RESUMO
Antitumoral immunity requires organized, spatially nuanced interactions between components of the immune tumor microenvironment (iTME). Understanding this coordinated behavior in effective versus ineffective tumor control will advance immunotherapies. We re-engineered co-detection by indexing (CODEX) for paraffin-embedded tissue microarrays, enabling simultaneous profiling of 140 tissue regions from 35 advanced-stage colorectal cancer (CRC) patients with 56 protein markers. We identified nine conserved, distinct cellular neighborhoods (CNs)-a collection of components characteristic of the CRC iTME. Enrichment of PD-1+CD4+ T cells only within a granulocyte CN positively correlated with survival in a high-risk patient subset. Coupling of tumor and immune CNs, fragmentation of T cell and macrophage CNs, and disruption of inter-CN communication was associated with inferior outcomes. This study provides a framework for interrogating how complex biological processes, such as antitumoral immunity, occur through concerted actions of cells and spatial domains.
Assuntos
Neoplasias Colorretais/imunologia , Neoplasias Colorretais/terapia , Invasividade Neoplásica/imunologia , Antígeno B7-H1/imunologia , Biomarcadores Tumorais/imunologia , Linfócitos T CD4-Positivos/imunologia , Linhagem Celular Tumoral , Feminino , Humanos , Imunoterapia/métodos , Masculino , Microambiente Tumoral/imunologiaRESUMO
A highly multiplexed cytometric imaging approach, termed co-detection by indexing (CODEX), is used here to create multiplexed datasets of normal and lupus (MRL/lpr) murine spleens. CODEX iteratively visualizes antibody binding events using DNA barcodes, fluorescent dNTP analogs, and an in situ polymerization-based indexing procedure. An algorithmic pipeline for single-cell antigen quantification in tightly packed tissues was developed and used to overlay well-known morphological features with de novo characterization of lymphoid tissue architecture at a single-cell and cellular neighborhood levels. We observed an unexpected, profound impact of the cellular neighborhood on the expression of protein receptors on immune cells. By comparing normal murine spleen to spleens from animals with systemic autoimmune disease (MRL/lpr), extensive and previously uncharacterized splenic cell-interaction dynamics in the healthy versus diseased state was observed. The fidelity of multiplexed spatial cytometry demonstrated here allows for quantitative systemic characterization of tissue architecture in normal and clinically aberrant samples.
Assuntos
Anticorpos/química , Modelos Animais de Doenças , Processamento de Imagem Assistida por Computador/métodos , Lúpus Eritematoso Sistêmico/patologia , Sondas de Oligonucleotídeos/química , Baço/patologia , Animais , Feminino , Masculino , Espectrometria de Massas , Camundongos , Camundongos Endogâmicos MRL lprRESUMO
BACKGROUND: Algorithmic cellular segmentation is an essential step for the quantitative analysis of highly multiplexed tissue images. Current segmentation pipelines often require manual dataset annotation and additional training, significant parameter tuning, or a sophisticated understanding of programming to adapt the software to the researcher's need. Here, we present CellSeg, an open-source, pre-trained nucleus segmentation and signal quantification software based on the Mask region-convolutional neural network (R-CNN) architecture. CellSeg is accessible to users with a wide range of programming skills. RESULTS: CellSeg performs at the level of top segmentation algorithms in the 2018 Kaggle Data Challenge both qualitatively and quantitatively and generalizes well to a diverse set of multiplexed imaged cancer tissues compared to established state-of-the-art segmentation algorithms. Automated segmentation post-processing steps in the CellSeg pipeline improve the resolution of immune cell populations for downstream single-cell analysis. Finally, an application of CellSeg to a highly multiplexed colorectal cancer dataset acquired on the CO-Detection by indEXing (CODEX) platform demonstrates that CellSeg can be integrated into a multiplexed tissue imaging pipeline and lead to accurate identification of validated cell populations. CONCLUSION: CellSeg is a robust cell segmentation software for analyzing highly multiplexed tissue images, accessible to biology researchers of any programming skill level.
Assuntos
Processamento de Imagem Assistida por Computador , Redes Neurais de Computação , Algoritmos , Fluorescência , SoftwareRESUMO
Multiparameter tissue imaging enables analysis of cell-cell interactions in situ, the cellular basis for tissue structure, and novel cell types that are spatially restricted, giving clues to biological mechanisms behind tissue homeostasis and disease. Here, we streamlined and simplified the multiplexed imaging method CO-Detection by indEXing (CODEX) by validating 58 unique oligonucleotide barcodes that can be conjugated to antibodies. We showed that barcoded antibodies retained their specificity for staining cognate targets in human tissue. Antibodies were visualized one at a time by adding a fluorescently labeled oligonucleotide complementary to oligonucleotide barcode, imaging, stripping, and repeating this cycle. With this we developed a panel of 46 antibodies that was used to stain five human lymphoid tissues: three tonsils, a spleen, and a LN. To analyze the data produced, an image processing and analysis pipeline was developed that enabled single-cell analysis on the data, including unsupervised clustering, that revealed 31 cell types across all tissues. We compared cell-type compositions within and directly surrounding follicles from the different lymphoid organs and evaluated cell-cell density correlations. This sequential oligonucleotide exchange technique enables a facile imaging of tissues that leverages pre-existing imaging infrastructure to decrease the barriers to broad use of multiplexed imaging.
Assuntos
Anticorpos , Histocitoquímica/métodos , Imagem Molecular/métodos , Oligonucleotídeos , Comunicação Celular , Contagem de Células , Humanos , Hibridização In Situ/métodos , Tecido Linfoide , Especificidade de Órgãos , Reprodutibilidade dos Testes , Sensibilidade e Especificidade , Análise de Célula Única/métodosRESUMO
Although literature suggests that resistance to TNF inhibitor (TNFi) therapy in patients with ulcerative colitis (UC) is partially linked to immune cell populations in the inflamed region, there is still substantial uncertainty underlying the relevant spatial context. Here, we used the highly multiplexed immunofluorescence imaging technology CODEX to create a publicly browsable tissue atlas of inflammation in 42 tissue regions from 29 patients with UC and 5 healthy individuals. We analyzed 52 biomarkers on 1,710,973 spatially resolved single cells to determine cell types, cell-cell contacts, and cellular neighborhoods. We observed that cellular functional states are associated with cellular neighborhoods. We further observed that a subset of inflammatory cell types and cellular neighborhoods are present in patients with UC with TNFi treatment, potentially indicating resistant niches. Last, we explored applying convolutional neural networks (CNNs) to our dataset with respect to patient clinical variables. We note concerns and offer guidelines for reporting CNN-based predictions in similar datasets.
Assuntos
Colite Ulcerativa , Humanos , Colite Ulcerativa/tratamento farmacológico , Colite Ulcerativa/complicações , Inibidores do Fator de Necrose Tumoral/uso terapêutico , Inflamação/complicações , BiomarcadoresRESUMO
A schematic of a biological system, i.e., a representation of its pieces, how they are combined, and what they do, would facilitate understanding its essential organization and alteration in pathogenesis or evolution. We present a computational approach for constructing tissue schematics (TSs) from high-parameter imaging data and a biological model for interpreting them. TSs map the spatial assembly of cellular neighborhoods into tissue motifs, whose modular composition, we propose, enables the generation of complex outputs. We developed our approach in human lymphoid tissue (HLT), identifying the follicular outer zone as a potential relay between neighboring zones and a core lymphoid assembly with modifications characteristic of each HLT type. Applying the TS approach to the tumor microenvironment in human colorectal cancer identified a higher-order motif, whose mutated assembly was negatively associated with patient survival. TSs may therefore elucidate how immune architectures can be specialized and become vulnerable to reprogramming by tumors.
Assuntos
Neoplasias , Microambiente Tumoral , Humanos , Modelos Biológicos , Neoplasias/patologiaRESUMO
Disease progression and relapse of chronic myeloid leukemia (CML) are caused by therapy resistant leukemia stem cells (LSCs), and cure relies on their eradication. The microenvironment in the bone marrow (BM) is known to contribute to LSC maintenance and resistance. Although leukemic infiltration of the spleen is a hallmark of CML, it is unknown whether spleen cells form a niche that maintains LSCs. Here, we demonstrate that LSCs preferentially accumulate in the spleen and contribute to disease progression. Spleen LSCs were located in the red pulp close to red pulp macrophages (RPM) in CML patients and in a murine CML model. Pharmacologic and genetic depletion of RPM reduced LSCs and decreased their cell cycling activity in the spleen. Gene expression analysis revealed enriched stemness and decreased myeloid lineage differentiation in spleen leukemic stem and progenitor cells (LSPCs). These results demonstrate that splenic RPM form a niche that maintains CML LSCs in a quiescent state, resulting in disease progression and resistance to therapy.
Assuntos
Leucemia Mielogênica Crônica BCR-ABL Positiva , Leucemia Mieloide , Humanos , Camundongos , Animais , Baço , Células-Tronco Neoplásicas/metabolismo , Leucemia Mielogênica Crônica BCR-ABL Positiva/tratamento farmacológico , Leucemia Mieloide/genética , Macrófagos/metabolismo , Progressão da Doença , Microambiente TumoralRESUMO
A patient-tailored, ex vivo drug response platform for glioblastoma (GBM) would facilitate therapy planning, provide insights into treatment-induced mechanisms in the immune tumor microenvironment (iTME), and enable the discovery of biomarkers of response. We cultured regionally annotated GBM explants in perfusion bioreactors to assess iTME responses to immunotherapy. Explants were treated with anti-CD47, anti-PD-1, or their combination, and analyzed by multiplexed microscopy [CO-Detection by indEXing (CODEX)], enabling the spatially resolved identification of >850,000 single cells, accompanied by explant secretome interrogation. Center and periphery explants differed in their cell type and soluble factor composition, and responses to immunotherapy. A subset of explants displayed increased interferon-γ levels, which correlated with shifts in immune cell composition within specified tissue compartments. Our study demonstrates that ex vivo immunotherapy of GBM explants enables an active antitumoral immune response within the tumor center and provides a framework for multidimensional personalized assessment of tumor response to immunotherapy.
RESUMO
Simultaneous visualization of the relationship between multiple biomolecules and their ligands or small molecules at the nanometer scale in cells will enable greater understanding of how biological processes operate. We present here high-definition multiplex ion beam imaging (HD-MIBI), a secondary ion mass spectrometry approach capable of high-parameter imaging in 3D of targeted biological entities and exogenously added structurally-unmodified small molecules. With this technology, the atomic constituents of the biomolecules themselves can be used in our system as the "tag" and we demonstrate measurements down to ~30 nm lateral resolution. We correlated the subcellular localization of the chemotherapy drug cisplatin simultaneously with five subnuclear structures. Cisplatin was preferentially enriched in nuclear speckles and excluded from closed-chromatin regions, indicative of a role for cisplatin in active regions of chromatin. Unexpectedly, cells surviving multi-drug treatment with cisplatin and the BET inhibitor JQ1 demonstrated near total cisplatin exclusion from the nucleus, suggesting that selective subcellular drug relocalization may modulate resistance to this important chemotherapeutic treatment. Multiplexed high-resolution imaging techniques, such as HD-MIBI, will enable studies of biomolecules and drug distributions in biologically relevant subcellular microenvironments by visualizing the processes themselves in concert, rather than inferring mechanism through surrogate analyses.
Assuntos
Azepinas/metabolismo , Cisplatino/metabolismo , Espaço Intracelular/metabolismo , Espectrometria de Massa de Íon Secundário/métodos , Triazóis/metabolismo , Antineoplásicos/metabolismo , Antineoplásicos/farmacocinética , Azepinas/farmacocinética , Linhagem Celular Tumoral , Núcleo Celular/metabolismo , Cisplatino/farmacocinética , Citoplasma/metabolismo , Células HeLa , Humanos , Células Jurkat , Microscopia Confocal , Triazóis/farmacocinéticaRESUMO
Cutaneous T cell lymphomas (CTCL) are rare but aggressive cancers without effective treatments. While a subset of patients derive benefit from PD-1 blockade, there is a critically unmet need for predictive biomarkers of response. Herein, we perform CODEX multiplexed tissue imaging and RNA sequencing on 70 tumor regions from 14 advanced CTCL patients enrolled in a pembrolizumab clinical trial (NCT02243579). We find no differences in the frequencies of immune or tumor cells between responders and non-responders. Instead, we identify topographical differences between effector PD-1+ CD4+ T cells, tumor cells, and immunosuppressive Tregs, from which we derive a spatial biomarker, termed the SpatialScore, that correlates strongly with pembrolizumab response in CTCL. The SpatialScore coincides with differences in the functional immune state of the tumor microenvironment, T cell function, and tumor cell-specific chemokine recruitment and is validated using a simplified, clinically accessible tissue imaging platform. Collectively, these results provide a paradigm for investigating the spatial balance of effector and suppressive T cell activity and broadly leveraging this biomarker approach to inform the clinical use of immunotherapies.
Assuntos
Anticorpos Monoclonais Humanizados/uso terapêutico , Imunoterapia/métodos , Linfoma Cutâneo de Células T/terapia , Receptor de Morte Celular Programada 1/antagonistas & inibidores , Neoplasias Cutâneas/terapia , Idoso , Antineoplásicos Imunológicos/uso terapêutico , Linfócitos T CD4-Positivos/imunologia , Feminino , Humanos , Estimativa de Kaplan-Meier , Ativação Linfocitária/imunologia , Linfoma Cutâneo de Células T/imunologia , Linfoma Cutâneo de Células T/metabolismo , Masculino , Pessoa de Meia-Idade , Micose Fungoide/imunologia , Micose Fungoide/metabolismo , Micose Fungoide/terapia , Receptor de Morte Celular Programada 1/imunologia , Receptor de Morte Celular Programada 1/metabolismo , Síndrome de Sézary/imunologia , Síndrome de Sézary/metabolismo , Síndrome de Sézary/terapia , Neoplasias Cutâneas/imunologia , Neoplasias Cutâneas/metabolismo , Resultado do TratamentoRESUMO
Influenza is a significant cause of morbidity and mortality worldwide. Here we show changes in the abundance and activation states of more than 50 immune cell subsets in 35 individuals over 11 time points during human A/California/2009 (H1N1) virus challenge monitored using mass cytometry along with other clinical assessments. Peak change in monocyte, B cell, and T cell subset frequencies coincided with peak virus shedding, followed by marked activation of T and NK cells. Results led to the identification of CD38 as a critical regulator of plasmacytoid dendritic cell function in response to influenza virus. Machine learning using study-derived clinical parameters and single-cell data effectively classified and predicted susceptibility to infection. The coordinated immune cell dynamics defined in this study provide a framework for identifying novel correlates of protection in the evaluation of future influenza therapeutics.
Assuntos
Vírus da Influenza A Subtipo H1N1/imunologia , Influenza Humana/imunologia , Células Matadoras Naturais/imunologia , Ativação Linfocitária , Linfócitos T/imunologia , Feminino , Humanos , MasculinoRESUMO
Comprehensive identification of factors that can specify neuronal fate could provide valuable insights into lineage specification and reprogramming, but systematic interrogation of transcription factors, and their interactions with each other, has proven technically challenging. We developed a CRISPR activation (CRISPRa) approach to systematically identify regulators of neuronal-fate specification. We activated expression of all endogenous transcription factors and other regulators via a pooled CRISPRa screen in embryonic stem cells, revealing genes including epigenetic regulators such as Ezh2 that can induce neuronal fate. Systematic CRISPR-based activation of factor pairs allowed us to generate a genetic interaction map for neuronal differentiation, with confirmation of top individual and combinatorial hits as bona fide inducers of neuronal fate. Several factor pairs could directly reprogram fibroblasts into neurons, which shared similar transcriptional programs with endogenous neurons. This study provides an unbiased discovery approach for systematic identification of genes that drive cell-fate acquisition.