Contemporary Prognostic Signatures and Refined Risk Stratification of Gliomas: An Analysis of 4,400 Tumors.

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.

Automated classification of cellular expression in multiplexed imaging data with Nimbus.

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.

Germline-mediated immunoediting sculpts breast cancer subtypes and metastatic proclivity.

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.

The multimodality cell segmentation challenge: toward universal solutions.

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.

Single-Cell Imaging Maps Inflammatory Cell Subsets to Pulmonary Arterial Hypertension Vasculopathy.

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.

Robust phenotyping of highly multiplexed tissue imaging data using pixel-level clustering.

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.

A spatially resolved timeline of the human maternal-fetal interface.

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.

Expanded vacuum-stable gels for multiplexed high-resolution spatial histopathology.

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.

Germline-mediated immunoediting sculpts breast cancer subtypes and metastatic proclivity.

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.

Loss-of-function mutations in Dnmt3a and Tet2 lead to accelerated atherosclerosis and concordant macrophage phenotypes.

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.

Single-cell spatial proteomic imaging for human neuropathology.

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.

Spatial epitope barcoding reveals clonal tumor patch behaviors.

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.

Structural variants shape driver combinations and outcomes in pediatric high-grade glioma.

We analyzed the contributions of structural variants (SVs) to gliomagenesis across 179 pediatric high-grade gliomas (pHGGs). The most recurrent SVs targeted MYC isoforms and receptor tyrosine kinases (RTKs), including an SV amplifying a MYC enhancer in 12% of diffuse midline gliomas (DMG), indicating an underappreciated role for MYC in pHGG. SV signature analysis revealed that tumors with simple signatures were TP53 wild type (TP53WT) but showed alterations in TP53 pathway members PPM1D and MDM4. Complex signatures were associated with direct aberrations in TP53, CDKN2A and RB1 early in tumor evolution and with later-occurring extrachromosomal amplicons. All pHGGs exhibited at least one simple-SV signature, but complex-SV signatures were primarily restricted to subsets of H3.3K27M DMGs and hemispheric pHGGs. Importantly, DMGs with complex-SV signatures were associated with shorter overall survival independent of histone mutation and TP53 status. These data provide insight into the impact of SVs on gliomagenesis and the mechanisms that shape them.

Combined protein and nucleic acid imaging reveals virus-dependent B cell and macrophage immunosuppression of tissue microenvironments.

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.

PPM1D mutations are oncogenic drivers of de novo diffuse midline glioma formation.

The role of PPM1D mutations in de novo gliomagenesis has not been systematically explored. Here we analyze whole genome sequences of 170 pediatric high-grade gliomas and find that truncating mutations in PPM1D that increase the stability of its phosphatase are clonal driver events in 11% of Diffuse Midline Gliomas (DMGs) and are enriched in primary pontine tumors. Through the development of DMG mouse models, we show that PPM1D mutations potentiate gliomagenesis and that PPM1D phosphatase activity is required for in vivo oncogenesis. Finally, we apply integrative phosphoproteomic and functional genomics assays and find that oncogenic effects of PPM1D truncation converge on regulators of cell cycle, DNA damage response, and p53 pathways, revealing therapeutic vulnerabilities including MDM2 inhibition.

The immunoregulatory landscape of human tuberculosis granulomas.

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.

Transition to invasive breast cancer is associated with progressive changes in the structure and composition of tumor stroma.

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.

A molecularly integrated grade for meningioma.

BACKGROUND: Meningiomas are the most common primary intracranial tumor in adults. Clinical care is currently guided by the World Health Organization (WHO) grade assigned to meningiomas, a 3-tiered grading system based on histopathology features, as well as extent of surgical resection. Clinical behavior, however, often fails to conform to the WHO grade. Additional prognostic information is needed to optimize patient management. METHODS: We evaluated whether chromosomal copy-number data improved prediction of time-to-recurrence for patients with meningioma who were treated with surgery, relative to the WHO schema. The models were developed using Cox proportional hazards, random survival forest, and gradient boosting in a discovery cohort of 527 meningioma patients and validated in 2 independent cohorts of 172 meningioma patients characterized by orthogonal genomic platforms. RESULTS: We developed a 3-tiered grading scheme (Integrated Grades 1-3), which incorporated mitotic count and loss of chromosome 1p, 3p, 4, 6, 10, 14q, 18, 19, or CDKN2A. 32% of meningiomas reclassified to either a lower-risk or higher-risk Integrated Grade compared to their assigned WHO grade. The Integrated Grade more accurately identified meningioma patients at risk for recurrence, relative to the WHO grade, as determined by time-dependent area under the curve, average precision, and the Brier score. CONCLUSION: We propose a molecularly integrated grading scheme for meningiomas that significantly improves upon the current WHO grading system in prediction of progression-free survival. This framework can be broadly adopted by clinicians with relative ease using widely available genomic technologies and presents an advance in the care of meningioma patients.

Multiplexed Ion Beam Imaging: Insights into Pathobiology.

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.