Defining the transcriptional dynamics of a temporal process such as cell differentiation is challenging owing to the high variability in gene expression between individual cells. Time-series gene ...expression analyses of bulk cells have difficulty distinguishing early and late phases of a transcriptional cascade or identifying rare subpopulations of cells, and single-cell proteomic methods rely on a priori knowledge of key distinguishing markers. Here we describe Monocle, an unsupervised algorithm that increases the temporal resolution of transcriptome dynamics using single-cell RNA-Seq data collected at multiple time points. Applied to the differentiation of primary human myoblasts, Monocle revealed switch-like changes in expression of key regulatory factors, sequential waves of gene regulation, and expression of regulators that were not known to act in differentiation. We validated some of these predicted regulators in a loss-of function screen. Monocle can in principle be used to recover single-cell gene expression kinetics from a wide array of cellular processes, including differentiation, proliferation and oncogenic transformation.
Intratumoral heterogeneity plays a critical role in tumor evolution. To define the contribution of DNA methylation to heterogeneity within tumors, we performed genome-scale bisulfite sequencing of ...104 primary chronic lymphocytic leukemias (CLLs). Compared with 26 normal B cell samples, CLLs consistently displayed higher intrasample variability of DNA methylation patterns across the genome, which appears to arise from stochastically disordered methylation in malignant cells. Transcriptome analysis of bulk and single CLL cells revealed that methylation disorder was linked to low-level expression. Disordered methylation was further associated with adverse clinical outcome. We therefore propose that disordered methylation plays a similar role to that of genetic instability, enhancing the ability of cancer cells to search for superior evolutionary trajectories.
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•CLL harbors higher intrasample methylation variability compared with normal B cells•Higher intrasample variability arises from stochastically disordered methylation•Methylation disorder is associated with transcriptional variation•Methylation disorder affects genetic evolution and clinical outcome
Landau et al. perform bisulfite sequencing of primary chronic lymphocytic leukemias and find high levels of intrasample variability in DNA methylation patterns. Their findings suggest that disordered methylation plays a role similar to that of genetic instability in conferring adaptive advantage to cancer cells.
Single-cell transcriptomics requires a method that is sensitive, accurate, and reproducible. Here, we present CEL-Seq2, a modified version of our CEL-Seq method, with threefold higher sensitivity, ...lower costs, and less hands-on time. We implemented CEL-Seq2 on Fluidigm's C1 system, providing its first single-cell, on-chip barcoding method, and we detected gene expression changes accompanying the progression through the cell cycle in mouse fibroblast cells. We also compare with Smart-Seq to demonstrate CEL-Seq2's increased sensitivity relative to other available methods. Collectively, the improvements make CEL-Seq2 uniquely suited to single-cell RNA-Seq analysis in terms of economics, resolution, and ease of use.
Advances in molecular biology, microfluidics and bioinformatics have empowered the study of thousands or even millions of individual cells from malignant tumours at the single-cell level of ...resolution. This high-dimensional, multi-faceted characterization of the genomic, transcriptomic, epigenomic and proteomic features of the tumour and/or the associated immune and stromal cells enables the dissection of tumour heterogeneity, the complex interactions between tumour cells and their microenvironment, and the details of the evolutionary trajectory of each tumour. Single-cell transcriptomics, the ability to track individual T cell clones through paired sequencing of the T cell receptor genes and high-dimensional single-cell spatial analysis are all areas of particular relevance to immuno-oncology. Multidimensional biomarker signatures will increasingly be crucial to guiding clinical decision-making in each patient with cancer. High-dimensional single-cell technologies are likely to provide the resolution and richness of data required to generate such clinically relevant signatures in immuno-oncology. In this Perspective, we describe advances made using transformative single-cell analysis technologies, especially in relation to clinical response and resistance to immunotherapy, and discuss the growing utility of single-cell approaches for answering important research questions.
Interactions between T cell receptors (TCRs) and their cognate tumour antigens are central to antitumour immune responses
; 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.
The tumor immune microenvironment plays a critical role in cancer progression and response to immunotherapy in clear cell renal cell carcinoma (ccRCC), yet the composition and phenotypic states of ...immune cells in this tumor are incompletely characterized. We performed single-cell RNA and T cell receptor sequencing on 164,722 individual cells from tumor and adjacent non-tumor tissue in patients with ccRCC across disease stages: early, locally advanced, and advanced/metastatic. Terminally exhausted CD8+ T cells were enriched in metastatic disease and were restricted in T cell receptor diversity. Within the myeloid compartment, pro-inflammatory macrophages were decreased, and suppressive M2-like macrophages were increased in advanced disease. Terminally exhausted CD8+ T cells and M2-like macrophages co-occurred in advanced disease and expressed ligands and receptors that support T cell dysfunction and M2-like polarization. This immune dysfunction circuit is associated with a worse prognosis in external cohorts and identifies potentially targetable immune inhibitory pathways in ccRCC.
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•scRNA-seq defines the infiltrating immune populations in ccRCC across disease stages•Terminally exhausted CD8+ T cells and M2-like TAMs are enriched in advanced ccRCC•Exhausted CD8+ T cells and TAMs interact to form an immune dysfunction circuit•Signature of terminal exhaustion/TAM interaction is associated with worse prognosis
The immune cell changes that occur with advancing disease stage in renal cell carcinoma are incompletely characterized. Braun et al. show that terminally exhausted CD8+ T cells and M2-like tumor-associated macrophages are enriched in advanced disease and interact to form an immune dysfunction circuit that is associated with poorer prognosis.
Chimeric antigen receptor (CAR)-T cell therapy has revolutionized the treatment of hematologic malignancies. Approximately half of patients with refractory large B cell lymphomas achieve durable ...responses from CD19-targeting CAR-T treatment; however, failure mechanisms are identified in only a fraction of cases. To gain new insights into the basis of clinical response, we performed single-cell transcriptome sequencing of 105 pretreatment and post-treatment peripheral blood mononuclear cell samples, and infusion products collected from 32 individuals with large B cell lymphoma treated with either of two CD19 CAR-T products: axicabtagene ciloleucel (axi-cel) or tisagenlecleucel (tisa-cel). Expansion of proliferative memory-like CD8 clones was a hallmark of tisa-cel response, whereas axi-cel responders displayed more heterogeneous populations. Elevations in CAR-T regulatory cells among nonresponders to axi-cel were detected, and these populations were capable of suppressing conventional CAR-T cell expansion and driving late relapses in an in vivo model. Our analyses reveal the temporal dynamics of effective responses to CAR-T therapy, the distinct molecular phenotypes of CAR-T cells with differing designs, and the capacity for even small increases in CAR-T regulatory cells to drive relapse.
Single cell RNA sequencing methods have been increasingly used to understand cellular heterogeneity. Nevertheless, most of these methods suffer from one or more limitations, such as focusing only on ...polyadenylated RNA, sequencing of only the 3' end of the transcript, an exuberant fraction of reads mapping to ribosomal RNA, and the unstranded nature of the sequencing data. Here, we developed a novel single cell strand-specific total RNA library preparation method addressing all the aforementioned shortcomings. Our method was validated on a microfluidics system using three different cancer cell lines undergoing a chemical or genetic perturbation and on two other cancer cell lines sorted in microplates. We demonstrate that our total RNA-seq method detects an equal or higher number of genes compared to classic polyA+ RNA-seq, including novel and non-polyadenylated genes. The obtained RNA expression patterns also recapitulate the expected biological signal. Inherent to total RNA-seq, our method is also able to detect circular RNAs. Taken together, SMARTer single cell total RNA sequencing is very well suited for any single cell sequencing experiment in which transcript level information is needed beyond polyadenylated genes.
Within the tumour microenvironment, CD4
T cells can promote or suppress antitumour responses through the recognition of antigens presented by human leukocyte antigen (HLA) class II molecules
, but ...how cancers co-opt these physiologic processes to achieve immune evasion remains incompletely understood. Here we performed in-depth analysis of the phenotype and tumour specificity of CD4
T cells infiltrating human melanoma specimens, finding that exhausted cytotoxic CD4
T cells could be directly induced by melanoma cells through recognition of HLA class II-restricted neoantigens, and also HLA class I-restricted tumour-associated antigens. CD4
T regulatory (T
) cells could be indirectly elicited through presentation of tumour antigens via antigen-presenting cells. Notably, numerous tumour-reactive CD4
T
clones were stimulated directly by HLA class II-positive melanoma and demonstrated specificity for melanoma neoantigens. This phenomenon was observed in the presence of an extremely high tumour neoantigen load, which we confirmed to be associated with HLA class II positivity through the analysis of 116 melanoma specimens. Our data reveal the landscape of infiltrating CD4
T cells in melanoma and point to the presentation of HLA class II-restricted neoantigens and direct engagement of immunosuppressive CD4
T
cells as a mechanism of immune evasion that is favoured in HLA class II-positive melanoma.
Gene expression in multiple individual cells from a tissue or culture sample varies according to cell-cycle, genetic, epigenetic and stochastic differences between the cells. However, single-cell ...differences have been largely neglected in the analysis of the functional consequences of genetic variation. Here we measure the expression of 92 genes affected by Wnt signaling in 1,440 single cells from 15 individuals to associate single-nucleotide polymorphisms (SNPs) with gene-expression phenotypes, while accounting for stochastic and cell-cycle differences between cells. We provide evidence that many heritable variations in gene function--such as burst size, burst frequency, cell cycle-specific expression and expression correlation/noise between cells--are masked when expression is averaged over many cells. Our results demonstrate how single-cell analyses provide insights into the mechanistic and network effects of genetic variability, with improved statistical power to model these effects on gene expression.
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