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Ductal carcinoma in situ (DCIS) is a pre-invasive lesion that is thought to be a precursor to invasive breast cancer (IBC). To understand the changes in the tumor microenvironment (TME) accompanying transition to IBC, we used multiplexed ion beam imaging by time of flight (MIBI-TOF) and a 37-plex antibody staining panel to interrogate 79 clinically annotated surgical resections using machine learning tools for cell segmentation, pixel-based clustering, and object morphometrics. Comparison of normal breast with patient-matched DCIS and IBC revealed coordinated transitions between four TME states that were delineated based on the location and function of myoepithelium, fibroblasts, and immune cells. Surprisingly, myoepithelial disruption was more advanced in DCIS patients that did not develop IBC, suggesting this process could be protective against recurrence. Taken together, this HTAN Breast PreCancer Atlas study offers insight into drivers of IBC relapse and emphasizes the importance of the TME in regulating these processes.
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Neoplasias de la Mama/patología , Carcinoma Intraductal no Infiltrante/patología , Diferenciación Celular , Estudios de Cohortes , Progresión de la Enfermedad , Células Epiteliales/patología , Epitelio/patología , Matriz Extracelular/metabolismo , Femenino , Fibroblastos/metabolismo , Fibroblastos/patología , Humanos , Persona de Mediana Edad , Invasividad Neoplásica , Recurrencia Local de Neoplasia/patología , Fenotipo , Análisis de la Célula Individual , Células del Estroma/patología , Microambiente TumoralRESUMEN
Tuberculosis (TB) in humans is characterized by formation of immune-rich granulomas in infected tissues, the architecture and composition of which are thought to affect disease outcome. However, our understanding of the spatial relationships that control human granulomas is limited. Here, we used multiplexed ion beam imaging by time of flight (MIBI-TOF) to image 37 proteins in tissues from patients with active TB. We constructed a comprehensive atlas that maps 19 cell subsets across 8 spatial microenvironments. This atlas shows an IFN-γ-depleted microenvironment enriched for TGF-ß, regulatory T cells and IDO1+ PD-L1+ myeloid cells. In a further transcriptomic meta-analysis of peripheral blood from patients with TB, immunoregulatory trends mirror those identified by granuloma imaging. Notably, PD-L1 expression is associated with progression to active TB and treatment response. These data indicate that in TB granulomas, there are local spatially coordinated immunoregulatory programs with systemic manifestations that define active TB.
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Granuloma/inmunología , Tuberculosis/inmunología , Antígeno B7-H1/inmunología , Células Cultivadas , Citocinas/inmunología , Perfilación de la Expresión Génica/métodos , Humanos , Indolamina-Pirrol 2,3,-Dioxigenasa/inmunología , Pulmón/inmunología , Mycobacterium tuberculosis/inmunología , Células Mieloides/inmunologíaRESUMEN
Understanding the mechanisms of HIV tissue persistence necessitates the ability to visualize tissue microenvironments where infected cells reside; however, technological barriers limit our ability to dissect the cellular components of these HIV reservoirs. Here, we developed protein and nucleic acid in situ imaging (PANINI) to simultaneously quantify DNA, RNA, and protein levels within these tissue compartments. By coupling PANINI with multiplexed ion beam imaging (MIBI), we measured over 30 parameters simultaneously across archival lymphoid tissues from healthy or simian immunodeficiency virus (SIV)-infected nonhuman primates. PANINI enabled the spatial dissection of cellular phenotypes, functional markers, and viral events resulting from infection. SIV infection induced IL-10 expression in lymphoid B cells, which correlated with local macrophage M2 polarization. This highlights a potential viral mechanism for conditioning an immunosuppressive tissue environment for virion production. The spatial multimodal framework here can be extended to decipher tissue responses in other infectious diseases and tumor biology.
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Infecciones por VIH , Ácidos Nucleicos , Síndrome de Inmunodeficiencia Adquirida del Simio , Virus de la Inmunodeficiencia de los Simios , Animales , Linfocitos T CD4-Positivos , Virus ADN , Terapia de Inmunosupresión , Macaca mulatta , Macrófagos , Virus de la Inmunodeficiencia de los Simios/fisiología , Carga ViralRESUMEN
Beginning in the first trimester, fetally derived extravillous trophoblasts (EVTs) invade the uterus and remodel its spiral arteries, transforming them into large, dilated blood vessels. Several mechanisms have been proposed to explain how EVTs coordinate with the maternal decidua to promote a tissue microenvironment conducive to spiral artery remodelling (SAR)1-3. However, it remains a matter of debate regarding which immune and stromal cells participate in these interactions and how this evolves with respect to gestational age. Here we used a multiomics approach, combining the strengths of spatial proteomics and transcriptomics, to construct a spatiotemporal atlas of the human maternal-fetal interface in the first half of pregnancy. We used multiplexed ion beam imaging by time-of-flight and a 37-plex antibody panel to analyse around 500,000 cells and 588 arteries within intact decidua from 66 individuals between 6 and 20 weeks of gestation, integrating this dataset with co-registered transcriptomics profiles. Gestational age substantially influenced the frequency of maternal immune and stromal cells, with tolerogenic subsets expressing CD206, CD163, TIM-3, galectin-9 and IDO-1 becoming increasingly enriched and colocalized at later time points. By contrast, SAR progression preferentially correlated with EVT invasion and was transcriptionally defined by 78 gene ontology pathways exhibiting distinct monotonic and biphasic trends. Last, we developed an integrated model of SAR whereby invasion is accompanied by the upregulation of pro-angiogenic, immunoregulatory EVT programmes that promote interactions with the vascular endothelium while avoiding the activation of maternal immune cells.
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Intercambio Materno-Fetal , Trofoblastos , Útero , Femenino , Humanos , Embarazo , Arterias/fisiología , Decidua/irrigación sanguínea , Decidua/citología , Decidua/inmunología , Decidua/fisiología , Primer Trimestre del Embarazo/genética , Primer Trimestre del Embarazo/metabolismo , Primer Trimestre del Embarazo/fisiología , Trofoblastos/citología , Trofoblastos/inmunología , Trofoblastos/fisiología , Útero/irrigación sanguínea , Útero/citología , Útero/inmunología , Útero/fisiología , Intercambio Materno-Fetal/genética , Intercambio Materno-Fetal/inmunología , Intercambio Materno-Fetal/fisiología , Factores de Tiempo , Proteómica , Perfilación de la Expresión Génica , Conjuntos de Datos como Asunto , Edad GestacionalRESUMEN
Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimental settings. Here, we present a multimodality cell segmentation benchmark, comprising more than 1,500 labeled images derived from more than 50 diverse biological experiments. The top participants developed a Transformer-based deep-learning algorithm that not only exceeds existing methods but can also be applied to diverse microscopy images across imaging platforms and tissue types without manual parameter adjustments. This benchmark and the improved algorithm offer promising avenues for more accurate and versatile cell analysis in microscopy imaging.
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Algoritmos , Aprendizaje Profundo , Procesamiento de Imagen Asistido por Computador , Análisis de la Célula Individual , Análisis de la Célula Individual/métodos , Procesamiento de Imagen Asistido por Computador/métodos , Humanos , Microscopía/métodos , AnimalesRESUMEN
Rationale: Unraveling immune-driven vascular pathology in pulmonary arterial hypertension (PAH) requires a comprehensive understanding of the immune cell landscape. Although patients with hereditary (H)PAH and bone morphogenetic protein receptor type 2 (BMPR2) mutations have more severe pulmonary vascular pathology, it is not known whether this is related to specific immune cell subsets. Objectives: This study aims to elucidate immune-driven vascular pathology by identifying immune cell subtypes linked to severity of pulmonary arterial lesions in PAH. Methods: We used cutting-edge multiplexed ion beam imaging by time of flight to compare pulmonary arteries (PAs) and adjacent tissue in PAH lungs (idiopathic [I]PAH and HPAH) with unused donor lungs, as controls. Measurements and Main Results: We quantified immune cells' proximity and abundance, focusing on those features linked to vascular pathology, and evaluated their impact on pulmonary arterial smooth muscle cells (SMCs) and endothelial cells. Distinct immune infiltration patterns emerged between PAH subtypes, with intramural involvement independently linked to PA occlusive changes. Notably, we identified monocyte-derived dendritic cells within PA subendothelial and adventitial regions, influencing vascular remodeling by promoting SMC proliferation and suppressing endothelial gene expression across PAH subtypes. In patients with HPAH, pronounced immune dysregulation encircled PA walls, characterized by heightened perivascular inflammation involving T cell immunoglobulin and mucin domain-3 (TIM-3)+ T cells. This correlated with an expanded DC subset expressing indoleamine 2,3-dioxygenase 1, TIM-3, and SAM and HD domain-containing deoxynucleoside triphosphate triphosphohydrolase 1, alongside increased neutrophils, SMCs, and alpha-smooth muscle actin (ACTA2)+ endothelial cells, reinforcing the heightened severity of pulmonary vascular lesions. Conclusions: This study presents the first architectural map of PAH lungs, connecting immune subsets not only with specific PA lesions but also with heightened severity in HPAH compared with IPAH. Our findings emphasize the therapeutic potential of targeting monocyte-derived dendritic cells, neutrophils, cellular interactions, and immune responses to alleviate severe vascular pathology in IPAH and HPAH.
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Hidralazina/análogos & derivados , Hipertensión Pulmonar , Hipertensión Arterial Pulmonar , Humanos , Receptor 2 Celular del Virus de la Hepatitis A/metabolismo , Células Endoteliales/metabolismo , Hipertensión Pulmonar Primaria Familiar/genética , Arteria Pulmonar , Receptores de Proteínas Morfogenéticas Óseas de Tipo II/genética , Proliferación Celular , HidrazonasRESUMEN
Structural variants (SVs), including small insertion and deletion variants (indels), are challenging to detect through standard alignment-based variant calling methods. Sequence assembly offers a powerful approach to identifying SVs, but is difficult to apply at scale genome-wide for SV detection due to its computational complexity and the difficulty of extracting SVs from assembly contigs. We describe SvABA, an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide local assembly with low memory and computing requirements. We evaluated SvABA's performance on the NA12878 human genome and in simulated and real cancer genomes. SvABA demonstrates superior sensitivity and specificity across a large spectrum of SVs and substantially improves detection performance for variants in the 20-300 bp range, compared with existing methods. SvABA also identifies complex somatic rearrangements with chains of short (<1000 bp) templated-sequence insertions copied from distant genomic regions. We applied SvABA to 344 cancer genomes from 11 cancer types and found that short templated-sequence insertions occur in â¼4% of all somatic rearrangements. Finally, we demonstrate that SvABA can identify sites of viral integration and cancer driver alterations containing medium-sized (50-300 bp) SVs.
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Genoma Humano/genética , Variación Estructural del Genoma/genética , Genómica , Mutación INDEL/genética , Bases de Datos Genéticas , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , Análisis de Secuencia de ADN , Eliminación de Secuencia/genética , Programas Informáticos , Integración Viral/genéticaRESUMEN
BACKGROUND: Meningiomas are the most common primary intracranial tumors in adults. While a majority of meningiomas are slow growing neoplasms that may cured by surgical resection, a subset demonstrates more aggressive behavior and insidiously recurs despite surgery and radiation, without effective alternative treatment options. Elucidation of critical mitogenic pathways in meningioma oncogenesis may offer new therapeutic strategies. We performed an integrated genomic and molecular analysis to characterize the expression and function of osteoglycin (OGN) in meningiomas and explored possible therapeutic approaches for OGN-expressing meningiomas. METHODS: OGN mRNA expression in human meningiomas was assessed by RNA microarray and RNAscope. The impact of OGN on cell proliferation, colony formation, and mitogenic signaling cascades was assessed in a human meningioma cell line (IOMM-Lee) with stable overexpression of OGN. Furthermore, the functional consequences of introducing an AKT inhibitor in OGN-overexpressing meningioma cells were assessed. RESULTS: OGN mRNA expression was dramatically increased in meningiomas compared to a spectrum of other brain tumors and normal brain. OGN-overexpressing meningioma cells demonstrated an elevated rate of cell proliferation, cell cycle activation, and colony formation as compared with cells transfected with control vector. In addition, NF2 mRNA and protein expression were both attenuated in OGN-overexpressing cells. Conversely, mTOR pathway and AKT activation increased in OGN-overexpressing cells compared to control cells. Lastly, introduction of an AKT inhibitor reduced OGN expression in meningioma cells and resulted in increased cell death and autophagy, suggestive of a reciprocal relationship between OGN and AKT. CONCLUSION: We identify OGN as a novel oncogene in meningioma proliferation. AKT inhibition reduces OGN protein levels in meningioma cells, with a concomitant increase in cell death, which provides a promising treatment option for meningiomas with OGN overexpression.
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Regulación Neoplásica de la Expresión Génica , Péptidos y Proteínas de Señalización Intercelular/genética , Neoplasias Meníngeas/metabolismo , Meningioma/metabolismo , Transducción de Señal , Autofagia , Línea Celular Tumoral , Proliferación Celular , Regulación hacia Abajo , Humanos , Péptidos y Proteínas de Señalización Intercelular/metabolismo , Neoplasias Meníngeas/genética , Meningioma/genética , Neurofibromina 2/genética , Neurofibromina 2/metabolismo , Proteínas Proto-Oncogénicas c-akt/metabolismo , ARN Mensajero/genética , ARN Mensajero/metabolismo , Serina-Treonina Quinasas TOR/metabolismoRESUMEN
Tumors with the same diagnosis can have different molecular profiles and response to treatment. It remains unclear when and why these differences arise. Somatic genomic aberrations occur within the context of a highly variable germline genome. Interrogating 5870 breast cancer lesions, we demonstrated that germline-derived epitopes in recurrently amplified genes influence somatic evolution by mediating immunoediting. Individuals with a high germline-epitope burden in human epidermal growth factor receptor 2 (HER2/ERBB2) are less likely to develop HER2-positive breast cancer compared with other subtypes. The same holds true for recurrent amplicons defining three aggressive estrogen receptor (ER)-positive subgroups. Tumors that overcome such immune-mediated negative selection are more aggressive and demonstrate an "immune cold" phenotype. These data show that the germline genome plays a role in dictating somatic evolution.
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Neoplasias de la Mama , Evolución Clonal , Mutación de Línea Germinal , Receptor ErbB-2 , Femenino , Humanos , Neoplasias de la Mama/genética , Neoplasias de la Mama/inmunología , Neoplasias de la Mama/patología , Epítopos/inmunología , Epítopos/genética , Células Germinativas/metabolismo , Metástasis de la Neoplasia , Receptor ErbB-2/genética , Receptores de Estrógenos/metabolismo , Receptores de Estrógenos/genéticaRESUMEN
Multiplexed imaging offers a powerful approach to characterize the spatial topography of tissues in both health and disease. To analyze such data, the specific combination of markers that are present in each cell must be enumerated to enable accurate phenotyping, a process that often relies on unsupervised clustering. We constructed the Pan-Multiplex (Pan-M) dataset containing 197 million distinct annotations of marker expression across 15 different cell types. We used Pan-M to create Nimbus, a deep learning model to predict marker positivity from multiplexed image data. Nimbus is a pre-trained model that uses the underlying images to classify marker expression across distinct cell types, from different tissues, acquired using different microscope platforms, without requiring any retraining. We demonstrate that Nimbus predictions capture the underlying staining patterns of the full diversity of markers present in Pan-M. We then show how Nimbus predictions can be integrated with downstream clustering algorithms to robustly identify cell subtypes in image data. We have open-sourced Nimbus and Pan-M to enable community use at https://github.com/angelolab/Nimbus-Inference.
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BACKGROUND: With the significant shift in the classification, risk stratification, and standards of care for gliomas, we sought to understand how the overall survival of patients with these tumors is impacted by molecular features, clinical metrics, and treatment received. METHODS: We assembled a cohort of patients with a histopathologically diagnosed glioma from The Cancer Genome Atlas, Project Genomics Evidence Neoplasia Information Exchange, and Dana-Farber Cancer Institute/Brigham and Women's Hospital. This incorporated retrospective clinical, histological, and molecular data alongside prospective assessment of patient survival. RESULTS: 4,400 gliomas were identified: 2,195 glioblastoma, 1,198 IDH1/2-mutant astrocytoma, 531 oligodendroglioma, 271 other IDH1/2-wildtype glioma, and 205 pediatric-type glioma. Molecular classification updated 27.2% of gliomas from their original histopathologic diagnosis. Examining the distribution of molecular alterations across glioma subtypes revealed mutually exclusive alterations within tumorigenic pathways. Non-TCGA patients had significantly improved overall survival compared to TCGA patients, with 26.7%, 55.6%, and 127.8% longer survival for glioblastoma, IDH1/2-mutant astrocytoma, and oligodendroglioma respectively (all p<0.01). Several prognostic features were characterized, including NF1 alteration and 21q loss in glioblastoma, and EGFR amplification and 22q loss in IDH1/2-mutant astrocytoma. Leveraging the size of this cohort, nomograms were generated to assess the probability of overall survival based on patient age, the molecular features of a tumor, and the treatment received. CONCLUSIONS: By applying modern molecular criteria, we characterize the genomic diversity across glioma subtypes, identify clinically applicable prognostic features, and provide a contemporary update on patient survival to serve as a reference for ongoing investigations.
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Cancer represents a broad spectrum of molecularly and morphologically diverse diseases. Individuals with the same clinical diagnosis can have tumors with drastically different molecular profiles and clinical response to treatment. It remains unclear when these differences arise during disease course and why some tumors are addicted to one oncogenic pathway over another. Somatic genomic aberrations occur within the context of an individual's germline genome, which can vary across millions of polymorphic sites. An open question is whether germline differences influence somatic tumor evolution. Interrogating 3,855 breast cancer lesions, spanning pre-invasive to metastatic disease, we demonstrate that germline variants in highly expressed and amplified genes influence somatic evolution by modulating immunoediting at early stages of tumor development. Specifically, we show that the burden of germline-derived epitopes in recurrently amplified genes selects against somatic gene amplification in breast cancer. For example, individuals with a high burden of germline-derived epitopes in ERBB2, encoding human epidermal growth factor receptor 2 (HER2), are significantly less likely to develop HER2-positive breast cancer compared to other subtypes. The same holds true for recurrent amplicons that define four subgroups of ER-positive breast cancers at high risk of distant relapse. High epitope burden in these recurrently amplified regions is associated with decreased likelihood of developing high risk ER-positive cancer. Tumors that overcome such immune-mediated negative selection are more aggressive and demonstrate an "immune cold" phenotype. These data show the germline genome plays a previously unappreciated role in dictating somatic evolution. Exploiting germline-mediated immunoediting may inform the development of biomarkers that refine risk stratification within breast cancer subtypes.
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While technologies for multiplexed imaging have provided an unprecedented understanding of tissue composition in health and disease, interpreting this data remains a significant computational challenge. To understand the spatial organization of tissue and how it relates to disease processes, imaging studies typically focus on cell-level phenotypes. However, images can capture biologically important objects that are outside of cells, such as the extracellular matrix. Here, we describe a pipeline, Pixie, that achieves robust and quantitative annotation of pixel-level features using unsupervised clustering and show its application across a variety of biological contexts and multiplexed imaging platforms. Furthermore, current cell phenotyping strategies that rely on unsupervised clustering can be labor intensive and require large amounts of manual cluster adjustments. We demonstrate how pixel clusters that lie within cells can be used to improve cell annotations. We comprehensively evaluate pre-processing steps and parameter choices to optimize clustering performance and quantify the reproducibility of our method. Importantly, Pixie is open source and easily customizable through a user-friendly interface.
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Diagnóstico por Imagen , Reproducibilidad de los Resultados , Análisis por ConglomeradosRESUMEN
Cellular organization and functions encompass multiple scales in vivo. Emerging high-plex imaging technologies are limited in resolving subcellular biomolecular features. Expansion Microscopy (ExM) and related techniques physically expand samples for enhanced spatial resolution, but are challenging to be combined with high-plex imaging technologies to enable integrative multiscaled tissue biology insights. Here, we introduce Expand and comPRESS hydrOgels (ExPRESSO), an ExM framework that allows high-plex protein staining, physical expansion, and removal of water, while retaining the lateral tissue expansion. We demonstrate ExPRESSO imaging of archival clinical tissue samples on Multiplexed Ion Beam Imaging and Imaging Mass Cytometry platforms, with detection capabilities of > 40 markers. Application of ExPRESSO on archival human lymphoid and brain tissues resolved tissue architecture at the subcellular level, particularly that of the blood-brain barrier. ExPRESSO hence provides a platform for extending the analysis compatibility of hydrogel-expanded biospecimens to mass spectrometry, with minimal modifications to protocols and instrumentation.
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Microscopía , Proteínas , Humanos , Vacio , Microscopía/métodos , Hidrogeles/químicaRESUMEN
Clonal hematopoiesis of indeterminate potential (CHIP) is defined by the presence of a cancer-associated somatic mutation in white blood cells in the absence of overt hematological malignancy. It arises most commonly from loss-of-function mutations in the epigenetic regulators DNMT3A and TET2. CHIP predisposes to both hematological malignancies and atherosclerotic cardiovascular disease in humans. Here we demonstrate that loss of Dnmt3a in myeloid cells increased murine atherosclerosis to a similar degree as previously seen with loss of Tet2. Loss of Dnmt3a enhanced inflammation in macrophages in vitro and generated a distinct adventitial macrophage population in vivo which merges a resident macrophage profile with an inflammatory cytokine signature. These changes surprisingly phenocopy the effect of loss of Tet2. Our results identify a common pathway promoting heightened innate immune cell activation with loss of either gene, providing a biological basis for the excess atherosclerotic disease burden in carriers of these two most prevalent CHIP mutations.
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Aterosclerosis , ADN (Citosina-5-)-Metiltransferasas , ADN Metiltransferasa 3A , Proteínas de Unión al ADN , Dioxigenasas , Modelos Animales de Enfermedad , Mutación con Pérdida de Función , Macrófagos , Fenotipo , Proteínas Proto-Oncogénicas , ADN Metiltransferasa 3A/genética , Animales , Aterosclerosis/genética , Aterosclerosis/patología , Aterosclerosis/inmunología , Macrófagos/metabolismo , Macrófagos/inmunología , ADN (Citosina-5-)-Metiltransferasas/genética , ADN (Citosina-5-)-Metiltransferasas/metabolismo , Proteínas Proto-Oncogénicas/genética , Proteínas de Unión al ADN/genética , Proteínas de Unión al ADN/metabolismo , Ratones Endogámicos C57BL , Ratones Noqueados , Masculino , Enfermedades de la Aorta/genética , Enfermedades de la Aorta/patología , Ratones , Citocinas/metabolismo , Citocinas/genética , Inmunidad Innata/genética , Mediadores de Inflamación/metabolismo , Hematopoyesis Clonal/genética , FemeninoRESUMEN
Next-generation tools for multiplexed imaging have driven a new wave of innovation in understanding how single-cell function and tissue structure are interrelated. In previous work, we developed multiplexed ion beam imaging by time of flight, a highly multiplexed platform that uses secondary ion mass spectrometry to image dozens of antibodies tagged with metal reporters. As instrument throughput has increased, the breadth and depth of imaging data have increased as well. To extract meaningful information from these data, we have developed tools for cell identification, cell classification, and spatial analysis. In this review, we discuss these tools and provide examples of their application in various contexts, including ductal carcinoma in situ, tuberculosis, and Alzheimer's disease. We hope the synergy between multiplexed imaging and automated image analysis will drive a new era in anatomic pathology and personalized medicine wherein quantitative spatial signatures are used routinely for more accurate diagnosis, prognosis, and therapeutic selection.
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Inmunohistoquímica , Espectrometría de Masas , Anticuerpos , Humanos , Inmunohistoquímica/métodos , Espectrometría de Masas/métodosRESUMEN
Neurodegenerative disorders are characterized by phenotypic changes and hallmark proteopathies. Quantifying these in archival human brain tissues remains indispensable for validating animal models and understanding disease mechanisms. We present a framework for nanometer-scale, spatial proteomics with multiplex ion beam imaging (MIBI) for capturing neuropathological features. MIBI facilitated simultaneous, quantitative imaging of 36 proteins on archival human hippocampus from individuals spanning cognitively normal to dementia. Customized analysis strategies identified cell types and proteopathies in the hippocampus across stages of Alzheimer's disease (AD) neuropathologic change. We show microglia-pathologic tau interactions in hippocampal CA1 subfield in AD dementia. Data driven, sample independent creation of spatial proteomic regions identified persistent neurons in pathologic tau neighborhoods expressing mitochondrial protein MFN2, regardless of cognitive status, suggesting a survival advantage. Our study revealed unique insights from multiplexed imaging and data-driven approaches for neuropathologic analysis and serves broadly as a methodology for spatial proteomic analysis of archival human neuropathology. TEASER: Multiplex Ion beam Imaging enables deep spatial phenotyping of human neuropathology-associated cellular and disease features.
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Enfermedad de Alzheimer , Proteómica , Animales , Humanos , Neuropatología , Enfermedad de Alzheimer/patología , Hipocampo/patología , Microglía/patología , Proteínas tau/metabolismoRESUMEN
Intratumoral heterogeneity is a seminal feature of human tumors contributing to tumor progression and response to treatment. Current technologies are still largely unsuitable to accurately track phenotypes and clonal evolution within tumors, especially in response to genetic manipulations. Here, we developed epitopes for imaging using combinatorial tagging (EpicTags), which we coupled to multiplexed ion beam imaging (EpicMIBI) for in situ tracking of barcodes within tissue microenvironments. Using EpicMIBI, we dissected the spatial component of cell lineages and phenotypes in xenograft models of small cell lung cancer. We observed emergent properties from mixed clones leading to the preferential expansion of clonal patches for both neuroendocrine and non-neuroendocrine cancer cell states in these models. In a tumor model harboring a fraction of PTEN-deficient cancer cells, we observed a non-autonomous increase of clonal patch size in PTEN wild-type cancer cells. EpicMIBI facilitates in situ interrogation of cell-intrinsic and cell-extrinsic processes involved in intratumoral heterogeneity.