitors.

Microtubule sliding drives proplatelet elongation and is dependent on cytoplasmic dynein.

Bone marrow megakaryocytes produce platelets by extending long cytoplasmic protrusions, designated proplatelets, into sinusoidal blood vessels. Although microtubules are known to regulate platelet production, the underlying mechanism of proplatelet elongation has yet to be resolved. Here we report that proplatelet formation is a process that can be divided into repetitive phases (extension, pause, and retraction), as revealed by differential interference contrast and fluorescence loss after photoconversion time-lapse microscopy. Furthermore, we show that microtubule sliding drives proplatelet elongation and is dependent on cytoplasmic dynein under static and physiological shear stress by using fluorescence recovery after photobleaching in proplatelets with fluorescence-tagged ß1-tubulin. A refined understanding of the specific mechanisms regulating platelet production will yield strategies to treat patients with thrombocythemia or thrombocytopenia.

Platelet bioreactor-on-a-chip.

Platelet transfusions total >2.17 million apheresis-equivalent units per year in the United States and are derived entirely from human donors, despite clinically significant immunogenicity, associated risk of sepsis, and inventory shortages due to high demand and 5-day shelf life. To take advantage of known physiological drivers of thrombopoiesis, we have developed a microfluidic human platelet bioreactor that recapitulates bone marrow stiffness, extracellular matrix composition,micro-channel size, hemodynamic vascular shear stress, and endothelial cell contacts, and it supports high-resolution live-cell microscopy and quantification of platelet production. Physiological shear stresses triggered proplatelet initiation, reproduced ex vivo bone marrow proplatelet production, and generated functional platelets. Modeling human bone marrow composition and hemodynamics in vitro obviates risks associated with platelet procurement and storage to help meet growing transfusion needs.

DNA Nanoparticles for Improved Protein Synthesis In Vitro.

The amplification and digital quantification of single DNA molecules are important in biomedicine and diagnostics. Beyond quantifying DNA molecules in a sample, the ability to express proteins from the amplified DNA would open even broader applications in synthetic biology, directed evolution, and proteomics. Herein, a microfluidic approach is reported for the production of condensed DNA nanoparticles that can serve as efficient templates for in vitro protein synthesis. Using phi29 DNA polymerase and a multiple displacement amplification reaction, single DNA molecules were converted into DNA nanoparticles containing up to about 10(4)  clonal gene copies of the starting template. DNA nanoparticle formation was triggered by accumulation of inorganic pyrophosphate (produced during DNA synthesis) and magnesium ions from the buffer. Transcription-translation reactions performed in vitro showed that individual DNA nanoparticles can serve as efficient templates for protein synthesis in vitro.

Single-cell transcriptional profiling of clear cell renal cell carcinoma reveals a tumor-associated endothelial tip cell phenotype.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent form of renal cancer, accounting for over 75% of cases. The asymptomatic nature of the disease contributes to late-stage diagnoses and poor survival. Highly vascularized and immune infiltrated microenvironment are prominent features of ccRCC, yet the interplay between vasculature and immune cells, disease progression and response to therapy remains poorly understood. Using droplet-based single-cell RNA sequencing we profile 50,236 transcriptomes from paired tumor and healthy adjacent kidney tissues. Our analysis reveals significant heterogeneity and inter-patient variability of the tumor microenvironment. Notably, we discover a previously uncharacterized vasculature subpopulation associated with epithelial-mesenchymal transition. The cell-cell communication analysis reveals multiple modes of immunosuppressive interactions within the tumor microenvironment, including clinically relevant interactions between tumor vasculature and stromal cells with immune cells. The upregulation of the genes involved in these interactions is associated with worse survival in the TCGA KIRC cohort. Our findings demonstrate the role of tumor vasculature and stromal cell populations in shaping the ccRCC microenvironment and uncover a subpopulation of cells within the tumor vasculature that is associated with an angiogenic phenotype.

Single Cell Analysis of Treatment-Resistant Prostate Cancer: Implications of Cell State Changes for Cell Surface Antigen Targeted Therapies.

Targeting cell surface molecules using radioligand and antibody-based therapies has yielded considerable success across cancers. However, it remains unclear how the expression of putative lineage markers, particularly cell surface molecules, varies in the process of lineage plasticity, wherein tumor cells alter their identity and acquire new oncogenic properties. A notable example of lineage plasticity is the transformation of prostate adenocarcinoma (PRAD) to neuroendocrine prostate cancer (NEPC)--a growing resistance mechanism that results in the loss of responsiveness to androgen blockade and portends dismal patient survival. To understand how lineage markers vary across the evolution of lineage plasticity in prostate cancer, we applied single cell analyses to 21 human prostate tumor biopsies and two genetically engineered mouse models, together with tissue microarray analysis (TMA) on 131 tumor samples. Not only did we observe a higher degree of phenotypic heterogeneity in castrate-resistant PRAD and NEPC than previously anticipated, but also found that the expression of molecules targeted therapeutically, namely PSMA, STEAP1, STEAP2, TROP2, CEACAM5, and DLL3, varied within a subset of gene-regulatory networks (GRNs). We also noted that NEPC and small cell lung cancer (SCLC) subtypes shared a set of GRNs, indicative of conserved biologic pathways that may be exploited therapeutically across tumor types. While this extreme level of transcriptional heterogeneity, particularly in cell surface marker expression, may mitigate the durability of clinical responses to novel antigen-directed therapies, its delineation may yield signatures for patient selection in clinical trials, potentially across distinct cancer types.

Deep generative model deciphers derailed trajectories in acute myeloid leukemia.

Single-cell genomics has the potential to map cell states and their dynamics in an unbiased way in response to perturbations like disease. However, elucidating the cell-state transitions from healthy to disease requires analyzing data from perturbed samples jointly with unperturbed reference samples. Existing methods for integrating and jointly visualizing single-cell datasets from distinct contexts tend to remove key biological differences or do not correctly harmonize shared mechanisms. We present Decipher, a model that combines variational autoencoders with deep exponential families to reconstruct derailed trajectories (https://github.com/azizilab/decipher). Decipher jointly represents normal and perturbed single-cell RNA-seq datasets, revealing shared and disrupted dynamics. It further introduces a novel approach to visualize data, without the need for methods such as UMAP or TSNE. We demonstrate Decipher on data from acute myeloid leukemia patient bone marrow specimens, showing that it successfully characterizes the divergence from normal hematopoiesis and identifies transcriptional programs that become disrupted in each patient when they acquire NPM1 driver mutations.