RESUMO
Melanoma brain metastasis (MBM) frequently occurs in patients with advanced melanoma; yet, our understanding of the underlying salient biology is rudimentary. Here, we performed single-cell/nucleus RNA-seq in 22 treatment-naive MBMs and 10 extracranial melanoma metastases (ECMs) and matched spatial single-cell transcriptomics and T cell receptor (TCR)-seq. Cancer cells from MBM were more chromosomally unstable, adopted a neuronal-like cell state, and enriched for spatially variably expressed metabolic pathways. Key observations were validated in independent patient cohorts, patient-derived MBM/ECM xenograft models, RNA/ATAC-seq, proteomics, and multiplexed imaging. Integrated spatial analyses revealed distinct geography of putative cancer immune evasion and evidence for more abundant intra-tumoral B to plasma cell differentiation in lymphoid aggregates in MBM. MBM harbored larger fractions of monocyte-derived macrophages and dysfunctional TOX+CD8+ T cells with distinct expression of immune checkpoints. This work provides comprehensive insights into MBM biology and serves as a foundational resource for further discovery and therapeutic exploration.
Assuntos
Neoplasias Encefálicas , Melanoma , Neoplasias Encefálicas/tratamento farmacológico , Neoplasias Encefálicas/secundário , Linfócitos T CD8-Positivos/patologia , Ecossistema , Humanos , RNA-SeqRESUMO
To date, no immunotherapy approaches have managed to fully overcome T-cell exhaustion, which remains a mandatory fate for chronically activated effector cells and a major therapeutic challenge. Understanding how to reprogram CD8+ tumor-infiltrating lymphocytes away from exhausted effector states remains an elusive goal. Our work provides evidence that orthogonal gene engineering of T cells to secrete an interleukin (IL)-2 variant binding the IL-2Rßγ receptor and the alarmin IL-33 reprogrammed adoptively transferred T cells to acquire a novel, synthetic effector state, which deviated from canonical exhaustion and displayed superior effector functions. These cells successfully overcame homeostatic barriers in the host and led-in the absence of lymphodepletion or exogenous cytokine support-to high levels of engraftment and tumor regression. Our work unlocks a new opportunity of rationally engineering synthetic CD8+ T-cell states endowed with the ability to avoid exhaustion and control advanced solid tumors.
Assuntos
Linfócitos T CD8-Positivos , Imunoterapia Adotiva , Interleucina-2 , Neoplasias Experimentais , Linfócitos T CD8-Positivos/imunologia , Exaustão das Células T , Linfócitos do Interstício Tumoral/imunologia , Interleucina-2/farmacologia , Interleucina-33 , Engenharia de Proteínas , Feminino , Animais , Camundongos , Camundongos Endogâmicos C57BL , Linhagem Celular Tumoral , Neoplasias Experimentais/terapia , Receptor de Morte Celular Programada 1/metabolismoRESUMO
Persistent exposure to antigen during chronic infection or cancer renders T cells dysfunctional. The molecular mechanisms regulating this state of exhaustion are thought to be common in infection and cancer, despite obvious differences in their microenvironments. Here we found that NFAT5, an NFAT family transcription factor that lacks an AP-1 docking site, was highly expressed in exhausted CD8+ T cells in the context of chronic infections and tumors but was selectively required in tumor-induced CD8+ T cell exhaustion. Overexpression of NFAT5 in CD8+ T cells reduced tumor control, while deletion of NFAT5 improved tumor control by promoting the accumulation of tumor-specific CD8+ T cells that had reduced expression of the exhaustion-associated proteins TOX and PD-1 and produced more cytokines, such as IFNÉ£ and TNF, than cells with wild-type levels of NFAT5, specifically in the precursor exhausted PD-1+TCF1+TIM-3-CD8+ T cell population. NFAT5 did not promote T cell exhaustion during chronic infection with clone 13 of lymphocytic choriomeningitis virus. Expression of NFAT5 was induced by TCR triggering, but its transcriptional activity was specific to the tumor microenvironment and required hyperosmolarity. Thus, NFAT5 promoted the exhaustion of CD8+ T cells in a tumor-selective fashion.
Assuntos
Coriomeningite Linfocítica , Neoplasias , Humanos , Fatores de Transcrição/metabolismo , Linfócitos T CD8-Positivos , Exaustão das Células T , Infecção Persistente , Microambiente Tumoral , Receptor de Morte Celular Programada 1/genética , Receptor de Morte Celular Programada 1/metabolismo , Vírus da Coriomeningite Linfocítica , Neoplasias/metabolismoRESUMO
Checkpoint blockade mediates a proliferative response of tumor-infiltrating CD8+ T lymphocytes (TILs). The origin of this response has remained elusive because chronic activation promotes terminal differentiation or exhaustion of tumor-specific T cells. Here we identified a subset of tumor-reactive TILs bearing hallmarks of exhausted cells and central memory cells, including expression of the checkpoint protein PD-1 and the transcription factor Tcf1. Tcf1+PD-1+ TILs mediated the proliferative response to immunotherapy, generating both Tcf1+PD-1+ and differentiated Tcf1-PD-1+ cells. Ablation of Tcf1+PD-1+ TILs restricted responses to immunotherapy. Tcf1 was not required for the generation of Tcf1+PD-1+ TILs but was essential for the stem-like functions of these cells. Human TCF1+PD-1+ cells were detected among tumor-reactive CD8+ T cells in the blood of melanoma patients and among TILs of primary melanomas. Thus, immune checkpoint blockade relies not on reversal of T cell exhaustion programs, but on the proliferation of a stem-like TIL subset.
Assuntos
Anticorpos Monoclonais/uso terapêutico , Linfócitos T CD8-Positivos/imunologia , Fator 1-alfa Nuclear de Hepatócito/metabolismo , Linfócitos do Interstício Tumoral/imunologia , Melanoma/terapia , Receptor de Morte Celular Programada 1/antagonistas & inibidores , Células-Tronco/imunologia , Subpopulações de Linfócitos T/imunologia , Animais , Linfócitos T CD8-Positivos/efeitos dos fármacos , Diferenciação Celular , Proliferação de Células , Receptor Celular 2 do Vírus da Hepatite A/antagonistas & inibidores , Fator 1-alfa Nuclear de Hepatócito/genética , Humanos , Imunoterapia , Linfócitos do Interstício Tumoral/efeitos dos fármacos , Melanoma/imunologia , Melanoma Experimental , Camundongos , Camundongos Endogâmicos C57BLRESUMO
Single-cell transcriptomics allows the study of immune cell heterogeneity at an unprecedented level of resolution. The Swiss portal for immune cell analysis (SPICA) is a web resource dedicated to the exploration and analysis of single-cell RNA-seq data of immune cells. In contrast to other single-cell databases, SPICA hosts curated, cell type-specific reference atlases that describe immune cell states at high resolution, and published single-cell datasets analysed in the context of these atlases. Additionally, users can privately analyse their own data in the context of existing atlases and contribute to the SPICA database. SPICA is available at https://spica.unil.ch.
Assuntos
Bases de Dados Genéticas , Transcriptoma/genética , Regulação da Expressão Gênica/genética , Humanos , RNA-Seq/métodos , Análise de Célula Única/métodos , Transcriptoma/imunologiaRESUMO
SUMMARY: A common bioinformatics task in single-cell data analysis is to purify a cell type or cell population of interest from heterogeneous datasets. Here, we present scGate, an algorithm that automatizes marker-based purification of specific cell populations, without requiring training data or reference gene expression profiles. scGate purifies a cell population of interest using a set of markers organized in a hierarchical structure, akin to gating strategies employed in flow cytometry. scGate outperforms state-of-the-art single-cell classifiers and it can be applied to multiple modalities of single-cell data (e.g. RNA-seq, ATAC-seq, CITE-seq). scGate is implemented as an R package and integrated with the Seurat framework, providing an intuitive tool to isolate cell populations of interest from heterogeneous single-cell datasets. AVAILABILITY AND IMPLEMENTATION: scGate is available as an R package at https://github.com/carmonalab/scGate (https://doi.org/10.5281/zenodo.6202614). Several reproducible workflows describing the main functions and usage of the package on different single-cell modalities, as well as the code to reproduce the benchmark, can be found at https://github.com/carmonalab/scGate.demo (https://doi.org/10.5281/zenodo.6202585) and https://github.com/carmonalab/scGate.benchmark. Test data are available at https://doi.org/10.6084/m9.figshare.16826071. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Assuntos
Análise de Célula Única , Software , RNA-Seq , Sequenciamento de Cromatina por Imunoprecipitação , Sequenciamento do ExomaRESUMO
Adenosine-to-inosine conversion at position 34 (A34-to-I) of certain tRNAs is essential for expanding their decoding capacity. This reaction is catalyzed by the adenosine deaminase acting on tRNA (ADAT) complex, which in Eukarya is formed by two subunits: ADAT2 and ADAT3. We herein identified and thoroughly characterized the ADAT molecules from the protozoan pathogen Trypanosoma cruzi, the causative agent of Chagas Disease. TcADAT2 and TcADAT3 spontaneously form a catalytically active complex, as shown by expression in engineered bacteria and/or by the increased ex vivo tRNA A-to-I deamination activity of T. cruzi epimastigotes overexpressing TcADAT subunits. Importantly, enhanced TcADAT2/3 activity in transgenic parasites caused a shift in their in vivo tRNAThrAGU signature, which correlated with significant changes in the expression of the Thr-rich TcSMUG proteins. To our knowledge, this is the first evidence indicating that T. cruzi tRNA editing can be modulated in vivo, in turn post-transcriptionally changing the expression of specific genes. Our findings suggest tRNA editing/availability as a forcible step in controlling gene expression and driving codon adaptation in T. cruzi. Moreover, we unveil certain differences between parasite and mammalian host tRNA editing and processing, such as cytosine-to-uridine conversion at position 32 of tRNAThrAGU in T. cruzi, that may be exploited for the identification of novel druggable targets of intervention.
Assuntos
Doença de Chagas , Trypanosoma cruzi , Animais , Doença de Chagas/genética , Expressão Gênica , Mamíferos , Mucinas , Processamento Pós-Transcricional do RNA , Trypanosoma cruzi/genéticaRESUMO
BACKGROUND: Single-cell RNA sequencing (scRNA-seq) technologies offer unique opportunities for exploring heterogeneous cell populations. However, in-depth single-cell transcriptomic characterization of complex tissues often requires profiling tens to hundreds of thousands of cells. Such large numbers of cells represent an important hurdle for downstream analyses, interpretation and visualization. RESULTS: We develop a framework called SuperCell to merge highly similar cells into metacells and perform standard scRNA-seq data analyses at the metacell level. Our systematic benchmarking demonstrates that metacells not only preserve but often improve the results of downstream analyses including visualization, clustering, differential expression, cell type annotation, gene correlation, imputation, RNA velocity and data integration. By capitalizing on the redundancy inherent to scRNA-seq data, metacells significantly facilitate and accelerate the construction and interpretation of single-cell atlases, as demonstrated by the integration of 1.46 million cells from COVID-19 patients in less than two hours on a standard desktop. CONCLUSIONS: SuperCell is a framework to build and analyze metacells in a way that efficiently preserves the results of scRNA-seq data analyses while significantly accelerating and facilitating them.
Assuntos
COVID-19 , Transcriptoma , Análise por Conglomerados , Humanos , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodosRESUMO
SUMMARY: STACAS is a computational method for the identification of integration anchors in the Seurat environment, optimized for the integration of single-cell (sc) RNA-seq datasets that share only a subset of cell types. We demonstrate that by (i) correcting batch effects while preserving relevant biological variability across datasets, (ii) filtering aberrant integration anchors with a quantitative distance measure and (iii) constructing optimal guide trees for integration, STACAS can accurately align scRNA-seq datasets composed of only partially overlapping cell populations. AVAILABILITY AND IMPLEMENTATION: Source code and R package available at https://github.com/carmonalab/STACAS; Docker image available at https://hub.docker.com/repository/docker/mandrea1/stacas_demo.
Assuntos
Análise de Célula Única , Software , RNA-Seq , Análise de Sequência de RNA , Sequenciamento do ExomaRESUMO
The immune system of vertebrate species consists of many different cell types that have distinct functional roles and are subject to different evolutionary pressures. Here, we first analyzed conservation of genes specific for all major immune cell types in human and mouse. Our results revealed higher gene turnover and faster evolution of trans-membrane proteins in NK cells compared with other immune cell types, and especially T cells, but similar conservation of nuclear and cytoplasmic protein coding genes. To validate these findings in a distant vertebrate species, we used single-cell RNA sequencing of lck:GFP cells in zebrafish and obtained the first transcriptome of specific immune cell types in a nonmammalian species. Unsupervised clustering and single-cell TCR locus reconstruction identified three cell populations, T cells, a novel type of NK-like cells, and a smaller population of myeloid-like cells. Differential expression analysis uncovered new immune-cell-specific genes, including novel immunoglobulin-like receptors, and neofunctionalization of recently duplicated paralogs. Evolutionary analyses confirmed the higher gene turnover of trans-membrane proteins in NK cells compared with T cells in fish species, suggesting that this is a general property of immune cell types across all vertebrates.
Assuntos
Evolução Molecular , Células Matadoras Naturais/imunologia , Receptores de IgG/genética , Transcriptoma , Proteínas de Peixe-Zebra/genética , Animais , Células Cultivadas , Sequência Conservada , Humanos , Células Matadoras Naturais/citologia , Camundongos , Análise de Célula Única , Peixe-Zebra/genética , Peixe-Zebra/imunologiaRESUMO
Innate lymphoid cells (ILCs) consist of natural killer (NK) cells and non-cytotoxic ILCs that are broadly classified into ILC1, ILC2, and ILC3 subtypes. These cells recently emerged as important early effectors of innate immunity for their roles in tissue homeostasis and inflammation. Over the last few years, ILCs have been extensively studied in mouse and human at the functional and molecular level, including gene expression profiling. However, sorting ILCs with flow cytometry for gene expression analysis is a delicate and time-consuming process. Here we propose and validate a novel framework for studying ILCs at the transcriptomic level using single-cell RNA-Seq data. Our approach combines unsupervised clustering and a new cell type classifier trained on mouse ILC gene expression data. We show that this approach can accurately identify different ILCs, especially ILC2 cells, in human lymphocyte single-cell RNA-Seq data. Our new model relies only on genes conserved across vertebrates, thereby making it in principle applicable in any vertebrate species. Considering the rapid increase in throughput of single-cell RNA-Seq technology, our work provides a computational framework for studying ILC2 cells in single-cell transcriptomic data and may help exploring their conservation in distant vertebrate species.
Assuntos
Sequenciamento de Nucleotídeos em Larga Escala/métodos , Imunidade Inata/genética , Células Matadoras Naturais/metabolismo , Linfócitos/metabolismo , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Animais , Bases de Dados Genéticas , Perfilação da Expressão Gênica , Humanos , Imunidade Inata/imunologia , Células Matadoras Naturais/imunologia , Linfócitos/classificação , Linfócitos/imunologia , CamundongosRESUMO
Complete characterization of antibody specificities associated to natural infections is expected to provide a rich source of serologic biomarkers with potential applications in molecular diagnosis, follow-up of chemotherapeutic treatments, and prioritization of targets for vaccine development. Here, we developed a highly-multiplexed platform based on next-generation high-density peptide microarrays to map these specificities in Chagas Disease, an exemplar of a human infectious disease caused by the protozoan Trypanosoma cruzi. We designed a high-density peptide microarray containing more than 175,000 overlapping 15 mer peptides derived from T. cruzi proteins. Peptides were synthesized in situ on microarray slides, spanning the complete length of 457 parasite proteins with fully overlapped 15 mers (1 residue shift). Screening of these slides with antibodies purified from infected patients and healthy donors demonstrated both a high technical reproducibility as well as epitope mapping consistency when compared with earlier low-throughput technologies. Using a conservative signal threshold to classify positive (reactive) peptides we identified 2,031 disease-specific peptides and 97 novel parasite antigens, effectively doubling the number of known antigens and providing a 10-fold increase in the number of fine mapped antigenic determinants for this disease. Finally, further analysis of the chip data showed that optimizing the amount of sequence overlap of displayed peptides can increase the protein space covered in a single chip by at least â¼ threefold without sacrificing sensitivity. In conclusion, we show the power of high-density peptide chips for the discovery of pathogen-specific linear B-cell epitopes from clinical samples, thus setting the stage for high-throughput biomarker discovery screenings and proteome-wide studies of immune responses against pathogens.
Assuntos
Doença de Chagas/imunologia , Mapeamento de Epitopos/métodos , Epitopos de Linfócito B/imunologia , Ensaios de Triagem em Larga Escala/métodos , Peptídeos/metabolismo , Análise Serial de Proteínas/métodos , Proteômica/métodos , Antígenos de Protozoários/imunologia , Linfócitos B/imunologia , Bases de Dados de Proteínas , Ensaio de Imunoadsorção Enzimática , Humanos , Reprodutibilidade dos TestesRESUMO
BACKGROUND: Chromosome ends are composed of telomeric repeats and subtelomeric regions, which are patchworks of genes interspersed with repeated elements. Although chromosome ends display similar arrangements in different species, their sequences are highly divergent. In addition, these regions display a particular nucleosomal composition and bind specific factors, therefore producing a special kind of heterochromatin. Using data from currently available draft genomes we have characterized these putative Telomeric Associated Sequences in Toxoplasma gondii. RESULTS: An all-vs-all pairwise comparison of T. gondii assembled chromosomes revealed the presence of conserved regions of â¼ 30 Kb located near the ends of 9 of the 14 chromosomes of the genome of the ME49 strain. Sequence similarity among these regions is â¼ 70%, and they are also highly conserved in the GT1 and VEG strains. However, they are unique to Toxoplasma with no detectable similarity in other Apicomplexan parasites. The internal structure of these sequences consists of 3 repetitive regions separated by high-complexity sequences without annotated genes, except for a gene from the Toxoplasma Specific Family. ChIP-qPCR experiments showed that nucleosomes associated to these sequences are enriched in histone H4 monomethylated at K20 (H4K20me1), and the histone variant H2A.X, suggesting that they are silenced sequences (heterochromatin). A detailed characterization of the base composition of these sequences, led us to identify a strong long-range compositional bias, which was similar to that observed in other genomic silenced fragments such as those containing centromeric sequences, and was negatively correlated to gene density. CONCLUSIONS: We identified and characterized a region present in most Toxoplasma assembled chromosomes. Based on their location, sequence features, and nucleosomal markers we propose that these might be part of subtelomeric regions of T. gondii. The identified regions display a unique trinucleotide compositional bias, which is shared (despite the lack of any detectable sequence similarity) with other silenced sequences, such as those making up the chromosome centromeres. We also identified other genomic regions with this compositional bias (but no detectable sequence similarity) that might be functionally similar.
Assuntos
Genoma de Protozoário , Toxoplasma/genética , Sequência de Bases , Cromossomos/genética , DNA de Protozoário/genética , Heterocromatina/genética , Histonas/química , Histonas/genética , Histonas/metabolismo , Metilação , Nucleossomos/genética , Sequências Repetitivas de Ácido NucleicoRESUMO
The TDR Targets Database (http://tdrtargets.org) has been designed and developed as an online resource to facilitate the rapid identification and prioritization of molecular targets for drug development, focusing on pathogens responsible for neglected human diseases. The database integrates pathogen specific genomic information with functional data (e.g. expression, phylogeny, essentiality) for genes collected from various sources, including literature curation. This information can be browsed and queried using an extensive web interface with functionalities for combining, saving, exporting and sharing the query results. Target genes can be ranked and prioritized using numerical weights assigned to the criteria used for querying. In this report we describe recent updates to the TDR Targets database, including the addition of new genomes (specifically helminths), and integration of chemical structure, property and bioactivity information for biological ligands, drugs and inhibitors and cheminformatic tools for querying and visualizing these chemical data. These changes greatly facilitate exploration of linkages (both known and predicted) between genes and small molecules, yielding insight into whether particular proteins may be druggable, effectively allowing the navigation of chemical space in a genomics context.
Assuntos
Bases de Dados Factuais , Descoberta de Drogas , Doenças Negligenciadas/tratamento farmacológico , Genoma Helmíntico , Genômica , Humanos , Doenças Negligenciadas/microbiologia , Doenças Negligenciadas/parasitologia , Preparações Farmacêuticas/química , Proteínas/química , Proteínas/genéticaRESUMO
Batch effects in single-cell RNA-seq data pose a significant challenge for comparative analyses across samples, individuals, and conditions. Although batch effect correction methods are routinely applied, data integration often leads to overcorrection and can result in the loss of biological variability. In this work we present STACAS, a batch correction method for scRNA-seq that leverages prior knowledge on cell types to preserve biological variability upon integration. Through an open-source benchmark, we show that semi-supervised STACAS outperforms state-of-the-art unsupervised methods, as well as supervised methods such as scANVI and scGen. STACAS scales well to large datasets and is robust to incomplete and imprecise input cell type labels, which are commonly encountered in real-life integration tasks. We argue that the incorporation of prior cell type information should be a common practice in single-cell data integration, and we provide a flexible framework for semi-supervised batch effect correction.
Assuntos
Perfilação da Expressão Gênica , Análise de Célula Única , Humanos , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Perfilação da Expressão Gênica/métodosRESUMO
T cells are endowed with T-cell antigen receptors (TCR) that give them the capacity to recognize specific antigens and mount antigen-specific adaptive immune responses. Because TCR sequences are distinct in each naïve T cell, they serve as molecular barcodes to track T cells with clonal relatedness and shared antigen specificity through proliferation, differentiation, and migration. Single-cell RNA sequencing provides coupled information of TCR sequence and transcriptional state in individual cells, enabling T-cell clonotype-specific analyses. In this protocol, we outline a computational workflow to perform T-cell states and clonal analysis from scRNA-seq data based on the R packages Seurat, ProjecTILs, and scRepertoire. Given a scRNA-seq T-cell dataset with TCR sequence information, cell states are automatically annotated by reference projection using the ProjecTILs method. TCR information is used to track individual clonotypes, assess their clonal expansion, proliferation rates, bias towards specific differentiation states, and the clonal overlap between T-cell subtypes. We provide fully reproducible R code to conduct these analyses and generate useful visualizations that can be adapted for the needs of the protocol user. Key features Computational analysis of paired scRNA-seq and scTCR-seq data Characterizing T-cell functional state by reference-based analysis using ProjecTILs Exploring T-cell clonal structure using scRepertoire Linking T-cell clonality to transcriptomic state to study relationships between clonal expansion and functional phenotype Graphical overview.
RESUMO
Strategies to increase intratumoral concentrations of an anticancer agent are desirable to optimize its therapeutic potential when said agent is efficacious primarily within a tumor but also have significant systemic side effects. Here, we generate a bifunctional protein by fusing interleukin-10 (IL-10) to a colony-stimulating factor-1 receptor (CSF-1R)-blocking antibody. The fusion protein demonstrates significant antitumor activity in multiple cancer models, especially head and neck cancer. Moreover, this bifunctional protein not only leads to the anticipated reduction in tumor-associated macrophages but also triggers proliferation, activation, and metabolic reprogramming of CD8+ T cells. Furthermore, it extends the clonotype diversity of tumor-infiltrated T cells and shifts the tumor microenvironment (TME) to an immune-active state. This study suggests an efficient strategy for designing immunotherapeutic agents by fusing a potent immunostimulatory molecule to an antibody targeting TME-enriched factors.
Assuntos
Antineoplásicos , Neoplasias , Humanos , Linfócitos T CD8-Positivos , Interleucina-10/metabolismo , Neoplasias/patologia , Antineoplásicos/farmacologia , Receptores Proteína Tirosina Quinases/metabolismo , Receptores de Fator Estimulador de Colônias/metabolismo , Microambiente TumoralRESUMO
CD4+ T cells are critical orchestrators of immune responses against a large variety of pathogens, including viruses. While multiple CD4+ T cell subtypes and their key transcriptional regulators have been identified, there is a lack of consistent definition for CD4+ T cell transcriptional states. In addition, the progressive changes affecting CD4+ T cell subtypes during and after immune responses remain poorly defined. Using single-cell transcriptomics, we characterized the diversity of CD4+ T cells responding to self-resolving and chronic viral infections in mice. We built a comprehensive map of virus-specific CD4+ T cells and their evolution over time, and identified six major cell states consistently observed in acute and chronic infections. During the course of acute infections, T cell composition progressively changed from effector to memory states, with subtype-specific gene modules and kinetics. Conversely, in persistent infections T cells acquired distinct, chronicity-associated programs. By single-cell T cell receptor (TCR) analysis, we characterized the clonal structure of virus-specific CD4+ T cells across individuals. Virus-specific CD4+ T cell responses were essentially private across individuals and most T cells differentiated into both Tfh and Th1 subtypes irrespective of their TCR. Finally, we showed that our CD4+ T cell map can be used as a reference to accurately interpret cell states in external single-cell datasets across tissues and disease models. Overall, this study describes a previously unappreciated level of adaptation of the transcriptional states of CD4+ T cells responding to viruses and provides a new computational resource for CD4+ T cell analysis.
Assuntos
Linfócitos T , Viroses , Animais , Linfócitos T CD4-Positivos , Camundongos , Receptores de Antígenos de Linfócitos T/genéticaRESUMO
Developing strategies to inflame tumors is critical for increasing response to immunotherapy. Here, we report that low-dose radiotherapy (LDRT) of murine tumors promotes T-cell infiltration and enables responsiveness to combinatorial immunotherapy in an IFN-dependent manner. Treatment efficacy relied upon mobilizing both adaptive and innate immunity and depended on both cytotoxic CD4+ and CD8+ T cells. LDRT elicited predominantly CD4+ cells with features of exhausted effector cytotoxic cells, with a subset expressing NKG2D and exhibiting proliferative capacity, as well as a unique subset of activated dendritic cells expressing the NKG2D ligand RAE1. We translated these findings to a phase I clinical trial administering LDRT, low-dose cyclophosphamide, and immune checkpoint blockade to patients with immune-desert tumors. In responsive patients, the combinatorial treatment triggered T-cell infiltration, predominantly of CD4+ cells with Th1 signatures. Our data support the rational combination of LDRT with immunotherapy for effectively treating low T cell-infiltrated tumors. SIGNIFICANCE: Low-dose radiation reprogrammed the tumor microenvironment of tumors with scarce immune infiltration and together with immunotherapy induced simultaneous mobilization of innate and adaptive immunity, predominantly CD4+ effector T cells, to achieve tumor control dependent on NKG2D. The combination induced important responses in patients with metastatic immune-cold tumors.This article is highlighted in the In This Issue feature, p. 1.
Assuntos
Adenocarcinoma Papilar/radioterapia , Neoplasias Ovarianas/radioterapia , Imunidade Adaptativa , Adenocarcinoma Papilar/imunologia , Animais , Linfócitos T CD4-Positivos , Linfócitos T CD8-Positivos , Modelos Animais de Doenças , Feminino , Humanos , Linfócitos do Interstício Tumoral , Camundongos , Camundongos Endogâmicos C57BL , Neoplasias Ovarianas/imunologia , Dosagem Radioterapêutica , Microambiente TumoralRESUMO
The TcSNP database (http://snps.tcruzi.org) integrates information on genetic variation (polymorphisms and mutations) for different stocks, strains and isolates of Trypanosoma cruzi, the causative agent of Chagas disease. The database incorporates sequences (genes from the T. cruzi reference genome, mRNAs, ESTs and genomic sequences); multiple sequence alignments obtained from these sequences; and single-nucleotide polymorphisms and small indels identified by scanning these multiple sequence alignments. Information in TcSNP can be readily interrogated to arrive at gene sets, or SNP sets of interest based on a number of attributes. Sequence similarity searches using BLAST are also supported. This first release of TcSNP contains nearly 170,000 high-confidence candidate SNPs, derived from the analysis of annotated coding sequences. As new sequence data become available, TcSNP will incorporate these data, mapping new candidate SNPs onto the reference genome sequences.