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AIMS/HYPOTHESIS: Diabetic kidney disease (DKD) is the leading cause of chronic and end-stage kidney disease in the USA and worldwide. Animal models have taught us much about DKD mechanisms, but translation of this knowledge into treatments for human disease has been slowed by the lag in our molecular understanding of human DKD. METHODS: Using our Spatial TissuE Proteomics (STEP) pipeline (comprising curated human kidney tissues, multiplexed immunofluorescence and powerful analysis tools), we imaged and analysed the expression of 21 proteins in 23 tissue sections from individuals with diabetes and healthy kidneys (n=5), compared to those with DKDIIA, IIA-B and IIB (n=2 each) and DKDIII (n=1). RESULTS: These analyses revealed the existence of 11 cellular clusters (kidney compartments/cell types): podocytes, glomerular endothelial cells, proximal tubules, distal nephron, peritubular capillaries, blood vessels (endothelial cells and vascular smooth muscle cells), macrophages, myeloid cells, other CD45+ inflammatory cells, basement membrane and the interstitium. DKD progression was associated with co-localised increases in inflammatory cells and collagen IV deposition, with concomitant loss of native proteins of each nephron segment. Cell-type frequency and neighbourhood analyses highlighted a significant increase in inflammatory cells and their adjacency to tubular and αSMA+ (α-smooth muscle actin-positive) cells in DKD. Finally, DKD progression showed marked regional variability within single tissue sections, as well as inter-individual variability within each DKD class. CONCLUSIONS/INTERPRETATION: Using the STEP pipeline, we found alterations in protein expression, cellular phenotypic composition and microenvironment structure with DKD progression, demonstrating the power of this pipeline to reveal the pathophysiology of human DKD.
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MOTIVATION: Spatial proteomics data have been used to map cell states and improve our understanding of tissue organization. More recently, these methods have been extended to study the impact of such organization on disease progression and patient survival. However, to date, the majority of supervised learning methods utilizing these data types did not take full advantage of the spatial information, impacting their performance and utilization. RESULTS: Taking inspiration from ecology and epidemiology, we developed novel spatial feature extraction methods for use with spatial proteomics data. We used these features to learn prediction models for cancer patient survival. As we show, using the spatial features led to consistent improvement over prior methods that used the spatial proteomics data for the same task. In addition, feature importance analysis revealed new insights about the cell interactions that contribute to patient survival. AVAILABILITY AND IMPLEMENTATION: The code for this work can be found at gitlab.com/enable-medicine-public/spatsurv.
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Neoplasias , Proteômica , Humanos , Neoplasias/diagnóstico por imagem , Comunicação Celular , Progressão da Doença , Análise de SobrevidaRESUMO
Radiological imaging is an integral component of cancer care, including diagnosis, staging, and treatment response monitoring. It contains rich information about tumor phenotypes that are governed not only by cancer cellintrinsic biological processes but also by the tumor microenvironment, such as the composition and function of tumor-infiltrating immune cells. By analyzing the radiological scans using a quantitative radiomics approach, robust relations between specific imaging and molecular phenotypes can be established. Indeed, a number of studies have demonstrated the feasibility of radiogenomics for predicting intrinsic molecular subtypes and gene expression signatures in breast cancer based on MRI. In parallel, promising results have been shown for inferring the amount of tumor-infiltrating lymphocytes, a key factor for the efficacy of cancer immunotherapy, from standard-of-care radiological images. Compared with the biopsy-based approach, radiogenomics offers a unique avenue to profile the molecular makeup of the tumor and immune microenvironment as well as its evolution in a noninvasive and holistic manner through longitudinal imaging scans. Here, we provide a systematic review of the state of the art radiogenomics studies in the era of immunotherapy and discuss emerging paradigms and opportunities in AI and deep learning approaches. These technical advances are expected to transform the radiogenomics field, leading to the discovery of reliable imaging biomarkers. This will pave the way for their clinical translation to guide precision cancer therapy.
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Neoplasias da Mama , Microambiente Tumoral , Biomarcadores Tumorais/genética , Neoplasias da Mama/tratamento farmacológico , Feminino , Genômica/métodos , Humanos , Imunoterapia , Linfócitos do Interstício Tumoral , Microambiente Tumoral/genéticaRESUMO
BACKGROUND AND AIMS: Patients with pancreatic ductal adenocarcinoma (PDA) have not yet benefitted from the revolution in cancer immunotherapy due in large part to a dominantly immunosuppressive tumor microenvironment. MEK inhibition combined with autophagy inhibition leads to transient tumor responses in some patients with PDA. We examined the functional effects of combined MEK and autophagy inhibition on the PDA immune microenvironment and the synergy of combined inhibition of MEK and autophagy with CD40 agonism (aCD40) against PDA using immunocompetent model systems. METHODS: We implanted immunologically "cold" murine PDA cells orthotopically in wide type C57BL/6J mice. We administered combinations of inhibitors of MEK1/2, inhibitors of autophagy, and aCD40 and measured anticancer efficacy and immune sequelae using mass cytometry and multiplexed immunofluorescence imaging analysis to characterize the tumor microenvironment. We also used human and mouse PDA cell lines and human macrophages in vitro to perform functional assays to elucidate the cellular effects induced by the treatments. RESULTS: We find that coinhibition of MEK (using cobimetinib) and autophagy (using mefloquine), but not either treatment alone, activates the STING/type I interferon pathway in tumor cells that in turn activates paracrine tumor associated macrophages toward an immunogenic M1-like phenotype. This switch is further augmented by aCD40. Triple therapy (cobimetinib + mefloquine + aCD40) achieved cytotoxic T-cell activation in an immunologically "cold" mouse PDA model, leading to enhanced antitumor immunity. CONCLUSIONS: MEK and autophagy coinhibition coupled with aCD40 invokes immune repolarization and is an attractive therapeutic approach for PDA immunotherapy development.
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Autofagia/imunologia , Azetidinas/farmacologia , Antígenos CD40/agonistas , Carcinoma Ductal Pancreático/imunologia , Mefloquina/farmacologia , Neoplasias Pancreáticas/imunologia , Piperidinas/farmacologia , Inibidores de Proteínas Quinases/farmacologia , Microambiente Tumoral/imunologia , Macrófagos Associados a Tumor/imunologia , Animais , Autofagia/efeitos dos fármacos , Linhagem Celular Tumoral , Sinergismo Farmacológico , Humanos , Hidroxicloroquina/farmacologia , Imunoterapia , Interferon Tipo I/efeitos dos fármacos , Interferon Tipo I/imunologia , MAP Quinase Quinase 1/antagonistas & inibidores , MAP Quinase Quinase 2/antagonistas & inibidores , Macrófagos , Proteínas de Membrana/efeitos dos fármacos , Proteínas de Membrana/imunologia , Camundongos , Comunicação Parácrina/efeitos dos fármacos , Comunicação Parácrina/imunologia , Evasão Tumoral , Microambiente Tumoral/efeitos dos fármacos , Macrófagos Associados a Tumor/efeitos dos fármacosRESUMO
Vascular endothelial cell (EC) plasticity plays a critical role in the progression of atherosclerosis by giving rise to mesenchymal phenotypes in the plaque lesion. Despite the evidence for arterial stiffening as a major contributor to atherosclerosis, the complex interplay among atherogenic stimuli in vivo has hindered attempts to determine the effects of extracellular matrix (ECM) stiffness on endothelial-mesenchymal transition (EndMT). To study the regulatory effects of ECM stiffness on EndMT, an in vitro model is developed in which human coronary artery ECs are cultured on physiological or pathological stiffness substrates. Leveraging single-cell RNA sequencing, cell clusters with mesenchymal transcriptional features are identified to be more prevalent on pathological substrates than physiological substrates. Trajectory inference analyses reveal a novel mesenchymal-to-endothelial reverse transition, which is blocked by pathological stiffness substrates, in addition to the expected EndMT trajectory. ECs pushed to a mesenchymal character by pathological stiffness substrates are enriched in transcriptional signatures of atherosclerotic ECs from human and murine plaques. This study characterizes at single-cell resolution the transcriptional programs that underpin EC plasticity in both physiological or pathological milieus, and thus serves as a valuable resource for more precisely defining EndMT and the transcriptional programs contributing to atherosclerosis.
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Early and comprehensive endoscopic detection of colonic dysplasia - the most clinically significant precursor lesion to colorectal adenocarcinoma - provides an opportunity for timely, minimally-invasive intervention to prevent malignant transformation. Here, the development and evaluation of biodegradable near-infrared fluorescent silica nanoparticles (FSN) is described that have the potential to improve adenoma detection during fluorescence-assisted white-light colonoscopic surveillance in rodent and human-scale models of colorectal carcinogenesis. FSNs are biodegradable (t1/2 of 2.7 weeks), well-tolerated, and enable detection and delineation of adenomas as small as 0.5 mm2 with high tumor-to-background ratios. Furthermore, in the human-scale, APC 1311/+ porcine model, the clinical feasibility and benefit of using FSN-guided detection of colorectal adenomas using video-rate fluorescence-assisted white-light endoscopy is demonstrated. Since nanoparticles of similar size (e.g., 100-150-nm) or composition (i.e., silica, silica/gold hybrid) have already been successfully translated to the clinic, and, clinical fluorescent/white light endoscopy systems are becoming more readily available, there is a viable path towards clinical translation of the proposed strategy for early colorectal cancer detection and prevention in high-risk patients.
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Signaling through the immune checkpoint programmed cell death protein-1 (PD-1) enables tumor progression by dampening antitumor immune responses. Therapeutic blockade of the signaling axis between PD-1 and its ligand programmed cell death ligand-1 (PD-L1) with monoclonal antibodies has shown remarkable clinical success in the treatment of cancer. However, antibodies have inherent limitations that can curtail their efficacy in this setting, including poor tissue/tumor penetrance and detrimental Fc-effector functions that deplete immune cells. To determine if PD-1:PD-L1-directed immunotherapy could be improved with smaller, nonantibody therapeutics, we used directed evolution by yeast-surface display to engineer the PD-1 ectodomain as a high-affinity (110 pM) competitive antagonist of PD-L1. In contrast to anti-PD-L1 monoclonal antibodies, high-affinity PD-1 demonstrated superior tumor penetration without inducing depletion of peripheral effector T cells. Consistent with these advantages, in syngeneic CT26 tumor models, high-affinity PD-1 was effective in treating both small (50 mm(3)) and large tumors (150 mm(3)), whereas the activity of anti-PD-L1 antibodies was completely abrogated against large tumors. Furthermore, we found that high-affinity PD-1 could be radiolabeled and applied as a PET imaging tracer to efficiently distinguish between PD-L1-positive and PD-L1-negative tumors in living mice, providing an alternative to invasive biopsy and histological analysis. These results thus highlight the favorable pharmacology of small, nonantibody therapeutics for enhanced cancer immunotherapy and immune diagnostics.
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Imunoterapia , Proteínas Mutantes/uso terapêutico , Neoplasias/diagnóstico por imagem , Neoplasias/terapia , Tomografia por Emissão de Pósitrons , Receptor de Morte Celular Programada 1/uso terapêutico , Engenharia de Proteínas , Sequência de Aminoácidos , Animais , Linhagem Celular Tumoral , Evolução Molecular Direcionada , Modelos Animais de Doenças , Humanos , Depleção Linfocítica , Camundongos Endogâmicos BALB C , Dados de Sequência Molecular , Neoplasias/imunologia , Receptor de Morte Celular Programada 1/química , Ligação Proteica , Linfócitos T/metabolismoRESUMO
BACKGROUND: Approximately 70% of all breast cancers express the estrogen receptor, and are regulated by estrogen. While the ovaries are the primary source of estrogen in premenopausal women, most breast cancer is diagnosed following menopause, when systemic levels of this hormone decline. Estrogen production from androgen precursors is catalyzed by the aromatase enzyme. Although aromatase expression and local estrogen production in breast adipose tissue have been implicated in the development of primary breast cancer, the source of estrogen involved in the regulation of estrogen receptor-positive (ER+) metastatic breast cancer progression is less clear. METHODS: Bone is the most common distant site of breast cancer metastasis, particularly for ER+ breast cancers. We employed a co-culture model using trabecular bone tissues obtained from total hip replacement (THR) surgery specimens to study ER+ and estrogen receptor-negative (ER-) breast cancer cells within the human bone microenvironment. Luciferase-expressing ER+ (MCF-7, T-47D, ZR-75) and ER- (SK-BR-3, MDA-MB-231, MCF-10A) breast cancer cells were cultured directly on bone tissue fragments or in bone tissue-conditioned media, and monitored over time with bioluminescence imaging (BLI). Bone tissue-conditioned media were generated in the presence vs. absence of aromatase inhibitors, and testosterone. Bone tissue fragments were analyzed for aromatase expression by immunohistochemistry. RESULTS: ER+ breast cancer cells were preferentially sustained in co-cultures with bone tissues and bone tissue-conditioned media relative to ER- cells. Bone fragments analyzed by immunohistochemistry revealed expression of the aromatase enzyme. Bone tissue-conditioned media generated in the presence of testosterone had increased estrogen levels and heightened capacity to stimulate ER+ breast cancer cell proliferation. Pretreatment of cultured bone tissues with aromatase inhibitors, which inhibited estrogen production, reduced the capacity of conditioned media to stimulate ER+ cell proliferation. CONCLUSIONS: These results suggest that a local estrogen signaling axis regulates ER+ breast cancer cell viability and proliferation within the bone metastatic niche, and that aromatase inhibitors modulate this axis. Although endocrine therapies are highly effective in the treatment of ER+ breast cancer, resistance to these treatments reduces their efficacy. Characterization of estrogen signaling networks within the bone microenvironment will identify new strategies for combating metastatic progression and endocrine resistance.
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Osso e Ossos/metabolismo , Osso e Ossos/patologia , Neoplasias da Mama/metabolismo , Neoplasias da Mama/patologia , Microambiente Celular , Estrogênios/metabolismo , Receptores de Estrogênio/metabolismo , Aromatase/genética , Aromatase/metabolismo , Inibidores da Aromatase/farmacologia , Biomarcadores Tumorais , Neoplasias Ósseas/patologia , Neoplasias Ósseas/secundário , Remodelação Óssea , Linhagem Celular Tumoral , Proliferação de Células/efeitos dos fármacos , Técnicas de Cocultura , Meios de Cultivo Condicionados/farmacologia , Ensaio de Imunoadsorção Enzimática , Feminino , Expressão Gênica , Humanos , Imuno-Histoquímica , Medições Luminescentes , Imagem Molecular , Técnicas de Cultura de TecidosRESUMO
Immune checkpoint signaling through the programmed death 1 (PD-1) axis to its ligand (PD-L1) significantly dampens anti-tumor immune responses. Cancer patients treated with checkpoint inhibitors that block this suppressive signaling have exhibited objective response rates of 20-40% for advanced solid tumors, lymphomas, and malignant melanomas. This represents a tremendous advance in cancer treatment. Unfortunately, all patients do not respond to immune checkpoint blockade. Recent findings suggest that patients with tumor infiltrating lymphocytes (TILs) expressing PD-1 may be most likely to respond to αPD-1/PD-L1 checkpoint inhibitors. There is a compelling need for diagnostic and prognostic imaging tools to assess the PD-1 status of TILs in vivo. Here we have developed a novel immunoPET tracer to image PD-1 expressing TILs in a transgenic mouse model bearing melanoma. A (64)Cu labeled anti-mouse antibody (IgG) PD-1 immuno positron emission tomography (PET) tracer was developed to detect PD-1 expressing murine TILs. Quality control of the tracer showed >95% purity by HPLC and >70% immunoreactivity in an in vitro cell binding assay. ImmunoPET scans were performed over 1-48 h on Foxp3+.LuciDTR4 mice bearing B16-F10 melanoma tumors. Mice receiving anti-PD-1 tracer (200 ± 10 µCi/10-12 µg/200 µL) revealed high tracer uptake in lymphoid organs and tumors. BLI images of FoxP3(+) CD4(+) Tregs known to express PD-1 confirmed lymphocyte infiltration of tumors at the time of PET imaging. Biodistribution measurements performed at 48 h revealed a high (11×) tumor to muscle uptake ratio of the PET tracer (p < 0.05). PD-1 tumors exhibited 7.4 ± 0.7%ID/g tracer uptake and showed a 2× fold signal decrease when binding was blocked by unlabeled antibody. To the best of our knowledge this data is the first report to image PD-1 expression in living subjects with PET. This radiotracer has the potential to assess the prognostic value of PD-1 in preclinical models of immunotherapy and may ultimately aid in predicting response to therapies targeting immune checkpoints.
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Linfócitos do Interstício Tumoral/patologia , Tomografia por Emissão de Pósitrons/métodos , Receptor de Morte Celular Programada 1/metabolismo , Compostos Radiofarmacêuticos/farmacocinética , Animais , Anticorpos Monoclonais/química , Morte Celular/imunologia , Radioisótopos de Cobre/química , Compostos Heterocíclicos/química , Imunoconjugados/química , Imunoconjugados/farmacocinética , Isotiocianatos/química , Linfócitos do Interstício Tumoral/imunologia , Melanoma/patologia , Camundongos Transgênicos , Receptor de Morte Celular Programada 1/imunologia , Distribuição Tecidual , Ensaios Antitumorais Modelo de XenoenxertoRESUMO
Subcellular protein localization is important for understanding functional states of cells, but measuring and quantifying this information can be difficult and typically requires high-resolution microscopy. In this work, we develop a metric to define surface protein polarity from immunofluorescence (IF) imaging data and use it to identify distinct immune cell states within tumor microenvironments. We apply this metric to characterize over two million cells across 600 patient samples and find that cells identified as having polar expression exhibit characteristics relating to tumor-immune cell engagement. Additionally, we show that incorporating these polarity-defined cell subtypes improves the performance of deep learning models trained to predict patient survival outcomes. This method provides a first look at using subcellular protein expression patterns to phenotype immune cell functional states with applications to precision medicine.
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Biologia Computacional , Proteômica , Humanos , Proteômica/métodosRESUMO
BACKGROUND: Kidney allograft rejections are orchestrated by a variety of immune cells. Because of the complex histopathologic features, accurate pathological diagnosis poses challenges even for expert pathologists. The objective of this study was to unveil novel spatial indices associated with transplant rejection by using a spatial bioinformatic approach using 36-plex immunofluorescence image data. METHODS: The image obtained from 11 T cell-mediated rejection (TCMR) and 12 antibody-mediated rejection (AMR) samples were segmented into 753 737 single cells using DeepCell's Mesmer algorithm. These cells were categorized into 13 distinct cell types through unsupervised clustering based on their biomarker expression profiles. Cell neighborhood analysis allowed us to stratify kidney tissue into 8 distinct neighborhood components consisting of unique cell type enrichment profiles. RESULTS: In contrast to TCMR samples, AMR samples exhibited a higher frequency of neighborhood components that were characterized by an enrichment of CD31+ endothelial cells. Although the overall frequency of CD68+ macrophages in AMR samples was not significantly high, CD68+ macrophages within endothelial cell-rich lesions exhibited a significantly higher frequency in AMR samples than TCMR samples. Furthermore, the frequency of interactions between CD31+ cells and CD68+ cells was significantly increased in AMR samples, implying the pivotal role of macrophages in AMR pathogenesis. Importantly, patients demonstrating a high frequency of CD31:CD68 interactions experienced significantly poorer outcomes in terms of chronic AMR progression. CONCLUSIONS: Collectively, these data indicate the potential of spatial bioinformatic as a valuable tool for aiding in pathological diagnosis and for uncovering new insights into the mechanisms underlying transplant rejection.
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Tissues are organized into anatomical and functional units at different scales. New technologies for high-dimensional molecular profiling in situ have enabled the characterization of structure-function relationships in increasing molecular detail. However, it remains a challenge to consistently identify key functional units across experiments, tissues, and disease contexts, a task that demands extensive manual annotation. Here, we present spatial cellular graph partitioning (SCGP), a flexible method for the unsupervised annotation of tissue structures. We further present a reference-query extension pipeline, SCGP-Extension, that generalizes reference tissue structure labels to previously unseen samples, performing data integration and tissue structure discovery. Our experiments demonstrate reliable, robust partitioning of spatial data in a wide variety of contexts and best-in-class accuracy in identifying expertly annotated structures. Downstream analysis on SCGP-identified tissue structures reveals disease-relevant insights regarding diabetic kidney disease, skin disorder, and neoplastic diseases, underscoring its potential to drive biological insight and discovery from spatial datasets.
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Multiplex immunofluorescence (mIF) assays multiple protein biomarkers on a single tissue section. Recently, high-plex CODEX (co-detection by indexing) systems enable simultaneous imaging of 40+ protein biomarkers, unlocking more detailed molecular phenotyping, leading to richer insights into cellular interactions and disease. However, high-plex data can be slower and more costly to collect, limiting its applications, especially in clinical settings. We propose a machine learning framework, 7-UP, that can computationally generate in silico 40-plex CODEX at single-cell resolution from a standard 7-plex mIF panel by leveraging cellular morphology. We demonstrate the usefulness of the imputed biomarkers in accurately classifying cell types and predicting patient survival outcomes. Furthermore, 7-UP's imputations generalize well across samples from different clinical sites and cancer types. 7-UP opens the possibility of in silico CODEX, making insights from high-plex mIF more widely available.
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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.
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Colite Ulcerativa , Humanos , Colite Ulcerativa/tratamento farmacológico , Colite Ulcerativa/complicações , Inibidores do Fator de Necrose Tumoral/uso terapêutico , Inflamação/complicações , BiomarcadoresRESUMO
BACKGROUNDPemphigus, a rare autoimmune bullous disease mediated by antidesmoglein autoantibodies, can be controlled with systemic medication like rituximab and high-dose systemic corticosteroids combined with immunosuppressants. However, some patients continue to experience chronically recurrent blisters in a specific area and require long-term maintenance systemic therapy.METHODSSkin with chronic blisters was obtained from patients with pemphigus. Immunologic properties of the skin were analyzed by immunofluorescence staining, bulk and single-cell RNA and TCR sequencing, and a highly multiplex imaging technique known as CO-Detection by indEXing (CODEX). Functional analyses were performed by flow cytometry and bulk RNA-Seq using peripheral blood from healthy donors. Intralesional corticosteroid was injected into patient skin, and changes in chronically recurrent blisters were observed.RESULTSWe demonstrated the presence of skin tertiary lymphoid structures (TLSs) with desmoglein-specific B cells in chronic blisters from patients with pemphigus. In the skin TLSs, CD4+ T cells predominantly produced CXCL13. These clonally expanded CXCL13+CD4+ T cells exhibited features of activated Th1-like cells and downregulated genes associated with T cell receptor-mediated signaling. Tregs are in direct contact with CXCL13+CD4+ memory T cells and increased CXCL13 production of CD4+ T cells through IL-2 consumption and TGF-ß stimulation. Finally, intralesional corticosteroid injection improved chronic blisters and reduced skin TLSs in patients with pemphigus.CONCLUSIONThrough this study we conclude that skin TLSs are associated with the persistence of chronically recurrent blisters in patients with pemphigus, and the microenvironmental network involving CXCL13+CD4+ T cells and Tregs within these structures plays an important role in CXCL13 production.TRIAL REGISTRATIONClinicalTrials.gov NCT04509570.FUNDINGThis work was supported by National Research Foundation of South Korea (NRF-2021R1C1C1007179) and Korea Drug Development Fund, which is funded by Ministry of Science and ICT; Ministry of Trade, Industry, and Energy; and Ministry of Health and Welfare (grant RS-2022-00165917).
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Doenças Autoimunes , Pênfigo , Humanos , Corticosteroides , Autoanticorpos , Doenças Autoimunes/tratamento farmacológico , Vesícula/tratamento farmacológico , Linfócitos T CD4-Positivos , Quimiocina CXCL13 , Desmogleína 3 , Pênfigo/tratamento farmacológicoRESUMO
Multiplexed immunofluorescence imaging allows the multidimensional molecular profiling of cellular environments at subcellular resolution. However, identifying and characterizing disease-relevant microenvironments from these rich datasets is challenging. Here we show that a graph neural network that leverages spatial protein profiles in tissue specimens to model tumour microenvironments as local subgraphs captures distinctive cellular interactions associated with differential clinical outcomes. We applied this spatial cellular-graph strategy to specimens of human head-and-neck and colorectal cancers assayed with 40-plex immunofluorescence imaging to identify spatial motifs associated with cancer recurrence and with patient survival after treatment. The graph deep learning model was substantially more accurate in predicting patient outcomes than deep learning approaches that model spatial data on the basis of the local composition of cell types, and it generated insights into the effect of the spatial compartmentalization of tumour cells and granulocytes on patient prognosis. Local graphs may also aid in the analysis of disease-relevant motifs in histology samples characterized via spatial transcriptomics and other -omics techniques.
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Aprendizado Profundo , Humanos , Microambiente Tumoral , Redes Neurais de Computação , Perfilação da Expressão Gênica/métodosRESUMO
When properly deployed, the immune system can eliminate deadly pathogens, eradicate metastatic cancers, and provide long-lasting protection from diverse diseases. Unfortunately, realizing these remarkable capabilities is inherently risky as disruption to immune homeostasis can elicit dangerous complications or autoimmune disorders. While current research is continuously expanding the arsenal of potent immunotherapeutics, there is a technological gap when it comes to controlling when, where, and how long these drugs act on the body. Here, this study explored the ability of a slow-releasing injectable hydrogel depot to reduce dose-limiting toxicities of immunostimulatory CD40 agonist (CD40a) while maintaining its potent anticancer efficacy. A previously described polymer-nanoparticle (PNP) hydrogel system is leveraged that exhibits shear-thinning and yield-stress properties that are hypothesized to improve locoregional delivery of CD40a immunotherapy. Using positron emission tomography, it is demonstrated that prolonged hydrogel-based delivery redistributes CD40a exposure to the tumor and the tumor draining lymph node (TdLN), thereby reducing weight loss, hepatotoxicity, and cytokine storm associated with standard treatment. Moreover, CD40a-loaded hydrogels mediate improved local cytokine induction in the TdLN and improve treatment efficacy in the B16F10 melanoma model. PNP hydrogels, therefore, represent a facile, drug-agnostic method to ameliorate immune-related adverse effects and explore locoregional delivery of immunostimulatory drugs.
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Melanoma , Nanopartículas , Anticorpos , Antígenos CD40 , Citocinas , Humanos , Hidrogéis/química , Polímeros , Tomografia Computadorizada por Raios XRESUMO
PURPOSE: Immunotherapy is a promising approach for many oncological malignancies, including glioblastoma, however, there are currently no available tools or biomarkers to accurately assess whole-body immune responses in patients with glioblastoma treated with immunotherapy. Here, the utility of OX40, a costimulatory molecule mainly expressed on activated effector T cells known to play an important role in eliminating cancer cells, was evaluated as a PET imaging biomarker to quantify and track response to immunotherapy. EXPERIMENTAL DESIGN: A subcutaneous vaccination approach of CpG oligodeoxynucleotide, OX40 mAb, and tumor lysate at a remote site in a murine orthotopic glioma model was developed to induce activation of T cells distantly while monitoring their distribution in stimulated lymphoid organs with respect to observed therapeutic effects. To detect OX40-positive T cells, we utilized our in-house-developed 89Zr-DFO-OX40 mAb and in vivo PET/CT imaging. RESULTS: ImmunoPET with 89Zr-DFO-OX40 mAb revealed strong OX40-positive responses with high specificity, not only in the nearest lymph node from vaccinated area (mean, 20.8%ID/cc) but also in the spleen (16.7%ID/cc) and the tumor draining lymph node (11.4%ID/cc). When the tumor was small (<106 p/sec/cm2/sr in bioluminescence imaging), a high number of responders and percentage shrinkage in tumor signal was indicated after only a single cycle of vaccination. CONCLUSIONS: The results highlight the promise of clinically translating cancer vaccination as a potential glioma therapy, as well as the benefits of monitoring efficacy of these treatments using immunoPET imaging of T-cell activation.
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Glioblastoma , Animais , Linhagem Celular Tumoral , Glioblastoma/diagnóstico por imagem , Glioblastoma/terapia , Humanos , Camundongos , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada/métodos , Tomografia por Emissão de Pósitrons , Linfócitos T/patologiaRESUMO
Diagnosis of organ transplant rejection relies upon biopsy approaches to confirm alloreactive T cell infiltration in the graft. Immune molecular monitoring is under investigation to screen for rejection, though these techniques have suffered from low specificity and lack of spatial information. ImmunoPET utilizing antibodies conjugated to radioisotopes has the potential to improve early and accurate detection of graft rejection. ImmunoPET is capable of noninvasively visualizing the dynamic distribution of cells expressing specific immune markers in the entire body over time. In this work, we identify and characterize OX40 as a surrogate biomarker for alloreactive T cells in organ transplant rejection and monitor its expression by utilizing immunoPET. In a dual murine heart transplant model that has both syngeneic and allogeneic hearts engrafted in bilateral ear pinna on the recipients, OX40 immunoPET clearly depicted alloreactive T cells in the allograft and draining lymph node that were not observed in their respective isograft counterparts. OX40 immunoPET signals also reflected the subject's immunosuppression level with tacrolimus in this study. OX40 immunoPET is a promising approach that may bridge molecular monitoring and morphological assessment for improved transplant rejection diagnosis.
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Rejeição de Enxerto , Transplante de Coração/efeitos adversos , Monitorização Imunológica/métodos , Ligante OX40 , Tomografia por Emissão de Pósitrons/métodos , Linfócitos T/imunologia , Animais , Antígenos de Diferenciação/análise , Biomarcadores/análise , Diagnóstico Precoce , Perfilação da Expressão Gênica/métodos , Rejeição de Enxerto/diagnóstico , Rejeição de Enxerto/imunologia , Humanos , Programas de Rastreamento/métodos , Camundongos , Ligante OX40/análise , Ligante OX40/imunologia , Radioimunoensaio/métodosRESUMO
Immunotherapy is innovating clinical cancer management. Nevertheless, only a small fraction of patient's benefit from current immunotherapies. To improve clinical management of cancer immunotherapy, it is critical to develop strategies for response monitoring and prediction. In this study, we describe inducible T-cell costimulator (ICOS) as a conserved mediator of immune response across multiple therapy strategies. ICOS expression was evaluated by flow cytometry, 89Zr-DFO-ICOS mAb PET/CT imaging was performed on Lewis lung cancer models treated with different immunotherapy strategies, and the change in tumor volume was used as a read-out for therapeutic response. ImmunoPET imaging of ICOS enabled sensitive and specific detection of activated T cells and early benchmarking of immune response. A STING (stimulator of interferon genes) agonist was identified as a promising therapeutic approach in this manner. The STING agonist generated significantly stronger immune responses as measured by ICOS ImmunoPET and delayed tumor growth compared with programmed death-1 checkpoint blockade. More importantly, ICOS ImmunoPET enabled early and robust prediction of therapeutic response across multiple treatment regimens. These data show that ICOS is an indicator of T-cell-mediated immune response and suggests ICOS ImmunoPET as a promising strategy for monitoring, comparing, and predicting immunotherapy success in cancer. SIGNIFICANCE: ICOS ImmunoPET is a promising strategy to noninvasively predict and monitor immunotherapy response.See related commentary by Choyke, p. 2975.